Connors VIX Reversal III invented by Dave LandryThis strategy is based on trading signals derived from the behavior of the Volatility Index (VIX) relative to its 10-day moving average. The rules are split into buying and selling conditions:
Buy Conditions:
The VIX low must be above its 10-day moving average.
The VIX must close at least 10% above its 10-day moving average.
If both conditions are met, a buy signal is generated at the market's close.
Sell Conditions:
The VIX high must be below its 10-day moving average.
The VIX must close at least 10% below its 10-day moving average.
If both conditions are met, a sell signal is generated at the market's close.
Exit Conditions:
For long positions, the strategy exits when the VIX trades intraday below its previous day’s 10-day moving average.
For short positions, the strategy exits when the VIX trades intraday above its previous day’s 10-day moving average.
This strategy is primarily a mean-reversion strategy, where the market is expected to revert to a more normal state after the VIX exhibits extreme behavior (i.e., large deviations from its moving average).
About Dave Landry
Dave Landry is a well-known figure in the world of trading, particularly in technical analysis. He is an author, trader, and educator, best known for his work on swing trading strategies. Landry focuses on trend-following and momentum-based techniques, teaching traders how to capitalize on shorter-term price swings in the market. He has written books like "Dave Landry on Swing Trading" and "The Layman's Guide to Trading Stocks," which emphasize practical, actionable trading strategies.
About Connors Research
Connors Research is a financial research firm known for its quantitative research in financial markets. Founded by Larry Connors, the firm specializes in developing high-probability trading systems based on historical market behavior. Connors’ work is widely respected for its data-driven approach, including systems like the RSI(2) strategy, which focuses on short-term mean reversion. The firm also provides trading education and tools for institutional and retail traders alike, emphasizing strategies that can be backtested and quantified.
Risks of the Strategy
While this strategy may appear to offer promising opportunities to exploit extreme VIX movements, it carries several risks:
Market Volatility: The VIX itself is a measure of market volatility, meaning the strategy can be exposed to sudden and unpredictable market swings. This can result in whipsaws, where positions are opened and closed in rapid succession due to sharp reversals in the VIX.
Overfitting: Strategies based on specific conditions like the VIX closing 10% above or below its moving average can be subject to overfitting, meaning they work well in historical tests but may underperform in live markets. This is a common issue in quantitative trading systems that are not adaptable to changing market conditions .
Mean-Reversion Assumption: The core assumption behind this strategy is that markets will revert to their mean after extreme movements. However, during periods of sustained trends (e.g., market crashes or rallies), this assumption may break down, leading to prolonged drawdowns.
Liquidity and Slippage: Depending on the asset being traded (e.g., S&P 500 futures, ETFs), liquidity issues or slippage could occur when executing trades at market close, particularly in volatile conditions. This could increase costs or worsen trade execution.
Scientific Explanation of the Strategy
The VIX is often referred to as the "fear gauge" because it measures the market's expectations of volatility based on options prices. Research has shown that the VIX tends to spike during periods of market stress and revert to lower levels when conditions stabilize . Mean reversion strategies like this one assume that extreme VIX levels are unsustainable in the long run, which aligns with findings from academic literature on volatility and market behavior.
Studies have found that the VIX is inversely correlated with stock market returns, meaning that higher VIX levels often correspond to lower stock prices and vice versa . By using the VIX’s relationship with its 10-day moving average, this strategy aims to capture reversals in market sentiment. The 10% threshold is designed to identify moments when the VIX is significantly deviating from its norm, signaling a potential reversal.
However, academic research also highlights the limitations of relying on the VIX alone for trading signals. The VIX does not predict market direction, only volatility, meaning that it cannot indicate the magnitude of price movements . Furthermore, extreme VIX levels can persist longer than expected, particularly during financial crises.
In conclusion, while the strategy is grounded in well-established financial principles (e.g., mean reversion and the relationship between volatility and market performance), it carries inherent risks and should be used with caution. Backtesting and careful risk management are essential before applying this strategy in live markets.
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Zero-lag TEMA Crosses Strategy[Pakun]Here's the adjusted strategy description in English, aligned with the house rules:
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### 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.
VAWSI and Trend Persistance Reversal Strategy SL/TPThis is a completely revamped version of my "RSI and ATR Trend Reversal Strategy."
What's New?
The RSI has been replaced with an original indicator of mine, the "VAWSI," as I've elected to call it.
The standard RSI measures a change in an RMA to determine the strength of a movement.
The VAWSI performs very similarly, except it uses another original indicator of mine, the VAWMA.
VAWMA stands for "Volume (and) ATR Weight Moving Average." It takes an average of the volume and ATR and uses the ratio of each bar to weigh a moving average of the source.
It has the same formula as an RSI, but uses the VAWMA instead of an RMA.
Next we have the Trend Persistence indicator, which is an index on how long a trend has been persisting for. It is another original indicator. It takes the max deviation the source has from lowest/highest of a specified length. It then takes a cumulative measure of that amount, measures the change, then creates a strength index with that amount.
The VAWSI is a measure of an emerging trend, and the Trend Persistence indicator is a measure of how long a trend has persisted.
Finally, the 3rd main indicator, is a slight variation of an ATR. Rather than taking the max of source - low or high- source and source - source , it instead takes the max of high-low and the absolute value of source - the previous source. It then takes the absolute value of the change of this, and normalizes it with the source.
Inputs
Minimum SL/TP ensures that the Stop Loss and Take Profit still exist in untrendy markets. This is the minimum Amount that will always be applied.
VAWSI Weight is a divided by 100 multiplier for the VAWSI. So value of 200 means it is multiplied by 2. Think of it like a percentage.
Trend Persistence weight and ATR Weight are applied the same. Higher the number, the more impactful on the final calculation it is.
Combination Mult is an outright multiplier to the final calculation. So a 2.0 = * 2.0
Trend Persistence Smoothing Length is the length of the weighted moving average applied to the Trend Persistence Strength index.
Length Cycle Decimal is a replacement of length for the script.
Here we used BlackCat1402's Dynamic Length Calculation, which can be found on his page. With his permission we have implemented it into this script. Big shout out to them for not only creating, but allowing us to use it here.
The Length Cycle Decimal is used to calculate the dynamic length. Because TradingView only allows series int for their built-in library, a lot of the baseline indicators we use have to be manually recreated as functions in the following section.
The Strategy
As usual, we use Heiken Ashi values for calculations.
