[-_-] Level Breakout, Auto Backtesting StrategyDescription:
A Long only strategy based on breakout from a certain level formed by High price. It has auto-backtesting capabilities (you set ranges for the three main parameters: Lookback, TP and SL; the strategy then goes through different combinations of those parameters and displays a table with results that you can sort by Percentage of profitable trades AND/OR Net profit AND/OR Number of trades). So you can, for example, sort only by Net profit to find combination of parameters that gives highest net profit, or sort by Net profit and Percentage profitable to find a combination of parameters that gives the best balance between profitability and profit. The auto-backtesting also takes into account the commission which is set in % in the inputs (make sure to set the same value in properties of the strategy so that auto-backtesting and real backtesting results match).
NOTE: auto-backtesting only find the best combinations and displays them in a table, you will then need to manually set the Lookback, TP and SL inputs for real backtesting to match.
Parameters:
- Lookback -> # of bars for filtering signals; recommended range from 2 to 5
- TP (%) -> take profit; recommended range from 5 to 10
- SL (%) -> stop loss; recommended range from 1 to 5
- Commission (%) -> commission per trade
- Min/Max Lookback -> lookback range for auto-backtesting
- Min/Max TP -> take profit range for auto-backtesting
- Min/Max SL -> stop loss range for auto-backtesting
- Percentage profitable -> sort by percentage of profitable trades
- Net profit -> sort by net profit
- Number of trades -> sort by number of trades
Cari dalam skrip untuk "profit"
LuxAlgo - Backtester (S&O)The S&O Backtester is an innovative strategy script that encompasses features + optimization methods from our Signals & Overlays™ toolkit and combines them into one easy-to-use script for backtesting the most detailed trading strategies possible.
Our Signals & Overlays™ toolkit is notorious for its signal optimization methods such as the 'Optimal Sensitivity' displayed in its dashboard which provides optimization backtesting of the Sensitivity parameter for the Confirmation & Contrarian Signals.
This strategy script allows even more detailed & precise backtests than anything available previously in the Signals & Overlays™ toolkit; including External Source inputs allowing users to use any indicator including our other paid toolkits for take profit & stop loss customization to develop strategies, along with 10+ pre-built filters directly Signals & Overlays™' features.
🔶 Features
Full Sensitivity optimization within the dashboard to find the Best Win rates or Best Profits.
Counter Trade Mode to reverse signals in undesirable market conditions (may introduce higher drawdowns)
Built-in filters for Confirmation Signals w/ Indicator Overlays from Signals & Overlays™.
Built-in Confirmation exit points are available within the settings & on by default.
External Source Input to filter signals or set custom Take Profits & Stop Losses.
Optimization Matrix dashboard option showing all possible permutations of Sensitivity.
Option to Maximize for Winrate or Best Profit.
🔶 Settings
Sensitivity signal optimizations for the Confirmation Signals algorithm
Buy & Sell conditions filters with Indicator Overlays & External Source
Take Profit exit signals option
External Source for Take Profit & Stop Loss
Sensitivity ranges
Backtest window default at 2,000 bars
External source
Dashboard locations
🔶 Usage
Backtests are not necessarily indicative of future results, although a trader may want to use a strategy script to have a deeper understanding of how their strategy responds to varying market conditions, or to use as a tool for identifying possible flaws in a strategy that could potentially be indicative of good or bad performance in the future.
A strategy script can also be useful in terms of it's ability to generate more complete & configurable alerts, giving users the option to integrate with external processes.
In the chart below we are using default settings and built-in optimization parameters to generate the highest win rate.
Results like the above will vary & finding a strategy with a high win rate does not necessarily mean it will persist into the future, however, some indications of a well-optimized strategy are:
A high number of closed trades (100+) with a consistently green equity curve
An equity curve that outperforms buy & hold
A low % max drawdown compared to the Net Profit %.
Profit factor around 1.5 or above
In the chart below we are using the Trend Catcher feature from Signals & Overlays™ as a filter for standard Confirmation Signals + exits on a higher timeframe.
By filtering bullish signals only when the Trend Catcher is bullish, as well as bearish signals for when the Trend Catcher is bearish, we have a highly profitable strategy created directly from our flagship features.
While the Signals & Overlays features being used as built-in filters can generate interesting backtests, the provided External Sources can allow for even more creativity when creating strategies. This feature allows you to use many indicators from TradingView as filters or to trigger take-profit/stop-loss events, even if they aren't from LuxAlgo.
The chart below shows the HyperWave Oscillator from our Oscillator Matrix™ being used for take-profit exit conditions, exiting a long position on a profit when crossing 80, and exiting a short position when crossing 20.
🔶 Counter Trade Mode
Our thesis has always firmly remained to use Confirmation Signals within Signals & Overlays™ as a supportive tool to find trends & use as extra confirmation within strategies.
We included the counter-trade mode as a logical way to use the Confirmation signals as direct entries for longs & shorts within more contrarian trading strategies. Many traders can relate to using a trend-following indicator and having the market not respect its conditions for entries.
This mode directly benefits a trader who is aware that market conditions are generally not-so-perfect trends all the time. Acknowledging this, allows the user to use this to their advantage by introducing countertrend following conditions as direct entries, which tend to perform very well in ranging markets.
The big downfall of using counter-trade mode is the potential for very large max-drawdowns during trending market conditions. We suggest for making a strategy to consider introducing stop-loss conditions that can efficiently minimize max-drawdowns during the process of backtesting your creations.
Sensitivity Optimization
Within the Signals & Overlays™ toolkit, we allow users to adjust the Confirmation Signals with a Sensitivity parameter.
We believe the Sensitivity paramter is the most realistic way to generate the most actionable Confirmation Signals that can navigate various market conditions, and the Confirmation Signals algorithm was designed specifically with this in mind.
This script takes this parameter and backtests it internally to generate the most profitable value to display on the dashboard located in the top right of the chart, as well as an optimization table if users enable it to visualize it's backtesting.
In the image below, we can see the optimization table showing permutations of settings within the user-selected Sensitivity range.
The suggested best setting is given at the current time for the backtesting window that's customizable within the indicator. Optimized settings for technical indicators are not indicative of future results and the best settings are highly likely / guaranteed to change over time.
Optimizing signal settings has become a popular activity amongst technical analysts, however, the real-time beneficial applications of optimizing settings are limited & best described as complicated (even with forward testing).
🔶 Strategy Properties (Important)
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from strategies built are realistic.
🔶 How to access
You can see the Author's Instructions below to learn how to get access on our website.
Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2
This script was originally shared by Wunderbit as a free open source script for the community to work with. This is my second published iteration of this idea.
WHAT THIS SCRIPT DOES:
It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading.
This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry.
This is a new and improved version geared for lower timeframes (15-5 minutes), but can be run on larger ones as well. I am testing it live as my high frequency trader.
HOW IT DOES IT:
It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability.
Take profits are now trailing profits, and the stop loss is now fixed. Why? I found that the trailing stop loss with ATR in the previous version yields very good results for back tests but becomes very difficult to deploy live due to transaction fees. As you can see the average trade is a higher profit percentage than the previous version.
HOW IS MY VERSION ORIGINAL:
Now instead of using ATR stop loss, we have a fixed stop loss - counter intuitively to what some may believe this performs better in live trading scenarios since it gives the strategy room to move. I noticed that the ATR trailing stop was stopping out too fast and was eating away balance due to transaction fees.
The take profit on the other hand is now a trailing profit with a customizable deviation. This ensures that you can have a minimum profit you want to take in order to exit.
I have depracated the old ATR trailing stop as it became too confusing to have those as different options. I kept the old version for others that want to experiment with it. The source code still requires some cleanup, but its fully functional.
I added in a way to show RSI values and ATR values with a checkbox so that you can use the new an improved ATR Filter (and grab the right RSI values for the RSI filter). This will help to filter out times of very low volatility where we are unlikely to find a profitable trade. Use the "Show Data" checkbox to see what the values are on the indicator pane, then use those values to gauge what you want to filter out.
Both versions
Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.)
Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address.
Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off)
Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots.
HOW TO USE IT:
It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found.
Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor.
Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well.
Select a time frame in configuration for your indicator calculations.
Select the strategy config for time frame (resolution). I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers.
Optimize your indicator without filters : customize your settings for MACD and MFI that are profitable with your chart and selected time frame calculation. Try different Take Profits (try about 2-5%) and stop loss (try about 5-8%). See if your back test is profitable and continue to optimize.
Use the Trend, RSI, ATR Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio.
You can use the open and close messages for a platform integration, but I choose to set mine up on the destination platform and let the platform close it. With certain platforms you cannot be sure what your entry point actually was compared to Trading View due to slippage and timing, so I let the platform decide when it is actually profitable.
Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
Short Selling EMA Cross (By Coinrule)BINANCE:AVAXUSDT
This short selling script works best in periods of downtrends and general bearish market conditions, with the ultimate goal to sell as the the price decreases further and buy back before a rebound.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to to hodl this cash, or use it to reinvest when the market reaches attractive buying levels.
Entry
The exponential moving average ( EMA ) 20 and EMA 50 have been used for the variables determining the entry to the short. EMAs can operate better than simple moving averages due to the additional weighting placed on the most recent data points, whereas simple moving averages weight all the data the same. This means that price is tracked more closely and the most recent volatile moves can be captured and exploited more efficiently using EMAs.
Our backtesting data revealed that the most profitable timeframe was the 30-minute timeframe, this also enabled a good frequency of trades and high profitability.
A fast (shorter term) exponential moving average , in this strategy the EMA 20, crossing under a slow (longer term) moving average, in this example the EMA 50, signals the price of an asset has started to trend to the downside, as the most recent data signals price is declining compared to earlier data. The entry acts on this principle and executes when the EMA 20 crosses under the EMA 50.
Enter Short: EMA 20 crosses under EMA 50.
Exit
This script utilises a take profit and stop loss for the exit. The take profit is set at -8% and the stop loss is set at +16% from the entry price. This would normally be a poor trade due to the risk:reward equalling 0.5. However, when looking at the backtesting data, the high profitability of the strategy (93.33%) leads to increased confidence and showcases the high probability of success according to historical data.
The take profit (-8%) and the stop loss (+16%) of the strategy are widely placed to ensure the move is captured without being stopped out due to relief rallies. The stop loss also plays a role of mitigating losses and minimising risk of being stuck in a short position once there has been a fundamental trend reversal and the market has become bullish .
Exit Short: -8% price decrease from entry price.
OR
Exit Short: +16% price increase from entry price.
Tip: Research what coins have consistent and large token unlocks / highly inflationary tokenomics, and target these during bear markets to short as they will most likely have substantial selling pressure that outweighs demand - leading to declining prices.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
The backtesting data was recorded from December 1st 2021, just as the market was beginning its downtrend. We therefore recommend analysing the market conditions prior to utilising this strategy as it operates best on weak coins during downtrends and bearish conditions.
BlueFX Strategy We are re publishing the script so the Script Title doesn't display the old version number, to stop further confusion with our members.
This title will now remain constant, until you click into the strategy and the latest version number will be shown.
The previous release notes below are copied from the previous descriptions with the release note updates shown.
Hi Traders,
I hope everyone is great - its a long one - but worth the read, I promise....
Firstly, thank you to our members for being patient with this release - it took longer than anticipated but now with even more functionality too - and some improved profitability in back-testing on our H1 time frame especially - explained further below.
Secondly, thank you to the individuals that have made this happen - you know who you are! Sounds like an Oscar speech right.... sorry.
This tool we believe really does change the game - please read on to find out more.
As a brief reminder this builds upon on initial V1 and V2 indicator/scripts ...
The strategy itself
Our strategy will help you identify the current trend in the markets and highlight when this is changing. The strategy itself is based upon 4 indicators lining up in total confluence to increase the probability of the trade being a success.
Absolutely no technical analysis is needed to trade this successfully - this can be used on all time frames and all pairs - obviously with varying profitability as all pairs work differently - this can be reviewed quickly in 'Strategy Tester' to hone in on your own desired settings.
When all criteria is in alignment the strategy will convert all candles to the relevant colour - Green for an uptrend and Red for a downtrend; a candle that is printed normally simply shows that no current trend is in place to warrant a colour change. A normal coloured candle could possibly indicate a change in current market direction or the market consolidating before a further move in the initial direction.
When a new signal is valid, 'Blue FX Buy'' or 'Blue FX Sell' will be displayed and the small arrow shown on candle open for entry. (*Now along with Entry Price (EP), Stop Loss (SL), Take Profit (TP) and Lot size that is based on the risk parameters you have set personally on V3)
Version 2 was created with H4 confluence built in and also a display of a suggested Stop Loss (SL) and multiple Take Profits (TP's) on the H1 (One Hour) time frame - thus making your entry even easier and your SL more reliable - these suggested SL's and targets were based on the ATR of that pair at that time - a popular choice amongst traders - automatically built in.
What is a Trading View Script?
