[Aegis]Original Turtle System for CryptoAs Richard Dennis once said, "Even if I published all the Turtle rules in the newspaper right now, no one would be able to 'execute' them," and 40 years later, even in modern financial markets (like the crypto market) where all the conditions have been disclosed, this strategy continues to deliver amazing performance. The following outlines the original Turtle rules as disclosed by Curtis Faith in his book *Way of the Turtle*, and a TradingView algorithm that translates these rules for application in the crypto market.
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### **The Original Turtle Trading Rules**
#### **1. Markets**
* Trade in liquid futures markets.
#### **2. Position Sizing**
The volatility measure, **N**, is used as the basis for all calculations.
**True Range (TR) Calculation:** Select the largest of the following three values:
* Current High - Current Low
* $|\text{Current High} - \text{Previous Close}|$ (Absolute Value)
* $|\text{Current Low} - \text{Previous Close}|$ (Absolute Value)
**N (Average True Range, ATR) Calculation:**
$$N = \frac{(19 \times \text{PDN} + \text{TR})}{20}$$
* **PDN:** Previous Day's N value
* **TR:** Current True Range
This is similar to a 20-day Exponential Moving Average, and is sometimes calculated using a Simple Moving Average.
**Unit Size Calculation:**
$$\text{Unit Size (Number of Contracts)} = \frac{1\% \text{ of Account Equity}}{(\text{N} \times \text{Dollars per Point})}$$
* **Dollars per Point (Tick Value):** The value of a 1-point change in price.
#### **3. Entries**
* **Entry:** Buy when the 55-day high is broken to the upside, and sell when the 55-day low is broken to the downside.
#### **5. Stops**
* The stop-loss for every unit is set at a price **2N** unfavorable from the entry price.
* For each additional unit added, the stop price for the **entire position** is adjusted favorably by **1/2 N**.
* In other words, the stop price of the last unit entered becomes the stop price for the entire position.
#### **6. Exits**
The exit rule for profitable positions (before a stop is hit) is as follows:
* **Long Positions:** Exit when the 20-day low is broken to the downside.
* **Short Positions:** Exit when the 20-day high is broken to the upside.
*Note: This exit rule is followed only if the price has moved up by a value greater than or equal to the N value multiplied by the criterion for changing the take-profit line (the original Korean text mentions a condition based on N, which is commonly interpreted as requiring a profit before applying the channel exit).*
๋ฆฌ์ฒ๋ ๋ฐ๋์ค๊ฐ ์์ "๋ด๊ฐ ์ง๊ธ ๋น์ฅ ํฐํ์ ๋ชจ๋ ๊ท์น์ ์ ๋ฌธ์ ๊ณตํํ๋ค๊ณ ํด๋ ์๋ฌด๋ '์คํ'ํ์ง ๋ชปํ ๊ฒ"๋ผ๊ณ ๋งํ๋ฏ 40๋
์ด ํ๋ฌ ๋ชจ๋ ์กฐ๊ฑด์ด ๊ณต๊ฐ๋ ํ๋ ๊ธ์ต์์ฅ(ํฌ๋ฆฝํ ์์ฅ)์์๋ ์ฌ์ ํ ์ด ์ ๋ต์ ๋๋ผ์ด ํผํฌ๋จผ์ค๋ฅผ ๊ธฐ๋กํ๊ณ ์์ต๋๋ค. ์๋๋ ์ปคํฐ์ค ํ์ด์ค๊ฐ ์์ ์ ์ ์ 'ํฐํ์ ๋ฐฉ์'์ ๊ณต๊ฐํ ์ค๋ฆฌ์ง๋ ํฐํ ๊ท์น๊ณผ ์ด๋ฅผ ์๊ณ ๋ฆฌ์ฆ์ผ๋ก ๋ณํํ์ฌ ํฌ๋ฆฝํ ๋ง์ผ์ ์ ์ฉํ ํธ๋ ์ด๋ฉ๋ทฐ ์๊ณ ๋ฆฌ์ฆ ์
๋๋ค.
##### 1. ์์ฅ (Markets)
โข ์ ๋์ฑ์ด ํ๋ถํ ์ ๋ฌผ ์์ฅ์์ ๊ฑฐ๋ํ๋ค.
##### 2. ํฌ์ง์
ํฌ๊ธฐ (Position Sizing)
๋ณ๋์ฑ ์ธก์ ๋จ์์ธ N์ ๋ชจ๋ ๊ณ์ฐ์ ๊ธฐ์ด๋ก ์ฌ์ฉํ๋ค.
**True Range (TR) ๊ณ์ฐ:** ๋ค์ ์ธ ๊ฐ์ง ๊ฐ ์ค ๊ฐ์ฅ ํฐ ๊ฐ์ ์ ํํ๋ค.
- โข ํ์ฌ ๊ณ ๊ฐ - ํ์ฌ ์ ๊ฐ
- โข |ํ์ฌ ๊ณ ๊ฐ - ์ ์ผ ์ข
๊ฐ| (์ ๋๊ฐ)
- โข |ํ์ฌ ์ ๊ฐ - ์ ์ผ ์ข
๊ฐ| (์ ๋๊ฐ)
**N (Average True Range, ATR) ๊ณ์ฐ:**
N = (19 ร PDN + TR) / 20
- โข PDN: ์ด์ ๋ ์ N ๊ฐ
- โข TR: ํ์ฌ True Range
์ด๋ 20์ผ ์ง์์ด๋ํ๊ท ๊ณผ ์ ์ฌํ๋ฉฐ, ๋จ์์ด๋ํ๊ท ์ผ๋ก ๊ณ์ฐํ๊ธฐ๋ ํ๋ค.