We begin by establishing the minimum SL/TP for use later.
Next we determine the amount of bars back since the last crossup or crossdown of our threshold line.
We then perform some normalization of our multipliers. We want a larger trend or larger VAWSI amount to narrow the threshold, so we have 1 divide them. This way, a higher reading outputs a smaller number and vice versa. We do this for both Trend Persistence, and the VAWSI.
The VAWSI we also normalize, where rather than it being a 0-100 reading of trend direction and strength, we absolute it so that as long as a trend is strong, regardless of direction, it will have a higher reading. With these normalized values, we add them together and simply subtract the ATR measurement rather than having 1 divide it.
Here you can see how the different measurements add up. A lower final number suggests imminent reversal, and a higher final number suggests an untrendy or choppy market.
ATR is in orange, the Trend Persistence is blue, the VAWSI is purple, and the final amount is green.
We take this final number and depending on the current trend direction, we multiply it by either the Highest or Lowest source since the last crossup or crossdown. We then take the highest or lowest of this calculation, and have it be our Stop Loss or Take Profit. This number cannot be higher/lower than the previous source to ensure a rapid spike doesn't immediately close your position on a still continuing trend. As well, the threshold cannot be higher/ lower than the the specified Stop Loss and Take Profit
Only after the source has fully crossed these lines do we consider it a crossup or crossdown. We confirm this with a barstate.isconfirmed to prevent repainting. Next, each time there is a crossup or crossdown we enter a long or a short respectively and plot accordingly.
I have the strategy configured to "process on order close" to ensure an accurate backtesting result. You could also set this to false and add a 1 bar delay to the "if crossup" and "if crossdown" lines under strategy so that it is calculated based on the open of the next bar.
Final Notes
The amounts have been preconfigured for performance on RIOT 5 Minute timeframe. Other timeframes are viable as well. With a few changes to the parameters, this strategy has backtested well on NVDA, AAPL, TSLA, and AMD. I recommend before altering settings to try other timeframes first.
This script does not seem to perform nearly as well in typically untrendy and choppy markets such as crypto and forex. With some setting changes, I have seen okay results with crypto, but overfitting could be the cause there.
Thank you very much, and please enjoy.
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
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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.
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.
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)
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.
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.
BOS FVG IndicatorBOS FVG Indicator (Smart Market Structure Tool)
🔎 Overview
The BOS FVG Indicator is a smart price-action–based tool that combines Break of Structure (BOS), Change of Character (CHoCH), Fair Value Gaps (FVG), Supertrend, and ADX strength into one powerful indicator.
It helps traders identify market structure shifts, imbalances, and high-probability trade setups while also highlighting no-trade zones (NTZ) where the market is choppy or lacks trend strength.
This indicator is designed for intraday and swing traders who follow ICT-style concepts or price-action based trading.
⚡ Key Features
Break of Structure (BOS) & CHoCH Detection
Labels bullish BOS (📈 BOS↑) and bearish BOS (📉 BOS↓).
Highlights structure shifts for trend confirmation.
Fair Value Gaps (FVG)
Auto-detects bullish and bearish FVGs.
Draws transparent boxes with labels where imbalances appear.
Supertrend Confirmation
Adaptive supertrend line with dynamic coloring (green = bullish, red = bearish).
No Trade Zone (NTZ)
Automatically shades background gray when ADX is weak or no BOS detected.
Helps avoid false signals in sideways/choppy markets.
Multi-Timeframe Context
Previous 4H candle range plotted as a dotted yellow box.
Useful for intraday traders tracking HTF liquidity zones.
Signal Strength
Regular and Strong Buy/Sell signals based on ADX confirmation.
Labels include entry info, RR (2:1), and trend strength.
Market Info Dashboard
Table on chart showing ADX strength, current trend, and trade zone status.
🛠 How to Use
Add to Chart → Apply the indicator to any timeframe (works best on 5m–1H for intraday, 4H–Daily for swing).
Choose Mode
Indicator Mode → Shows visual signals, BOS, FVG, NTZ zones, and dashboard.
Strategy Mode → Displays trade entry labels with RR info for backtesting setups.
Filters
Only trade signals when ADX > threshold and NTZ is inactive.
Confirm with Supertrend direction + BOS + FVG alignment.
Entries & Exits
Long Entry → Bullish BOS + Bullish FVG + Trend bullish.
Short Entry → Bearish BOS + Bearish FVG + Trend bearish.
Stop Loss: Recent swing high/low.
Take Profit: Auto-suggested 2:1 RR.
🔔 Alerts
Set alerts to never miss key signals:
✅ Bullish / Bearish BOS
✅ Bullish / Bearish FVG
✅ Strong Buy / Sell
✅ Regular Buy / Sell
✅ Long / Short Entries
✅ No Trade Zone active
Alerts are pre-configured with clear messages (📈, 📉, 🚀, 🟢, 🔴, ⚪).
📌 Best Use Cases
ICT-style liquidity and FVG traders.
Intraday traders filtering strong vs weak signals.
Swing traders using multi-timeframe confirmation.
Traders who want an all-in-one market structure toolkit.
👉 This script is not financial advice. Always backtest before using in live markets.
FlowStateTrader FlowState Trader - Advanced Time-Filtered Strategy
## Overview
FlowState Trader is a sophisticated algorithmic trading strategy that combines precision entry signals with intelligent time-based filtering and adaptive risk management. Built for traders seeking to achieve their optimal performance state, FlowState identifies high-probability trading opportunities within user-defined time windows while employing dynamic trailing stops and partial position management.
## Core Strategy Philosophy
FlowState Trader operates on the principle that peak trading performance occurs when three elements align: **Focus** (precise entry signals), **Flow** (optimal time windows), and **State** (intelligent position management). This strategy excels at finding reversal opportunities at key support and resistance levels while filtering out suboptimal trading periods to keep traders in their optimal flow state.