A script is like an indicator but better, we can prove the success of our strategy by using Trading Views strategy tester function. As shown below and on the chart - you can see the 'Buy' and 'Close Buy' on the chart, supported by a live trading log showing you the entry, entry price date, volume and closing price.
This is a great function for numerous reasons; firstly, you know you are using a profitable strategy, secondly you can use this as a trading journal to support your trading too. This in itself can help you with your trading psychology - letting winning trades run is a prime example of this. Take confidence in the statistics and performance over time.
Ultimately, we believe we have saved YOU the need to firstly, find an edge and a strategy - and all of the time it takes to BACKTEST a strategy - to then find it may or may not work - and then you start again!
Well guess what?
We know this works and it takes you seconds to see it.
Everyone can see the statistics themselves for 2020 to date (and previous!); an account gain of over 500% if you managed to catch all trades risking 1% per trade. I understand that catching all trades is difficult but even if you caught a third, that's still not too bad right?
Disclaimer alert; Please remember past performance is exactly that - how our strategy performed over those dates tested, it is not obviously a guarantee of future performance.
Even better, you/we can still hone in these settings to find an improved performance per pair on any given time frame and money management plan. (We are currently looking into automating this process too)
Default settings are set for use with the H1 time frame - no extra confluence checking is needed with these settings.
So what are the specific changes I hear you ask?
- Visibility of the SL and TP labels across all time frames.
- Visibility of all previous SL and TP labels with the click of a button (Prev. was only 2).
- Proof of the profitability of the strategy - we had this in V1 but this was based on trend following with the exit - we didn't in V2 when we added the SL and TP display function.
- The ability to customise the parameters and see the instant impact of the desired pair/time-frame and testing date range - of course some work better than others and will do at different times - once we have found a way to test this in an automated way we could look to do this monthly/quarterly to ensure we are using 'optimal' parameters at all times.
- Another game changer here is the addition of a lot size calculator - set your balance, set your risk and the LOT SIZE you should be trading will appear as if by magic - no need to use any other tool to do this. For inexperienced traders and especially trading stocks/ gold / commodities we suggest you check the contract sizes first as some brokers may operate differently. This visual cue will help ensure you are managing your risk and save you time in checking the right Lot Size for your trade (every pair has a different pip value and every trade a different SL).
- Although not required in our H1 settings currently - we have added more higher time frame confluences - which can improve the profitability of different pairs on different time frames in testing.
- As our tool can be used across all instruments we have a pull down menu for Crypto/Metals/Stocks/ Commodities , etc.
- The option to also test fixed lot size or percentage - see the benefit of compounding right away.
- The option to turn the testing function on and off.
Let's see an example......
An example trade - display Entry, SL, multiple TP, lot size and contract size.
snapshot
We have deliberately set the TP3 to be an increased target, this way we can capitalise on a large move in the market, should the move reverse and the opposite signal appears we close the trade anyway and follow the new signal.
I am unable to add other pictures in this Script description - but we will include in our Public channel and update our website to show them over the coming days.
I hope you can all see the functionality in this tool, the profitability in historic tests and how it can be used to give you your edge.
How do you access this I hear you ask?
Please visit our website for signup / purchase information in the first instance (the link is on our trading view profile / signature) or send us a private message on here - its impossible to keep track of comments on our posts so to ensure we don't miss you, a private DM will be great please.
Thank you for reading, we hope you choose to join our vastly growing community.
Kind regards
Darren
Blue FX
Jun 14
Release Notes: Default settings have been improved, providing a 600% gain YTD in back testing with less trades too.
Jul 4
Release Notes: Trend filter using ADX - our strategy is based on a trending market, adding the ADX filter to our strategy allows us to remove trades under the threshold level set. Previously - we tried to teach our members how to spot the ranging markets to help further increase their successes (although the stats were not based on any manual intervention) - now they don't have too.
Specific parameters set into the code - detects the pair and TF to shown them automatically - our method has been solid YOY growth based on a fixed 0.01 lot size to gain consistent yearly consistent results.
Trade volumes substantially reduced with a much higher win rate - due to the specific parameters and ADX filter.
No pull down menu when flicking between instruments - all done automatically; making it easier for trades flicking between trading instruments.
More TP options for testing - we have TP1/2/3 and other variables including FT (Follow Trend) / FT + SL (Follow trend with Stop loss) / TS (Trail Stop function)
Smaller labels showing entry, SL and TP, etc - much clearer on screen and on your app.
Lot sizes fixed - we had a previous bug affecting some currencies - as always where money is involved and managing risk, ensure you check and are comfortable this is correct of course
Filter for days of the week - some pairs hate specific days, a great tool, see how removing Fridays affects the performance in seconds.
Back testing on all instruments - not previously available - trade stocks like Tesla or Lloyds - or indices? We can give you back testing data for them all.
Filter for trading sessions - like the days of the week - if you are only trading London and US sessions, back testing data for other sessions is pretty pointless - now you can remove them too!
If you wish to just stay with the default V3 settings its simple, turn 'Use pre-defined parameter?' Off - and turn off ADX - your chart will then look like the initial v3.0 strategy anyway. However, every pair has improved performance we have found when including ADX - each pair is affected differently with a higher or lower ADX Threshold - this is parameter #9.
I don't think there is much more that can be added now - fuelled by our ambition - to provide our members with an easy yet profitable trading strategy for both beginner or experienced trader. We have this at the forefront of our minds when adding and reviewing functions.
Follow the trades, stay disciplined and don't focus on the money. Focus on the 'process' of following the strategy, its much easier on your mind too. Far easier following instructions than trying to do something without - follow your plan, the process and the money will follow.
If you wish to see all of the back testing data for each pair - hop into our Discord Server and check out the #public-backtesting-channel - all of them will be there when I post them tonight.
Jul 5
Release Notes: Another quick update.
More days of week added - Sat and Sunday trading sessions - (Sat - just crypto is open on TV)
Also a specific setting for trading just a certain time of day - this is based on EST time you will will need to convert back to your time zone for this to work.
For example, if you would like to test trading EURUSD between 7am and 11am - you will need to find the EST time for this which is 2am to 6am, you will then see these trades in the list of trades section. This is ideal for scalping certain sessions where all trades will be open and closed promptly.
I use the 'Time Buddy' app for this as its quite straight forward.
Regards
Darren
18 hours ago
Release Notes: Update - correcting the entry price label error.
Grover Llorens Activator Strategy AnalysisThe Grover Llorens Activator is a trailing stop indicator deeply inspired by the parabolic SAR indicator, and aim to provide early exit points and reversal detection. The indicator was posted not so long ago, you can find it here :
Today a strategy using the indicator is proposed, and its profitability is analyzed on 3 different markets with the main time frame being 1 hour, remember that lower time frames involve lower absolute price changes, therefore we are way more affected by the spread, and we can require a larger position sizing depending on our investment target, trading higher time-frames is always a good practice and this is why 1 hour is selected. Based on the result we might make various conclusions regarding the indicator accuracy and might have ideas on future improvements of the indicator.
I'am not great when it comes to strategy design, i still hope to share correct and useful information in this post, let me know your thoughts on the post format and if i should make more of these.
Setup And Rules
The analysis is solely based on the indicator signals, money management isn't taken into account, this allow us to have an idea on the indicator robustness and resilience, particularly on extremely volatile markets and ones exhibiting a chaotic structure, altho it is normally good practice to close any position before a market closure in order to avoid any potential major gaps.
The settings used are 480 for length and 14 for mult, this create relatively mid term signals that are suited for a trend indicator such as the Grover Llorens Activator, unfortunately we can't infer the indicator optimal settings, thats how it is with any technical indicator anyway.
Here are the rules of our strategy :
long : closing price cross over the indicator
short : closing price cross under the indicator
We use constant position sizing, once a signal is triggered all the previous positions are closed.
Description Of The Statistics Used
Various statistics are presented in this post, here is a brief description of the main ones :
Percent Profitability (higher = better): Percentage of winning trades, that is : winning trades/total number of trades × 100
Maximum Drawdown (lower = better) : The highest difference between a peak and a valley in the balance, that is : peak - valley , in percentage : (peak - valley)/peak × 100
Profit Factor (higher = better) : Gross profit divided by gross loss, values under 1 represent gross losses superior to the gross profits
Remember that more volatility = more risk, since higher absolute price changes can logically cause larger losses.
EURUSD
The first market analyzed is the Forex market with the EURUSD major pair with a position sizing of 1000 units (1 micro lot). Since October EURUSD is not showing any particular strong trend but posses a discrete rising motion, fortunately cycles can be observed.
The equity was rising until two trades appeared causing a decline in the equity. Before October a bearish market could be observed.
We can see that the equity is rising, the trend still posses various retracements that affect our indicator, however we can see that the indicator totally nail the end of the trend, thats the power of converging toward the price.
In short :
$ 86.63 net profit
340 closed trades
37.65 % profitable (thats a lot of loosing trades)
1.19 profit factor
$ 76.67 max drawdown
Applying a spread would create negative results (in general the average spread is used), not a great start...
BTCUSD
The cryptocurrency market is relatively more volatile than others, which also mean potentially higher returns, we test the indicator using certainly the most traded cryptocurrency, BTCUSD. We will use a position sizing of 1 unit.
In the case of BTCUSD the strategy balance is relatively stationary around the initial capital, with of course high dispersion.
from september to december the market is bearish with various ranging periods, no apparent cycles can be observed, except maybe in the ranging period of october, this ranging period is followed by a non linear trend (relatively parabolic) that the indicator failed to capture in its integrity (this is a recurrent problem and it is starting to piss me off xD).
In short :
$ 2010.64 net profit (aka how i bet the crypto market)
395 closed trades
38.23 % profitable
1.036 profit factor
$ 5738.01 max drawdown (aka how i lost to the crypto market)
AMD
AMD stand for Advanced Micro Devices and is a company focused on the development of computer technology, i love the microprocessor market and i really like AMD who start this year in a pretty great way with a net bullish trend.
The performance of the indicator on AMD is decent (at last !) with the equity producing many new higher highs. The indicator performance still drop in the middle end of 2019 with a large equity drawdown of 17$ caused by the gap of august 8. Unfortunately AMD, like lot of well behaving stocks can only tells us that the indicator has good performances on heavily trending markets with no excess of noise or chaotic structures.
In short :
$ 17.86 net profit (Enough for a consistent lunch)
295 closed trades
36.27 % profitable
1.414 profit factor
$ 10.37 max drawdown.
Conclusion
A strategy using the recently proposed Grover Llorens activator has been presented. We can easily conclude that the indicator can't possibly generate long term returns under chaotic and volatile markets, and could even produce unnecessary trades in trending markets without much parasitic fluctuations such as noise and retracements (think about a simple linear trend) since the indicator converge toward the price and would therefore automatically cross over/under the trend, thus guaranteeing a false signal.
However we have seen its ability to provide accurate early reversal detection shine from time to time, thus over performing lagging indicators in this aspect, however the duration of price fluctuations isn't fixed at a certain period, the rate of convergence should be way faster during volatile fluctuations, of moderate speed during more cyclic fluctuations, and really slow with apparent long term trends, this could be achieved by making the indicator adaptive, but it won't really make it necessarily perform better.
That said i still believe that converging trend indicators are really interesting and aim to capture the non lasting behavior of price fluctuations, they shouldn't receive so much hate (think about the poor p-sar).
Thanks for reading !
Cyatophilum Bands Pro Trader V3 [BACKTEST]An Original Automated Strategy that can be used for Manual or Bot Trading, on any timeframe and market.
>> Presentation <<
How it works
No, these are NOT Bollinger Bands..
The Cyatophilum Bands are an original formula that I created. You will probably never find it anywhere else.
Their behavior is the following:
When they are horizontal it means the trend is going sideways and they represent supports (lower band) and resistances (upper band).
When they are climbing or falling it means the trend is either bullish or bearish and they represent Trend Lines.
The strategy enters Long on a Bull Breakout and enters Short on a Bear Breakout.
The exits are triggered either on a Trend Reversal, a Stop Loss or a Take Profit.
FEATURES
Take Profit System
Stop Loss System
Show Net profit Line
More features here
Finding a profitable configuration is GUARANTEED
0. Choose your symbol and timeframe. Then add the Backtest version to your chart. If at any time you decide to change your timeframe, go back to step 1.
1. Open the strategy tester and look at the buy & hold line.
If it is mostly climbing (last value greater than 0) then it means we are in a bull market. You should then opt or a long only strategy.
If it is mostly dropping (last value lower than 0) then it means we are in a bear market. You should then opt or a short only strategy.
Note : This first step is really important. Trading against the market has very little chances to succeed.
2. Go into the Strategy Input Parameters:
check "Enable Long Results" and uncheck "Enable Short Results" if you are in a long only strategy.
check "Enable Short Results" and uncheck "Enable Long Results" if you are in a short only strategy.
3. Open the Strategy Tester and open the Strategy Properties.
We are going to find the base parameters for the Bands.
