Chimpanzee V2.5 part A by joylay83Hi everyone, I am an amateur pinecoder. I would like to share my script which is coded with the intention of generating signals to send to 3commas webhook. It is still in development and revision.
This collection of indicators use:
Chart: 15m.
Inverse Fisher Transformation of the RSI to detect dips in the 15m timeframe.
Bollinger band (4H) to filter out false signals.
Triple EMA 21: to mimic price action for easier coding alerts. Currently not involved in generating signals. will be incorporated in the future.
StochRSI: As a visual filter. Currently not involved in generating signals. will be incorporated in the future.
Background will be green if stochRSI is low and red if stockRSI is high.
Candlesticks will be marked with a flag is TEMA breached BB.
One would need to play around with timeframes, BB settings and IFTRSI threshold for different signals.
There are 2 Signal Modes (with regards to IFTRSI):
Threshold: When price action falls below BB and IFTRSI hits buy threshold, a buy/sell signal is generated. Eg if IFTRSI buy threshold is set to -0.9, the buy signal will remain continuously positive as long as IFTRSI is < 0.9.
Cross: When price action falls below BB and IFTRSI hits threshold, nothing happens. It will wait until the IFTRSI cross back over the threshold before firing a signal.
There is another identical set of indicators running on a higher time frame (IFTRSI: 4H, BB: D or 3D, TEMA 21 4H) but on the same chart. This tend to generate less signals but are more reliable. A usage example would be to send a larger buy order if the signal comes from this higher time frame, or execute a sell order after multiple buys from the lower time frame.
It comes in 2 parts:
Part A: Contains overlay display. This displays BB, Triple EMA, buy/sell and StochRSI in labels. the labels are self explanatory.
Part B (please search for it): which is actually the same code but contain non-overlay display. You may also put part B overlay=true but scale to LEFT. The advantage of using overlay=true is that you can move the signal right over the candlesticks (mainly for troubleshooting/debugging). This part contains Inverse Fisher RSI, %B, Signal Line. %B is supposedly idential to Bollinger Bands in Part A.
By default, when there is a buy/sell signal:
lower time frame 15m: Signal Line in Part B will turn blue with a value 1 or -1 which corresponds to a buy or sell label in Part A
higher time frame 4H: Signal Line in Part B will turn red with a value 2 or -2 which corresponds to a HTF buy or sell label in Part A
Part A or B may be used to send signal to the webhook. You have to make sure that the settings of Part A and B are identical.
You may choose to un-display some items to reduce clutter.
Current problems:
1. Still too many buy signals
Although many times it will generate excellent buy signal at many swing lows, but there are many buy signals prior to a major swing low. This can be observed in the picture above. It also generate a couple of buy signals prior to the swing lows. I am currently experimenting with 20m and hourly timeframe to address this issue. More filters are needed eg an oscillator or detecting candlestick patterns.
2. Premature sell signals.
The sell signal is often generated at the beginning of a major bull run. My idea to solve this problem is to move to a higher timeframe and sell only when TEMA crossunder the upper bollinger band.
3. Lack of a backtester that can test multiple concurrent deals.
Buy -> Buy (average down) -> Buy (average down) -> Buy (average down) -> Sell
4. Lack of the ability to calculate average purchase price
Probably have to code it as a strategy
5. Display lag
As the browser is running 2 copies of the idential script, it tends to lag when you drag your chart around. So far there are no timeouts or delay in firing alerts to 3commas.
I do welcome any suggestion for improvement and constructive criticism. tqvm.
Credits : Thank you for doing an awesome job. I learnt a lot from your codes and tutorials.
Credits not listed in any order. If your code is used here and did not receive due credit, kindly drop me a note. tq.
Blessing 3 by JTA Today
@ZenAndTheArtOfTrading (extremely-easy-to-understand tutorials eg fixing repainting)
@LazyBear (various codes)
@Galactus-B Argo I
@TheTradingParrot (Inverse Fisher RSI and Gavin's backtester)
@zendog123 (backtester and various codes)
@ydeniz2000 (Bollinger Bands)
TradingView built-in scripts
Cari dalam skrip untuk "backtest"
Excitement - Crypto Surfer v1For those of us who need more excitement in our crypto journey besides just HODL, here’s a simple crypto robot that trades on the hourly (1H) candles. I call it the Crypto Surfer because it uses the 20 and 40 EMAs (Exponential Moving Averages) to decide when to enter and exit; price tends to “surf” above these EMAs when it is bullish, and “sink” below these EMAs when it is bearish. An additional 160 SMA (Simple Moving Average) with slope-angle detection, was added as a bull / bear filter to reduce the sting of drawdowns, by filtering-out long trades in a prolonged bear market.
USER NOTES:
- This script will buy $10,000 USD worth of crypto-currency per trade.
- It will only open one trade at a time.
- It has been backtested on all the high market cap coins such as Bitcoin, Ethereum, Binance Coin, Polkadot, Cardano.
- It should be run on the Hourly (H1) chart.
- In general, this moving average strategy *should be* profitable for 80% to 90% of the coins out there
- The 160 SMA filter with slope angle detection is designed to stop you from going long in a bear market.
- It is recommended you copy this script and modify it to suit your preferred coin during backtesting, before running live.
- Trading is inherently risky (exciting), and I shall not be liable for any losses you incur, even if these losses are due to sampling bias.
Fractal Adaptive Entry IndicatorThis entry indicator was inspired by John Ehle'rs "Fractal Adaptive Moving Average"
It's a very sensitive entry indicator that must be paired with a long-term trend detector in order to filter false positives.
Warning I have not backtested this indicator and will not make any claims to its performance.
Visually, it looks promising, however, backtesting and statistical analysis takes time.
Happy trading
<3
Uhl MA System - Strategy AnalysisThe Uhl MA crossover system was specifically designed to provide an adaptive MA crossover system that didn't committed the same errors of more classical MA systems. This crossover system is based on a fast and a slow moving average, with the slow moving average being the corrected moving average (CMA) originally proposed by Andreas Uhl, and the fast moving average being the corrected trend step (CTS) which is also based on the corrected moving average design.
For more information see :
In this post, the performances of this system are analyzed on various markets.
Setup And Rules
The analysis is solely based on the indicator signals, therefore no spread is applied. Constant position sizing is used. The strategy will be backtested on the 15 minute time-frame. The mult setting is discarded, the default setting used for length is 100.
Here are the rules of our strategy :
long: CTS crossover CMA
short: CTS crossunder CMA
Results And Data
EURUSD:
Net Profit: $ 0.08
Total number of trades: 99
Profitability: 35.35 %
Profit Factor: 1.834
Max Drawdown: $ 0.01
EURUSD behaved pretty well, and was most of time showing long term trends without exhibiting particularly tricky structures, the moving averages still did cross during ranging phases, since march 9 we can see a downtrend with more pronounced cyclical variations (retracements) that could potentially lead to loosing trades.