## Key Features
### 🎯 Focus Entry System
**Support/Resistance Zone Trading**:
- Dynamic identification of key price levels using configurable lookback periods
- Entry signals triggered when price interacts with these critical zones
- Volume confirmation ensures genuine breakout/reversal momentum
- Trend filter alignment prevents counter-trend disasters
**Entry Conditions**:
- **Long Signals**: Price closes above support buffer, touches support level, with above-average volume
- **Short Signals**: Price closes below resistance buffer, touches resistance level, with above-average volume
- Optional trend filter using EMA or SMA for directional bias confirmation
### ⏰ FlowState Time Filtering System
**Comprehensive Time Controls**:
- **12-Hour Format Trading Windows**: User-friendly AM/PM time selection
- **Multi-Timezone Support**: UTC, EST, PST, CST with automatic conversion
- **Day-of-Week Filtering**: Trade only weekdays, weekends, or both
- **Lunch Hour Avoidance**: Automatically skips low-volume lunch periods (12-1 PM)
- **Visual Time Indicators**: Background coloring shows active/inactive trading periods
**Smart Time Features**:
- Handles overnight trading sessions seamlessly
- Prevents trades during historically poor performance periods
- Customizable trading hours for different market sessions
- Real-time trading window status in dashboard
### 🛡️ Adaptive Risk Management
**Multi-Level Take Profit System**:
- **TP1**: First profit target with optional partial position closure
- **TP2**: Final profit target for remaining position
- **Flexible Scaling**: Choose number of contracts to close at each level
**Dynamic Trailing Stop Technology**:
- **Three Operating Modes**:
- **Conservative**: Earlier activation, tighter trailing (protect profits)
- **Balanced**: Optimal risk/reward balance (recommended)
- **Aggressive**: Later activation, wider trailing (let winners run)
- **ATR-Based Calculations**: Adapts to current market volatility
- **Automatic Activation**: Engages when position reaches profitability threshold
### 📊 Intelligent Position Sizing
**Contract-Based Management**:
- Configurable entry quantity (1-1000 contracts)
- Partial close quantities for profit-taking
- Clear position tracking and P&L monitoring
- Real-time position status updates
### 🎨 Professional Visualization
**Enhanced Chart Elements**:
- **Entry Zone Highlighting**: Clear visual identification of trading opportunities
- **Dynamic Risk/Reward Lines**: Real-time TP and SL levels with price labels
- **Trailing Stop Visualization**: Live tracking of adaptive stop levels
- **Support/Resistance Lines**: Key level identification
- **Time Window Background**: Visual confirmation of active trading periods
**Dual Dashboard System**:
- **Strategy Dashboard**: Real-time position info, settings status, and current levels
- **Performance Scorecard**: Live P&L tracking, win rates, and trade statistics
- **Customizable Sizing**: Small, Medium, or Large display options
### ⚙️ Comprehensive Customization
**Core Strategy Settings**:
- **Lookback Period**: Support/resistance calculation period (5-100 bars)
- **ATR Configuration**: Period and multipliers for stops/targets
- **Reward-to-Risk Ratios**: Customizable profit target calculations
- **Trend Filter Options**: EMA/SMA selection with adjustable periods
**Time Filter Controls**:
- **Trading Hours**: Start/end times in 12-hour format
- **Timezone Selection**: Four major timezone options
- **Day Restrictions**: Weekend-only, weekday-only, or unrestricted
- **Session Management**: Lunch hour avoidance and custom periods
**Risk Management Options**:
- **Trailing Stop Modes**: Conservative/Balanced/Aggressive presets
- **Partial Close Settings**: Enable/disable with custom quantities
- **Alert System**: Comprehensive notifications for all trade events
### 📈 Performance Tracking
**Real-Time Metrics**:
- Net profit/loss calculation
- Win rate percentage
- Profit factor analysis
- Maximum drawdown tracking
- Total trade count and breakdown
- Current position P&L
**Trade Analytics**:
- Winner/loser ratio tracking
- Real-time performance scorecard
- Strategy effectiveness monitoring
- Risk-adjusted return metrics
### 🔔 Alert System
**Comprehensive Notifications**:
- Entry signal alerts with price and quantity
- Take profit level hits (TP1 and TP2)
- Stop loss activations
- Trailing stop engagements
- Position closure notifications
## Strategy Logic Deep Dive
### Entry Signal Generation
The strategy identifies high-probability reversal points by combining multiple confirmation factors:
1. **Price Action**: Looks for price interaction with key support/resistance levels
2. **Volume Confirmation**: Ensures sufficient market interest and liquidity
3. **Trend Alignment**: Optional filter prevents counter-trend positions
4. **Time Validation**: Only trades during user-defined optimal periods
5. **Zone Analysis**: Entry occurs within calculated buffer zones around key levels
### Risk Management Philosophy
FlowState Trader employs a three-tier risk management approach:
1. **Initial Protection**: ATR-based stop losses set at strategy entry
2. **Profit Preservation**: Trailing stops activate once position becomes profitable
3. **Scaled Exit**: Partial profit-taking allows for both security and potential
### Time-Based Edge
The time filtering system recognizes that not all trading hours are equal:
- Avoids low-volume, high-spread periods
- Focuses on optimal liquidity windows
- Prevents trading during news events (lunch hours)
- Allows customization for different market sessions
## Best Practices and Optimization
### Recommended Settings
**For Scalping (1-5 minute charts)**:
- Lookback Period: 10-20
- ATR Period: 14
- Trailing Stop: Conservative mode
- Time Filter: Major session hours only
**For Day Trading (15-60 minute charts)**:
- Lookback Period: 20-30
- ATR Period: 14-21
- Trailing Stop: Balanced mode
- Time Filter: Extended trading hours
**For Swing Trading (4H+ charts)**:
- Lookback Period: 30-50
- ATR Period: 21+
- Trailing Stop: Aggressive mode
- Time Filter: Disabled or very broad
### Market Compatibility
- **Forex**: Excellent for major pairs during active sessions
- **Stocks**: Ideal for liquid stocks during market hours
- **Futures**: Perfect for index and commodity futures
- **Crypto**: Effective on major cryptocurrencies (24/7 capability)
### Risk Considerations
- **Market Conditions**: Performance varies with volatility regimes
- **Timeframe Selection**: Lower timeframes require tighter risk management
- **Position Sizing**: Never risk more than 1-2% of account per trade
- **Backtesting**: Always test on historical data before live implementation
## Educational Value
FlowState serves as an excellent learning tool for:
- Understanding support/resistance trading
- Learning proper time-based filtering
- Mastering trailing stop techniques
- Developing systematic trading approaches
- Risk management best practices
## Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly backtest the strategy and understand all risks before live trading. Always use proper position sizing and never risk more than you can afford to lose.