The "Bands Lookback" is the main parameter to configure for any strategy. It corresponds to how strong of a support and resistance the bands will behave. The lower the timeframe, the higher lookback you will need. It can move from 10 to 60. For example 60 is a good value for a 3 minute timeframe. Try different values, and look at the "net profit" value in the Overview tab of the Strategy Tester. Keep the Lookback value that shows the best net profit value.
Then play with the "Bands Smoothing" from 2 to 20 and keep the best net profit value.
The "Band Smoothing" is used to reduce noise.
Usually, the default value (10) is what gives the best results.
From this point you should already be able to have a profitable strategy (net profit>0), but we can improve it using the Stop Loss and the Take Profit feature.
4. To activate the Stop Loss feature, click on the "SECURITY" checkbox
You should see horizontal red lines appear.
A Long/short exit alert will be triggered if the price were to cross this line. (A red Xcross will appear)
Choose the Stop Loss percentage.
On top of that, you can enable the feature "Trailing Stop". It will make the red line follow the price, at a speed that you can configure with the "Trailing Speed" parameter.
Now, sometimes a stop is triggered and it was just a fakeout. You can enable "Re-entries after a stop" to avoid missing additional opportunities.
5. To activate the Take Profit feature, click on the "TAKE PROFIT" checkbox
You should see horizontal green lines appear.
A Long/short exit alert will be triggered if the price were to cross this line. (A flag will appear)
Choose the Take Profit percentage.
A low takeprofit will provide a safer strategy but can reduce potential profits.
A higher takeprofit will increase risk but can provide higher potential profits.
6. Money Management
You can configure the backtest according to your own money management.
Let's say you have 10 000 $ as initial capital and want to trade only 5%, set the Order Size to 5% of Equity.
You can increase net profit by increasing the order size but this is at your own risk.
How to create alerts explained here
Sample Uses Cases
Use it literally anywhere
This indicator can be used on any timeframe and market (not only cryptocurrencies).
About the Backtest below
The Net Profit (Gross profit - Gross loss) is calculated with a commission of 0.05% on each order.
No leverage used. This is a long strategy.
Each trade is made with 10 % of equity from an inital capital of 10 000$. The net profit can be bigger by increasing the % of equity but this a trader's rule to minimise the risk.
I am selling access to all my indicators on my website : blockchainfiesta.com
To get a 2 days free trial, just leave a comment , thanks !
Join my Discord for help, configurations, requests, etc. discord.gg
cryptomars 1.0 signal Concussion trend
Description:
1. In the indicator, there is an orange signal that fluctuates linearly. It is a buy signal when it goes from bottom to top. When the signal line remains in the upper position, it indicates a multi-party trend.
2. When it goes from top to bottom, it indicates a sell signal. When the signal line remains below, it indicates a sales trend.
3. Depending on the time level, when the position of the signal line changes, determine whether the current candle is completed or not according to the time level of the chart you selected to determine the signal. For example, if you select a chart level of 5 meters, then when the signal line changes, for example, it will send a sell signal from top to bottom. At this time, please do not rush to sell. You should wait for this 5 meter candlestick to complete. When the candle is over and the next candle is started, if the signal line remains in the top-down form, the sell signal is normal and you can sell it.
Because the position of the signal appears, it is the location of the sale. During the completion of the candlestick , the signal may disappear after disappearing. We only have to wait for a while to get a more stable deal.
4. The alarm setting is very simple. There are two lines in the indicator. One is the orange signal line that fluctuates up and down, and the other is the fixed zero line of “zero”.
We set it in the alarm. When the signal line passes "zero" from the top, the short signal is sent only when the candle map is completed. When the signal line passes "zero" from "up" below, the signal is sent for a long time when the candlestick is completed.
One trick, the appearance of the signal, is that the price runs in one direction for a while, so it appears at or near the bottom. Because, when we have already made a profit in the transaction, we can make a profit in advance, and we do not need to wait for the opposite signal to stop the profit and reduce the risk of profit retracement.
Because in this market, the fluctuations are very large, and the people who compete are also very fierce. What we need to do is to make every transaction as possible, and we are all profitable. If we sell and find that the price is still rising, please don't feel sorry, don't consider eating all the profits.
6. When the signal appears, in most cases, even in the impact trend, it will still run a distance in the direction of the signal, that is, you will profit, so please close the position and make a profit in time. Otherwise, when the price volatility is too small, you miss the profit point, the price starts to run in the opposite direction, and you may change from profit to loss.
BITMEX's trailing stop loss is a great feature, please use it flexibly.
7, if it is a shock trend, please try not to trade.
8. We recommend that you turn on the “cryptomars 3.0” and “cryptomars 2.0” indicators. No matter who signs the trade first, you can trade, which can help you get more profit.
9. Remember, I hope this indicator will be your powerful assistant, but please don't rely on it completely. Learning more trading knowledge and skills is even more important. Therefore, when we consider the profitable position, you can use your trading skills, MACD , KDJ, etc. to assist and profit in a more suitable position.
cryptomars signal short 2.0Description:
1. In the indicator, there is an orange signal that fluctuates linearly. It is a buy signal when it goes from bottom to top. When the signal line remains in the upper position, it indicates a multi-party trend.
2. When it goes from top to bottom, it indicates a sell signal. When the signal line remains below, it indicates a sales trend.
3. Depending on the time level, when the position of the signal line changes, determine whether the current candle is completed or not according to the time level of the chart you selected to determine the signal. For example, if you select a chart level of 5 meters, then when the signal line changes, for example, it will send a sell signal from top to bottom. At this time, please do not rush to sell. You should wait for this 5 meter candlestick to complete. When the candle is over and the next candle is started, if the signal line remains in the top-down form, the sell signal is normal and you can sell it.
Because the position of the signal appears, it is the location of the sale. During the completion of the candlestick , the signal may disappear after disappearing. We only have to wait for a while to get a more stable deal.
4. The alarm setting is very simple. There are two lines in the indicator. One is the orange signal line that fluctuates up and down, and the other is the fixed zero line of “zero”.
We set it in the alarm. When the signal line passes "zero" from the top, the short signal is sent only when the candle map is completed. When the signal line passes "zero" from "up" below, the signal is sent for a long time when the candlestick is completed.
One trick, the appearance of the signal, is that the price runs in one direction for a while, so it appears at or near the bottom. Because, when we have already made a profit in the transaction, we can make a profit in advance, and we do not need to wait for the opposite signal to stop the profit and reduce the risk of profit retracement.
Because in this market, the fluctuations are very large, and the people who compete are also very fierce. What we need to do is to make every transaction as possible, and we are all profitable. If we sell and find that the price is still rising, please don't feel sorry, don't consider eating all the profits.
6. When the signal appears, in most cases, even in the impact trend, it will still run a distance in the direction of the signal, that is, you will profit, so please close the position and make a profit in time. Otherwise, when the price volatility is too small, you miss the profit point, the price starts to run in the opposite direction, and you may change from profit to loss.
BITMEX's trailing stop loss is a great feature, please use it flexibly.
7, if it is a shock trend, please try not to trade.
8. We recommend that you turn on the “cryptomars 3.0” and “cryptomars 1.0” indicators. No matter who signs the trade first, you can trade, which can help you get more profit.
9. Remember, I hope this indicator will be your powerful assistant, but please don't rely on it completely. Learning more trading knowledge and skills is even more important. Therefore, when we consider the profitable position, you can use your trading skills, MACD , KDJ, etc. to assist and profit in a more suitable position.
cryptomars signal 3.0Description:
1. In the indicator, there is an orange signal that fluctuates linearly. It is a buy signal when it goes from bottom to top. When the signal line remains in the upper position, it indicates a multi-party trend.
2. When it goes from top to bottom, it indicates a sell signal. When the signal line remains below, it indicates a sales trend.
3. Depending on the time level, when the position of the signal line changes, determine whether the current candle is completed or not according to the time level of the chart you selected to determine the signal. For example, if you select a chart level of 5 meters, then when the signal line changes, for example, it will send a sell signal from top to bottom. At this time, please do not rush to sell. You should wait for this 5 meter candlestick to complete. When the candle is over and the next candle is started, if the signal line remains in the top-down form, the sell signal is normal and you can sell it.
Because the position of the signal appears, it is the location of the sale. During the completion of the candlestick , the signal may disappear after disappearing. We only have to wait for a while to get a more stable deal.
4. The alarm setting is very simple. There are two lines in the indicator. One is the orange signal line that fluctuates up and down, and the other is the fixed zero line of “zero”.
We set it in the alarm. When the signal line passes "zero" from the top, the short signal is sent only when the candle map is completed. When the signal line passes "zero" from "up" below, the signal is sent for a long time when the candlestick is completed.
One trick, the appearance of the signal, is that the price runs in one direction for a while, so it appears at or near the bottom. Because, when we have already made a profit in the transaction, we can make a profit in advance, and we do not need to wait for the opposite signal to stop the profit and reduce the risk of profit retracement.
Because in this market, the fluctuations are very large, and the people who compete are also very fierce. What we need to do is to make every transaction as possible, and we are all profitable. If we sell and find that the price is still rising, please don't feel sorry, don't consider eating all the profits.
6. When the signal appears, in most cases, even in the impact trend, it will still run a distance in the direction of the signal, that is, you will profit, so please close the position and make a profit in time. Otherwise, when the price volatility is too small, you miss the profit point, the price starts to run in the opposite direction, and you may change from profit to loss.
BITMEX's trailing stop loss is a great feature, please use it flexibly.
7, if it is a shock trend, please try not to trade.
8. We recommend that you turn on the “cryptomars 2.0” and “cryptomars 1.0” indicators. No matter who signs the trade first, you can trade, which can help you get more profit.
9. Remember, I hope this indicator will be your powerful assistant, but please don't rely on it completely. Learning more trading knowledge and skills is even more important. Therefore, when we consider the profitable position, you can use your trading skills, MACD , KDJ, etc. to assist and profit in a more suitable position.
T7 JNSARUpdated code for the T7 JNSAR system earlier published here -
Following updates made to the code
1. Buy / Sell arrows now appear when the corresponding conditions are met.
2. Support for Heikin-Ashi Candles added
3. Different Backtesting Position Sizing Algorithms added for evaluation
Also am republishing the trading rules here again with some modification
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Place an After Market Order @ Market Price with your broker after market close so that you get to execute the trade next trading day @ Market open to capture near similar price as the daily open price seen on the chart. This execution mode will give you the best chance to minimise the slippage and mimic the backtester results as closely as practically possible.
7. Follow all the 6 rules above religiously, as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Happy Trading !!! As always am looking out for your valuable feedback.
T7 JNSARJNSAR stands for Just Nifty Stop & Reverse. This is a trend following daily bar trading system for NIFTY. Original idea belongs to ILLANGO @ I coded the pine version of this system based on a request from @stocksonfire. Use it at your own risk after validation at your end. Neither me or my company is responsible for any losses you may incur using this system. Hope you like this system and enjoy trading it !!!
While trading this system you must follow these simple rules.
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Follow all the 5 rules above religiously as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
RC - Crypto Scalper v3Cryptocurrency scalping strategy for perpetual futures with risk management and automation capabilities.
## Strategy Overview
This strategy identifies high-probability scalping opportunities in cryptocurrency perpetual futures markets using adaptive position sizing, dynamic stop losses, and intelligent exit management to maintain consistent risk-adjusted returns across varying market conditions.
## Technical Foundation
The strategy employs exponential moving averages for trend detection, Bollinger Bands for volatility measurement and mean reversion signals, RSI for momentum confirmation and overbought/oversold conditions, ATR for dynamic volatility-based stop placement, and VWAP for institutional price level identification. These technical indicators are combined with volume analysis and optional multi-timeframe confirmation to filter low-probability setups.
## Entry Methodology
The strategy identifies trading opportunities using three complementary approaches that can be enabled individually or in combination:
Momentum-Based Entries: Detects directional price movements aligned with short-term and intermediate-term trend indicators, with momentum oscillator confirmation to avoid entries at exhaustion points. Volume analysis provides additional confirmation of institutional participation.
Mean Reversion Entries: Identifies price extremes using statistical volatility bands combined with momentum divergence, targeting high-probability reversal zones in ranging market conditions. Entries require initial price structure confirmation to reduce false signals.
Institutional Flow Entries: Monitors volume-weighted price levels to identify areas where institutional orders are likely concentrated, entering on confirmed breaks of these key levels with supporting directional bias from trend indicators.
Each methodology uses distinct combinations of the technical indicators mentioned above, with specific parameter relationships and confirmation requirements that can be customized based on trader preference and market conditions.
## Exit Framework
Adaptive Stop Loss: Uses ATR-based stops (default 0.7x multiplier on 14-period ATR) that automatically adjust to current market volatility. Stop distance expands during volatile periods to avoid premature stops while tightening during consolidation to protect capital. Alternative percentage-based stops available for traders preferring fixed-distance risk management.
