Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe
This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice.
0. Publication mode and rationale
This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible.
Why Protected
The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users.
Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results.
1. What the strategy does in one paragraph
Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity.
Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor.
Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal.
2. Why it is original and useful
It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance.
The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise.
Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants.
Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates.
The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about.
3. Plain language overview of the math
Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural.
Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases.
Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one.
Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow.
Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band.
4. Entries, exits, and position sizing
Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs.
Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate.
Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active.
Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn.
Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts.
5. Inputs quick guide with recommended ranges
Every input has a tooltip in the script. The same guidance appears here for fast reading.
Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing.
Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55.
Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more.
Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence.
Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical.
Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets.
Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts.
Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more.
Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes.
AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes.
Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70.
Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20.
Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2.
Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts.
Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior.
Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits.
Background heat opacity . Cosmetic. Set to taste. Zero disables it.
6. Properties used on the published chart
The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results.
Initial capital 100000
Base currency USD
Order size 2 percent of equity coming from our risk management inputs.
Pyramiding 0
Commission 0.05 percent
Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research.
Recalculate after order is filled off. On every tick off.
Using bar magnifier on. On bar close on.
Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1.
7. Visual elements and alerts
The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan.
8. How to reproduce the example
Open a BTCUSD daily chart with regular candles.
Add the strategy and load the defaults that match the values above.
Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on.
Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown.
9. Practical tuning recipes
Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions.
Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar.
Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday.
Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions.
Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it.
10. Strengths and limitations
Strengths
Self scaling unit through AAR makes the tool portable across markets and timeframes.
Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align.
Adaptive centering reduces structural bias at the score level which helps during regime flips.
Limitations
In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable.
Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate.
Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research.
The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases.
11. Realism and responsible publication
No promises or projections of performance are made. Past results never guarantee future outcomes.
Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange.
Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model.
Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size.
Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders.
12. Suggested research workflow
Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history.
Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value.
Try one higher timeframe blend with a modest weight. Large weights can drown the signal.
Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop.
Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy.
Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods.
13. How to read the HUD and heat map
The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty.
14. Frequently asked questions
Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch.
Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly.
Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off.
Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown.
Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing.
Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context.
15. Concepts glossary
AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops.
Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity.
Geometric mean growth . Rate that preserves the effect of compounding over many bars.
Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound.
Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale.
Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew.
16. Educational notice and risk statement
Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results.
17. Final notes for readers and moderators
The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments.
Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence.
Thank you for your time to read all of this
Strategy
Binary Options Fast Scalping [TradingFinder] M1 & M5 Signals🔵 Introduction
In the structure of financial markets, spiky moments and sudden price movements play a key role in Liquidity Grabs and Market Structure Resets. These movements usually occur after the accumulation of orders in Buy Side or Sell Side Liquidity zones and are accompanied by rapid breaks in the form of Break of Structure (BoS) or Change of Character (CHoCH).
At this stage, the market temporarily moves in the direction of liquidity to trigger counter orders and then enters a Retracement or Pullback phase, a point where professional traders using the Smart Money Concept (SMC) look for candle confirmation to enter with precision.
This strategy is built upon the same logic : an initial spiky move as a signal of institutional or liquidity driven algorithms, followed by a controlled pullback toward areas such as the Order Block, Fair Value Gap (FVG), or Imbalance Zone, and finally an entry based on a strong confirmation candle (Engulf, Rejection, Breaker) that defines the true direction of order flow.
This combination of price behavior, especially on lower timeframes such as M1 or M5, provides an ideal setup for fast Scalping, Micro Structure Trading, and even short term directional prediction in Binary Options Trading.
Since the main focus of this method is on identifying liquidity phases, structural confirmations, and momentum confirmation candles, the trader can design entries with high probability and logical stop loss placement using the concepts of Fractal Market Structure and Multi Timeframe Confirmation.
In the scalping version, the main objective is to capture the move toward the next liquidity pool or opposite demand and supply zone, while in the binary version, only the prediction of the next candle’s direction matters. This strategy inherently operates based on Smart Money Behavior, Liquidity Engineering, and Order Flow Dynamics, allowing the extraction of fast and profitable moves from the internal logic of market structure.
🔵 How to Use
The operational logic of this strategy is based on Liquidity Sweep, Pullback, and Confirmation Candle. The trader should first identify the initial Impulse Move, which is often accompanied by liquidity absorption around Buy Side or Sell Side Liquidity areas. After that, the market enters the Retracement phase and returns to structural zones such as the Order Block or the Fair Value Gap (FVG).
At this point, a position is taken only when a confirmation candle (Engulf, Breaker, or Rejection Candle) closes in the direction of continuation and aligns with the new structure (BOS or CHoCH). Applying this model on lower timeframes offers the highest precision for fast Scalping or for predicting the next candle’s direction in Binary Option trading.
🟣 Bullish Setup
In the bullish setup, the market first forms a spiky upward move with a sudden increase in momentum, indicating the activation of liquidity flow in the Buy Side Liquidity zone. This movement is usually accompanied by a Break of Structure (BOS) to the upside and marks the beginning of the Impulse Move phase. After this move, the price enters the Pullback phase and returns to structural areas such as the Bullish Order Block, Fair Value Gap (FVG), or Mitigation zone.
At this stage, the trader waits for a bullish confirmation candle (Bullish Engulf or Breaker Candle) to validate the end of the retracement. Entry is made at the close of the confirmation candle or on a minor pullback, with the stop loss placed below the Swing Low or below the pullback zone. The target is set at the next Buy Side Liquidity or Equal Highs. In the binary version, only the direction of the next candle matters and the entry takes place immediately after the confirmation candle.
🟣 Bearish Setup
In the bearish setup, the market first forms a spiky downward move, signaling increased selling pressure and liquidity absorption at the Sell Side Liquidity zone. This movement is accompanied by a Break of Structure (BOS) to the downside and represents the beginning of a bearish momentum phase. After the spike, the price enters the Retracement phase and returns to the Bearish Order Block or bearish Fair Value Gap zone. Within these areas, the formation of a bearish confirmation candle (Bearish Engulf, Breaker, or Rejection Candle) validates the continuation of the downtrend.
The entry is taken at the close of the confirmation candle, with the stop loss placed above the Swing High or above the pullback zone, and the target set toward the next Sell Side Liquidity or Equal Lows. In binary applications, only the direction of the next candle is considered and the confirmation candle serves as the entry trigger.
🔵 Conclusion
This strategy, by combining the principles of the Smart Money Concept, Liquidity Dynamics, and Candle Confirmation Logic, offers a precise and multi functional approach to market entry. Its core structure, identifying the initial spiky movement, waiting for a structural pullback, and entering based on a confirmation candle allows quick interpretation of institutional liquidity behavior and provides trading opportunities with high accuracy and controlled risk.
On lower timeframes, this logic becomes a powerful tool for Scalping and Micro Structure Trading, while in binary markets it delivers high success rates due to its focus on predicting the next candle’s direction. Built upon the foundations of Order Flow, Market Structure, and Fractal Liquidity Behavior, this strategy demonstrates that even in the fastest and noisiest market conditions, the order of Smart Money remains observable and exploitable.
AI Bot Regime Feed (v6) — stableThis indicator generates real-time, structured JSON alerts for external trading bots or automation systems.