BTCUSD:
Net Profit: $ 4371.57
Total number of trades: 94
Profitability: 32.98 %
Profit Factor: 1.749
Max Drawdown: $ 1409.96
The strategy didn't started well, producing its largest drawdown after only a few trades, the strategy still managed to recover. BTCUSD exhibited a strong downtrend, the strategy profited from that to recover, signals still occurred on ranging phases, and where mostly caused by a short term volatile move, unfortunately the CMA can converge toward ranging/flat price zones where false signals might occur at higher frequency.
AMD:
Net Profit: $ 16.09
Total number of trades: 95
Profitability: 29.47 %
Profit Factor: 1.288
Max Drawdown: $ 20.11
On AMD the strategy started relatively well with a raising balance, then the balance quickly fallen, this downtrend in the balance lasted quite some time (almost 48 trades), the strategy finally recovered in Nov 2019 and the balance made a new highest high at the end of February. AMD had numerous trends during the backtesting period, yet results are poor.
AAPL:
Net Profit: $ -28.17
Total number of trades: 89
Profitability: 28.09 %
Profit Factor: 0.894
Max Drawdown: $ 63.21
AAPL show the poorest results so far, with a stationary balance around the initial capital (in short the evolution of the balance is not showing any particular trend and oscillate around the initial capital value).
AAPL had some significant retracements in its up-trend, which triggered some trades (of course), and the ranging period from Jan 24 to Feb 13 heavily damaged the strategy performance, generating 6 significant loosing trades. AAPL show the worst results so far, mostly due by ranging phases.
Conclusions
The Uhl MA crossover system strategy has been tested and based on the results don't show particularly interesting performances, and might even be outperformed by simpler MA systems that prove to be more robust against ranging markets. The total number of executed trades are on average 94, and the profitability is on average 31%. The strategy might prove more interesting if we can correct the behavior of the CMA, who sometimes converged toward ranging/flat markets.
MACD Volume Strategy (BBO + MACD State, Reversal Type)Overview
MACD Volume Strategy (BBO + MACD State, Reversal Type) is a momentum-based reversal system that combines MACD crossover logic with volume filtering to enhance signal accuracy and minimize noise. It aims to identify structural trend shifts and manage risk using predefined parameters.
※This strategy is for educational and research purposes only. All results are based on historical simulations and do not guarantee future performance.
Strategy Objectives
Identify early trend transitions with high probability
Filter entries using volume dynamics to validate momentum
Maintain continuous exposure using a reversal-style model
Apply a consistent 1:1.5 risk-to-reward ratio per trade
Key Features
Integrated MACD and volume oscillator filtering
Zero repainting (all signals confirmed on closed candles)
Automatic position flipping for seamless direction shifts
Stop-loss and take-profit based on recent structural highs/lows
Trading Rules
Long Entry Conditions
MACD crosses above the zero line (BBO Buy arrow)
Volume oscillator is positive (short EMA > long EMA)
MACD is above the signal line
Close any existing short and enter a new long
Short Entry Conditions
MACD crosses below the zero line (BBO Sell arrow)
Volume oscillator is positive
MACD is below the signal line
Close any existing long and enter a new short
Exit Rules
Take Profit (TP) = Entry ± (risk distance × 1.5)
Stop Loss (SL) = Recent swing low (for long) or high (for short)
Early Exit = Triggered when a reversal signal appears (flip logic)
Risk Management Parameters
Pair: ETH/USD
Timeframe: 10-minute
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted for sustainable practice)
Total Trades: 312 (backtest on selected dataset)
※Risk parameters are fully configurable and should be adjusted to suit each trader's personal setup and broker conditions.
Parameters & Configurations
Volume Short Length: 6
Volume Long Length: 12
MACD Fast Length: 11
MACD Slow Length: 21
Signal Smoothing: 10
Oscillator MA Type: SMA
Signal Line MA Type: SMA
Visual Support
Green arrow = Long entry
Red arrow = Short entry
MACD lines, signal line, and histogram
SL/TP markers plotted directly on the chart
Strategic Advantages & Uniqueness
Volume filtering eliminates low-participation, weak signals
Structurally aligned SL/TP based on recent market pivots
No repainting — decisions are made only on closed candles
Always in the market due to the reversal-style framework
Inspirations & Attribution
This strategy is inspired by the excellent work of:
Bitcoinblockchainonline – “BBO_Roxana_Signals MACD + vol”
Leveraging MACD zero-line cross and volume oscillator for intuitive signal generation.
HasanRifat – “MACD Fake Filter ”
Introduced a signal filter using MACD wave height averaging to reduce false positives.
This strategy builds upon those ideas to create a more automated, risk-aware, and technically adaptive system.
Summary
MACD Volume Strategy is a clean, logic-first automated trading system built for precision-seeking traders. It avoids discretionary bias and provides consistent signal logic under backtested historical conditions.
100% mechanical — no discretionary input required
Designed for high-confidence entries
Can be extended with filters, alerts, or trailing stops
※Strategy performance depends on market context. Past performance is not indicative of future results. Use with proper risk management and careful configuration.
Zero-lag TEMA Crosses Strategy[Pakun]Here's the adjusted strategy description in English, aligned with the house rules:
---
### Strategy Name: Zero-lag TEMA Cross Strategy
**Purpose:** This strategy aims to identify entry and exit points in the market using Zero-lag Triple Exponential Moving Averages (TEMA). It focuses on minimizing lag and improving the accuracy of trend-following signals.
### Uniqueness and Usefulness
**Uniqueness:** This strategy employs the less commonly used Zero-lag TEMA, compared to standard moving averages. This unique approach reduces lag and provides more timely signals.
**Usefulness:** This strategy is valuable for traders looking to capture trend reversals or continuations with reduced lag. It has the potential to enhance the profitability and accuracy of trades.
### Entry Conditions
**Long Entry:**
- **Condition:** A crossover occurs where the short-term Zero-lag TEMA surpasses the long-term Zero-lag TEMA.
- **Signal:** A buy signal is generated, indicating a potential uptrend.
**Short Entry:**
- **Condition:** A crossunder occurs where the short-term Zero-lag TEMA falls below the long-term Zero-lag TEMA.
- **Signal:** A sell signal is generated, indicating a potential downtrend.
### Exit Conditions
**Exit Strategy:**
- **Stop Loss:** Positions are closed if the price moves against the trade and hits the predefined stop loss level. The stop loss is set based on recent highs/lows.
- **Take Profit:** Positions are closed when the price reaches the profit target. The profit target is calculated as 1.5 times the distance between the entry price and the stop loss level.