Trailing Profit System: Employs a dual-target exit approach combining fixed limit orders with dynamic trailing stops. The system activates trailing stops when positions reach profitable thresholds, allowing winning trades to capture extended moves while protecting accumulated gains. The high fixed limit (6R default) serves as a ceiling for exceptional moves while the trailing mechanism handles the majority of exits at optimal profit levels.
Time-Based Management: Implements maximum holding period constraints (50 bars default) to prevent capital from being trapped in directionless price action. This ensures consistent capital turnover and prevents the strategy from holding through extended consolidation periods.
Breakeven Protection: Automatically adjusts stop loss to entry price plus commission costs once trades reach predefined profit thresholds (0.7R default), eliminating downside risk on positions that have demonstrated directional follow-through.
## Risk Management
Position Sizing: Dynamic position sizing based on account equity percentage risk model (2% default). Calculates optimal position size based on entry price, stop distance, and account risk tolerance. Includes maximum position exposure caps and minimum position size thresholds to ensure practical trade execution.
Daily Loss Limits: Automatic trading suspension when intraday losses exceed configured threshold (5% of equity default). Prevents catastrophic drawdown days and removes emotional decision-making during adverse market conditions. Resets automatically at the start of each new trading day.
Leverage Controls: Comprehensive leverage monitoring with built-in liquidation protection for margined positions. Strategy calculates liquidation prices based on leverage settings and automatically closes positions approaching critical margin levels, preventing forced liquidations.
Exposure Management: Multiple layers of position size controls including maximum position value as percentage of equity (50% default), leverage-adjusted margin requirements, and minimum capital availability thresholds before opening new positions.
## Market Filters
Session-Based Filtering: Configurable trading windows for Asian (00:00-08:00 UTC), London (08:00-16:00 UTC), and New York (13:00-21:00 UTC) sessions. Allows traders to focus on specific market hours or avoid illiquid periods based on their asset and trading style.
Volatility Requirements: Minimum and maximum ATR percentage thresholds ensure strategy only operates within optimal volatility ranges. Prevents trading during both insufficient movement periods and extreme volatility events where execution quality deteriorates.
Trend Alignment: Optional higher timeframe trend filter ensures directional bias aligns with broader market structure, reducing counter-trend entries during strong directional moves.
Volume Confirmation: Configurable volume requirements for entry validation, ensuring sufficient market participation and reducing false signals during low-liquidity periods.
## Automation Support
Built-in webhook integration generates JSON payloads compatible with popular broker automation platforms. Alert system provides comprehensive notifications for all entry signals, exit executions, risk limit breaches, and daily trading status updates. Supports both automated and manual execution workflows.
## Settings Explanation
Initial Capital: $5,000
Selected as realistic starting point for retail traders entering crypto futures markets. Strategy scales proportionally - larger accounts show similar percentage returns with proportionally larger absolute gains and position sizes.
Risk Per Trade: 2%
Conservative default providing significant drawdown tolerance. With 51% historical win rate and positive expectancy, risking 2% per trade allows for extended losing streaks without account impairment. Adjustable from 0.5% (very conservative) to 5% (aggressive, experienced traders only).
Leverage: 10x
Standard cross-margin leverage for cryptocurrency perpetual futures. Combined with 2% risk setting and maximum 50% equity position size caps, actual exposure remains controlled despite leverage. Built-in liquidation protection provides additional safety layer.
Commission: 0.055%
Modeled on major exchange maker fee structures (Bybit, Binance Futures).
**Slippage: 50 ticks**
Ultra-conservative slippage assumption representing extreme worst-case execution scenarios. ETH perpetual tick size is $0.01, therefore 50 ticks equals $0.50 per side or $1.00 round trip slippage per trade.
Real-world slippage on 30-minute timeframe typically ranges from 2-5 ticks ($0.02-0.05 round trip) under normal conditions, with 10-20 ticks during highly volatile periods. The 50-tick setting assumes every single trade executes during extreme market stress conditions.
This ultra-conservative modeling approach means real-world trading performance under typical market conditions may exceed backtest results, as the strategy has been tested under punishing execution cost assumptions that represent worst-case scenarios rather than expected outcomes.
Stop Loss: ATR-based (0.7x multiplier)
Volatility-adaptive stops optimized for 30-minute cryptocurrency perpetuals. The 0.7x multiplier balances protection against premature stops due to normal market noise. Lower multipliers (0.5-0.6x) suitable for lower timeframes, higher multipliers (0.8-1.2x) for higher timeframes.
Take Profit: 6R (Risk:Reward)
High target designed to work in conjunction with trailing stop system rather than as primary exit mechanism. Historical analysis shows most profitable trades exit via trailing stops at lower multiples, with the 6R limit capturing occasional extended moves. This configuration allows the trailing stop system to operate optimally while providing upside capture on exceptional price runs.
Trailing Stop: Activates at 1R | Offset 0.5R
Trailing mechanism engages when position reaches 1:1 risk-reward, then maintains 0.5R distance from peak favourable price. This configuration allows profitable trades room to develop while protecting accumulated gains from reversals.
Maximum Holding Period: 50 bars
Automatic exit trigger after 50 bars (25 hours on 30-minute timeframe) prevents capital commitment to non-trending price action. Adjustable based on timeframe and trading style preferences.
## Backtest Performance
Test Period: November 2023 - November 2025 (2 years)
Asset: ETH/USDT Perpetual Futures
Timeframe: 30 minutes
Initial Capital: $5,000
Performance Metrics:
- Final Equity: $25,353.99
- Net Profit: $20,353.99
- Total Return: 407.08%
- Annualized Return: ~204%
- Total Trades: 2,549
- Winning Trades: 1,308 (51.28%)
- Losing Trades: 1,241 (48.72%)
- Profit Factor: 1.215
- Sharpe Ratio: 0.813
- Sortino Ratio: 6.428
- Maximum Drawdown: 11.53%
- Average Drawdown: <2%
Trade Statistics:
- Average Win: 1.15% per trade
- Average Loss: -0.98% per trade
- Win/Loss Ratio: 1.17:1
- Largest Win: 7.14%
- Largest Loss: -2.31%
- Average Trade Duration: ~8 hours
- Trades Per Month: ~106
Cost Analysis:
- Total Commission Paid: $21,277.06
- Commission as % of Gross Profit: 18.5%
- Modeled Slippage Impact: $2,549.00 (50 ticks per trade)
- Total Trading Costs: $23,826.06
- Net Profit After All Costs: $20,353.99
Risk-Adjusted Performance:
- Return/Max DD Ratio: 35.3
- Profit Per Trade: $7.98 average
- Risk of Ruin: <0.001% (with 2% risk, 51% win rate, 1.17 R:R)
## Bear Market Validation
To validate robustness across different market conditions, the strategy was additionally tested during the 2022 cryptocurrency bear market:
Test Period: May 2022 - November 2022 (7 months)
Market Conditions: ETH declined 57% (from ~$2,900 to ~$1,200)
Bear Market Results:
- Net Profit: $4,959.69
- Return: 99.19%
- Total Trades: 845
- Win Rate: 51.72%
- Maximum Drawdown: 18.54%
- Profit Factor: 1.235
- Outperformance vs Buy & Hold: +156.3%
The strategy demonstrated profitable performance during severe market decline, with short positions showing particular strength (54.1% win rate on shorts vs 49.4% on longs). This validates that the edge is not dependent on bullish market conditions and the multiple entry methodologies adapt naturally to different market environments.
## Recommended Usage
Optimal Timeframes:
- Primary: 30-minute (tested and optimized)
- Alternative: 1-hour (more selective, fewer trades)
- Not recommended: <15-minute (execution quality deteriorates)
Suitable Assets:
High-liquidity cryptocurrency perpetual futures recommended:
- BTC/USDT (>$2B daily volume)
- ETH/USDT (>$1B daily volume)
- SOL/USDT, AVAX/USDT (>$100M daily volume)
- Avoid low-liquidity pairs (<$50M daily volume)
Risk Configuration:
- Conservative: 1-1.5% per trade
- Moderate: 2-3% per trade (default: 2%)
- Aggressive: 3-5% per trade (requires discipline)
## Important Considerations
Backtesting vs Live Trading: Always paper trade first. Real-world results vary based on execution quality, broker-specific factors, network latency, and individual trade management decisions. Backtest performance represents historical simulation with ultra-conservative cost assumptions, not guaranteed future results.
Market Conditions: Strategy designed for liquid, actively-traded markets. Performance characteristics:
- Strong trends: Optimal (trailing stops capture extended moves)
- Ranging markets: Moderate (mean reversion component provides edge)
- Low volatility: Reduced (ATR filter prevents most entries)
- Extreme volatility: Protected (maximum volatility filter prevents entries)
Cost Impact: Commission represents approximately 18.5% of gross profit in backtests. The 50-tick slippage assumption is deliberately punitive - typical execution will likely be 5-10x better (2-10 ticks actual vs 50 ticks modeled), meaning real-world net results may significantly exceed backtest performance under normal market conditions.
Execution Quality: 30-minute timeframe provides sufficient time for order placement and management. Automated execution recommended for consistency. Manual execution requires discipline to follow signals without hesitation or second-guessing.
Starting Procedures:
1. Run backtest on your specific asset and timeframe
2. Paper trade for minimum 50 trades or 2 weeks
3. Start with minimum position sizes (0.5-1% risk)
4. Gradually scale to target risk levels as confidence builds
5. Monitor actual execution costs vs backtest assumptions
## Strategy Limitations
- Requires liquid markets; performance degrades significantly on low-volume pairs
- No built-in news event calendar; traders should manually avoid scheduled high-impact events
- Weekend/holiday trading may experience wider spreads and different price behaviour
- Does not model spread costs (assumes mid-price fills); add 1-2 ticks additional cost for market orders
- Performance during market structure changes (regime shifts) may differ from backtest period
- Requires consistent monitoring during active trading hours for optimal automated execution
- Slippage assumptions are deliberately extreme; actual slippage will typically be much lower
## Risk Disclosure
Cryptocurrency trading involves substantial risk of loss. Leverage amplifies both gains and losses. This strategy will experience losing streaks and drawdowns. The 11.53% maximum historical drawdown in bull market testing and 18.54% in bear market testing do not represent ceilings - larger drawdowns are possible and should be expected in live trading.
Past performance does not guarantee future results. Market conditions evolve, and historical edge may diminish or disappear. No strategy works in all market conditions. The strategy has been tested with extremely conservative slippage assumptions (50 ticks per trade) that significantly exceed typical execution costs; this provides a safety margin but does not eliminate risk.
Capital at Risk: Only trade with capital you can afford to lose completely. The strategy's positive historical performance across both bull and bear markets does not eliminate the possibility of significant losses or account impairment.
Not Financial Advice: This strategy is an educational tool, not investment advice. Users are solely responsible for their trading decisions, risk management, and outcomes. The developer assumes no liability for trading losses.
Leverage Warning: Trading with leverage can result in losses exceeding initial investment. Ensure you understand leverage mechanics and liquidation risks before using leveraged products.
## Technical Requirements
- TradingView Premium subscription (for strategy testing and alerts)
- Understanding of risk management principles
- Familiarity with perpetual futures mechanics
- Broker account supporting crypto perpetuals (if trading live)
- For automation: Webhook-compatible execution platform
## Version History
v3.0 - November 2025 (Initial Release)
- Multi-methodology entry system (Momentum, Mean Reversion, VWAP)
- Comprehensive risk management framework
- Adaptive exit system with trailing stops
- Session and volatility filtering
- Webhook automation support
- Validated across bull market (2024-25) and bear market (2022) periods
- Tested with ultra-conservative 50-tick slippage assumptions
Disclaimer: This strategy is provided "as-is" for educational purposes. Past performance does not indicate future results. All backtests conducted with 50-tick slippage (ultra-conservative assumptions). Actual trading costs typically significantly lower. Trade responsibly and at your own risk.
Range Oscillator Strategy + Stoch Confirm🔹 Short summary
This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades.
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0. Legal / risk disclaimer
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• This script is FREE and public. I do not charge any fee for it.
• It is for EDUCATIONAL PURPOSES ONLY.
• It is NOT financial advice and does NOT guarantee profits.
• Backtest results can be very different from live results.
• Markets change over time; past performance is NOT indicative of future performance.
• You are fully responsible for your own trades and risk.
Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital.
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1. About default settings and risk (very important)
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The script is configured with the following defaults in the `strategy()` declaration:
• `initial_capital = 10000`
→ This is only an EXAMPLE account size.
• `default_qty_type = strategy.percent_of_equity`
• `default_qty_value = 100`
→ This means 100% of equity per trade in the default properties.
→ This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade.
TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to:
1. Open **Strategy Settings → Properties**.
2. Set:
• Order size: **Percent of equity**
• Order size (percent): e.g. **1–2%** per trade
3. Make sure **commission** and **slippage** match your own broker conditions.
• By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets.
If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading.
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2. What this strategy tries to do (conceptual overview)
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This is a LONG-ONLY strategy designed to explore the combination of:
1. **Range Oscillator (Zeiierman-based)**
- Measures how far price has moved away from an adaptive mean.