It combines multiple technical layers to identify market regimes and high-probability buy/sell events, and sends them to any webhook endpoint (e.g., a FastAPI or Zapier listener).
MACD Master Strategy Suite🧩 Overview
The MACD Master Strategy Suite is not a basic MACD crossover system, but a complete backtesting tool designed for traders who want to explore and optimize MACD-based logic.
This suite offers a host of configurable options that transform the standard MACD into a powerful research framework. You can test multiple entry styles, apply trend filters, run contrarian setups, and study seasonality — all from one script.
⚙️ Key Features
Multiple MACD entry modes: classic cross, zero-line flip, pullback, momentum burst, divergence, and more.
Dual-EMA trend filter with optional Contrarian Mode.
Higher-timeframe trend confirmation.
Calendar filters for weekday, month, and day-of-month testing.
Realistic trade management: stop/target exits, cooldowns, and same-bar recalculation guard.
Adjustable position sizing and leverage for accurate SPY-style backtests.
🧠 How It Differs From TradingView’s Built-In MACD Strategy
The built-in MACD strategy uses only histogram zero-cross entries with no filters or risk controls.
The MACD Master Strategy Suite expands this into a fully modular testing environment, allowing you to analyze how different MACD behaviors perform under diverse market conditions — turning MACD from a simple signal into a measurable system.
⚖️ Disclaimer
For research and educational use only. This script does not constitute financial advice or guarantee performance.
Supertrend + MACD + EMA200 (Pro) V2 — Strict & TrailingThis strategy uses Supertrend, MACD and EMA 200 as indicators. When all three indicators shows the sema direction, you enter the trade.
Force of Strategy (FoS, Multi TF/TA, Backtest, Alerts)Introducing the FoS Trading System
A comprehensive and innovative solution designed for both novice and experienced traders to enhance their intraday trading.
The basic idea of creating this script is to stay profitable in any market
Key Features:
There are over 25 no-repaint strategies for generating buy and sell signals to choose from
10 symbols for simultaneous trading
Webhook alerts in TTA format (tradingview to anywhere) pre-configured to send messages for trading cross-margin futures on major Crypto Exchanges: Binance, Bitget, BingX, Bybit, GateIO and OKX
A unique automated "Strategy switcher" feature for backtesting and live trading—not just a specific strategy, but the logic behind choosing a trading one or another strategy based on backtesting data obtained in real time
Advanced risk management options and backtest result metrics
Higher Timeframe filters (Technical Rating, ADX, Volatility) and ability for check backtest results with 9 main higher timeframes
Buy and sell signals are generated using TradingView Technical Ratings, indicators with adaptive length algorithms and various classic indicators with standard settings to avoid overfitting
Next, I will describe in detail what this script does and what settings it operates with:
"All Strategies" off
- In the global settings block, as shown in the main chart screenshot, you select how long the script will perform backtests in days, with a limitation on the number of bars for calculations. This limitation is necessary to maintain an acceptable calculation speed. You also choose which two higher timeframes we will use for signal and filters when confirming the opening of trades
- With "All Strategies" off - as in the example on the main chart screenshot, trading is carried out by strategy #1 on 10 selected tickers simultaneously. By default, I selected the 9 top-capitalized cryptocurrencies on the Bitget exchange and the chart symbol. You can change that choice of 9 non chart opened instruments and # strategy for each them
- The first row in the table 1 shows some of the main choosen script settings, in attached example: initial capital 20$, leverage 50L, 20 backtest days, 3$ is invest in one deal, 60m - is chart timeframe, next 60m is higher timeframe 1 and last 90m is higher timeframe 2. In first column you see shortened to 5 characters ticker names
- The exchange name in the second row determines the alert messages format
I've attached another example of trading with setting "All strategies" off in the image below. In this example, trading 10 standard symbols on an hourly timeframe, 2 coins from 10: 1000SATS and DOGE have generated a profit of over $65 over the past 20 days using strategy #4
Can you browse a wide range of trading instruments and select the 10 best strategies and settings for future trading? Of course, trading is what this script is do!
The parameters in the table 1 mean the following:
TR - count of closed trading deals
WR - Winning Rate, PF - Profit Factor
MDD - Max Draw Down for all calculated time from initial capital
R$ - trading profit result in usd
The parameters in the table 2 is just more metrics for chart symbol:
PT - result in usd Per one Trade
PW - result Per Win, PL - result Per Lose
ROI - Rate of Investments
SR - Sharpe Ratio, MR - CalMAR ration
Tx - Commision Fee in Usd
R$ - trading profit result in usd again
Table 2 separate trade results of backtesting for longs and shorts. In first column you see how many USD were invested in one trade, taking into account possible position splitting (will be discussed in more detail in the risk management section)
Settings:
"All Strategies" on, "Check Last" off
When "All Strategies" is active, trading changed from 10 symbols and one strategy to all strategies and one chart symbol. If option "Check Last" is inactive you will see backtest results for each of strategy in backtest setting days. This is useful, for example, if you want to see backtest results under different settings over a long period of time for calibrating risk management or entry rules
"All Strategies" on, "Check Last" on
- If "All Strategies" and "Check Last" is active trading will occur on the chart symbol only for those strategies that meet the criteria of the settings block for the enabled "All Strategies" option. For example your criteria is: for last 5 trades for all strategies, open next trade only on strategy which reached ROI 25% and WinRate 50%. When strategy with this setting criteria receive Buy or Sell Signal this trade will be opened, and when trade will be close "check last" will repeat. This feature i called "Strategy switcher"
-In Table 1 if strategy meet criteria you will see "Ok" label, if strategy meet criteria and have maximum from other reached ROI they labeled "Best". Chart strategy labeled "Chart", Chart and Ok labels in one time is "Chart+", "Chart" and "Best" is labeled "Best+"
- The color in the first column of table 1 indicates that the strategy is currently in an open position: green means an open long position, red means an open short position.
In picture bellow you will see good example for trading with check results for last 10 trades, and make desicion for trading when criteries 0.25 ROI and WinRate 50% reached for Top 2 by ROI strategies from all list of them. This example of trading logic in last 20 days (include periods when strategy don't arise 10 trades) give a profit $30+. At the bottom of the screen, you can see Labels with the numbers of the strategies that opened the trades. In this example, trades were primarily opened using strategy number 2, and the second most effective strategy after the 20-day backtest was strategy number 9
Who can promise you'll make a profit of $30 in the next 20 days with a drawdown of no more than $8 from the initial $20 with invest in one trade just 2.7$? No one. But this script guarantees that in the future it will repeat the same logic of switching trading strategies that brought profit over the last 20 days
Risk management options
- When a buy or sell trade is opened, you'll see three lines on the chart: a red stop-loss line (SL), a green take-profit line (TP), and a blue line representing the entry price. The trade will be closed if the high price or low price reaches the line TP or SL (no wait for bar close) and alert will be triggered once per bar when script recalculates
- Several options are available to control the behavior of SL/TP lines, such as stop-loss by percentage, ATR, or Highest High (HH) and Lowest Low (LL). Take Profit can be in percent, ATR or in Risk Reward ratio. There some Trailing Stop with start trail trigger options, like ATR, percent or HH / LL
- Additionally, in risk managment settings a function has been implemented for adding a position when the breakeven level expressed in the current ROI is reached for opened trade (splitting position). The position is added within the bar.