---
*FlowState Trader represents the evolution of systematic trading - combining classical technical analysis with modern risk management and intelligent time filtering to help traders achieve their optimal performance state through systematic, disciplined execution.*
Wickless Tap Signals Wickless Tap Signals — TradingView Indicator (v6)
A precision signal-only tool that marks BUY/SELL events when price “retests” the base of a very strong impulse candle (no wick on the retest side) in the direction of trend.
What it does (in plain English)
Finds powerful impulse candles:
Bull case: a green candle with no lower wick (its open ≈ low).
Bear case: a red candle with no upper wick (its open ≈ high).
Confirms trend with an EMA filter:
Only looks for bullish bases while price is above the EMA.
Only looks for bearish bases while price is below the EMA.
Waits for the retest (“tap”):
Later, if price revisits the base of that wickless candle
Bullish: taps the candle’s low/open → BUY signal
Bearish: taps the candle’s high/open → SELL signal
Optional level “consumption” so each base can trigger one signal, not many.
The idea: a wickless impulse often marks strong initiative order flow. The first retest of that base frequently acts as a springboard (bull) or ceiling (bear).
Exact rules (formal)
Let tick = syminfo.mintick, tol = tapTicks * tick.
Trend filter
inUp = close > EMA(lenEMA)
inDn = close < EMA(lenEMA)
Wickless impulse candles (confirmed on bar close)
Bullish wickless: close > open and abs(low - open) ≤ tol
Bearish wickless: close < open and abs(high - open) ≤ tol
When such a candle closes with trend alignment:
Store bullTapLevel = low (for bull case) and its bar index.
Store bearTapLevel = high (for bear case) and its bar index.
Signals (must happen on a later bar than the origin)
BUY: low ≤ bullTapLevel + tol and inUp and bar_index > bullBarIdx
SELL: high ≥ bearTapLevel - tol and inDn and bar_index > bearBarIdx
One-shot option
If enabled, once a signal fires, the stored level is cleared so it won’t trigger again.
Inputs (Settings)
Trend EMA Length (lenEMA): Default 200.
Use 50–100 for intraday, 200 for swing/position.
Tap Tolerance (ticks) (tapTicks): Default 1.
Helps account for tiny feed discrepancies. Set 0 for strict equality.
One Signal per Level (oneShot): Default ON.
If OFF, multiple taps can create multiple signals.
Plot Tap Levels (plotLevels): Draws horizontal lines at active bases.
Show Pattern Labels (showLabels): Marks the origin wickless candles.
Plots & Visuals
EMA trend line for context.
Tap Levels:
Green line at bullish base (origin candle’s low/open).
Red line at bearish base (origin candle’s high/open).
Signals:
BUY: triangle-up below the bar on the tap.
SELL: triangle-down above the bar on the tap.
Labels (optional):
Marks the original wickless impulse candle that created each level.
Alerts
Two alert conditions are built in:
“BUY Signal” — fires when a bullish tap occurs.
“SELL Signal” — fires when a bearish tap occurs.
How to set:
Add the indicator to your chart.
Click Alerts (⏰) → Condition = this indicator.
Choose BUY Signal or SELL Signal.
Set your alert frequency and delivery method.
Recommended usage
Timeframes: Works on any; start with 5–15m intraday, or 1H–1D for swing.
Markets: Equities, futures, FX, crypto. For thin/illiquid assets, consider a slightly larger Tap Tolerance.
Confluence ideas (optional, but helpful):
Higher-timeframe trend agreeing with your chart timeframe.
Volume surge on the origin wickless candle.
S/R, order blocks, or SMC structures near the tap level.
Avoid major news moments when slippage is high.
No-repaint behavior
Origin patterns are detected only on bar close (barstate.isconfirmed), so bases are created with confirmed data.
Signals come after the origin bar, on subsequent taps.
There is no lookahead; lines and shapes reflect information known at the time.
(As with all real-time indicators, an intrabar tap can trigger an alert during the live bar; the signal then remains if that condition held at bar close.)
Known limitations & design choices
Single active level per side: The script tracks only the most recent bullish base and most recent bearish base.
Want a queue of multiple simultaneous bases? That’s possible with arrays; ask and we’ll extend it.
Heikin Ashi / non-standard candles: Wick definitions change; for consistent behavior use regular OHLC candles.
Gaps: On large gaps, taps can occur instantly at the open. Consider one-shot ON to avoid rapid repeats.
This is an indicator, not a strategy: It does not place trades or compute PnL. For backtesting, we can convert it into a strategy with SL/TP logic (ATR or structure-based).
Practical tips
Tap Tolerance:
If you miss obvious taps by a hair, increase to 1–2 ticks.
For FX/crypto with tiny ticks, even 0 or 1 is often enough.
EMA length:
Shorten for faster signals; lengthen for cleaner trend selection.
Risk management (manual suggestion):
For BUY signals, consider a stop slightly below the tap level (or ATR-based).
For SELL signals, consider a stop slightly above the tap level.
Scale out or trail using structure or ATR.
Quick checklist
✅ Price above EMA → watch for a green no-lower-wick candle → store its low → BUY on tap.
✅ Price below EMA → watch for a red no-upper-wick candle → store its high → SELL on tap.
✅ Use Tap Tolerance to avoid missing precise touches by one tick.
✅ Consider One Signal per Level to keep trades uncluttered.
FAQ
Q: Why did I not get a signal even though price touched the level?
A: Check Tap Tolerance (maybe too strict), trend alignment at the tap bar, and that the tap happened after the origin candle. Also confirm you’re on regular candles.
Q: Can I see multiple bases at once?
A: This version tracks the latest bull and bear bases. We can extend to arrays to keep N recent bases per side.
Q: Will it repaint?
A: No. Bases form on confirmed closes, and signals only on later bars.
Q: Can I backtest it?
A: This is a study. Ask for the strategy variant and we’ll add entries, exits, SL/TP, and stats.
Keltner Channel Based Grid Strategy # KC Grid Strategy - Keltner Channel Based Grid Trading System
## Strategy Overview
KC Grid Strategy is an innovative grid trading system that combines the power of Keltner Channels with dynamic position sizing to create a mean-reversion trading approach. This strategy automatically adjusts position sizes based on price deviation from the Keltner Channel center line, implementing a systematic grid-based approach that capitalizes on market volatility and price oscillations.