- Uses an ATR-based range to normalize deviation.
- High positive oscillator values indicate strong price expansion away from the mean in a bullish direction.
2. **Stochastic as a timing filter**
- A classic Stochastic (%K and %D) is used.
- The logic requires %K to be below a user-defined level and then crossing above %D.
- This is intended to catch moments when momentum turns up again, rather than chasing every extreme.
3. **EMA Exit Filter (trend slope)**
- An EMA with configurable length (default 70) is calculated.
- The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition.
- This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted.
4. **Optional risk-management layer**
- Percentage-based Stop Loss and Take Profit (SL/TP).
- Risk/Reward (R-multiple) exit based on the distance from entry to SL.
- Implemented as OCO orders that work *on top* of the logical exits.
The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes.
────────────────────────
3. Components and how they work together
────────────────────────
(1) Range Oscillator (based on “Range Oscillator (Zeiierman)”)
• The script computes a weighted mean price and then measures how far price deviates from that mean.
• Deviation is normalized by an ATR-based range and expressed as an oscillator.
• When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction.
• When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled).
(2) Stochastic confirmation
• Classic Stochastic (%K and %D) is calculated.
• An entry requires:
- %K to be below a user-defined “Cross Level”, and
- then %K to cross above %D.
• This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point.
(3) EMA Exit Filter
• The EMA length is configurable via `emaLength` (default 70).
• The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA.
• If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition.
• This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit.
(4) Risk management (optional)
• Stop Loss (SL) and Take Profit (TP):
- Defined as percentages relative to average entry price.
- Both are disabled by default, but you can enable them in the Inputs.
• Risk/Reward Exit:
- Uses the distance from entry to SL to project a profit target at a configurable R-multiple.
- Also optional and disabled by default.
These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first.
────────────────────────
4. Entry & Exit logic (high level)
────────────────────────
A) Time filter
• You can choose a **Start Year** in the Inputs.
• Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`).
• This prevents accidental use of tiny cherry-picked windows and makes tests more honest.
B) Entry condition (long-only)
A long entry is allowed when ALL the following are true:
1. `timeCondition` is true (inside the backtest window).
2. If `useOscEntry` is true:
- Range Oscillator value must be above `entryLevel`.
3. If `useStochEntry` is true:
- Stochastic condition (`stochCondition`) must be true:
- %K < `crossLevel`, then %K crosses above %D.
If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`.
C) Exit condition (logical exits)
A position can be closed when:
1. `timeCondition` is true AND a long position is open, AND
2. At least one of the following is true:
- If `useOscExit` is true: Oscillator is below `exitLevel`.
- If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`).
In that case, `strategy.close("Long")` is called.
D) Risk-management exits
While a position is open:
• If SL or TP is enabled:
- `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages.
• If Risk/Reward exit is enabled:
- `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance.
These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels.
────────────────────────
5. Recommended backtest configuration (to avoid misleading results)
────────────────────────
To align with TradingView House Rules and avoid misleading backtests:
1. **Initial capital**
- 10 000 (or any value you personally want to work with).
2. **Order size**
- Type: **Percent of equity**
- Size: **1–2%** per trade is a reasonable starting point.
- Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice.
3. **Commission & slippage**
- Commission: around 0.1% if that matches your broker.
- Slippage: a few ticks (e.g. 3) to account for real fills.
4. **Timeframe & markets**
- Volatile symbols (e.g. crypto like BTCUSDT, or major indices).
- Timeframes: 1H / 4H / **1D (Daily)** are typical starting points.
- I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes.
5. **No “caution warning”**
- Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages.
- If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period.
────────────────────────
5a. About low trade count and rare signals
────────────────────────
This strategy is intentionally designed to trade RARELY:
• It is **long-only**.
• It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter).
• On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest.
TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case:
• The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window.
• The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals.
• Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data.
Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample.
────────────────────────
6. How to use this strategy (step-by-step)
────────────────────────
1. Add the script to your chart.
2. Open the **Inputs** tab:
- Set the backtest start year.
- Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter.
- Optionally enable SL, TP, and Risk/Reward exits.
3. Open the **Properties** tab:
- Set a realistic account size if you want.
- Set order size to a realistic % of equity (e.g. 1–2%).
- Confirm that commission and slippage are realistic for your broker.
4. Run the backtest:
- Look at Net Profit, Max Drawdown, number of trades, and equity curve.
- Remember that a low trade count means the statistics are not very strong.
5. Experiment:
- Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params.
- See how the metrics and trade frequency change.
6. Forward-test:
- Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time.
────────────────────────
7. Originality and usefulness (why this is more than a mashup)
────────────────────────
This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component:
• Range Oscillator:
- Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric.
• Stochastic:
- Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn.
• EMA Exit Filter:
- Trend-slope-based safety net to exit when the medium-term direction changes against the position.
• Risk module:
- Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic.
It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product.
────────────────────────
8. Limitations and good practices
────────────────────────
• No single strategy works on all markets or in all regimes.
• This script is long-only; it does not short the market.
• Performance can degrade when market structure changes.
• Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit.
Good practices:
- Test on multiple symbols and timeframes.
- Focus on stability and drawdown, not only on how high the profit line goes.
- View this as a learning tool and a basis for your own research.
────────────────────────
9. Licensing and credits
────────────────────────
• Core oscillator idea & base code:
- “Range Oscillator (Zeiierman)”
- © Zeiierman, licensed under CC BY-NC-SA 4.0.
• Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer:
- Modifications by jokiniemi.
Please respect both the original license and TradingView House Rules if you fork or republish any part of this script.
────────────────────────
10. No payments / no vendor pitch
────────────────────────
• This script is completely FREE to use on TradingView.
• There is no paid subscription, no external payment link, and no private signals group attached to it.
• If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice.
Use this script as a tool to learn, experiment, and build your own understanding of markets.
────────────────────────
11. Example backtest settings used in screenshots
────────────────────────
To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration:
• Symbol: BTCUSDT (or similar major BTC pair)
• Timeframe: 1D (Daily)
• Backtest period: from 2018 to the most recent data
• Initial capital: 10 000
• Order size type: Percent of equity
• Order size: 2% per trade
• Commission: 0.1%
• Slippage: 3 ticks
• Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default
• Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled
If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
[Bybit BTCUSD.P] 7Years Backtest Results. 2,609% +Non-Repainting📊 I. Strategy Overview: Trust Backed by Numbers
The ADX Sniper v12 strategy has been rigorously tested over 7 years, from November 14, 2018 to November 8, 2025, spanning every major cycle of the Bitcoin
BTCUSD.P futures market. This strategy successfully balances two often-conflicting goals: maximizing profitability while minimizing volatility, all supported by objective performance data.
This strategy has been validated across all Bitcoin (BTCUSD.P) futures market cycles over a 7-year period.
■ Visual Proof: Bar Replay Simulation
The chart above demonstrates actual entry and exit points captured via TradingView's Bar Replay feature. The green rectangle highlights the core profitable trading zone, showing where the strategy successfully captured sustained uptrends. This visual evidence confirms:
Confirmed buy/sell signals with exact execution prices (marked in red and blue)
No repainting or signal distortion after candle close
Consistent performance across multiple market cycles within the highlighted zone
💰 Core Performance Metrics:
Cumulative Return: 2,609.14% (compounded growth over 7 years)
Maximum Drawdown (MDD): 6.999% (preserving over 93% of capital)
Average Profit/Loss Ratio: 8.003 (industry-leading risk-reward efficiency)
Total Trades: 24 (focused exclusively on high-conviction opportunities)
Sortino Ratio: 11.486 (mathematically proving robustness and stability)
✅ This strategy has been validated across all Bitcoin BTCUSD.P futures market cycles over a 7-year period.
📊 I. 전략 개요: 숫자로 입증된 신뢰
ADX Sniper v12 전략은 2018년 11월 14일부터 2025년 11월 8일까지 약 7년간 비트코인 (BTCUSD.P) 선물 시장의 모든 주요 사이클을 거치며 엄격하게 검증되었습니다. 수익성 극대화와 변동성 최소화라는 상충되는 목표를 동시에 달성한 이 전략의 핵심 성과 지표를 객관적 데이터를 통해 확인하실 수 있습니다.
본 전략은 7년간의 모든 비트코인 (BTCUSD.P) 선물 시장 사이클에서 검증되었습니다.
■ 시각적 증명: 바 리플레이 시뮬레이션
위 차트는 TradingView의 바 리플레이 기능으로 포착된 실제 진입 및 청산 시점을 보여줍니다. 녹색 네모는 핵심 수익 구간을 표시하며, 전략이 지속적인 상승 추세를 성공적으로 포착한 영역을 나타냅니다. 본 시각 자료는 다음을 입증합니다:
정확한 체결 가격이 표기된 확정된 매수/매도 신호 (빨강색과 파랑색으로 표시)
캔들 종가 후 신호 왜곡이나 리페인팅 없음
강조 표시된 구간 내 여러 시장 사이클에 걸친 일관된 성과
💰 핵심 성과 지표:
누적 수익률: 2,609.14% (7년간 복리 성장 입증)
최대 낙폭 (MDD): 6.999% (7년간 자본의 93% 이상 보존)
평균 손익비: 8.003 (업계 최고 수준의 위험-보상 효율성)
총 거래 횟수: 24회 (고확신 기회에만 집중)
소르티노 비율: 11.486 (전략의 견고성과 안정성을 수학적으로 입증)
✅ 본 전략은 7년간의 모든 비트코인 (BTCUSD.P) 선물 시장 사이클에서 검증되었습니다.
🛡️ II. Core Philosophy: Cut Losses Short, Let Profits Run
Why MDD Stays Below 7% in a Volatile Market
The crypto futures market typically experiences daily volatility exceeding 10%, with most strategies enduring drawdowns between 30% and 50%. In stark contrast, this strategy has never exceeded a 7% account loss over seven years. This exceptional low MDD is achieved through deliberate design mechanisms, not luck:
🎯 Entry Filtering: The 'ADX Pop-up Filter' is the core component. It enables the strategy to strictly avoid trading when market conditions indicate major reversals or consolidation phases, thereby minimizing exposure to high-risk zones.
🏛️ Capital Preservation Priority: The strategy prioritizes investor psychological stability and capital preservation over pursuing maximum potential returns.
The Power of an 8.003 Profit Factor
The Profit Factor measures the ratio of total profitable trades to total losing trades. It's the most critical metric for assessing risk-adjusted returns.
A Profit Factor of 8.003 means that for every dollar lost, the strategy earns an average of eight dollars. This demonstrates the efficiency of a true trend-following strategy:
Cutting losses quickly (averaging $177,419 USD loss per trade)
Riding winners for maximum extension (averaging $1,419,920 USD profit per trade)
🛡️ II. 핵심 철학: 손실은 빠르게 자르고, 수익은 끝까지
암호화폐 시장에서 MDD <7%의 의미
암호화폐 선물 시장은 일일 변동성이 10%를 초과하는 경우가 빈번하며, 일반적인 전략들은 30~50%의 MDD를 겪습니다. 이와 극명한 대조로, 본 전략은 7년간 단 한 번도 7%를 초과하는 계좌 손실을 기록하지 않았습니다. 이렇게 극도로 낮은 MDD는 운이 아닌 체계적인 메커니즘을 통해 달성되었습니다:
🎯 진입 필터링: 'ADX 팝업 필터'가 핵심 구성 요소로, 시장 상황이 주요 반전이나 횡보를 나타낼 때 거래를 엄격히 회피하여 고위험 구간 노출을 최소화합니다.
🏛️ 자본 보존 우선: 본 전략은 최대 잠재 손실을 감수하기보다 투자자의 심리적 안정성과 자본 보존을 우선시하도록 설계되었습니다.
손익비 8.003의 힘
손익비는 '총 수익 거래'와 '총 손실 거래'의 비율로, 위험 조정 수익을 측정하는 핵심 지표입니다.
8.003이라는 값은 1달러를 잃을 때마다 평균적으로 8달러 이상을 벌어들이는 구조를 의미합니다. 이는 진정한 추세 추종 전략의 최대 효율성을 보여줍니다:
손실은 빠르게 자르고 ($177,419 USD 평균 손실)
수익은 최대한 연장합니다 ($1,419,920 USD 평균 수익)
🎯 III. Strategy Reliability and Structural Edge
The Secret of 24 Trades in 7 Years
Only 24 trades over 7 years signifies that this strategy ignores 99% of market volatility and targets only the 1% of 'most certain buying cycles'. This approach eliminates the drag from excessive trading:
❌ No commission bleed
❌ No slippage erosion
❌ No psychological wear from overtrading
📈 Long-Term Trend Following: The strategy analyzes Bitcoin's long-term price cycles to capture the onset of massive trends while remaining undisturbed by short-term market noise.
Non-Repainting Structure: Alignment of Reality and Simulation
🎬 Non-Repainting Proof Video Available
※↑ "If you wish, I can also show you a video as evidence of the non-repainting throughout the 7 years."