### Risk Management
**Risk Management Rules:**
- This strategy incorporates a dynamic stop loss mechanism based on recent highs/lows over a specified period.
- The take profit level ensures a reward-to-risk ratio of 1.5 times the stop loss distance.
- These measures aim to manage risk and protect capital.
**Account Size:** ¥500,000
**Commissions and Slippage:** 94 pips per trade and 1 pip slippage
**Risk per Trade:** 1% of account equity
### Configurable Options
**Configurable Options:**
- Lookback Period: The number of bars to calculate recent highs/lows.
- Fast Period: Length of the short-term Zero-lag TEMA (69).
- Slow Period: Length of the long-term Zero-lag TEMA (130).
- Signal Display: Option to display buy/sell signals on the chart.
- Bar Color: Option to change bar colors based on trend direction.
### Adequate Sample Size
**Sample Size Justification:**
- To ensure the robustness and reliability of the strategy, it should be tested with a sufficiently long period of historical data.
- It is recommended to backtest across multiple market cycles to adapt to different market conditions.
- This strategy was backtested using 10 days of historical data, including 184 trades.
### Notes
**Additional Considerations:**
- This strategy is designed for educational purposes and should be thoroughly tested in a demo environment before live trading.
- Settings should be adjusted based on the asset being traded and current market conditions.
### Credits
**Acknowledgments:**
- The concept and implementation of Zero-lag TEMA are based on contributions from technical analysts and the trading community.
- Special thanks to John Doe for the TEMA concept.
- Thanks to Zero-lag TEMA Crosses .
- This strategy has been enhanced by adding new filtering algorithms and risk management rules to the original TEMA code.
### Clean Chart Description
**Chart Appearance:**
- This strategy provides a clean and informative chart by plotting Zero-lag TEMA lines and optional entry/exit signals.
- The display of signals and color bars can be toggled to declutter the chart, improving readability and analysis.
Chandelier Exit Strategy with 200 EMA FilterStrategy Name and Purpose
Chandelier Exit Strategy with 200EMA Filter
This strategy uses the Chandelier Exit indicator in combination with a 200-period Exponential Moving Average (EMA) to generate trend-based trading signals. The main purpose of this strategy is to help traders identify high-probability entry points by leveraging the Chandelier Exit for stop loss levels and the EMA for trend confirmation. This strategy aims to provide clear rules for entries and exits, improving overall trading discipline and performance.
Originality and Usefulness
This script integrates two powerful indicators to create a cohesive and effective trading strategy:
Chandelier Exit : This indicator is based on the Average True Range (ATR) and identifies potential stop loss levels. The Chandelier Exit helps manage risk by setting stop loss levels at a distance from the highest high or lowest low over a specified period, multiplied by the ATR. This ensures that the stop loss adapts to market volatility.
200-period Exponential Moving Average (EMA) : The EMA acts as a trend filter. By ensuring trades are only taken in the direction of the overall trend, the strategy improves the probability of success. For long entries, the close price must be above the 200 EMA, indicating a bullish trend. For short entries, the close price must be below the 200 EMA, indicating a bearish trend.
Combining these indicators adds layers of confirmation and risk management, enhancing the strategy's effectiveness. The Chandelier Exit provides dynamic stop loss levels based on market volatility, while the EMA ensures trades align with the prevailing trend.
Entry Conditions
Long Entry
A buy signal is generated by the Chandelier Exit.
The close price is above the 200 EMA, indicating a strong bullish trend.
Short Entry
A sell signal is generated by the Chandelier Exit.
The close price is below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions: The position is closed when a sell signal is generated by the Chandelier Exit.
For short positions: The position is closed when a buy signal is generated by the Chandelier Exit.
Risk Management
Account Size: 1,000,00 yen
Commission and Slippage: 17 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
Stop Loss: For long trades, the stop loss is placed slightly below the candle that generated the buy signal. For short trades, the stop loss is placed slightly above the candle that generated the sell signal. The stop loss levels are dynamically adjusted based on the ATR.
Settings Options
ATR Period: Set the period for calculating the ATR to determine the Chandelier Exit levels.
ATR Multiplier: Set the multiplier for ATR to define the distance of stop loss levels from the highest high or lowest low.
Use Close Price for Extremums: Choose whether to use the close price for calculating the extremums.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show Buy/Sell Labels: Choose whether to display buy and sell labels on the chart for visual confirmation.
Highlight State: Choose whether to highlight the bullish or bearish state on the chart.
Sufficient Sample Size
The strategy has been backtested with a sufficient sample size to evaluate its performance accurately. This ensures that the strategy's results are statistically significant and reliable.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the Chandelier Exit indicator. Special thanks to the original contributors for their work on the Chandelier Exit concept.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
FVG Positioning Average with 200EMA Auto Trading [Pakun]Description
Strategy Name and Purpose
FVG Positioning Average with 200EMA Auto Trading
This strategy uses Fair Value Gaps (FVG) combined with a 200-period Exponential Moving Average (EMA) and Average True Range (ATR) to generate trend-based trading signals. It is designed to help traders identify high-probability entry points by leveraging the gaps between fair value prices and current market prices.
Originality and Usefulness
This script combines multiple indicators to create a cohesive trading strategy that is greater than the sum of its parts. While FVG is a powerful tool on its own, combining it with the EMA and ATR adds layers of confirmation and risk management, enhancing its effectiveness. Here’s how the components work together:
Fair Value Gap (FVG): Identifies gaps in the market where price action has not fully filled, indicating potential reversal or continuation points.
200-period Exponential Moving Average (EMA): Acts as a trend filter to ensure trades are taken in the direction of the overall trend, improving the probability of success.
Average True Range (ATR): Used to filter out insignificant gaps and set dynamic stop-loss levels based on market volatility, enhancing risk management.
Entry Conditions
Long Entry
The close price crosses above the downtrend FVG.
The close price, FVG up average, and down average are all above the 200 EMA, indicating a strong bullish trend.
Short Entry
The close price crosses below the uptrend FVG.
The close price, FVG up average, and down average are all below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions, the stop loss is set at the recent low, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
For short positions, the stop loss is set at the recent high, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
Risk Management
Account Size: 1,000,000 yen
Commission and Slippage: 2 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
The stop loss is based on the recent low or recent high, ensuring trades are exited when the market moves against the position.
Settings Options
FVG Lookback: Set the lookback period for calculating FVGs.
Lookback Type: Choose the type of lookback (Bar Count or FVG Count).
ATR Multiplier: Set the multiplier for ATR to filter significant gaps.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show FVGs on Chart: Choose whether to display FVGs on the chart for visual confirmation.
Bullish/Bearish Color: Set the color for bullish and bearish FVGs to distinguish them easily.