- Webhook alerts in TTA format with message contained next info : Buy / Sell or adding Quantity, Leverage, SL price, TP price and close trade
Keep in mind if the stop-loss changed when adding a position, the stop-loss will not be able to be higher than the current bar's low price, regardless of your settings, as backtest trades do not use intra-bar data, in this situation SL will be correct at next bar (but alert message don't be sended twice). And please note that this script does not have an option to simultaneously open trades in different directions. Only 1 trade can be opened for 1 trading instrument at a time
Backtest Engine
Backtest is a very important part of this script. Here describe how its calculate:
- Profit or Loss is USD: close trade price * open trade quantity - open trade price * open trade quantity - open trade quantity * (open trade price + close trade price)/2 * commision fee
Possible slippage or alert sending delay needed to be include in commission % which you will set in risk managment settings block, default settings is 0.15% (0,06% for open, 0,06% for close and 0,03% for possible slippage or additional fees)
- Maximum Draw Down: Drawdown = (peak - current equity) / peak * 100 ;
Drawdown > maxDrawdown ? maxDrawdown = Drawdown
- ROI: profit result in USD / sum of all positions margin
- CalMAR Ratio: ROI / (-MaxDrawDown)
- Sharpe Ratio: ROI / standard deviation for (Sum of all Profits and Loses) / (Sum of all Position Margins)
This description was added because in metrics i don't use parameters like "The risk-free rate of return". Keep in mind how exactly this script calculate profit and perfomance when adjusting key criteria in the strategy switching parameters block of script settings
Strategies itself
For trading, you can enable or disable various Higher Timeframes Filters (ADX, volatility, technical rating).
With filters enabled, trades will only open when the setting parameters are reached
- Strategy number 1, 2 and 3: is Higher Timeframe TradingView Technical Ratings itself, 1 is summary total rating, 2 is oscillators and 3 is moving averages. When TR filter cross filter levels trade will be open at chart bar close. By Default on chart you see Summary Technical Rating oscillator, but here the options for change it to Oscillator TR or Moving Average TR
- Strategy number 4, 5 and 6: is Chart TimeFrame TR. Trades will open when its values (Summary, Oscillators and Moving Averages) reached setting buy sell level
- Strategy number 7, 8 and 9: is Alternative buy sell logic for Chart TimeFrame TR, trades will open when counting rising or falling values will be reached
- Strategies with number from 10 to 18: is chosen by user adaptive moving averages and oscillators indicators. There in settings you will see many different adaptive length algorithms for trading and different types of moving averages and oscillators. In tooltips in settings you will find very more information, and in settings you will see list of all indicators and algorithms (more than 30 variations). All adaptive strategies have their options in settings for calibrating and plotting
- Strategies with number from 19: its can't be chosen or calibarted, this is needed for avoid overfitting, i try to found mostly time worked strategies and use its with standard settings. In future it's possible to changing current or adding additional strategies. At the time of publication this script uses: Dynamic Swing HH LL (19), Composite indicator (20), %R Exhausting with different signals (21,22,23), Pivot Point SuperTrend (24), Ichimoku Cloud (25), TSI (26), Fib Level RSI (27). I don't plot classic strategies in this script
Let me explain, the value of this script is not in the strategies it includes, but in how exactly it collects the results of their work, how it filters the opening of trades, what risk management it applies and what strategy switching logic it performs. The system itself that you are now reading about represents the main value of this script
Finally if you get access for this script
- You will see many other not described options and possibilities like Kelly position or list of settings for adaptive strategies, also i added many usefull tooltips in script settings
Happy trading, and stay tuned for updates!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorized for this script, and the information published with them. This script is strictly for individual use. No one know future and Investments are always made at your own risk. I am not responsible for any losses you may incur. Please before investment make sure that chosen logic is enaugh profitable on virtual demo account.
AMF PG Strategy v2.3 The AMF PG Strategy (Praetorian Guard) is an advanced trading system designed to seamlessly adapt to market conditions. Its unique structure balances precise entries with intelligent protection, giving traders confidence in both trending and volatility environments.
Key points include:
Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts for clearer long- and short-term opportunities and generates a robust tracking line.
Praetorian Guard – A built-in protective shield that activates in extreme conditions and helps stabilize performance when markets become turbulent.
Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments.
Clarity – Clear visual signals and color-coded monitoring for instant decision-making.
This strategy is designed for traders who want more than just entries and exits; it offers a command center for disciplined, adaptable, and resilient trading.
Disclaimer:
It should be noted that no strategy is guaranteed. This strategy does not provide buy-sell-hold advice. Responsibility rests with the user.
Version 2.3: Bugs overlooked in Version 2 have been corrected and improvements have been made.
DCA with the Money Supply Index DCA with the Money Supply Index (MSI) by zdmre
This strategy is based on the Money Supply Index (MSI) by zdmre and enhances it with two functional options for users: a DCA (Dollar-Cost Averaging) approach and a signal-based buy/sell mode. It’s designed to help traders and investors make data-driven, disciplined entry decisions based on monetary supply trends.
🧠 Concept Overview
The Money Supply Index (MSI) provides insight into how liquidity (money supply) influences market movements. This strategy builds upon that foundation by allowing users to either:
Accumulate positions over time using DCA, based on favorable MSI conditions.
Execute a single buy and sell trade, optimized for bull market conditions.
⚙️ Inputs Explained
General Parameters
Start Bar Index / Stop Bar Index
Defines the range of bars (historical data) for backtesting or strategy visualization.
Long DCA
Activates the DCA mode. If unchecked, the strategy operates in single-entry/single-exit signal mode.
Trading Signal
Enables signal-based entries and exits when the MSI reaches predefined thresholds.
DCA Parameters
Entry Value
The MSI value that triggers a DCA buy event. When the MSI crosses below this value, the strategy considers it a favorable moment to deploy the saved capital.
Saved Amount
The amount of money set aside regularly (e.g., monthly) for investment. This simulates the DCA effect by accumulating capital and deploying it when conditions are optimal.
Data Inputs
Money Supply
The data source for the Money Supply Index (default: ECONOMICS:USM2).
Relational Symbol
The market instrument to compare against the money supply (default: NASDAQ_DLY:NDX). This allows the strategy to measure liquidity impact on a specific market.
Chart Display Options
You can toggle these metrics on the chart for better visualization:
Entry Price (green) – The price level of executed buys.
Cash Balance (yellow) – Remaining uninvested capital.
Invested Capital (red) – Total amount currently invested.
Current Value (blue) – The current valuation of the investment.
Profit (purple) – The total realized and unrealized profit.
Trades on Chart / Signal Labels / Quantity – Enables trade markers, signal text, and position size visualization.
📈 How the Strategy Works
1️⃣ DCA Mode
In DCA mode, the strategy simulates periodic savings and only invests when the MSI indicates favorable liquidity conditions (based on the Entry Value).
This approach aims to achieve the best possible average entry price over time — a powerful strategy for long-term investors seeking stable accumulation with reduced emotional bias.
2️⃣ Signal-Based Mode
In signal mode (with DCA disabled), the strategy performs one buy and one sell trade based on MSI turning points.
It’s most effective during bull markets, where liquidity expansion supports upward momentum.
This mode helps identify high-probability entry and exit zones rather than averaging in continuously.