## Core Principles
### Keltner Channel Foundation
The strategy builds upon the Keltner Channel indicator, which consists of:
- **Center Line**: Moving average (EMA or SMA) of the price
- **Upper Band**: Center line + (ATR/TR/Range × Multiplier)
- **Lower Band**: Center line - (ATR/TR/Range × Multiplier)
### Grid Trading Logic
The strategy implements a sophisticated grid system where:
1. **Position Direction**: Inversely correlated to price position within the channel
- When price is above center line → Short positions
- When price is below center line → Long positions
2. **Position Size**: Proportional to distance from center line
- Greater deviation = Larger position size
3. **Grid Activation**: Positions are adjusted only when the difference exceeds a predefined grid threshold
### Mathematical Foundation
The core calculation uses the KC Rate formula:
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
This creates a mean-reversion system where positions increase as price moves further from the mean, expecting eventual return to equilibrium.
## Parameter Guide
### Time Range Settings
- **Start Date**: Beginning of strategy execution period
- **End Date**: End of strategy execution period
### Core Parameters
1. **Number of Grids (NumGrid)**: Default 12
- Controls grid sensitivity and position adjustment frequency
- Higher values = More frequent but smaller adjustments
- Lower values = Less frequent but larger adjustments
2. **Length**: Default 10
- Period for moving average and volatility calculations
- Shorter periods = More responsive to recent price action
- Longer periods = Smoother, less noisy signals
3. **Grid Coefficient (kcRateMult)**: Default 1.33
- Multiplier for channel width calculation
- Higher values = Wider channels, less frequent trades
- Lower values = Narrower channels, more frequent trades
4. **Source**: Default Close
- Price source for calculations (Close, Open, High, Low, etc.)
- Close price typically provides most reliable signals
5. **Use Exponential MA**: Default True
- True = Uses EMA (more responsive to recent prices)
- False = Uses SMA (equal weight to all periods)
6. **Bands Style**: Default "Average True Range"
- **Average True Range**: Smoothed volatility measure (recommended)
- **True Range**: Current bar's volatility only
- **Range**: Simple high-low difference
## How to Use
### Setup Instructions
1. **Apply to Chart**: Add the strategy to your desired timeframe and instrument
2. **Configure Parameters**: Adjust settings based on market characteristics:
- Volatile markets: Increase Grid Coefficient, reduce Number of Grids
- Stable markets: Decrease Grid Coefficient, increase Number of Grids
3. **Set Time Range**: Define your backtesting or live trading period
4. **Monitor Performance**: Watch strategy performance metrics and adjust as needed
### Optimal Market Conditions
- **Range-bound markets**: Strategy performs best in sideways trending markets
- **High volatility**: Benefits from frequent price oscillations around the mean
- **Liquid instruments**: Ensures efficient order execution and minimal slippage
### Position Management
The strategy automatically:
- Calculates optimal position sizes based on account equity
- Adjusts positions incrementally as price moves through grid levels
- Maintains risk control through maximum position limits
- Executes trades only during specified time periods
## Risk Warnings
### ⚠️ Important Risk Considerations
1. **Trending Market Risk**:
- Strategy may underperform or generate losses in strong trending markets
- Mean-reversion assumption may fail during sustained directional moves
- Consider market regime analysis before deployment
2. **Leverage and Position Size Risk**:
- Strategy uses pyramiding (up to 20 positions)
- Large positions may accumulate during extended moves
- Monitor account equity and margin requirements closely
3. **Volatility Risk**:
- Sudden volatility spikes may trigger multiple rapid position adjustments
- Consider volatility filters during high-impact news events
- Backtest across different volatility regimes
4. **Execution Risk**:
- Strategy calculates on every tick (calc_on_every_tick = true)
- May generate frequent orders in volatile conditions
- Ensure adequate execution infrastructure and consider transaction costs
5. **Parameter Sensitivity**:
- Performance highly dependent on parameter optimization
- Over-optimization may lead to curve-fitting
- Regular parameter review and adjustment may be necessary
## Suitable Scenarios
### Ideal Market Conditions
- **Sideways/Range-bound markets**: Primary use case
- **Mean-reverting instruments**: Forex pairs, some commodities
- **Stable volatility environments**: Consistent ATR patterns
- **Liquid markets**: Major currency pairs, popular stocks/indices
## Important Notes
### Strategy Limitations
1. **No Stop Loss**: Strategy relies on mean reversion without traditional stop losses
2. **Capital Requirements**: Requires sufficient capital for grid-based position sizing
3. **Market Regime Dependency**: Performance varies significantly across different market conditions
## Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly test the strategy and understand its mechanics before risking real capital. The author assumes no responsibility for trading losses incurred through the use of this strategy.
---
# KC网格策略 - 基于肯特纳通道的网格交易系统
## 策略概述
KC网格策略是一个创新的网格交易系统，它将肯特纳通道的力量与动态仓位调整相结合，创建了一个均值回归交易方法。该策略根据价格偏离肯特纳通道中心线的程度自动调整仓位大小，实施系统化的网格方法，利用市场波动和价格振荡获利。