Show Gradient Areas: Choose whether to display gradient areas to highlight the zones of interest.
Sufficient Sample Size
The strategy has been backtested with 113 trades, providing a sufficient sample size to evaluate its performance.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the FVG Positioning Average Strategy indicator. Thanks to for their contribution.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
Smart Money Concepts Probability (Expo)█ Overview
The Smart Money Concept Probability (Expo) is an indicator developed to track the actions of institutional investors, commonly known as "smart money." This tool calculates the likelihood of smart money being actively engaged in buying or selling within the market, referred to as the "smart money order flow."
The indicator measures the probability of three key events: Change of Character ( CHoCH ), Shift in Market Structure ( SMS ), and Break of Structure ( BMS ). These probabilities are displayed as percentages alongside their respective levels, providing a straightforward and immediate understanding of the likelihood of smart money order flow.
Finally, the backtested results are shown in a table, which gives traders an understanding of the historical performance of the current order flow direction.
█ Calculations
The algorithm individually computes the likelihood of the events ( CHoCH , SMS , and BMS ). A positive score is assigned for events where the price successfully breaks through the level with the highest probability, and a negative score when the price fails to do so. By doing so, the algorithm determines the probability of each event occurring and calculates the total profitability derived from all the events.
█ Example
In this case, we have an 85% probability that the price will break above the upper range and make a new Break Of Structure and only a 16.36% probability that the price will break below the lower range and make a Change Of Character.
█ Settings
The Structure Period sets the pivot period to use when calculating the market structure.
The Structure Response sets how responsive the market structure should be. A low value returns a more responsive structure. A high value returns a less responsive structure.
█ How to use
This indicator is a perfect tool for anyone that wants to understand the probability of a Change of Character ( CHoCH ), Shift in Market Structure ( SMS ), and Break of Structure ( BMS )
The insights provided by this tool help traders gain an understanding of the smart money order flow direction, which can be used to determine the market trend.
█ Any Alert function call
An alert is sent when the price breaks the upper or lower range, and you can select what should be included in the alert. You can enable the following options:
Ticker ID
Timeframe
Probability percentage
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Dual Fibonacci Zone & Ranged Vol DCA Strategy - R3c0nTraderWhat does this do?
This is for educational purposes and allows one to backtest two Fibonacci Zones simultaneously. This also includes an option for Ranged Volume as a parameter.
Pre-requisites:
First off, this is a Long only strategy as I wrote it with DCA in mind. It cannot be used for shorting. Shorting defeats the purpose of a DCA bot which has a goal that is Long a position not Short a position. If you want to short, there are plenty of free scripts out there that do this.
You must have some base knowledge or experience with Fibonacci trading, understanding what is ADX, +DI (and -DI), etc.
You can use this script without a 3Commas account and see how 3Commas DCA Bot would perform. However, I highly recommend inexperienced uses get a free account and going through the tutorials, FAQ's and knowledgebase. This would give you a base understanding of the settings you will see in this strategy and why you will need to know them. Only then should you try testing this strategy with a paper bot.
Background
After I had created and released "Fibonacci Zone DCA Strategy", I began expanding and testing other ideas.
The first idea was to add Ranged Volume to the Fibonacci Zone DCA strategy which I wanted for providing further confirmation before entering a trade. The second idea was to add a second Fibonacci Zone that was just as configurable as the first Fibonacci Zone. I managed to add both and they can be easily enabled or disabled via the strategy settings menu.
Things Got Real Interesting
Things got real interesting when I started testing strategies with two Fibonacci zones. Here's a quick list of what I found I was able to do:
Mix and match exit strategies. I could set the Fib-1 zone strategy to exit with a take profit % and separately set the Fib-2 zone strategy to exit when the price crosses the top-high fib border
Trade the trend. A common phrase amongst traders is "the Trend is your friend" and with the help of an additional Fib Zone, I was able to trade the trend more often by using two different Fib Zone strategies which if configured properly can shorten time to re-deploy capital, increase number of closed trades, and in some cases increase net profit.
Trade both bull market uptrends and bear market downtrends in the same strategy. I found I could configure one Fib Zone strategy to be really good in uptrends and another Fib Zone strategy to be really good in downtrends. In some cases, with both Fib Zone strategies enabled together in a single strategy I got better results than if the strategies were backtested separately.
There are many other trade strategies I am finding with this. One could be to trade a convergence or divergence of the two different Fib Zones. This could possibly be achieved by setting one strategy to have different Fibonacci length.
Credits:
Thank you "EvoCrypto" for granting me permission to use "Ranged Volume" to create this strategy
Thank you "eykpunter" for granting me permission to use "Fibonacci Zones" to create this strategy
Thank you "junyou0424" for granting me permission to use "DCA Bot with SuperTrend Emulator" which I used for adding bot inputs, calculations, and strategy
Crypto Scannner for Traffic Lights StrategyI allways try to make trading easier. Developing Scripts for a quick backtest and improvement of a strategy, getting alerts for entry and exit a position. Loading data to a spreadsheet is also important and takes time.
In this case finding good parameters in different markets or assets to enter in a position, is a bit exhausting. It is something you have to do everyday, and sometimes in different moments of the day.
So I manage to develop a Screener, to take a quick look at specific hours, and tell if I have a buy or sell condition in an specific asset. Obviously this is not an alert to make a trade instantaneusly, but this help you filter a lot of information in matters of seconds. Then open those specific charts and make a better analisys.
A few weeks ago, I published a scrpipt called "Traffic Lights Strategy", that uses 4 emas to get a buy or a sell condition.
It is easy to understand and use, but if you don´t want to missed some opportunities, and don't want to be look at the screen in all the time looking for them, I have here a simple solution.
This script works plotting 2 labels. The first one plots all the assets in which the condition is true (fastema > medema > slowema > filterema or fastema < medema < slowema < filterema)
The second one plots the assets were the condition is true only if happened up to 5 candles back, so you can be in time to enter a trade.
You can take the script and customize it for a different strategy or assets. I coded like this because I backtested this strategy in this specific assets, and statistics suggest that it might be profitable.
I hope this works for you. In other time I'll try to code a script for the others strategies I published.
Nico's SPX Dynamic ChannelsTest of dynamic channels and some statistics made by hand.
This indicator was done specifically for the S&P500 index.
As you can see, below the 125 EMA there's a lot more volatility than in the upside. I've made some kind of a dynamic linear regression of the lows and the highs.
I've chosen the MA that best fits the SPX, and then calculated in Excel the percental mean and SDs of most important peaks and valleys that I've chosen in comparison to the 125 MA. This lead to the green, orange and red zones. BUT, I've calculated the peaks and valleys separately, as I assumed that a bear market and crashes have way more volatility than bull markets. That's why the difference between the upper and the lower channels.