💡 Additional Notes
This strategy includes helpful metrics to monitor your personal investment performance — showing invested capital, cash reserves, and profit in real-time.
The goal is to combine macroeconomic insight (money supply) with disciplined execution and capital management.
⚠️ Disclaimer
This strategy is for educational and research purposes only. It does not constitute financial advice. Always conduct your own analysis before making investment decisions.
OPR 4 ZonesThe OPR 4-Zone Boxes indicator visualizes four distinct market sessions on your chart by automatically drawing boxed ranges (high / low) and dotted midlines for each session. Each session box is created using time-based timestamps (timezone-aware) and updates in real time during the session. When the session closes, the box is locked to the session end, while an optional extension can display the session range for a configurable period afterward — useful for spotting retests, breakouts, and bias zones.
Designed for traders who rely on session structure and price-action, OPR 4-Zone provides clear, non-intrusive visuals and is fully configurable: enable or disable individual sessions, set start/end and extension times per session, choose colors and transparency for both the primary box and the extension, and display dotted midlines to quickly gauge session control. Objects are cleaned up at the start of each new day to prevent clutter and ensure reliable behavior when scrolling or changing timeframes.
Key features :
- Four independent session boxes (Morning, Afternoon, Evening, Night) with separate enable switches
- Timezone-aware timestamping so boxes align with the session times you want
- Locked session ranges at session close and optional extension period after close
- Dotted midline for quick reference to the session midpoint
- Customizable colors and background transparency for both base and extended boxes
- Automatic cleanup of session objects on new trading day to avoid frozen or stray boxes
- Lightweight and overlay-friendly with sensible defaults for fast setup
Suggested usage :
Use the indicator to mark session ranges for intraday support/resistance, identify where price is trading relative to session midpoint, and watch for breakout or rejection setups near session highs/lows. Combine with volume-based or momentum indicators to confirm breakouts through the session box.
Trend-Following & Breakout — Index Quant Strategy (NASDAQ)📈 Trend-Following & Breakout — Index Quant Strategy (NASDAQ & S&P 500)
Type: Invite-only strategy
Markets: NASDAQ 100 (NAS100 / US100 / NQ), S&P 500 (US500 / SPX), and other major equity indices.
🧠 Concept: Continuous trend model combining EWMAC (trend-following) and Donchian (breakout) signals, scaled by forecast strength and portfolio risk.
⚙️ Execution: Rebalances only on decision-bar closes, using hysteresis and a no-trade band to reduce churn.
📊 Default bias: Long-only — aligned with equity index drift.
🧩 How it works
• EWMAC Trend: Difference between fast and slow EMAs, normalized by an EWMA of absolute returns.
• Donchian Breakout: Distance beyond a 200-bar channel (Strict mode) or relative z-score position within it.
• Forecast combination: Weighted sum of trend and breakout points, clamped to ± capPoints.
• Hysteresis: Prevents quick sign flips near zero forecast.
• Risk scaling: Maps forecast strength to position size using equity × risk budget × ATR-based stop distance.
• Rebalance: Executes only if the required quantity change exceeds the Δqty threshold; can optionally block increases on Sundays (for CFDs).
⚙️ Default parameters
Deployed on NQ / US100 / NAS100 on Daily Timeframe
• Decision timeframe = 360 min (other options from 1 min to 1 week).
• Trend (EWMAC): Fast = 64, Slow = 256, Vol Norm = 32, Weight = 0.8.
• Breakout (Donchian): Length = 200, Mode = Strict, Weight = 0.2.
• Forecast scaling: ptsPerSigma = 1.0, capPoints = 10.
• Risk % per rebalance = 4 % of equity.
• ATR stop: ATR(14) × 1.0.
• No-trade band (Δqty) = 4 units.
• Hysteresis = 2 forecast points.
• Bias = Long-only (Neutral / Long-bias 50 % optional).
• Skip Sunday increases = false (default).
📋 Backtest properties (documented)
• Initial capital = 100 000 USD.
• Commission = 0.20 % per trade.
• Pyramiding = 10.
• Calc on every tick = false.
• Point value = 1 (for NAS100 CFD).
• No financing or slippage modeled.
• If using CFDs, account for overnight funding.
• On futures (NQ / ES), carry is implicit.
📊 Typical behaviour
• Many small scratches, a few large winners.
• Performs best during multi-week / multi-month trends.
• Underperforms in tight or volatile ranges.
• Average hold ≈ 30 – 90 days in historical tests.
💡 Risk and performance guide (illustrative)
Sharpe ≈ 1.25
Sortino ≈ 1.10 – 1.30
Max drawdown ≈ –18 % to –25 %
Annual volatility ≈ 24 – 28 %
CAGR ≈ 50 – 60 % (at 4 % risk)
Edge ratio ≈ 5 (MFE / MAE)
Historical backtests only — past performance does not guarantee future results.
🌍 Intended markets and timeframes
Optimized for NASDAQ 100 and S&P 500; also effective on similar indices (DAX, Dow Jones, FTSE).
Best on Daily or higher timeframes.
Aligns with long-term index drift — suitable for long-bias systematic trend portfolios.
⚠️ Limitations
• Backtests exclude CFD funding costs.
• Trend models will have losing streaks in range-bound markets.
• Designed for experienced traders seeking systematic exposure.
🔑 Requesting access
Send a private TradingView message to with the text:
“Request access to Trend-Following & Breakout — Index Quant Strategy.”
Access is granted only on explicit request.
For further information, see my TradingView Signature.
🆕 Release notes (v1.0)
• Initial release (360 min TF): EWMAC 64/256 + Donchian 200 Strict.
• Risk 4 %, ATR × 1.0, Long-only bias, hysteresis 2 pts, Δqty ≥ 4.
• Developed for NASDAQ 100 and S&P 500 indices.
• Implements continuous risk-scaled positioning and no-trade band logic.
🧾 Originality statement
This strategy is original work built entirely from TradingView built-ins (EMA, ATR, Highest, Lowest).
It does not reuse open-source invite-only code.
Any future reuse of open scripts will be done with explicit permission and credit.
Not Your Daddy's EMA CrossoverNot Your Daddy's EMA Crossover - Quick Guide
What It Does
This isn't your typical 50/200 EMA crossover. It uses academically-proven, optimized EMA periods specifically backtested for crypto markets. Instead of generic settings, it adapts to different trading styles with research-backed parameter combinations that have demonstrated real returns.
Core Logic
Enters when fast EMA crosses slow EMA in the trend direction (confirmed by 200 SMA filter)
Exits either on opposite EMA cross (trend-following) or at fixed profit targets (scalping)
Uses a 200 SMA to filter trades - only longs above it, only shorts below it
Key Settings & Toggles
1. Trading Style (Auto-adjusts EMA periods):
"15 Min Scalping": 9/21 EMA - Fast-paced, frequent signals
"1 Hour Swing": 13/48 EMA - For swing trading
"Daily Trend": 15/150 MA - Captured +97.87% in bull runs
2. Entry Method:
"Crossover Entry": Enters immediately on EMA cross
"Pullback to EMA Entry": Waits for first pullback to slow EMA (better risk/reward)
3. Exit Method:
"EMA Cross Exit": Trend-following, lets winners run until EMAs reverse
"Fixed % Target (Scalping)": Quick 0.5-1% profits with tight stops
4. Optional Features:
MACD Confirmation: Adds 6-15-1 MACD filter for higher-probability setups
Periodic Compounding: Compounds every 30 hours (research shows 1-30 hour compounding is optimal)
Recommended Timeframes
📊 Match your chart to your selection:
Select "15 Min Scalping" → Use 15-minute chart
Select "1 Hour Swing" → Use 1-hour chart
Select "Daily Trend" → Use daily chart
I personally like this on the daily, which coincidentally is printing a long signal today on Bitcoin.