✅ Real-Time Trading Reliability: This strategy is built with a non-repainting structure, generating buy/sell signals only after each candle's closing price is confirmed.
✅ Preventing Data Exaggeration: This design ensures that backtest results do not 'repaint' or distort past performance, guaranteeing high correlation between simulated results and actual live trading environments.
✅ Live Trading Advantage: While simulations use closing prices, live trading may allow entry at more favorable prices before candle close, potentially yielding even better execution than backtest results.
🎯 III. 전략의 신뢰성과 구조적 우위
7년간 24회 거래의 비밀
7년간 단 24회의 거래는 시장 변동성의 99%를 무시하고 오직 1%의 '가장 확실한 매수 사이클'만을 타겟으로 한다는 것을 의미합니다. 이는 과도한 거래로 인한 문제를 근본적으로 제거합니다:
❌ 수수료 소모 없음
❌ 슬리피지 침식 없음
❌ 과도한 트레이딩으로 인한 심리적 소모 없음
📈 장기 추세 추종: 비트코인 가격 역사를 지배하는 장기 사이클 분석을 활용하여, 단기 시장 노이즈에 흔들리지 않고 대규모 추세의 시작점을 포착하는 데 집중합니다.
논-리페인팅 구조: 현실과 시뮬레이션의 일치
🎬 논-리페인팅 증명 영상 제공 가능
※↑ "원하신다면 7년간 리페인팅이 없음을 증명하는 영상도 보여드릴 수 있습니다."
✅ 실시간 거래 신뢰성: 본 전략은 논-리페인팅 구조로 구축되어, 캔들의 종가가 확정된 후에만 매수/매도 신호를 생성합니다.
✅ 데이터 과장 방지: 이러한 설계는 백테스트 결과가 과거 성과를 '리페인팅'하거나 과장하지 않도록 보장하며, 시뮬레이션 결과와 실제 라이브 거래 환경 간의 높은 상관관계를 보장합니다.
✅ 라이브 실행 우위 가능성: 시뮬레이션은 종가 기준이지만, 라이브 운영 시 캔들이 마감되기 전 더 유리한 가격에 진입할 수 있어 시뮬레이션 결과보다 더 나은 실행 성과를 얻을 가능성이 있습니다.
📈 IV. Performance Summary (November 14, 2018 - November 8, 2025)
| Metric | Value || Metric | Value |
|--------|-------|
| Initial Capital | $1,000,000 |
| Net Profit | +$26,091,383.74 |
| Cumulative Return | +2,609.14% |
| Maximum Drawdown | -6.999% |
| Total Trades | 24 |
| Winning Trades | 19 (79.17%) |
| Losing Trades | 5 (20.83%) |
| Avg Winning Trade | +$1,419,920.16 |
| Avg Losing Trade | -$177,419.86 |
| Profit Factor | 8.003 |
| Sortino Ratio | 11.486 |
| Win/Loss Ratio | 8.003 |
⚙️ Default Settings:
Slippage: 0 ticks
Commission: 0.333% (Bybit standard)
📈 IV. 성과 지표 요약 (2018년 11월 14일 ~ 2025년 11월 8일)
|| 지표 | 값 |
|--------|-------|
| 초기 자본 | $1,000,000 |
| 순이익 | +$26,091,383.74 |
| 누적 수익률 | +2,609.14% |
| 최대 낙폭 | -6.999% |
| 총 거래 횟수 | 24 |
| 수익 거래 | 19 (79.17%) |
| 손실 거래 | 5 (20.83%) |
| 평균 수익 거래 | +$1,419,920.16 |
| 평균 손실 거래 | -$177,419.86 |
| 손익비 | 8.003 |
| 소르티노 비율 | 11.486 |
| 평균 손익 비율 | 8.003 |
⚙️ 기본 설정:
슬리피지: 0틱 (기본값)
수수료: 0.333% (Bybit 표준)
👥 V. Who Is This Strategy For?
✅ Long-term Bitcoin investors seeking stable, low-drawdown returns
✅ Traders tired of overtrading who prefer surgical, sniper-style precision entries
✅ Investors seeking psychological stability by avoiding large account swings
✅ Data-driven decision makers who value proven performance over marketing claims
👥 V. 이 전략은 누구를 위한 것인가요?
✅ 안정적이고 낮은 낙폭의 수익을 추구하는 장기 비트코인 투자자
✅ 과도한 매매에 지친 트레이더로 저격수 스타일의 정밀한 진입을 선호하는 분
✅ 큰 계좌 변동을 피하여 심리적 안정성을 추구하는 투자자
✅ 주장보다 검증된 객관적 성과를 중시하는 데이터 기반 의사 결정자
🔒 VI. Access & Disclaimer
🔐 Access Type: Invite-Only (Protected Source Code)
💬 How to Get Access: Send a private message or leave a comment below
⚠️ Important Disclaimer:
Past performance does not guarantee future results. Cryptocurrency and futures trading involve substantial risk of loss. This strategy is provided for educational and informational purposes only. Users should conduct their own research and consult with a financial advisor before making investment decisions. The author is not responsible for any financial losses incurred from using this strategy.
🔒 VI. 접근 방법 및 면책사항
🔐 접근 유형: 초대 전용 (소스코드 보호)
💬 접근 방법: 비공개 메시지 또는 아래 댓글 남기기
⚠️ 중요 면책사항:
과거 성과가 미래 결과를 보장하지 않습니다. 암호화폐 및 선물 거래는 상당한 손실 위험을 수반합니다. 본 전략은 교육 및 정보 제공 목적으로만 제공됩니다. 사용자는 투자 결정을 내리기 전 자체 조사를 수행하고 재무 자문가와 상담해야 합니다. 저자는 본 전략 사용으로 인한 재정적 손실에 대해 책임지지 않습니다.
🏷️ VII. Tags
Bitcoin |Bitcoin | BTCUSD | BTCUSD.P | Bybit | DailyChart | LongTerm | TrendFollowing | ADX | NonRepainting | Strategy | BacktestProven | SevenYears | LowDrawdown | HighProfitFactor | StableReturns | CapitalPreservation | Ichimoku | DMI | SuperTrend | TechnicalAnalysis | Volatility | RiskManagement | AutoTrading | Futures | PerpetualFutures | AlgorithmicTrading | SystematicTrading | DataDriven | InviteOnly | ProtectedScript | SnipperTrading | HighConviction | MDD | SortinoRatio
🏷️ VII. 태그
비트코인 |비트코인 | BTCUSD | BTCUSD.P | 바이비트 | 일봉 | 장기투자 | 추세추종 | ADX | 논리페인팅 | 전략 | 백테스트검증 | 7년검증 | 저낙폭 | 고손익비 | 안정수익 | 자본보존 | 일목균형표 | DMI | 슈퍼트렌드 | 기술적분석 | 변동성 | 위험관리 | 자동매매 | 선물 | 무기한선물 | 알고리즘트레이딩 | 시스템트레이딩 | 데이터기반 | 초대전용 | 보호스크립트 | 저격수트레이딩 | 고확신 | MDD | 소르티노비율
📌 Note: This strategy is designed exclusively for Bybit BTCUSD.P perpetual futures on the 1-day (daily) timeframe. Performance may vary significantly on other symbols or timeframes.
📌 참고: 본 전략은 Bybit BTCUSD.P 무기한 선물 계약의 1일봉(Daily) 타임프레임에 전용으로 설계되었습니다. 다른 심볼이나 타임프레임에서는 성과가 크게 달라질 수 있습니다.
[Bybit BTCUSD.P] 7Years Backtest Results. 2,609% +Non-Repainting
📊 I. Strategy Overview: Trust Backed by Numbers
The ADX Sniper v12 strategy has been rigorously tested over 7 years, from November 14, 2018 to November 8, 2025, spanning every major cycle of the Bitcoin BTCUSD.P futures market. This strategy successfully balances two often-conflicting goals: maximizing profitability while minimizing volatility, all supported by objective performance data.
This strategy has been validated across all Bitcoin (BTCUSD.P) futures market cycles over a 7-year period.
■ Visual Proof: Bar Replay Simulation
The chart above demonstrates actual entry and exit points captured via TradingView's Bar Replay feature. The green rectangle highlights the core profitable trading zone, showing where the strategy successfully captured sustained uptrends. This visual evidence confirms:
1) Confirmed buy/sell signals with exact execution prices (marked in red and blue)
2) No repainting or signal distortion after candle close
3) Consistent performance across multiple market cycles within the highlighted zone
💰 Core Performance Metrics:
Cumulative Return : 2,609.14% (compounded growth over 7 years)
Maximum Drawdown (MDD) : 6.999% (preserving over 93% of capital)
Average Profit/Loss Ratio : 8.003 (industry-leading risk-reward efficiency)
Total Trades : 24 (focused exclusively on high-conviction opportunities)
Sortino Ratio : 11.486 (mathematically proving robustness and stability)
✅ This strategy has been validated across all Bitcoin BTCUSD.P futures market cycles over a 7-year period.
🛡️ II. Core Philosophy: Cut Losses Short, Let Profits Run
Why MDD Stays Below 7% in a Volatile Market
The crypto futures market typically experiences daily volatility exceeding 10%, with most strategies enduring drawdowns between 30% and 50%. In stark contrast, this strategy has never exceeded a 7% account loss over seven years. This exceptional low MDD is achieved through deliberate design mechanisms, not luck:
🎯 Entry Filtering: The 'ADX Pop-up Filter' is the core component. It enables the strategy to strictly avoid trading when market conditions indicate major reversals or consolidation phases, thereby minimizing exposure to high-risk zones.
🏛️ Capital Preservation Priority: The strategy prioritizes investor psychological stability and capital preservation over pursuing maximum potential returns.
The Power of an 8.003 Profit Factor
The Profit Factor measures the ratio of total profitable trades to total losing trades. It's the most critical metric for assessing risk-adjusted returns.
A Profit Factor of 8.003 means that for every dollar lost, the strategy earns an average of eight dollars. This demonstrates the efficiency of a true trend-following strategy:
Cutting losses quickly (averaging $177,419 USD loss per trade)
Riding winners for maximum extension (averaging $1,419,920 USD profit per trade)
🎯 III. Strategy Reliability and Structural Edge
The Secret of 24 Trades in 7 Years
Only 24 trades over 7 years signifies that this strategy ignores 99% of market volatility and targets only the 1% of 'most certain buying cycles'. This approach eliminates the drag from excessive trading:
❌ No commission bleed
❌ No slippage erosion
❌ No psychological wear from overtrading
📈 Long-Term Trend Following: The strategy analyzes Bitcoin's long-term price cycles to capture the onset of massive trends while remaining undisturbed by short-term market noise.
Non-Repainting Structure: Alignment of Reality and Simulation
🎬 Non-Repainting Proof Video Available
※↑ "If you wish, I can also show you a video as evidence of the non-repainting throughout the 7 years."
✅ Real-Time Trading Reliability: This strategy is built with a non-repainting structure, generating buy/sell signals only after each candle's closing price is confirmed.
✅ Preventing Data Exaggeration: This design ensures that backtest results do not 'repaint' or distort past performance, guaranteeing high correlation between simulated results and actual live trading environments.
✅ Live Trading Advantage: While simulations use closing prices, live trading may allow entry at more favorable prices before candle close, potentially yielding even better execution than backtest results.
📈 IV. Performance Summary (November 14, 2018 - November 8, 2025)
|| Metric | Value |
|--------|-------|
| Initial Capital | $1,000,000 |
| Net Profit | +$26,091,383.74 |
| Cumulative Return | +2,609.14% |
| Maximum Drawdown | -6.999% |
| Total Trades | 24 |
| Winning Trades | 19 (79.17%) |
| Losing Trades | 5 (20.83%) |
| Avg Winning Trade | +$1,419,920.16 |
| Avg Losing Trade | -$177,419.86 |
| Profit Factor | 8.003 |
| Sortino Ratio | 11.486 |
| Win/Loss Ratio | 8.003 |
⚙️ Default Settings:
Slippage: 0 ticks
Commission: 0.333% (Bybit standard)
👥 V. Who Is This Strategy For?
✅ Long-term Bitcoin investors seeking stable, low-drawdown returns
✅ Traders tired of overtrading who prefer surgical, sniper-style precision entries
✅ Investors seeking psychological stability by avoiding large account swings
✅ Data-driven decision makers who value proven performance over marketing claims
🔒 VI. Access & Disclaimer
🔐 Access Type: Invite-Only (Protected Source Code)
💬 How to Get Access: Send a private message or leave a comment below
⚠️ Important Disclaimer:
Past performance does not guarantee future results. Cryptocurrency and futures trading involve substantial risk of loss. This strategy is provided for educational and informational purposes only. Users should conduct their own research and consult with a financial advisor before making investment decisions. The author is not responsible for any financial losses incurred from using this strategy.