The neutral blue zone is composed by an upper EMA of the highs and lower EMA of the lows. No MA in this script uses the close price as a source.
This MA makes sense because it represents a semester of trading, for this particular asset.
Backtest results
It's also interesting to try it here too, as it has a little bit more of data:
SPCFD:SPX
As it's not a trading system, I have no batting average nor ratios for this.
Still, the measures of the peaks and valleys are very accurate and repeat themselves over and over again. The results were:
3rd resistance: 12.88%
2nd resistance: 10.12%
1st resistance: 7.36%
1st support: -6.42%
2nd support: -14.8%
3rd support: -23.18%
All referred to the mean, which is the 125 EMA zone.
After the 1950's works like magic, but not before. You will see that it doesn't work in the great depression and it's crash.
How to use this indicator
Green = First grade support/resistance .
Orange = Second grade support/resistance . Caution.
Red = Third grade support/resistance . High chances of mean reversal.
Blue zone = This is the neutral zone, where the prices are not cheap nor expensive.
Often in a trending market, the price will have the blue zone as it's main support and when trending the price will stick to the green MA.
When the price touches the orange MA, the most probable is that it will return to the green MA.
If the price touches the red zone, there's a high chance that this is a big turning point and it will reverse to the mean (green or blue zone).
Imagine you've bought each time the price touched the red support, check that and you'll start liking this indicator. I think it is a great entry point for investors. The red resistance is good too, but of course it works for a short period of time.
I've backtested this indicator since the beginning of the dataset and it works like magic, but ONLY for the SPX index (spot price).
Leave a comment or some coins if you like it!!!
(I've posted it before like an analysis, not as a script, my bad)
DAKELAX-XRPUSDT Bollinger Band Strategy for TradebotlerDAKELAX-XRPUSDT is a Tradebotler strategy designed to run on XRPUSDT for binance, it's a simple reverse to mean strategy and when backtested on may-aug 2019 on H1 timeframe it performs pretty well in backtest as well as running live.
In order to get started install the Tradebotler extension and connect the strategy with Binance or other crypto exchanges of your choice such as Kraken, Bitstamp, Bitmex, Bittrex, Polyneux etc, etc.
(Mustang Algo) Stochastic RSI + Triple EMAStochastic RSI + Triple EMA (StochTEMA)
Overview
The Stochastic RSI + Triple EMA indicator combines the Stochastic RSI oscillator with a Triple Exponential Moving Average (TEMA) overlay to generate clear buy and sell signals on the price chart. By measuring RSI overbought/oversold conditions and confirming trend direction with TEMA, this tool helps traders identify high-probability entries and exits while filtering out noise in choppy markets.
Key Features
Stochastic RSI Calculation
Computes a standard RSI over a user-defined period (default 50).
Applies a Stochastic oscillator to the RSI values over a second user-defined period (default 50).
Smooths the %K line by taking an SMA over a third input (default 3), and %D is an SMA of %K over another input (default 3).
Defines oversold when both %K and %D are below 20, and overbought when both are above 80.
Triple EMA (TEMA)
Calculates three successive EMAs on the closing price with the same length (default 9).
Combines them using TEMA = 3×(EMA1 – EMA2) + EMA3, producing a fast-reacting trend line.
Bullish trend is identified when price > TEMA and TEMA is rising; bearish trend when price < TEMA and TEMA is falling; neutral/flat when TEMA change is minimal.
Signal Logic
Strong Buy: Previous bar’s Stoch RSI was oversold (both %K and %D < 20), %K crosses above %D, and TEMA is in a bullish trend.
Medium Buy: %K crosses above %D (without requiring oversold), TEMA is bullish, and previous %K < 50.
Weak Buy: Previous bar’s %K and %D were oversold, %K crosses above %D, TEMA is flat or bullish (not bearish).
Strong Sell: Previous bar’s Stoch RSI was overbought (both %K and %D > 80), %K crosses below %D, and TEMA is bearish.
Medium Sell: %K crosses below %D (without requiring overbought), TEMA is bearish, and previous %K > 50.
Weak Sell: Previous bar’s %K and %D were overbought, %K crosses below %D, TEMA is flat or bearish (not bullish).
Visual Elements on Chart
TEMA Line: Plotted in cyan (#00BCD4) with a medium-thick line for clear trend visualization.
Buy/Sell Markers:
BUY STRONG: Lime label below the candle
BUY MEDIUM: Green triangle below the candle
BUY WEAK: Semi-transparent green circle below the candle
SELL STRONG: Red label above the candle
SELL MEDIUM: Orange triangle above the candle
SELL WEAK: Semi-transparent orange circle above the candle
Candle & Background Coloring: When a strong buy or sell signal occurs, the candle body is tinted (semi-transparent lime/red) and the chart background briefly flashes light green (buy) or light red (sell).
Dynamic Support/Resistance:
On a strong buy signal, a green dot is plotted under that bar’s low as a temporary support marker.
On a strong sell signal, a red dot is plotted above that bar’s high as a temporary resistance marker.
Alerts
Strong Buy Alert: Triggered when Stoch RSI is oversold, %K crosses above %D, and TEMA is bullish.
Strong Sell Alert: Triggered when Stoch RSI is overbought, %K crosses below %D, and TEMA is bearish.
General Buy Alert: Triggered on any bullish crossover (%K > %D) when TEMA is not bearish.
General Sell Alert: Triggered on any bearish crossover (%K < %D) when TEMA is not bullish.
Inputs
Stochastic RSI Settings (group “Stochastic RSI”):
K (smoothK): Period length for smoothing the %K line (default 3, minimum 1)
D (smoothD): Period length for smoothing the %D line (default 3, minimum 1)
RSI Length (lengthRSI): Number of bars used for the RSI calculation (default 50, minimum 1)
Stochastic Length (lengthStoch): Number of bars for the Stochastic oscillator applied to RSI (default 50, minimum 1)
RSI Source (src): Price source for the RSI (default = close)
TEMA Settings (group “Triple EMA”):
TEMA Length (lengthTEMA): Number of bars used for each of the three EMAs (default 9, minimum 1)
How to Use
Add the Script
Copy and paste the indicator code into TradingView’s Pine Editor (version 6).
Save the script and add it to your chart as “Stochastic RSI + Triple EMA (StochTEMA).”
Adjust Inputs
Choose shorter lengths for lower timeframes (e.g., intraday scalping) and longer lengths for higher timeframes (e.g., swing trading).
Fine-tune the Stochastic RSI parameters (K, D, RSI Length, Stochastic Length) to suit the volatility of the instrument.
Modify TEMA Length if you prefer a faster or slower moving average response.