## 核心原理
### 肯特纳通道基础
该策略建立在肯特纳通道指标之上，包含：
- **中心线**: 价格的移动平均线（EMA或SMA）
- **上轨**: 中心线 + (ATR/TR/Range × 乘数)
- **下轨**: 中心线 - (ATR/TR/Range × 乘数)
### 网格交易逻辑
该策略实施复杂的网格系统：
1. **仓位方向**: 与价格在通道中的位置呈反向关系
- 当价格高于中心线时 → 空头仓位
- 当价格低于中心线时 → 多头仓位
2. **仓位大小**: 与距离中心线的距离成正比
- 偏离越大 = 仓位越大
3. **网格激活**: 只有当差异超过预定义的网格阈值时才调整仓位
### 数学基础
核心计算使用KC比率公式：
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
这创建了一个均值回归系统，当价格偏离均值越远时仓位越大，期望最终回归均衡。
## 参数说明
### 时间范围设置
- **开始日期**: 策略执行期间的开始时间
- **结束日期**: 策略执行期间的结束时间
### 核心参数
1. **网格数量 (NumGrid)**: 默认12
- 控制网格敏感度和仓位调整频率
- 较高值 = 更频繁但较小的调整
- 较低值 = 较少频繁但较大的调整
2. **长度**: 默认10
- 移动平均线和波动率计算的周期
- 较短周期 = 对近期价格行为更敏感
- 较长周期 = 更平滑，噪音更少的信号
3. **网格系数 (kcRateMult)**: 默认1.33
- 通道宽度计算的乘数
- 较高值 = 更宽的通道，较少频繁的交易
- 较低值 = 更窄的通道，更频繁的交易
4. **数据源**: 默认收盘价
- 计算的价格来源（收盘价、开盘价、最高价、最低价等）
- 收盘价通常提供最可靠的信号
5. **使用指数移动平均**: 默认True
- True = 使用EMA（对近期价格更敏感）
- False = 使用SMA（对所有周期等权重）
6. **通道样式**: 默认"平均真实范围"
- **平均真实范围**: 平滑的波动率测量（推荐）
- **真实范围**: 仅当前K线的波动率
- **范围**: 简单的高低价差
## 使用方法
### 设置说明
1. **应用到图表**: 将策略添加到您所需的时间框架和交易品种
2. **配置参数**: 根据市场特征调整设置：
- 波动市场：增加网格系数，减少网格数量
- 稳定市场：减少网格系数，增加网格数量
3. **设置时间范围**: 定义您的回测或实盘交易期间
4. **监控表现**: 观察策略表现指标并根据需要调整
### 最佳市场条件
- **区间震荡市场**: 策略在横盘趋势市场中表现最佳
- **高波动性**: 受益于围绕均值的频繁价格振荡
- **流动性强的品种**: 确保高效的订单执行和最小滑点
### 仓位管理
策略自动：
- 根据账户权益计算最优仓位大小
- 随着价格在网格水平移动逐步调整仓位
- 通过最大仓位限制维持风险控制
- 仅在指定时间段内执行交易
## 风险警示
### ⚠️ 重要风险考虑
1. **趋势市场风险**:
- 策略在强趋势市场中可能表现不佳或产生损失
- 在持续方向性移动期间均值回归假设可能失效
- 部署前考虑市场制度分析
2. **杠杆和仓位大小风险**:
- 策略使用金字塔加仓（最多20个仓位）
- 在延长移动期间可能积累大仓位
- 密切监控账户权益和保证金要求
3. **波动性风险**:
- 突然的波动性激增可能触发多次快速仓位调整
- 在高影响新闻事件期间考虑波动性过滤器
- 在不同波动性制度下进行回测
4. **执行风险**:
- 策略在每个tick上计算（calc_on_every_tick = true）
- 在波动条件下可能产生频繁订单
- 确保充足的执行基础设施并考虑交易成本
5. **参数敏感性**:
- 表现高度依赖于参数优化
- 过度优化可能导致曲线拟合
- 可能需要定期参数审查和调整
## 适用场景
### 理想市场条件
- **横盘/区间震荡市场**: 主要用例
- **均值回归品种**: 外汇对，某些商品
- **稳定波动性环境**: 一致的ATR模式
- **流动性市场**: 主要货币对，热门股票/指数
## 注意事项
### 策略限制
1. **无止损**: 策略依赖均值回归而无传统止损
2. **资金要求**: 需要充足资金进行基于网格的仓位调整
3. **市场制度依赖性**: 在不同市场条件下表现差异显著
## 免责声明
该策略仅供教育和研究目的。过往表现不保证未来结果。交易涉及重大损失风险，并非适合所有投资者。用户应在投入真实资金前彻底测试策略并理解其机制。作者对使用此策略产生的交易损失不承担任何责任。
---
**Strategy Version**: Pine Script v6
**Author**: Signal2Trade
**Last Updated**: 2025-8-9
**License**: Open Source (Mozilla Public License 2.0)
Options Strategy V2.0📈 Options Strategy V2.0 – Intraday Reversal-Resilient Momentum System
Overview:
This strategy is designed specifically for intraday SPY, TSLA, MSFT, etc. options trading (0DTE or 1DTE), using high-probability signals derived from a confluence of technical indicators: EMA crossovers, RSI thresholds, ATR-based risk control, and volume spikes. The strategy aims to capture strong directional moves while avoiding overtrading, thanks to a built-in cooldown logic and optional time/session filters.
⚙️ Core Concept
The strategy executes trades only in the direction of the prevailing trend, determined by short- and long-term Exponential Moving Averages (EMA). Entry signals are generated when the Relative Strength Index (RSI) confirms momentum in the direction of the trend, and volume spikes suggest institutional activity.
To increase adaptability and user control, it includes a highly customizable parameter set for both long and short entries independently.
📌 Key Features
✅ Trend-Following Logic
Long entries are only allowed when EMA(short) > EMA(long)
Short entries are only allowed when EMA(short) < EMA(long)
✅ RSI Confirmation
Long: Requires RSI crossover above a configurable threshold
Short: Requires RSI crossunder below a configurable threshold
Optional rejection filters: Entry blocked above/below specific RSI extremes
✅ Volume Spike Filter
Confirms institutional participation by comparing current volume to an average multiplied by a user-defined factor.
✅ ATR-Based Risk Management
Both Stop Loss (SL) and Take Profit (TP) are dynamically calculated using ATR × a multiplier.
TP/SL ratio is fully configurable.
✅ Cooldown Control
After every trade, the system waits for a set number of bars before allowing new entries.
This prevents overtrading and increases signal quality.
Optionally, cooldown is ignored for reversal trades, ensuring the system can react immediately to a confirmed trend change.
✅ Candle Body Filter (Noise Control)
Avoids trades on candles with too small bodies relative to wicks (often noise or indecision candles).
✅ VWAP Confirmation (Optional)
Ensures price is trading above VWAP for long entries, or below for short entries.
✅ Time & Session Filters
Trades only during regular market hours (09:30–16:00 EST).
No-trade zone (e.g., 14:15–15:45 EST) to avoid low-liquidity traps or late-day whipsaws.
✅ End-of-Day Auto Close
All open positions are force-closed at 15:55 EST, protecting against overnight risk (especially relevant for 0DTE options).
📊 Visual Aids
EMA plots show trend direction
VWAP line provides real-time mean-reversion context
Stop Loss and Take Profit lines appear dynamically with each trade
Alerts notify of entry signals and exit triggers
🔧 Customization Panel
Nearly every element of the strategy can be tailored:
EMA lengths (short and long, for both sides)
RSI thresholds and length
ATR length, SL multiplier, and TP/SL ratio
Volume spike sensitivity
Minimum EMA distance filter
Candle body ratio filter
Session restrictions
Cooldown logic (duration + reversal exception)
This makes the strategy extremely versatile, allowing both conservative and aggressive configurations depending on the trader’s profile and the market context.