🏷️ VII. Tags
Bitcoin |Bitcoin | BTCUSD | BTCUSD.P | Bybit | DailyChart | LongTerm | TrendFollowing | ADX | NonRepainting | Strategy | BacktestProven | SevenYears | LowDrawdown | HighProfitFactor | StableReturns | CapitalPreservation | Ichimoku | DMI | SuperTrend | TechnicalAnalysis | Volatility | RiskManagement | AutoTrading | Futures | PerpetualFutures | AlgorithmicTrading | SystematicTrading | DataDriven | InviteOnly | ProtectedScript | SnipperTrading | HighConviction | MDD | SortinoRatio
📌 Note: This strategy is designed exclusively for Bybit BTCUSD.P perpetual futures on the 1-day (daily) timeframe. Performance may vary significantly on other symbols or timeframes.
Tight Entry Trend Engine Strategy═══════════════════════════════════════
TIGHT ENTRY TREND ENGINE
═══════════════════════════════════════
A breakout-based trend-following system designed to capture explosive
moves by entering at precise resistance/support breakouts with minimal
entry risk and massive profit potential.
⚠️ LOW WIN RATE, HIGH REWARD SYSTEM ⚠️
This is NOT a high win-rate strategy. Expect 25-35% winners, but
when it hits, winners are typically 10X+ larger than losers.
═══════════════════════════════════════
🎯 WHAT THIS SYSTEM DOES
═══════════════════════════════════════
The Tight Entry Trend Engine identifies powerful breakout opportunities
by detecting when price breaks through established trendlines with
confirmation from higher timeframe trends:
1. DYNAMIC TRENDLINE DETECTION (3 BANKS)
• Automatically draws support and resistance trendlines
• 3 separate "banks" capture short-term, medium-term, and long-term levels
• Each bank has configurable parameters (required pivot touch count,
angle limits, lengths)
2. BREAKOUT ENTRY TIMING
• Enters LONG when price breaks ABOVE resistance trendlines
• Enters SHORT when price breaks BELOW support trendlines
• Entry Alert occurs at the exact moment of breakout = "tight entry"
• Stop-loss placed just below/above the broken trendline (configurable)
3. HIGHER TIMEFRAME TREND FILTER
• Uses Hull Moving Average (HMA) on higher timeframe for trend following
• Auto-adjusts HTF based on your chart timeframe
• Optional filters prevent entries against major trend
• Optional "overextension" filter avoids buying parabolic moves
4. VOLATILITY-ADAPTIVE RISK MANAGEMENT
• Stop-loss calculated using Average True Range (ATR)
• Tighter stops = better R:R
• Profit targets adjust dynamically with volatility
• Breakeven stop moves automatically when in profit
• Extended profit targets when far from HTF trend
═══════════════════════════════════════
📊 HOW IT WORKS (METHODOLOGY)
═══════════════════════════════════════
STEP 1: TRENDLINE FORMATION
The system continuously scans for pivot highs and pivot lows to
construct trendlines. You control:
BANK 1 (Short-Term):
- Pivot Length: How many bars to look back for swing points
- Min Touches: How many pivots needed to form a line (default: 3)
- Max Length: How far back lines can reach (default: 180 bars)
- Angle Limits: Maximum steepness allowed for valid trendlines
- Tolerance: How close pivots must align to form horizontal lines
BANK 2 (Medium-Term):
- Slightly longer pivot periods for more significant levels
- Captures medium-term trend structure
- Default Max Length: 200 bars
BANK 3 (Long-Term):
- Focuses on major support/resistance zones
- Often uses horizontal levels (angled lines disabled by default)
- Default Max Length: 300 bars
The system draws RESISTANCE lines (red) above price and SUPPORT
lines (green) below price. These adapt in real-time as new pivots form.
STEP 2: BREAKOUT DETECTION
LONG SIGNALS:
- Price closes above a resistance trendline
- Higher timeframe trend is up (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
SHORT SIGNALS:
- Price closes below a support trendline
- Higher timeframe trend is down (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
The "tight" aspect: Because you're entering right at the trendline
break, your stop-loss can be placed very close (just below the
broken resistance for longs), creating exceptional risk/reward ratios.
STEP 3: POSITION SIZING
Choose between:
- Fixed $ Risk Per Trade: Risk same dollar amount every trade
- % Risk Per Trade: Risk percentage of current equity
Position size automatically calculated based on:
- Your risk amount
- Distance to stop-loss (ATR-based)
- Works with stocks, futures, crypto (auto-adjusts for contract multipliers)
STEP 4: EXIT MANAGEMENT
Multiple exit methods working together:
- PROFIT TARGET: Exits when profit reaches 100x your risk
- EXTENDED PROFIT: Earlier exit (80R) when very far from HTF trend
- STOP LOSS: Fixed ATR-based stop below entry
- HTF TREND EXIT: Exits when price crosses below HTF trend with profit
- BREAKEVEN PULLBACK: Exits if profit drops below 0.6R after reaching breakeven
- PARTIAL PROFITS: Optional - take partial profits at specified R-multiple
═══════════════════════════════════════
🔧 KEY COMPONENTS EXPLAINED
═══════════════════════════════════════
HULL MOVING AVERAGE (HMA)
A smoothed moving average that reduces lag compared to traditional
MAs. The system uses HMA on a higher timeframe to determine the
dominant trend direction. You can choose:
- Auto HTF: System picks appropriate HTF based on your chart timeframe
- Manual HTF: You specify the higher timeframe
AVERAGE TRUE RANGE (ATR)
Measures current market volatility. Used for:
- Stop-loss distance (tighter when volatility low)
- Profit targets (larger when volatility high)
- Position sizing (smaller positions in volatile conditions)
- Breakeven trigger distance
TRENDLINE ANGLE FILTERING
Each trendline bank has angle limits to ensure quality:
- Resistance lines: Max downward/upward slope allowed
- Support lines: Max downward/upward slope allowed
- Angles automatically adjust based on current volatility
- Prevents overly steep/unreliable trendlines
SENSITIVITY CONTROL
One master slider adjusts multiple parameters:
- Trendline detection sensitivity
- HTF MA length
- Exit timing
- Auto-adjusts for daily+ timeframes (60% increase)
═══════════════════════════════════════
⚙️ WHAT YOU SEE ON YOUR CHART
═══════════════════════════════════════
TRENDLINES:
✓ Red resistance lines above price
✓ Green support lines below price
✓ Orange broken lines (past breakouts)
✓ Lines extend to show current levels
HTF TREND:
✓ Thick colored line showing higher timeframe trend
✓ Color gradient: Red (bearish) → Orange → Yellow → Green (bullish)
✓ 250-bar smoothed curve for visual clarity
ENTRY/EXIT SIGNALS:
✓ Small green dot below bar = Long entry
✓ Small red dot above bar = Short entry
✓ Small red dot above = Long exit
✓ Small black dot below = Short exit
OPTIONAL DETAILED LABELS:
✓ Bank number that triggered entry (Bank 1, 2, or 3)
✓ Exit reason (Profit Target, Stop Loss, HTF Exit, etc.)
✓ Partial profit notifications
POSITION TRACKING:
✓ Yellow dashed line at entry price (extends right)
✓ Green/red fill showing current profit/loss zone
✓ Lime arrows at top = Currently in long position
✓ Red arrows at bottom = Currently in short position
✓ Gray background = No position (flat)
STATS TABLE (Top Right):
✓ Current position (LONG/SHORT/FLAT)
✓ Risk per trade ($ or %)
✓ Entry price
✓ Unrealized P/L in dollars
✓ P/L in R-multiples (how many R's profit/loss)
✓ Average winner/loser R ($ mode) OR CAGR (% mode)
═══════════════════════════════════════
📈 OPTIMAL USAGE
═══════════════════════════════════════
BEST ASSETS:
- NASDAQ:QQQ on 1-hour (reg) chart ⭐ (PRIMARY OPTIMIZATION)
- Strong trending stocks: NVDA, AAPL, TSLA, MSFT, GOOGL, AMZN
- High volatility tech stocks
- Crypto: BTC, ETH
- Any liquid asset with clear trends and momentum (GOLD)
AVOID:
- Low volatility stocks
- Ranging/choppy markets
- Penny stocks or illiquid assets
- Assets without clear directional movement
BEST TIMEFRAMES:
- PRIMARY: 1-hour charts (optimal for QQQ)
- ALSO EXCELLENT: 2H, 4H, 8H
- WORKS: 15min, 30min (only momentum leaders, more noise)
- WORKS WITH ADJUSTMENTS: 1D, 2D (decrease trendline pivot lengths)
═══════════════════════════════════════
📊 BACKTEST RESULTS (QQQ 1H (Reg hours), 1999-2024)
═══════════════════════════════════════
The system showed on NASDAQ:QQQ 1-hour timeframe (regular hours):
- Total Return: 1,100,000%+ over 24 years
- Total Trades: 500+
- Win Rate: ~20-24% (LOW - this is by design!)
- Average Winner: 8-15% gain
- Average Loser: 2-4% loss
- Win/Loss Ratio: 10:1 (winners much bigger than losers)
- Profit Factor: 3+
- Max Drawdown: 45-50%
- Risk per trade: 3% of capital
KEY INSIGHT: This is a LOW WIN RATE, HIGH REWARD system. You will
lose more trades than you win, but the few winners are so large
they more than compensate for many small losses.
IMPORTANT: These are backtested results using optimal parameters
on historical data. Real trading results will vary based on:
- Your execution and timing
- Slippage and commissions
- Your emotional discipline
- Market conditions during your trading period
═══════════════════════════════════════
🎓 WHO IS THIS FOR?
═══════════════════════════════════════
IDEAL FOR:
✓ Swing traders comfortable holding winners for longer period
✓ Part-time traders (1H = check 2-3x per day)
✓ Traders seeking exceptional risk/reward ratios
✓ Those comfortable with low win rates if winners are huge
✓ Technical analysis enthusiasts
✓ Breakout traders
✓ Trend followers
═══════════════════════════════════════
🚀 GETTING STARTED - STEP BY STEP
═══════════════════════════════════════
STEP 1: APPLY TO YOUR CHART
- Search "Tight Entry Trend Engine" in indicators
- Click to apply to your chart
- Trendlines and HTF line will appear immediately
STEP 2: CHOOSE YOUR SETTINGS
For BEGINNERS - Use These Settings First:
1. Trade Direction & Filters:
• ENABLE LONGS: ✓ ON
• ENABLE SHORTS: ✗ OFF (start with longs only)
• Sensitivity: 1.0 (default)
• HTF Trend Entry Filter: ✓ ON (safer entries)
• Block Entries When Overextended: ✓ ON (avoid parabolic tops)
2. Position Sizing & Risk:
• Position Sizing: "Per Risk"
• RISK Type: "$ Per Trade"
• Risk Amount: $200 (or 1-3% of your account)
3. Visual Settings:
• Show Support Lines: ✗ OFF (unless trading shorts)
• Show Detailed Entry/Exit Labels: ✓ ON
• Show Stats Table: ✓ ON
• Show Entry Line & P/L Fill: ✓ ON
4. Leave everything else at DEFAULT for now
STEP 3: UNDERSTAND WHAT YOU SEE
When trendlines appear:
- RED lines above = Resistance (watch for price breaking UP through these)
- GREEN lines below = Support (watch for price breaking DOWN)
- When price breaks a red line = Potential LONG entry
- When price breaks a green line = Potential SHORT entry
The HTF trend line (thick colored):
- Green/lime = Strong uptrend (favorable for longs)
- Red = Strong downtrend (favorable for shorts if enabled)
- Orange/yellow = Transitioning
STEP 4: OBSERVE SIGNALS
- Small GREEN dot below bar = System entered LONG
- Small RED dot above bar = System exited LONG
- Check the label to see which "Bank" triggered (Bank 1, 2, or 3)
- Watch the yellow entry line and colored fill show your P/L
STEP 5: PAPER TRADE FIRST
- Use TradingView's paper trading feature
- Watch how signals perform on YOUR chosen asset
- Understand the win rate will be LOW (20-35%)
- Verify that winners are indeed much larger than losers
- Test for at least 20-30 signals before going live
STEP 6: OPTIMIZE FOR YOUR ASSET (OPTIONAL)
If default settings aren't working well:
For FASTER signals (more trades):
- Reduce Pivot Length 1 to 3-4
- Reduce Max Length 1 to 120-150
- Increase Sensitivity to 1.2-1.5
For SLOWER signals (higher quality):
- Increase Pivot Length 1 to 7-10
- Increase Max Length 1 to 250+
- Decrease Sensitivity to 0.7-0.9
For DAILY timeframes:
- Increase all Pivot Lengths by 30-50%
- Increase all Max Lengths significantly
- Sensitivity: 0.6-0.8
═══════════════════════════════════════
⚙️ ADVANCED SETTINGS EXPLAINED
═══════════════════════════════════════
TRENDLINE BANK SETTINGS:
Each bank (1, 2, 3) has these parameters:
- Min Touches: Minimum pivots to form a line
- Lower (2) = More lines, earlier detection
- Higher (4+) = Fewer lines, higher quality
- Pivot Length: Lookback for swing points
- Lower (3-5) = Reacts to recent price action
- Higher (10+) = Only major swing points
- Max Length: How old a trendline can be
- Shorter (100-150) = Only recent lines
- Longer (300+) = Include historical levels
- Tolerance: Alignment strictness for horizontal lines
- Lower (3.0-3.5) = Very strict horizontal
- Higher (4.5+) = More forgiving alignment
- Allow Angled Lines: Enable diagonal trendlines
- ON = Catches sloped support/resistance
- OFF = Only horizontal levels
- Angle Limits: Maximum steepness allowed
- Lower (1-2) = Only gentle slopes
- Higher (4-6) = Accept steeper angles
- Automatically adjusts for volatility
ATR MULTIPLIERS:
- STOP LOSS ATR (0.6): Distance to stop-loss
- Lower (0.4-0.5) = Tighter stops, stopped out more
- Higher (0.8-1.0) = Wider stops, more room
- PROFIT TARGET ATR (100): Main profit target
- This is 100x your risk = 10,000% R:R
- Lower (50-80) = Take profits sooner
- Higher (120+) = Let winners run longer
- BREAKEVEN ATR (40): When to move stop to breakeven
- Lower (20-30) = Protect profits earlier
- Higher (60+) = Give more room before protecting
HIGHER TIMEFRAME:
- Auto HTF: Automatically selects appropriate HTF
- 5min chart → uses 2H
- 15-30min → uses 6H
- 1-4H → uses 2D
- Daily → uses 4D
- HTF MA Length (300): HMA period for trend
- Lower (150-250) = More responsive
- Higher (400-500) = Smoother, less whipsaw
- HTF Trend Following Exit: Exits when crossing HTF
- ON = Additional exit method
- OFF = Rely only on profit targets/stops
- HTF Trend Entry Filter: Only trade with HTF trend
- ON = Safer, fewer signals
- OFF = More aggressive, more signals
- Block Entries When Overextended: Prevents chasing
- ON = Avoids parabolic tops/bottoms
- OFF = Enter all breakouts regardless
═══════════════════════════════════════
💡 TRADING PHILOSOPHY & EXPECTATIONS
═══════════════════════════════════════
This system is built on one core principle:
"ACCEPT SMALL, FREQUENT LOSSES TO CAPTURE RARE, MASSIVE WINS"
What this means:
- You WILL lose 65%-75% of your trades
- Most losses will be small (1-2R)
- Some winners hit 80R+
- Over time, math works in your favour
AltCoin & MemeCoin Index Correlation [Eddie_Bitcoin]🧠 Philosophy of the Strategy
The AltCoin & MemeCoin Index Correlation Strategy by Eddie_Bitcoin is a carefully engineered trend-following system built specifically for the highly volatile and sentiment-driven world of altcoins and memecoins.