Interpret Signals
Primary Entries/Exits: Focus on “BUY STRONG” and “SELL STRONG” signals, as they require both oversold/overbought conditions and a confirming TEMA trend.
Confirmation Signals: Use “BUY MEDIUM”/“BUY WEAK” to confirm or add to an existing position when the market is trending. Similarly, “SELL MEDIUM”/“SELL WEAK” can be used to scale out or confirm bearish momentum.
Support/Resistance Dots: These help identify recent swing lows (green dots) and swing highs (red dots) that were tagged by strong signals—useful to place stop-loss or profit-target orders.
Set Alerts
Open the Alerts menu (bell icon) in TradingView, choose this script, and select the desired alert condition (e.g., “BUY Signal Strong”).
Configure notifications (popup, email, webhook) according to your trading workflow.
Notes & Best Practices
Filtering False Signals: By combining Stoch RSI crossovers with TEMA trend confirmation, most false breakouts during choppy price action are filtered out.
Timeframe Selection: This indicator works on all timeframes, but shorter timeframes may generate frequent signals—consider higher-timeframe confirmation when trading lower timeframes.
Risk Management: Always use proper position sizing and stop-loss placement. An “oversold” or “overbought” reading can remain extended for some time in strong trends.
Backtesting/Optimization: Before live trading, backtest different parameter combinations on historical data to find the optimal balance between sensitivity and reliability for your chosen instrument.
No Guarantee of Profits: As with any technical indicator, past performance does not guarantee future results. Use in conjunction with other forms of analysis (volume, price patterns, fundamentals).
Author: Your Name or Username
Version: 1.0 (Pine Script v6)
Published: June 2025
Feel free to customize input values and visual preferences. If you find bugs or have suggestions for improvements, open an issue or leave a comment below. Trade responsibly!
Volatility Bias ModelVolatility Bias Model
Overview
Volatility Bias Model is a purely mathematical, non-indicator-based trading system that detects directional probability shifts during high volatility market phases. Rather than relying on classic tools like RSI or moving averages, this strategy uses raw price behavior and clustering logic to determine potential breakout direction based on recent market bias.
How It Works
Over a defined lookback window (default 10 bars), the strategy counts how many candles closed in the same direction (i.e., bullish or bearish).
Simultaneously, it calculates the price range during that window.
If volatility is above a minimum threshold and a clear directional bias is detected (e.g., >60% of closes are bullish), a trade is opened in the direction of that bias.
This approach assumes that when high volatility is coupled with directional closing consistency, the market is probabilistically more likely to continue in that direction.
ATR-based stop-loss and take-profit levels are applied, and trades auto-exit after 20 bars if targets are not hit.
Key Features
- 100% non-indicator-based logic
- Statistically-driven directional bias detection
- Works across all timeframes (1H, 4H, 1D)
- ATR-based risk management
- No pyramiding, slippage and commissions included
- Compatible with real-world backtesting conditions
Realism & Assumptions
To make this strategy more aligned with actual trading environments, it includes 0.05% commission per trade and a 1-point slippage on every entry and exit.
Additionally, position sizing is set at 10% of a $10,000 starting capital, and no pyramiding is allowed.
These assumptions help avoid unrealistic backtest results and make the performance metrics more representative of live conditions.
Parameter Explanation
Bias Window (10 bars): Number of past candles used to evaluate directional closings
Bias Threshold (0.60): Required ratio of same-direction candles to consider a bias valid
Minimum Range (1.5%): Ensures the market is volatile enough to avoid noise
ATR Length (14): Used to dynamically define stop-loss and target zones
Risk-Reward Ratio (2.0): Take-profit is set at twice the stop-loss distance
Max Holding Bars (20): Trades are closed automatically after 20 bars to prevent stagnation
Originality Note
Unlike common strategies based on oscillators or moving averages, this script is built on pure statistical inference. It models the market as a probabilistic process and identifies directional intent based on historical closing behavior, filtered by volatility. This makes it a non-linear, adaptive model grounded in real-world price structure — not traditional technical indicators.
Disclaimer
This strategy is for educational and experimental purposes only. It does not constitute financial advice. Always perform your own analysis and test thoroughly before applying with real capital.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
[blackcat] L2 MTF Heikin-Ashi SR LevelsOVERVIEW
The L2 MTF Heikin-Ashi SR Levels indicator is a sophisticated tool designed to help traders identify critical support and resistance levels across multiple timeframes. This script employs Heikin-Ashi candles, which provide a smoothed representation of price action, making it easier to spot trends and reversals. By integrating multi-timeframe analysis, this indicator offers a comprehensive view of market dynamics, enabling traders to make more informed decisions 📊✅.
This indicator not only calculates essential support and resistance levels but also visually represents them on the chart with gradient colors based on Relative Strength Index (RSI) values. Additionally, it features customizable alerts and labels to enhance user experience and ensure timely execution of trades.
FEATURES
Advanced Trend Identification:
Uses Heikin-Ashi candles for smoother price action analysis.
Helps filter out noise and focus on significant trends.
Ideal for both short-term and long-term trading strategies.
Multi-Timeframe Analysis:
Allows users to select different resolutions for deeper insights.
Ensures compatibility with various trading styles and preferences.
Comprehensive Support and Resistance Calculation:
Computes four distinct levels: Support Level 1, Support Level 2, Resistance Level 1, and Resistance Level 2.
Each level serves as a reference point for potential price reversals or continuations.
Gradient Color Visualization:
Employs a spectrum of colors derived from RSI values to represent support and resistance lines.
Enhances readability and helps traders quickly assess market sentiment 🎨.
Dynamic Labels and Alerts:
Automatically generates buy ('Buy') and sell ('Sell') labels when price crosses key levels.
Provides real-time alerts for crossing events, ensuring traders never miss important signals 🔔.
Customizable Parameters:
Offers adjustable Length and Resolution inputs for tailored performance.
Allows traders to fine-tune the indicator according to their unique needs and strategies.
HOW TO USE
Adding the Indicator:
Open your TradingView chart and navigate to the indicators list.
Search for ' L2 MTF Heikin-Ashi SR Levels' and add it to your chart.
Configuring Settings:
Adjust the Length parameter to determine the period over which calculations are made.
A shorter length increases sensitivity, while a longer length smoothens the output.
Choose a specific Resolution to analyze different timeframes simultaneously.
For example, set it to 'D' for daily charts or 'W' for weekly charts.
Interpreting the Chart:
Observe the plotted support and resistance lines on the chart.
Look for price interactions with these levels to identify potential entry and exit points.
Pay attention to the gradient colors, which reflect underlying market momentum.
Setting Up Alerts:
Configure alerts based on the generated signals to receive instant notifications.
Customize alert messages and conditions to suit your trading plan.