Enjoy!
AstraAlgo BacktesterOVERVIEW
The AstraAlgo Backtester allows traders to simulate and evaluate trading strategies directly on TradingView. By simulating trades across different timeframes and markets, it provides valuable insights into win rates, drawdowns, and overall strategy effectiveness.
SIGNAL MODES
Signal Modes generate proprietary trade signals based on live price data. Users can choose between Off, Basic, Advanced, or Custom modes to evaluate strategies under different conditions and refine their trading approach.
ADJUSTABLE BACKTESTING
Parameters for historical simulations can be customized to test different market conditions and trading scenarios. This allows traders to measure strategy performance, including win rate, profit/loss, and risk/reward ratios, helping refine and optimize strategies before live execution.
BAR COLORING
Bar Coloring highlights bullish and bearish bars on historical charts, allowing traders to visually assess trend direction and trade outcomes during backtesting. This makes it easier to analyze momentum and strategy effectiveness at a glance.
ASTRA CLOUD
Astra Cloud overlays dynamic support and resistance levels on live price data. These zones adapt automatically to past market movements, helping traders identify areas where trades would have reacted, aiding strategy evaluation and optimization.
Price Deviation StrategyThis strategy getting in long position only after the price drop
The % of the drop is Determined by SMA for the first trade
The inputs of SMA and % of the drop can be adjust from the User
After that bot start taking safe trades if not take profit from the first trade
The safe trades are Determined by step down deviation % and by quantity
There is no Stop loss is not for one with small tolerance to getting under
Take profit is average price + take profit - note if you use % trailing profit back test is not realistic but is working on real time
Max Safe Trades = 15
Capital max = $30000
Doge-USDT is just a example What the Strategy Can do
Green line - take profit
Black line - Brake even with fee - adjust for exchange
RSI Momentum ScalperOverview
The "RSI Momentum Scalper" is a Pine Script v5 strategy crafted for trading highly volatile markets, with a special focus on newly listed cryptocurrencies. This strategy harnesses the Relative Strength Index (RSI) alongside volume analysis and momentum thresholds to pinpoint short-term trading opportunities. It supports both long and short trades, managed with customizable take profit, stop loss, and trailing stop levels, which are visually plotted on the chart for easy tracking.
Why I Created This Strategy
I developed the "RSI Momentum Scalper" because I was seeking a reliable trading strategy tailored to newly listed, highly volatile cryptocurrencies. These assets often experience rapid price fluctuations, rendering traditional strategies less effective. I aimed to create a tool that could exploit momentum and volume spikes while managing risk through adaptable exit parameters. This strategy is designed to address that need, offering a flexible approach for traders in dynamic crypto markets.
How It Works
The strategy utilizes RSI to identify momentum shifts, combined with volume confirmation, to trigger long or short entries. Trades are controlled with take profit, stop loss, and trailing stop levels, which adjust dynamically as the price moves in your favor. The trailing stop helps lock in profits, while the plotted exit levels provide clear visual cues for trade management.
Customizable Settings
The script is highly customizable, allowing you to adjust it to various market conditions and trading styles. Here’s a brief overview of the key settings:
Trade Mode: Select "Both," "Long Only," or "Short Only" to determine the trade direction.
(Default: Both)
RSI Length: Sets the lookback period for the RSI calculation (2 to 30).
(Default: 8)
A shorter length increases RSI sensitivity, suitable for volatile assets.
RSI Overbought: Defines the upper RSI threshold (60 to 99) for short entries.
(Default: 90)
Higher values signal stronger overbought conditions.
RSI Oversold: Defines the lower RSI threshold (1 to 40) for long entries.
(Default: 10)
Lower values indicate stronger oversold conditions.
RSI Momentum Threshold: Sets the minimum RSI momentum change (1 to 15) to trigger entries.
(Default: 14)
Adjusts the sensitivity to price momentum.
Volume Multiplier: Multiplies the volume moving average to filter high-volume bars (1.0 to 3.0).
(Default: 1)
Higher values require stronger volume confirmation.
Volume MA Length: Sets the lookback period for the volume moving average (5 to 50).
(Default: 13)
Influences the volume trend sensitivity.
Take Profit %: Sets the profit target as a percentage of the entry price (0.1 to 10.0).
(Default: 4.15)
Determines when to close a winning trade.
Stop Loss %: Sets the loss limit as a percentage of the entry price (0.1 to 6.0).
(Default: 1.85)
Protects against significant losses.
Trailing Stop %: Sets the trailing stop distance as a percentage (0.1 to 4.0).
(Default: 2.55)
Locks in profits as the price moves favorably.
Visual Features
Exit Levels: Take profit (green), fixed stop loss (red), and trailing stop (orange) levels are plotted when in a position.
Performance Table: Displays win rate, total trades, and net profit in the top-right corner.
How to Use
Add the strategy to your chart in TradingView.
Adjust the input settings based on the cryptocurrency and timeframe you’re trading.
Monitor the plotted exit levels for trade management.
Use the performance table to assess the strategy’s performance over time.
Notes
Test the strategy on a demo account or with historical data before live trading.
The strategy is optimized for short-term scalping; adjust settings for longer timeframes if needed.
1m OPTION BUY_Multi indi-01 (P) SEMI AUTOEnter every monday choose the option price range between 50 tp 100 , set strategy for a week or 3 three days, set upper limit 120 and lower limit 30 and input your own contract size and all parameters as you wish, and execute the alert (this is how the strtegy made). if you dont have any idea of market direction execute this strtegy for put and call both. be aware this strategy may incurred loss . we r not recomending to use this strategy , this is for education purpose only, watch and analyze then take your own decision.
Quantura - Quantified Price Action StrategyIntroduction
“Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices.
Originality & Value
The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of:
Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity.
Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs.
RSI filter: Can be set to normal or aggressive, confirming momentum before trades.
Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies.
EMA filter: Aligns trades with the broader market trend.
Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions.
This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow.
Functionality & Indicators
Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap.
Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection.
RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness.
FVG filter: Adds validation by requiring price interaction with inefficiency zones.
EMA filter: Ensures longs are above EMA and shorts below EMA.
Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status.
Parameters & Customization
Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options.
Liquidity filter: Mode (Run or Sweep), display, and swing length.
RSI: Enable/disable, length, and style (normal or aggressive).
Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles.
EMA: Length, enable/disable, and visualization.
Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing.
Visualization: Custom candle coloring and optional overlay for better clarity.
Default Properties (Strategy Settings)
Initial Capital: 10,000 USD
Position Size: 100% of equity per trade (backtest default)
Commission: 0.1%
Slippage: 1
Pyramiding: 0 (only one position at a time)
Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%.