📌 Example Use Case: SPY Options (0DTE or 1DTE)
This system was designed and tested specifically for SPY and other intraday options trading, where:
Delta is around 0.50 or higher
Trades are short-lived (often 1–5 candles)
You aim to trade 1–3 signals per day, filtering out weak entries
🚫 Important Notes
It is not a scalping strategy; it relies on confirmed breakouts with trend support
No pyramiding or re-entries without cooldown to preserve risk integrity
Should be used with real-time alerts and manual broker execution
📈 Alerts Included
📈 Long Entry Signal
📉 Short Entry Signal
⚠️ Auto-closed all positions at 15:55 EST
✅ Proven Settings – Real Trades + Backtest Results
The current version of the strategy includes the optimal settings I’ve arrived at through extensive backtesting, as well as 3 months of real trading with consistent profitability. These results reflect real-world execution under live market conditions using 0DTE SPY options, with disciplined trade management and risk control.
🧠 Final Thoughts
Options Strategy V2.0 is a robust, highly tunable intraday strategy that blends momentum, trend-following, and volume confirmation. It is ideal for disciplined traders focused on SPY or other 0DTE/1DTE options, and it includes guardrails to reduce false signals and improve execution timing.
Perfect for those who seek precision, flexibility, and risk-defined setups—not blind automation.
Combo 2/20 EMA & Bandpass Filter by TamarokDescription:
This strategy combines a 2/20 exponential moving average (EMA) crossover with a custom bandpass filter to generate buy and sell signals.
Use the Fast EMA and Slow EMA inputs to adjust trend sensitivity, and the Bandpass Filter Length, Delta, and Zones to fine-tune momentum turns.
Signals occur when both EMA and BPF agree in direction, with optional reversal and time filters.
How to use:
1. Add the script to your chart in TradingView.
2. Adjust the EMA and BP Filter parameters to match your asset’s volatility.
3. Enable ‘Reverse Signals’ to trade counter-trend, or use the time filter to limit sessions.
4. Set alerts on Long Alert and Short Alert for automated notifications.
Inspiration:
Based on HPotter’s original combo strategy (Stocks & Commodities Mar 2010).
Updated to Pine Script v6 with streamlined code and alerts.
WARNING:
For purpose educate only
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
Contrarian Market Structure BreakMarket Structure Break application was inspired and adapted from Market Structure Oscillator indicator developed by Lux Algo. So much credit to their work.
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Indicator Description: Contrarian Market Structure BreakOverview
The "Contrarian Market Structure Break" indicator is a versatile tool tailored for traders seeking to identify potential reversal opportunities by analyzing market structure across multiple timeframes. Built on Institutional Concepts of Structure (ICT), this indicator detects Break of Structure (BOS) and Change of Character (CHoCH) patterns across short-term, intermediate-term, and long-term swings, plotting them with customizable lines and labels. It generates contrarian buy and sell signals when price breaks key swing levels, with a unique "Blue Dot Tracker" to monitor consecutive buy signals for trend confirmation. Optimized for the daily timeframe, this indicator is adaptable to other timeframes with proper testing, making it ideal for traders of forex, stocks, or cryptocurrencies.
How It Works
The indicator combines three key components to provide a comprehensive view of market dynamics: Multi-Timeframe Market Structure Analysis: It identifies swing highs and lows across short-term, intermediate-term, and long-term periods, plotting BOS (continuation) and CHoCH (reversal) events with customizable line styles and labels.
Contrarian Signal Generation: Buy and sell signals are triggered when the price crosses below swing lows (buy) or above swing highs (sell), indicating potential reversals in overextended markets.
Blue Dot Tracker: A unique feature that counts consecutive buy signals ("blue dots") and highlights a "Hold Investment" state with a yellow background when three or more buy signals occur, suggesting a potential trend continuation.
Signals are visualized as small circles below (buy) or above (sell) price bars, and a table in the bottom-right corner displays the blue dot count and recommended action (Hold or Flip Investment), enhancing decision-making clarity.
Mathematical Concepts Swing Detection: The indicator identifies swing highs and lows by comparing price patterns over three bars, ensuring robust detection of pivot points. A swing high occurs when the middle bar’s high is higher than the surrounding bars, and a swing low occurs when the middle bar’s low is lower.
Market Structure Logic: BOS is detected when the price breaks a prior swing high (bullish) or low (bearish) in the direction of the current trend, while CHoCH signals a potential reversal when the price breaks a swing level against the trend. These are calculated across three timeframes for a multi-dimensional perspective.
Blue Dot Tracker: This feature counts consecutive buy signals and tracks the entry price. If three or more buy signals occur without a sell signal, the indicator enters a "Hold Investment" state, marked by a yellow background, until the price exceeds the entry price or a sell signal occurs.
Entry and Exit Rules Buy Signal (Blue Dot Below Bar): Triggered when the closing price crosses below a swing low on either the intermediate-term or long-term timeframe, suggesting an oversold condition and potential reversal upward. Short-term signals can be enabled but are disabled by default to reduce noise.
Sell Signal (White Dot Above Bar): Triggered when the closing price crosses above a swing high on either the intermediate-term or long-term timeframe, indicating an overbought condition and potential reversal downward.
Blue Dot Tracker Logic: After a buy signal, the indicator increments a blue dot counter and records the entry price. If three or more consecutive buy signals occur (blueDotCount ≥ 3), the indicator enters a "Hold Investment" state, highlighted with a yellow background, suggesting a potential trend continuation. The "Hold Investment" state ends when the price exceeds the entry price or a sell signal occurs, resetting the counter.
Exit Rules: Traders can exit buy positions when a sell signal appears, the price exceeds the entry price during a "Hold Investment" state, or based on additional confirmation from BOS/CHoCH patterns or other technical analysis tools. Always use proper risk management.
Recommended Usage
The indicator is optimized for the daily timeframe, where it effectively captures significant reversal and continuation patterns in trending or ranging markets. It can be adapted to other timeframes (e.g., 1H, 4H, 15M) with careful testing of settings, particularly enabling/disabling short-term structure analysis to suit market conditions. Backtesting is recommended to optimize performance for your chosen asset and timeframe.
Customization Options Market Structure Display: Toggle short-term, intermediate-term, and long-term structures on or off, with customizable line styles (solid, dashed, dotted) and colors for bullish and bearish breaks.
Labels: Enable or disable BOS/CHoCH labels for each timeframe to reduce chart clutter.