Utilizing Labels:
Use the automatically placed buy and sell labels as quick references for decision-making.
Combine these labels with other technical analyses for confirmation.
Backtesting and Optimization:
Thoroughly test the indicator on historical data to evaluate its performance.
Optimize settings and refine your strategy based on backtest results.
Live Trading:
Apply the indicator to live charts and monitor real-time price movements.
Execute trades based on the generated signals and adjust positions accordingly.
Combining with Other Tools:
Integrate this indicator with other technical tools and fundamental analyses for a holistic approach.
Consider using moving averages, oscillators, or volume indicators alongside L2 MTF Heikin-Ashi SR Levels.
LIMITATIONS
Market Volatility:
In highly volatile or ranging markets, the indicator might produce false signals due to erratic price movements 🌪️.
Traders should exercise caution during such periods and consider additional confirmations.
Timeframe Dependency:
The effectiveness of the indicator can vary significantly depending on the chosen timeframe and asset.
Always validate the indicator's performance across different contexts before relying solely on it.
Over-reliance Risk:
While powerful, no single indicator guarantees success in all market conditions.
Combining this tool with other analytical methods enhances reliability and reduces risk.
NOTES
Data Requirements:
Ensure your chart has enough historical data to perform accurate calculations.
Insufficient data may lead to inaccurate or incomplete results.
Demo Testing:
Before deploying the indicator in live trading, conduct extensive testing on demo accounts.
Familiarize yourself with how the indicator behaves under various market scenarios.
Parameter Tuning:
Experiment with different Length and Resolution settings to find what works best for your trading style.
Regularly review and update parameters as market conditions evolve.
Continuous Learning:
Stay updated with the latest developments in technical analysis and trading strategies.
Adapt your use of the indicator based on new insights and experiences.
THANKS
Additionally, gratitude goes to the broader TradingView community for fostering collaboration and knowledge-sharing among traders worldwide. Together, we strive to elevate our understanding and application of financial markets 🌍💡.
[blackcat] L3 Magic-9 MACD SetupOVERVIEW
The L3 Magic-9 MACD Setup indicator is meticulously crafted to assist traders in identifying precise buy and sell signals through an enhanced Moving Average Convergence Divergence (MACD) methodology. This advanced tool integrates the Magic-9 Sequential technique to refine signal accuracy by filtering out market noise. By providing clear visual cues via labeled charts and real-time alerts, it empowers users to make informed trading decisions swiftly and confidently 📈✅.
FEATURES
Customizable MACD Parameters:
Fast Length: Adjustable parameter to control the sensitivity of the fast moving average.
Slow Length: Configurable setting for the slow moving average to balance responsiveness and stability.
Signal Length: Modifiable value to determine the smoothing factor applied to the MACD line.
Dynamic Plot Visuals:
MACD Line: Representing the difference between short-term and long-term EMAs.
Signal Line: A smoothed version of the MACD line used to generate crossover signals.
Histogram: Illustrating the distance between the MACD and Signal lines, highlighting momentum changes.
All elements feature adjustable colors and styles for personalized visualization preferences 🎨.
Advanced Filtering Mechanism:
Utilizes the Magic-9 Sequential method to analyze consecutive price movements, enhancing signal reliability.
Counts sequential occurrences above or below initial values to detect trends more accurately 🔍.
Sequential Labels:
Displays numerical labels (e.g., '5', '6', etc.) at key points where sequential conditions are met, offering insights into trend strength.
Highlights significant reversals with special labels like '9' and '13' for critical decision-making moments 🏷️.
Buy/Sell Signals:
Generates clear 'B' (buy) and 'S' (sell) labels based on predefined conditions derived from sequential analysis.
Provides actionable trade suggestions directly on the chart for easy interpretation.
Alert System:
Supports customizable alerts to notify users instantly when buy/sell conditions are triggered.
Ensures timely responses to market movements without constant monitoring 🔔.
HOW TO USE
Add Indicator to Chart:
Access the TradingView platform and navigate to the indicators section.
Select ' L3 Magic-9 MACD Setup' from the list and add it to your desired chart.
Configure Settings:
Open the settings panel to adjust MACD parameters such as Fast Length, Slow Length, and Signal Length according to your trading strategy.
Modify plot colors and styles to suit your visual preferences for better readability.
Analyze Chart Labels:
Monitor the chart for sequentially numbered labels indicating trend strength and potential reversal points.
Pay close attention to special labels like '9' and '13' for crucial trading signals.
Combine with Other Tools:
Use additional technical indicators or fundamental analysis to confirm signals generated by the L3 Magic-9 MACD Setup.
Enhance decision-making accuracy by cross-verifying multiple data sources.
LIMITATIONS
Market Conditions Sensitivity:
The indicator may produce fewer reliable signals during periods of low volatility or range-bound markets.
Traders should be cautious of false positives in highly choppy environments 🌪️.
Dependency on Historical Data:
Accurate performance requires sufficient historical price data; insufficient data may lead to inaccurate calculations.
Regular updates and backtesting are essential to maintain effectiveness over time.
Single Indicator Risk:
Relying solely on MACD-based signals can miss broader market context; combining with other analytical tools is recommended.
Always validate signals through multiple lenses to mitigate risks associated with single-indicator strategies.
NOTES
Data Sufficiency:
Ensure your chart has enough historical data loaded to support robust MACD computations.
Periodically review and update data inputs to reflect current market dynamics.
Testing and Validation:
Conduct thorough testing on demo accounts before deploying the indicator in live trading scenarios.
Backtest across various market cycles to assess its resilience under different conditions.
Parameter Optimization:
Experiment with different parameter settings tailored to specific asset classes or trading styles.
Fine-tune the lookback period and other configurable options to align with personal trading objectives.
Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
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.
-Dskyz
AI Volume StrategyAI Volume Strategy detects significant volume spikes and combines them with trend direction and candlestick color to generate buy and sell signals. The strategy uses an Exponential Moving Average (EMA) of volume to identify abnormal volume spikes that may indicate strong market activity. Additionally, it uses a 50-period EMA of price to filter the trend and decide on entry direction.
Key Features:
Volume Spike Detection: The strategy detects when the current volume exceeds the EMA of volume by a user-defined multiplier, signaling abnormal increases in market activity.
Trend Direction Filter: The strategy uses a 50-period EMA of price to determine the market trend. Buy signals are generated when the price is above the EMA (uptrend), and sell signals are generated when the price is below the EMA (downtrend).
Candle Color Filter: The strategy generates a buy signal only when the current candle is bullish (green) and a sell signal only when the current candle is bearish (red).
Exit after X Bars: The strategy automatically closes the position after a specified number of bars (default is 5 bars), but the exit condition can be adjusted based on user preference, timeframe, and backtesting results. The default exit is after 5 bars, but users can set it to 1 bar or any other number depending on their preferences and strategy.