Backtesting & Performance
Backtests on XPTUSD over 2.5 years with the default settings produced:
129 trades
73.64% win rate
Profit factor: 2.6
Maximum drawdown: 18.2%
These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (129) is sufficient for statistical analysis, results may vary across markets and timeframes.
Risk Management
Three configurable take-profit levels with percentage allocation.
Initial stop-loss based on user-defined percentage.
Dynamic stop-loss that adjusts with market movement.
Break-even logic that shifts stops to entry after predefined gains.
Position sizing based on risk percentage of equity.
This framework allows both conservative and aggressive configurations, depending on user preference.
Limitations & Market Conditions
Works best in volatile and liquid markets such as crypto, metals, indices, and FX.
May produce false signals in low-volume or sideways environments.
Unexpected news or macro events can override technical conditions.
Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use.
Usage Guide
Add “Quantura – Quantified Price Action Strategy” to your chart.
Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe.
Configure risk management: take-profits, stop-loss, and risk-per-trade percentage.
Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions.
Optimize parameters before applying the strategy to different markets.
Author & Access
Developed 100% by Quantura. Published as an Invite-Only script. Access is available upon request via the Author’s Instructions field.
Important
This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Lead Levels TP/SL v1.3 (close-only entries)Lead Levels — close-only signals, clean execution
Notice: Designed for BTC 15-minute charts only.
What it shows
Four reliability tiers: L1, L2, L3, L4.
A black “DON’T BET” marker for extreme conditions you should skip.
All triangles print only on bar close to avoid repaint.
How to read
▲ BUY L1–L4: higher level → stronger confidence.
▼ SELL L1–L4: higher level → stronger confidence.
DON’T BET (black): stand aside. No trade.
How to trade it
When a triangle prints, run a 1:1 target/stop:
Long: TP +1%, SL −1%.
Short: TP −1%, SL +1%.
Focus on normal conditions. Skip when the black marker appears.
One entry per signal. Keep sizing consistent.
Why traders like it
Close-only printing keeps charts honest.
Simple 1:1 playbook. No guesswork.
The Best Strategy Template[LuciTech]Hello Traders,
This is a powerful and flexible strategy template designed to help you create, backtest, and deploy your own custom trading strategies. This template is not a ready-to-use strategy but a framework that simplifies the development process by providing a wide range of pre-built features and functionalities.
What It Does
The LuciTech Strategy Template provides a robust foundation for building your own automated trading strategies. It includes a comprehensive set of features that are essential for any serious trading strategy, allowing you to focus on your unique trading logic without having to code everything from scratch.
Key Features
The LuciTech Strategy Template integrates several powerful features to enhance your strategy development:
•
Advanced Risk Management: This includes robust controls for defining your Risk Percentage per Trade, setting a precise Risk-to-Reward Ratio, and implementing an intelligent Breakeven Stop-Loss mechanism that automatically adjusts your stop to the entry price once a specified profit threshold is reached. These elements are crucial for capital preservation and consistent profitability.
•
Flexible Stop-Loss Options: The template offers adaptable stop-loss calculation methods, allowing you to choose between ATR-Based Stop-Loss, which dynamically adjusts to market volatility, and Candle-Based Stop-Loss, which uses structural price points from previous candles. This flexibility ensures the stop-loss strategy aligns with diverse trading styles.
•
Time-Based Filtering: Optimize your strategy's performance by restricting trading activity to specific hours of the day. This feature allows you to avoid unfavorable market conditions or focus on periods of higher liquidity and volatility relevant to your strategy.
•
Customizable Webhook Alerts: Stay informed with advanced notification capabilities. The template supports sending detailed webhook alerts in various JSON formats (Standard, Telegram, Concise Telegram) to external platforms, facilitating real-time monitoring and potential integration with automated trading systems.
•
Comprehensive Visual Customization: Enhance your analytical clarity with extensive visual options. You can customize the colors of entry, stop-loss, and take-profit lines, and effectively visualize market inefficiencies by displaying and customizing Fair Value Gap (FVG) boxes directly on your chart.
How It Does It
The LuciTech Strategy Template is meticulously crafted using Pine Script, TradingView's powerful and expressive programming language. The underlying architecture is designed for clarity and modularity, allowing for straightforward integration of your unique trading signals. At its core, the template operates by taking user-defined entry and exit conditions and then applying a sophisticated layer of risk management, position sizing, and trade execution logic.
For instance, when a longCondition or shortCondition is met, the template dynamically calculates the appropriate position size. This calculation is based on your specified risk_percent of equity and the stop_distance (the distance between your entry price and the calculated stop-loss level). This ensures that each trade adheres to your predefined risk parameters, a critical component of disciplined trading.
The flexibility in stop-loss calculation is achieved through a switch statement that evaluates the sl_type input. Whether you choose an ATR-based stop, which adapts to market volatility, or a candle-based stop, which uses structural price points, the template seamlessly integrates these methods. The ATR calculation itself is further refined by allowing various smoothing methods (RMA, SMA, EMA, WMA), providing granular control over how volatility is measured.
Time-based filtering is implemented by comparing the current bar's time with user-defined start_hour, start_minute, end_hour, and end_minute inputs. This allows the strategy to activate or deactivate trading during specific market sessions or periods of the day, a valuable tool for optimizing performance and avoiding unfavorable conditions.
Furthermore, the template incorporates advanced webhook alert functionality. When a trade is executed, a customizable JSON message is formatted based on your webhook_format selection (Standard, Telegram, or Concise Telegram) and sent via alert function. This enables seamless integration with external services for real-time notifications or even automated trade execution through third-party platforms.
Visual feedback is paramount for understanding strategy behavior. The template utilizes plot and fill functions to clearly display entry prices, stop-loss levels, and take-profit targets directly on the chart. Customizable colors for these elements, along with dedicated options for Fair Value Gap (FVG) boxes, enhance the visual analysis during backtesting and live trading, making it easier to interpret the strategy's actions.
How It's Original
The LuciTech Strategy Template distinguishes itself in the crowded landscape of TradingView scripts through its unique combination of integrated, advanced risk management features, highly flexible stop-loss methodologies, and sophisticated alerting capabilities, all within a user-friendly and modular framework. While many templates offer basic entry/exit signal integration, LuciTech goes several steps further by providing a robust, ready-to-use infrastructure for managing the entire trade lifecycle once a signal is generated.
Unlike templates that might require users to piece together various risk management components or code complex stop-loss logic from scratch, LuciTech offers these critical functionalities out-of-the-box. The inclusion of dynamic position sizing based on a user-defined risk percentage, a configurable risk-to-reward ratio, and an intelligent breakeven mechanism significantly elevates its utility. This comprehensive approach to capital preservation and profit targeting is a cornerstone of professional trading and is often overlooked or simplified in generic templates.
Furthermore, the template's provision for multiple stop-loss calculation types—ATR-based for volatility adaptation, and candle-based for structural support/resistance—demonstrates a deep understanding of diverse trading strategies. The underlying code for these calculations is already implemented, saving developers considerable time and effort. The subtle yet powerful inclusion of FVG (Fair Value Gap) related inputs also hints at advanced price action concepts, offering a sophisticated layer of analysis and execution that is not commonly found in general-purpose templates.
The advanced webhook alerting system, with its support for various JSON formats tailored for platforms like Telegram, showcases an originality in catering to the needs of modern, automated trading setups. This moves beyond simple TradingView pop-up alerts, enabling seamless integration with external systems for real-time trade monitoring and execution. This level of external connectivity and customizable data output is a significant differentiator.