Signal Visibility: Hide buy/sell signals if desired for a cleaner chart.
Blue Dot Tracker: Monitor the blue dot count and action (Hold or Flip Investment) via the table display, which is fully customizable in terms of position and appearance.
Why Use This Indicator?
The "Contrarian Market Structure Break" indicator offers a robust framework for identifying high-probability reversal and continuation setups using ICT principles. Its multi-timeframe analysis, clear signal visualization, and innovative Blue Dot Tracker provide traders with actionable insights into market dynamics. Whether you're a swing trader or a day trader, this indicator’s flexibility and intuitive design make it a valuable addition to your trading arsenal.
Note for TradingView Moderators
This script complies with TradingView's House Rules by providing an educational and transparent description without performance claims or guarantees. It is designed to assist traders in technical analysis and should be used alongside proper risk management and personal research. The code is original, well-documented, and includes customizable inputs and clear visual outputs to enhance the user experience.
Tips for Users:
Backtest thoroughly on your chosen asset and timeframe to validate signal reliability. Combine with other indicators or price action analysis for confirmation of entries and exits. Adjust timeframe settings and enable/disable short-term structures to match market volatility and your trading style.
Hope the "Contrarian Market Structure Break" indicator enhances your trading strategy and helps you navigate the markets with confidence! Happy trading!
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Ticker Pulse Meter + Fear EKG StrategyDescription
The Ticker Pulse Meter + Fear EKG Strategy is a technical analysis tool designed to identify potential entry and exit points for long positions based on price action relative to historical ranges. It combines two proprietary indicators: the Ticker Pulse Meter (TPM), which measures price positioning within short- and long-term ranges, and the Fear EKG, a VIX-inspired oscillator that detects extreme market conditions. The strategy is non-repainting, ensuring signals are generated only on confirmed bars to avoid false positives. Visual enhancements, such as optional moving averages and Bollinger Bands, provide additional context but are not core to the strategy's logic. This script is suitable for traders seeking a systematic approach to capturing momentum and mean-reversion opportunities.
How It Works
The strategy evaluates price action using two key metrics:
Ticker Pulse Meter (TPM): Measures the current price's position within short- and long-term price ranges to identify momentum or overextension.
Fear EKG: Detects extreme selling pressure (akin to "irrational selling") by analyzing price behavior relative to historical lows, inspired by volatility-based oscillators.
Entry signals are generated when specific conditions align, indicating potential buying opportunities. Exits are triggered based on predefined thresholds or partial position closures to manage risk. The strategy supports customizable lookback periods, thresholds, and exit percentages, allowing flexibility across different markets and timeframes. Visual cues, such as entry/exit dots and a position table, enhance usability, while optional overlays like moving averages and Bollinger Bands provide additional chart context.
Calculation Overview
Price Range Calculations:
Short-Term Range: Uses the lowest low (min_price_short) and highest high (max_price_short) over a user-defined short lookback period (lookback_short, default 50 bars).
Long-Term Range: Uses the lowest low (min_price_long) and highest high (max_price_long) over a user-defined long lookback period (lookback_long, default 200 bars).
Percentage Metrics:
pct_above_short: Percentage of the current close above the short-term range.
pct_above_long: Percentage of the current close above the long-term range.
Combined metrics (pct_above_long_above_short, pct_below_long_below_short) normalize price action for signal generation.
Signal Generation:
Long Entry (TPM): Triggered when pct_above_long_above_short crosses above a user-defined threshold (entryThresholdhigh, default 20) and pct_below_long_below_short is below a low threshold (entryThresholdlow, default 40).
Long Entry (Fear EKG): Triggered when pct_below_long_below_short crosses under an extreme threshold (orangeEntryThreshold, default 95), indicating potential oversold conditions.
Long Exit: Triggered when pct_above_long_above_short crosses under a profit-taking level (profitTake, default 95). Partial exits are supported via a user-defined percentage (exitAmt, default 50%).
Non-Repainting Logic: Signals are calculated using data from the previous bar ( ) and only plotted on confirmed bars (barstate.isconfirmed), ensuring reliability.
Visual Enhancements:
Optional moving averages (SMA, EMA, WMA, VWMA, or SMMA) and Bollinger Bands can be enabled for trend context.
A position table displays real-time metrics, including open positions, Fear EKG, and Ticker Pulse values.
Background highlights mark periods of high selling pressure.
Entry Rules
Long Entry:
TPM Signal: Occurs when the price shows strength relative to both short- and long-term ranges, as defined by pct_above_long_above_short crossing above entryThresholdhigh and pct_below_long_below_short below entryThresholdlow.
Fear EKG Signal: Triggered by extreme selling pressure, when pct_below_long_below_short crosses under orangeEntryThreshold. This signal is optional and can be toggled via enable_yellow_signals.
Entries are executed only on confirmed bars to prevent repainting.
Exit Rules
Long Exit: Triggered when pct_above_long_above_short crosses under profitTake.
Partial exits are supported, with the strategy closing a user-defined percentage of the position (exitAmt) up to four times per position (exit_count limit).
Exits can be disabled or adjusted via enable_short_signal and exitPercentage settings.
Inputs
Backtest Start Date: Defines the start of the backtesting period (default: Jan 1, 2017).
Lookback Periods: Short (lookback_short, default 50) and long (lookback_long, default 200) periods for range calculations.
Resolution: Timeframe for price data (default: Daily).
Entry/Exit Thresholds:
entryThresholdhigh (default 20): Threshold for TPM entry.
entryThresholdlow (default 40): Secondary condition for TPM entry.
orangeEntryThreshold (default 95): Threshold for Fear EKG entry.
profitTake (default 95): Exit threshold.
exitAmt (default 50%): Percentage of position to exit.
Visual Options: Toggle for moving averages and Bollinger Bands, with customizable types and lengths.
Notes
The strategy is designed to work across various timeframes and assets, with data sourced from user-selected resolutions (i_res).
Alerts are included for long entry and exit signals, facilitating integration with TradingView's alert system.
The script avoids repainting by using confirmed bar data and shifted calculations ( ).
Visual elements (e.g., SMA, Bollinger Bands) are inspired by standard Pine Script practices and are optional, not integral to the core logic.
Usage
Apply the script to a chart, adjust input settings to suit your trading style, and use the visual cues (entry/exit dots, position table) to monitor signals. Enable alerts for real-time notifications.
Designed to work best on Daily timeframe.