Signals:
Buy Signal: Generated when a volume spike occurs, the trend is upward, and the current candle is bullish.
Sell Signal: Generated when a volume spike occurs, the trend is downward, and the current candle is bearish.
Alerts:
Buy Alert: Alerts the user when a buy signal is triggered.
Sell Alert: Alerts the user when a sell signal is triggered.
Visualization:
Buy Signal: A green label appears below the bar when the buy conditions are met.
Sell Signal: A red label appears above the bar when the sell conditions are met.
Volume EMA: Optionally, the Volume EMA line can be plotted on the chart to visualize volume trends.
This strategy helps traders identify potential entry points based on increased volume activity while considering trend direction and candlestick patterns. With the ability to adjust the exit condition, users can fine-tune the strategy to their specific needs and backtest results.
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
External Signals Strategy TesterExternal Signals Strategy Tester
This strategy is designed to help you backtest external buy/sell signals coming from another indicator on your chart. It is a flexible and powerful tool that allows you to simulate real trading based on signals generated by any indicator, using input.source connections.
🔧 How It Works
Instead of generating signals internally, this strategy listens to two external input sources:
One for buy signals
One for sell signals
These sources can be connected to the plots from another indicator (for example, custom indicators, signal lines, or logic-based plots).
To use this:
Add your indicator to the chart (it must be visible on the same pane as this strategy).
Open the settings of the strategy.
In the fields Buy Signal and Sell Signal, select the appropriate plot (line, value, etc.) from the indicator that represents the buy/sell logic.
The strategy will open positions when the selected buy signal crosses above 0, and sell signal crosses above 0.
This logic can be easily adapted by modifying the crossover rule inside the script if your signal style is different.
⚙️ Features Included
✅ Configurable trade direction:
You can choose whether to allow long trades, short trades, or both.
✅ Optional close on opposite signal:
When enabled, the strategy will exit the current position if an opposite signal appears.
✅ Optional full position reversal:
When enabled, the strategy will close the current position and immediately open an opposite one on the reverse signal.
✅ Risk Management Tools:
You can define:
Take Profit (TP): Position will be closed once the specified profit (in %) is reached.
Stop Loss (SL): Position will be closed if the price drops to the specified loss level (in %).
BreakEven (BE): Once the specified profit threshold is reached, the strategy will move the stop-loss to the entry price.
📌 If any of these values (TP, SL, BE) are set to 0, the feature is disabled and will not be applied.
🧪 Best Use Cases
Backtesting signals from custom indicators, without rewriting the logic into a strategy.
Comparing the performance of different signal sources.
Testing external indicators with optional position management logic.
Validating strategies using external filters, oscillators, or trend signals.
📌 Final Notes
You can visualize where the strategy detected buy/sell signals using green/red markers on the chart.
All parameters are customizable through the strategy settings panel.
This strategy does not repaint, and it processes signals in real-time only (no lookahead bias).
TrendPredator FOTrendPredator Fakeout Highlighter (FO)
The TrendPredator Fakeout Highlighter is designed to enhance multi-timeframe trend analysis by identifying key market behaviors that indicate trend strength, weakness, and potential reversals. Inspired by Stacey Burke’s trading approach, this tool focuses on trend-following, momentum shifts, and trader traps, helping traders capitalize on high-probability setups.
At its core, this indicator highlights peak formations—anchor points where price often locks in trapped traders before making decisive moves. These principles align with George Douglas Taylor’s 3-day cycle and Steve Mauro’s BTMM method, making the FO Highlighter a powerful tool for reading market structure. As markets are fractal, this analysis works on any timeframe.
How It Works
The TrendPredator FO highlights key price action signals by coloring candles based on their bias state on the current timeframe.
It tracks four major elements:
Breakout/Breakdown Bars – Did the candle close in a breakout or breakdown relative to the last candle?
Fakeout Bars (Trend Close) – Did the candle break a prior high/low and close back inside, but still in line with the trend?
Fakeout Bars (Counter-Trend Close) – Did the candle break a prior high/low, close back inside, and against the trend?
Switch Bars – Did the candle lose/ reclaim the breakout/down level of the last bar that closed in breakout/down, signalling a possible trend shift?
Reading the Trend with TrendPredator FO
The annotations in this example are added manually for illustration.
- Breakouts → Strong Trend
Multiple candles closing in breakout signal a healthy and strong trend.
- Fakeouts (Trend Close) → First Signs of Weakness
Candles that break out but close back inside suggest a potential slowdown—especially near key levels.
- Fakeouts (Counter-Trend Close) → Stronger Reversal Signal
Closing against the trend strengthens the reversal signal.
- Switch Bars → Momentum Shift
A shift in trend is confirmed when price crosses back through the last closed breakout candles breakout level, trapping traders and fuelling a move in the opposite direction.
- Breakdowns → Trend Reversal Confirmed
Once price breaks away from the peak formation, closing in breakdown, the trend shift is validated.
Customization & Settings
- Toggle individual candle types on/off
- Customize colors for each signal
- Set the number of historical candles displayed
Example Use Cases
1. Weekly Template Analysis
The weekly template is a core concept in Stacey Burke’s trading style. FO highlights individual candle states. With this the state of the trend and the developing weekly template can be evaluated precisely. The analysis is done on the daily timeframe and we are looking especially for overextended situations within a week, after multiple breakouts and for peak formations signalling potential reversals. This is helpful for thesis generation before a session and also for backtesting. The annotations in this example are added manually for illustration.
📈 Example: Weekly Template Analysis snapshot on daily timeframe
2. High Timeframe 5-Star Setup Analysis (Stacey Burke "ain't coming back" ACB Template)
This analysis identifies high-probability trade opportunities when daily breakout or down closes occur near key monthly levels mid-week, signalling overextensions and potentially large parabolic moves. Key signals for this are breakout or down closes occurring on a Wednesday. This is helpful for thesis generation before a session and also for backtesting. The annotations in this example are added manually for illustration. Also an indicator can bee seen on this chart shading every Wednesday to identify the signal.
📉 Example: High Timeframe Setup snapshot
3. Low Timeframe Entry Confirmation
FO helps confirm entry signals after a setup is identified, allowing traders to time their entries and exits more precisely. For this the highlighted Switch and/ or Fakeout bars can be highly valuable.
📊 Example (M15 Entry & Exit): Entry and Exit Confirmation snapshot
📊 Example (M5 Scale-In Strategy): Scaling Entries snapshot
The annotations in this examples are added manually for illustration.
Disclaimer
This indicator is for educational purposes only and does not guarantee profits.
None of the information provided shall be considered financial advice.
Users are fully responsible for their trading decisions and outcomes.