In essence, the LuciTech Strategy Template is original not just in its individual features, but in how these features are cohesively integrated to form a powerful, opinionated, yet highly adaptable system. It empowers traders to focus their creative energy on developing their core entry/exit signals, confident that the underlying framework will handle the complexities of risk management, trade execution, and external communication with precision and flexibility. It's a comprehensive solution designed to accelerate the development of robust and professional trading strategies.
How to Modify the Logic to Apply Your Strategy
The LuciTech Strategy Template is designed with modularity in mind, making it exceptionally straightforward to integrate your unique trading strategy logic. The template provides a clear separation between the core strategy management (risk, position sizing, exits) and the entry signal generation. This allows you to easily plug in your own buy and sell conditions without altering the robust underlying framework.
Here’s a step-by-step guide on how to adapt the template to your specific trading strategy:
1.
Locate the Strategy Logic Section:
Open the Pine Script editor in TradingView and navigate to the section clearly marked with the comment //Strategy Logic Example:. This is where the template’s placeholder entry conditions (a simple moving average crossover) are defined.
2.
Define Your Custom Entry Conditions:
Within this section, you will find variables such as longCondition and shortCondition. These are boolean variables that determine when a long or short trade should be initiated. Replace the existing example logic with your own custom buy and sell conditions. Your conditions can be based on any combination of indicators, price action patterns, candlestick formations, or other market analysis techniques. For example, if your strategy involves a combination of RSI and MACD, you would define longCondition as (rsi > 50 and macd_line > signal_line) and shortCondition as (rsi < 50 and macd_line < signal_line).
3.
Leverage the Template’s Built-in Features:
Once your longCondition and shortCondition are defined, the rest of the template automatically takes over. The integrated risk management module will calculate the appropriate position size based on your Risk % input and the chosen Stop Loss Type. The Risk:Reward ratio will determine your take-profit levels, and the Breakeven at R feature will manage your stop-loss dynamically. The time filter (Use Time Filter) will ensure your trades only occur within your specified hours, and the webhook alerts will notify you of trade executions.
Adaptive Cortex Strategy (Demo)Adaptive Cortex Strategy - The Smart, Adaptive Investment System
Don't Get Lost in the Market Noise. Learn to Understand the Market.
Every investor faces the same dilemma: Why does a strategy that worked perfectly yesterday struggle today when the market's character changes?
Because the market isn't static. It's a dynamic structure that constantly changes, breathes, and enters different regimes. So, why shouldn't your strategy adapt to this dynamism?
Adaptive Cortex Strategy (ACS)
What is This Strategy?
The Adaptive Cortex Strategy isn't just a simple indicator that gives you buy and sell signals. It's a holistic analysis framework that attempts to understand the changing nature of the market and adapt its decision-making mechanism accordingly. Its core philosophy is to identify data-driven, high-probability investment opportunities by combining (amalgamating) many different market dynamics.
The strategy's power comes from its proprietary technology, which we call the "Smart Decision Engine." This engine performs two primary functions:
Market Memory: The system continuously analyzes past significant market turning points and price levels. This allows the strategy to dynamically recognize and deeply understand the current market structure.
Situational Awareness: The system continuously measures the current market "mood." It detects whether we are in a strong trend or indecisive sideways movement and automatically adjusts its analysis accordingly. This allows it to adopt the most appropriate approach in each market.
What Does ACS Promise?
Clarity: By transforming complex market data into clear, conclusive signals, it provides you with an objective perspective during decision-making.
Discipline: With its rules-based structure, it helps you protect yourself from emotional traps like fear and greed, the market's greatest enemies.
Adaptation: Instead of searching for a "one-size-fits-all" strategy, it offers a system logic that "adapts to every market."
Risk Management: With advanced position management modules, it constantly reminds you that preserving capital is more important than making money.
What Doesn't It Promise? Guaranteed Profit or the "Holy Grail": No system in the financial markets can offer 100% certainty. Losing trades are a natural and inevitable part of professional investing. ACS aims not to eliminate losses, but to manage them and statistically maximize profit potential.
This is not a "run the robot and get rich" system. ACS is your most powerful analytical assistant, but the ultimate decision and responsibility always rest with the investor.
The Dream of Getting Rich Overnight: Successful investing is a marathon, not a sprint. ACS is designed to help disciplined and patient investors achieve statistical advantage over the long term.
Who Is This System Suitable For?
For Beginner Investors: It offers a disciplined and structured roadmap that avoids emotional decisions and confusion. For Experienced Analysts: It serves as a powerful quantitative aid that validates or challenges their technical analysis.
For Investors Seeking a System: It offers a professional-grade risk management framework that offers not only entry but also position management and multiple exit scenarios.
DMI Toolbox StrategyThe Directional Movement Index (DMI) was originally developed by J. Welles Wilder Jr. in 1978. Wilder introduced the DMI along with the Average Directional Index (ADX) in his book, “New Concepts in Technical Trading Systems,” which became a foundational reference for technical analysis.
The indicator can offer a myriad of signals for building a trading strategy. In an effort to provide the user with a meaningful way to evaluate these signals, this DMI Toolbox Strategy offers the chance to back-test various combinations and permutations of DMI signals on long trades. By default it will open a long position on the +DI (upward movement) crossing above the -DI (downward movement). By default, It exits long positions when the ADX (trend strength) reverses.
Suggested Use
Try a wide variety of long entry and exit signals across many different timeframes to see what is most effective for the item you wish to trade. There is a table in the upper right corner that will give a quick view of which signal is dominant across 5 timeframes, based on your current settings. Adjust the pyramidding, slippage, and commission values to more closely match your situation.
Visual Helpers
The DMI indicator has been altered to include a smoothed version of the ADX, as well as a colored background to show which signal is dominant (+DI or -DI). Small up arrows call your attention to ADX crossovers that may indicate a significant threshold in trend strength.
Volume Profile Auto POC📌 Overview
Volume Profile Auto POC is a trend-following strategy that uses the automatically calculated Point of Control (POC) from the volume profile, combined with ATR zones, to capture reversals and breakouts.
By basing decisions on volume concentration, it dynamically visualizes the price levels most watched by market participants.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
Automatically detect the volume concentration area (POC) to improve entry accuracy
Optimize risk management through ATR-based volatility adjustment
Provide early and consistent signals when trends emerge
✨ Key Features
Automatic POC Detection : Updates the volume profile over a defined lookback window in real time
ATR Zone Integration : Defines a POC ± 0.5 ATR zone to clarify potential reversals/breakouts
Visual Support : Plots the POC line and zones on the chart for intuitive decision-making
📊 Trading Rules
Long Entry:
Price breaks above the POC + 0.5 ATR zone
Volume is above average to support the breakout
Short Entry:
Price breaks below the POC - 0.5 ATR zone
Volume is above average to support the downside move
Exit (or Reverse Position):
Price returns to the POC area
Or touches the ATR band
⚙️ Trading Parameters & Considerations
Indicator Name: Volume Profile Auto POC
Parameters:
Lookback Bars: 50
Bins for Volume Profile: 24
ATR Length: 14
ATR Multiplier: 2.0
🖼 Visual Support
POC line plotted in red
POC ± 0.5 ATR zone displayed as a semi-transparent box
ATR bands plotted in blue for confirmation
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by traditional Volume Profile + ATR analysis,
while adding the improvement of a sliding-window mechanism for automatic POC updates.