This strategy recognizes that crypto markets—especially niche sectors like memecoins—are not only influenced by individual price action but also by the relative strength or weakness of their broader sector. Hence, it attempts to improve the reliability of trading signals by requiring alignment between a specific coin’s trend and its sector-wide index trend.
Rather than treating each crypto asset in isolation, this strategy dynamically incorporates real-time dominance metrics from custom indices (OTHERS.D and MEME.D) and combines them with local price action through dual exponential moving average (EMA) crossovers. Only when both the asset and its sector are moving in the same direction does it allow for trade entries—making it a confluence-based system rather than a single-signal strategy.
It supports risk-aware capital allocation, partial exits, configurable stop loss and take profit levels, and a scalable equity-compounding model.
✅ Why did I choose OTHERS.D and MEME.D as reference indices?
I selected OTHERS.D and MEME.D because they offer a sector-focused view of crypto market dynamics, especially relevant when trading altcoins and memecoins.
🔹 OTHERS.D tracks the market dominance of all cryptocurrencies outside the top 10 by market cap.
This excludes not only BTC and ETH, but also major stablecoins like USDT and USDC, making it a cleaner indicator of risk appetite across true altcoins.
🔹 This is particularly useful for detecting "Altcoin Season"—periods where capital rotates away from Bitcoin and flows into smaller-cap coins.
A rising OTHERS.D often signals the start of broader altcoin rallies.
🔹 MEME.D, on the other hand, captures the speculative behavior of memecoin segments, which are often driven by retail hype and social media activity.
It's perfect for timing momentum shifts in high-risk, high-reward tokens.
By using these indices, the strategy aligns entries with broader sector trends, filtering out noise and increasing the probability of catching true directional moves, especially in phases of capital rotation and altcoin risk-on behavior.
📐 How It Works — Core Logic and Execution Model
At its heart, this strategy employs dual EMA crossover detection—one pair for the asset being traded and one pair for the selected market index.
A trade is only executed when both EMA crossovers agree on the direction. For example:
Long Entry: Coin's fast EMA > slow EMA and Index's fast EMA > slow EMA
Short Entry: Coin's fast EMA < slow EMA and Index's fast EMA < slow EMA
You can disable the index filter and trade solely based on the asset’s trend just to make a comparison and see if improves a classic EMA crossover strategy.
Additionally, the strategy includes:
- Adaptive position sizing, based on fixed capital or current equity (compound mode)
- Take Profit and Stop Loss in percentage terms
- Smart partial exits when trend momentum fades
- Date filtering for precise backtesting over specific timeframes
- Real-time performance stats, equity tracking, and visual cues on chart
⚙️ Parameters & Customization
🔁 EMA Settings
Each EMA pair is customizable:
Coin Fast EMA: Default = 47
Coin Slow EMA: Default = 50
Index Fast EMA: Default = 47
Index Slow EMA: Default = 50
These control the sensitivity of the trend detection. A wider spread gives smoother, slower entries; a narrower spread makes it more responsive.
🧭 Index Reference
The correlation mechanism uses CryptoCap sector dominance indexes:
OTHERS.D: Dominance of all coins EXCLUDING Top 10 ones
MEME.D: Dominance of all Meme coins
These are dynamically calculated using:
OTHERS_D = OTHERS_cap / TOTAL_cap * 100
MEME_D = MEME_cap / TOTAL_cap * 100
You can select:
Reference Index: OTHERS.D or MEME.D
Or disable the index reference completely (Don't Use Index Reference)
💰 Position Sizing & Risk Management
Two capital allocation models are supported:
- Fixed % of initial capital (default)
- Compound profits, which scales positions as equity grows
Settings:
- Compound profits?: true/false
- % of equity: Between 1% and 200% (default = 10%)
This is critical for users who want to balance growth with risk.
🎯 Take Profit / Stop Loss
Customizable thresholds determine automatic exits:
- TakeProfit: Default = 99999 (disabled)
- StopLoss: Default = 5 (%)
These exits are percentage-based and operate off the entry price vs. current close.
📉 Trend Weakening Exit (Scale Out)
If the position is in profit but the trend weakens (e.g., EMA color signals trend loss), the strategy can partially close a configurable portion of the position:
- Scale Position on Weak Trend?: true/false
- Scaled Percentage: % to close (default = 65%)
This feature is useful for preserving profits without exiting completely.
📆 Date Filter
Useful for segmenting performance over specific timeframes (e.g., bull vs bear markets):
- Filter Date Range of Backtest: ON/OFF
- Start Date and End Date: Custom time range
OTHER PARAMETERS EXPLANATION (Strategy "Properties" Tab):
- Initial Capital is set to 100 USD
- Commission is set to 0.055% (The ones I have on Bybit)
- Slippage is set to 3 ticks
- Margin (short and long) are set to 0.001% to avoid "overspending" your initial capital allocation
📊 Visual Feedback and Debug Tools
📈 EMA Trend Visualization
The slow EMA line is dynamically color-coded to visually display the alignment between the asset trend and the index trend:
Lime: Coin and index both bullish
Teal: Only coin bullish
Maroon: Only index bullish
Red: Both bearish
This allows for immediate visual confirmation of current trend strength.
💬 Real-Time PnL Labels
When a trade closes, a label shows:
Previous trade return in % (first value is the effective PL)
Green background for profit, Red for losses.
📑 Summary Table Overlay
This table appears in a corner of the chart (user-defined) and shows live performance data including:
Trade direction (yellow long, purple short)
Emojis: 💚 for current profit, 😡 for current loss
Total number of trades
Win rate
Max drawdown
Duration in days
Current trade profit/loss (absolute and %)
Cumulative PnL (absolute and %)
APR (Annualized Percentage Return)
Each metric is color-coded:
Green for strong results
Yellow/orange for average
Red/maroon for poor performance
You can select where this appears:
Top Left
Top Right
Bottom Left
Bottom Right (default)
📚 Interpretation of Key Metrics
Equity Multiplier: How many times initial capital has grown (e.g., “1.75x”)
Net Profit: Total gains including open positions
Max Drawdown: Largest peak-to-valley drop in strategy equity
APR: Annualized return calculated based on equity growth and days elapsed
Win Rate: % of profitable trades
PnL %: Percentage profit on the most recent trade
🧠 Advanced Logic & Safety Features
🛑 “Don’t Re-Enter” Filter
If a trade is closed due to StopLoss without a confirmed reversal, the strategy avoids re-entering in that same direction until conditions improve. This prevents false reversals and repetitive losses in sideways markets.
🧷 Equity Protection
No new trades are initiated if equity falls below initial_capital / 30. This avoids overleveraging or continuing to trade when capital preservation is critical.
Keep in mind that past results in no way guarantee future performance.
Eddie Bitcoin
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Btc and Eth 5 min winnerWhat the Strategy Does
Finding the Trend (Like Watching the Bus Move): The strategy uses special tools called Hull Moving Averages (HMAs) to figure out if Bitcoin (BTC) Ethereum (ETH) prices are generally going up or down. It looks at short-term (5 minutes) and long-term (10 minutes) price movements to make sure the “bus” (the market) is moving strongly in one direction—up for buying, down for selling.
Spotting Good Times to Jump On (Buy or Sell Signals): It looks for two types of opportunities:
Pullbacks: When the price dips a little while still moving up (like the bus slowing down but not stopping), it’s a chance to buy.
Breakouts: When the price suddenly jumps higher after being stuck (like the bus speeding up), it’s another chance to buy. It does the opposite for selling when prices are dropping.
It also checks if there’s enough “passenger activity” (volume) and momentum (speed of price change) to make sure it’s a good move.
Avoiding Traffic Jams (Filters): The strategy uses tools like RSI (to check if the market’s too fast or too slow), volume (to see if enough people are trading), and ATR (to measure how wild the price swings are). It skips trades if things look too chaotic or if the trend isn’t strong enough.
Setting Safety Stops and Profit Targets: Once you’re on the “bus,” it sets rules to protect you:
Stop-Loss: If the price moves against you by a small amount (0.5% of the typical price swing), you jump off to avoid losing too much—think of it as getting off before the bus crashes.
Take-Profit: If the price moves in your favor by a small amount (1.0% of the typical swing), you cash out—imagine getting off at your stop with a profit.
Trailing Stop: If the price keeps moving your way, it adjusts your exit point to lock in more profit, like moving your stop closer as the bus keeps going.
Using Leverage (10x Boost): This strategy uses 10x leverage on Binance futures, meaning for every $1 you have, you trade like you have $10. This can make profits (or losses) 10 times bigger, so it’s risky but can be rewarding if you’re careful.
Why 5 Minutes and Bitcoin and Ethereum?
5-Minute Chart: This is like checking the bus every 5 minutes to make quick, small trades—perfect for fast, short profits.
Bitcoin Ethereum (BTC/USD)(ETH/USD): It’s the most popular and liquid crypto, so there’s lots of activity, making it easier to jump on and off without getting stuck.
Why It Aims for 90% Wins (But Be Realistic)
The goal is to win 9 out of 10 trades by being super picky about when to trade—only jumping on when the trend, momentum, and volume are all perfect. But in real trading, markets can be unpredictable, so 90% is very hard to achieve. Still, this strategy tries to be as accurate as possible by avoiding bad moves and focusing on strong trends.
Risks for a New Trader
Leverage: Trading with 10x leverage means small price moves can lead to big losses if you’re not careful. Start with a demo account (pretend money) on TradingView or Binance to practice.
Learning Curve: This strategy uses technical terms (like HMAs, RSI) and tools you’ll need to learn over time. Don’t rush—just practice and ask questions!
How to Use It
Go to TradingView, load this strategy on a 5-minute BTC/USD futures chart on Binance.
Watch the green triangles (buy signals) and red triangles (sell signals) on the chart—they tell you when to trade.
Use the stops and targets to manage your trades—don’t guess, let the strategy guide you.
Start small, learn from each trade, and don’t risk money you can’t afford to lose.
This is like learning to ride a bike—start slow, practice, and you’ll get better. If you have more questions or want simpler tips, feel free to ask! Trading can be fun and rewarding, but it takes patience and practice.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