Compared with conventional trend-following approaches,
its strength lies in combining both price and volume perspectives for decision-making.
✅ Summary
Volume Profile Auto POC automatically extracts key market levels (POC) and combines them with ATR-based zones,
providing a responsive trend-following method.
It balances clarity with practicality, aiming for both usability and reproducibility.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use proper risk management when applying it.
Siege Gold Strategy-1m
Siege Gold Strategy - An Advanced Trading Strategy with a Multi-Confirmation System
This powerful indicator is designed to help you base your trading decisions on solid foundations. Thanks to its advanced algorithms and multi-confirmation mechanism, it helps you understand market trends more clearly.
Key Features
Trend Pivot Points: Instantly identify trend reversals and potential support/resistance levels with intelligent pivot points that react to real-time price movements. This allows you to analyze the trend's strength and direction more accurately.
Relative Strength Index (RSI) Integration: We combine the classic overbought/oversold signals of the RSI with our custom strategies to generate more reliable and filtered signals. This integration minimizes false signals.
"Range" Module: This feature measures the volatility range the price is currently in, showing whether the market is consolidating or moving. This helps reduce the risk of making incorrect trades in sideways markets.
Who Is This For?
Traders who follow trend-following strategies.
Anyone who wants to automatically determine support and resistance levels.
Those looking for a multi-confirmation mechanism instead of relying on a single indicator.
Anyone who wants to generate more reliable trading signals.
This strategy can be used in the XAUUSD pair, as well as in crypto and forex markets. To use this strategy more accurately, we encourage you to watch a few videos. It's important to remember that every instrument and indicator setting yields different results, and we cannot guarantee that you will make a profit.
Dynamic Swing Anchored VWAP STRAT (Zeiierman/PineIndicators)Dynamic Swing Anchored VWAP STRATEGY — Zeiierman × PineIndicators (Pine Script v6)
A pivot-to-pivot Anchored VWAP strategy that adapts to volatility, enters long on bullish structure, and closes on bearish structure. Built for TradingView in Pine Script v6.
Full credits to zeiierman.
Repainting notice: The original indicator logic is repainting. Swing labels (HH/HL/LH/LL) are finalized after enough bars have printed, so labels do not occur in real time. It is not possible to execute at historical label points. Treat results as educational and validate with Bar Replay and paper trading before considering any discretionary use.
Concept
The script identifies swing highs/lows over a user-defined lookback ( Swing Period ). When structure flips (most recent swing low is newer than the most recent swing high, or vice versa), a new regime begins.
At each confirmed pivot, a fresh Anchored VWAP segment is started and updated bar-by-bar using an EWMA-style decay on price×volume and volume.
Responsiveness is controlled by Adaptive Price Tracking (APT) . Optionally, APT auto-adjusts with an ATR ratio so that high volatility accelerates responsiveness and low volatility smooths it.
Longs are opened/held in bullish regimes and closed when the regime turns bearish. No short positions are taken by design.
How it works (under the hood)
Swing detection: Uses ta.highestbars / ta.lowestbars over prd to update swing highs (ph) and lows (pl), plus their bar indices (phL, plL).
Regime logic: If phL > plL → bullish regime; else → bearish regime. A change in this condition triggers a re-anchor of the VWAP at the newest pivot.
Adaptive VWAP math: APT is converted to an exponential decay factor ( alphaFromAPT ), then applied to running sums of price×volume and volume, producing the current VWAP estimate.
Rendering: Each pivot-anchored VWAP segment is drawn as a polyline and color-coded by regime. Optional structure labels (HH/HL/LH/LL) annotate the swing character.
Orders: On bullish flips, strategy.entry("L") opens/maintains a long; on bearish flips, strategy.close("L") exits.
Inputs & controls
Swing Period (prd) — Higher values identify larger, slower swings; lower values catch more frequent pivots but add noise.
Adaptive Price Tracking (APT) — Governs the VWAP’s “half-life.” Smaller APT → faster/closer to price; larger APT → smoother/stabler.
Adapt APT by ATR ratio — When enabled, APT scales with volatility so the VWAP speeds up in turbulent markets and slows down in quiet markets.
Volatility Bias — Tunes the strength of APT’s response to volatility (above 1 = stronger effect; below 1 = milder).
Style settings — Colors for swing labels and VWAP segments, plus line width for visibility.
Trade logic summary
Entry: Long when the swing structure turns bullish (latest swing low is more recent than the last swing high).
Exit: Close the long when structure turns bearish.
Position size: qty = strategy.equity / close × 5 (dynamic sizing; scales with account equity and instrument price). Consider reducing the multiplier for a more conservative profile.
Recommended workflow
Apply to instruments with reliable volume (equities, futures, crypto; FX tick volume can work but varies by broker).
Start on your preferred timeframe. Intraday often benefits from smaller APT (more reactive); higher timeframes may prefer larger APT (smoother).
Begin with defaults ( prd=50, APT=20 ); then toggle “Adapt by ATR” and vary Volatility Bias to observe how segments tighten/loosen.
Use Bar Replay to watch how pivots confirm and how the strategy re-anchors VWAP at those confirmations.
Layer your own risk rules (stops/targets, max position cap, session filters) before any discretionary use.
Practical tips
Context filter: Consider combining with a higher-timeframe bias (e.g., daily trend) and using this strategy as an entry timing layer.
First pivot preference: Some traders prefer only the first bullish pivot after a bearish regime (and vice versa) to reduce whipsaw in choppy ranges.
Deviations: You can add VWAP deviation bands to pre-plan partial exits or re-entries on mean-reversion pulls.
Sessions: Session-based filters (RTH vs. ETH) can materially change behavior on futures and equities.
Extending the script (ideas)
Add stops/targets (e.g., ATR stop below last swing low; partial profits at k×VWAP deviation).
Introduce mirrored short logic for two-sided testing.
Include alert conditions for regime flips or for price-VWAP interactions.
Incorporate HTF confirmation (e.g., only long when daily VWAP slope ≥ 0).
Throttle entries (e.g., once per regime flip) to avoid over-trading in ranges.
Known limitations
Repainting: Swing labels and pivot confirmations depend on future bars; historical labels can look “perfect.” Treat them as annotations, not executable signals.
Execution realism: Strategy includes commission and slippage fields, yet actual fills differ by venue/liquidity.
No guarantees: Past behavior does not imply future results. This publication is for research/education only and not financial advice.
Defaults (backtest environment)
Initial capital: 10,000
Commission value: 0.01
Slippage: 1
Overlay: true
Max bars back: 5000; Max labels/polylines set for deep swing histories
Quick checklist
Add to chart and verify that the instrument has volume.
Use defaults, then tune APT and Volatility Bias with/without ATR adaptation.
Observe how each pivot re-anchors VWAP and how regime flips drive entries/exits.
Paper trade across several symbols/timeframes before any discretionary decisions.
Attribution & license
Original indicator concept and logic: Zeiierman — please credit the author.
Strategy wrapper and publication: PineIndicators .
License: CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike). Respect the license when forking or publishing derivatives.