**1 ์ ๋(Unit)์ ํฌ๊ธฐ ๊ณ์ฐ:**
์ ๋ ํฌ๊ธฐ (๊ณ์ฝ ์) = ๊ณ์ข ์์ฐ์ 1% / (N ร ํฑ ๊ฐ์น)
โข ํฑ ๊ฐ์น(Dollars per Point): 1ํฌ์ธํธ ๋ณ๋ ์์ ๊ฐ์น
##### 3. ์ง์
(Entries)
- โข ์ง์
: 55์ผ ๊ณ ๊ฐ๋ฅผ ์ํฅ ๋ํํ๋ฉด ๋งค์, 55์ผ ์ ๊ฐ๋ฅผ ํํฅ ๋ํํ๋ฉด ๋งค๋ํ๋ค.
##### 5. ์์ (Stops)
- โข ๋ชจ๋ ์ ๋์ ๋ํ ์์ ๊ธฐ์ค์ ์ง์
๊ฐ๊ฒฉ์ผ๋ก๋ถํฐ 2N ๋งํผ ๋ถ๋ฆฌํ ๊ฐ๊ฒฉ์ ์ค์ ํ๋ค.
- โข ์ ๋์ด ์ถ๊ฐ๋ ๋๋ง๋ค ์ ์ฒด ํฌ์ง์
์ ์์ ๊ฐ๊ฒฉ์ 1/2 N ๋งํผ ์ ๋ฆฌํ ๋ฐฉํฅ์ผ๋ก ์ํฅ ์กฐ์ ํ๋ค.
- โข ์ฆ, ๋ง์ง๋ง์ผ๋ก ์ง์
ํ ์ ๋์ ์์ ๊ฐ๊ฒฉ์ด ์ ์ฒด ํฌ์ง์
์ ์์ ๊ฐ๊ฒฉ์ด ๋๋ค.
##### 6. ์ฒญ์ฐ (Exits)
์์ ์ ๋๋ฌํ๊ธฐ ์ ์์ต ์ค์ธ ํฌ์ง์
์ ์ฒญ์ฐ ๊ท์น์ ๋ค์๊ณผ ๊ฐ๋ค.
- โข ๋งค์ ํฌ์ง์
: 20์ผ ์ ๊ฐ๋ฅผ ํํฅ ๋ํํ ๋ ์ฒญ์ฐํ๋ค.
- โข ๋งค๋ ํฌ์ง์
: 20์ผ ๊ณ ๊ฐ๋ฅผ ์ํฅ ๋ํํ ๋ ์ฒญ์ฐํ๋ค.
๋จ, N๊ฐ์ ์ต์ ์ ๋ณ๊ฒฝ ๊ธฐ์ค์ ๊ณฑํ ๊ฐ ์ด์์ผ๋ก ๊ฐ๊ฒฉ์ด ์์นํ ๊ฒฝ์ฐ, ์ ๊ท์น์ ๋ฐ๋ฅธ๋ค.
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DayFlow VWAP Relay Forex Majors StrategySummary in one paragraph
DayFlow VWAP Relay is a day-trading strategy for major FX pairs on intraday timeframes, demonstrated on EURUSD 15 minutes. It waits for alignment between a daily anchored VWAP regime check, residual percentiles, and lower-timeframe micro flow before suggesting trades. The originality is the fusion of daily VWAP residual percentiles with a live micro-flow score from 1 minute data to switch between fade and breakout behavior inside the same session. Add it to a clean chart and use the markers and alerts.
Scope and intent
โข Markets: Major FX pairs such as EURUSD, GBPUSD, USDJPY, AUDUSD, USDCHF, USDCAD
โข Timeframes: One minute to one hour
โข Default demo in this publication: EURUSD on 15 minutes
โข Purpose: Reduce false starts by acting only when context, location and micro flow agree
โข Limits: This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
โข Core novelty: Residual percentiles to daily anchored VWAP decide โbalanced versus expanding dayโ. A separate 1 minute micro-flow score confirms direction, so the same model fades extremes in balance and rides range breaks in expansion
โข Failure modes addressed: Chop fakeouts and unconfirmed breakouts are filtered by the expansion gate and micro-flow threshold
โข Testability: Every input is exposed. Bands, background regime color, and markers show why a suggestion appears
โข Portable yardstick: Stops and targets are ATR multiples converted to ticks, which transfer across symbols
โข Open source status: No reused third-party code that requires attribution
Method overview in plain language
The day is anchored with a VWAP that updates from the daily session start. Price minus VWAP is the residual. Percentiles of that residual measured over a rolling window define location extremes for the current day. A regime score compares residual volatility to price volatility. When expansion is low, the day is treated as balanced and the model fades residual extremes if 1 minute micro flow points back to VWAP. When expansion is high, the model trades breakouts outside the VWAP bands if slope and micro flow agree with the move.
Base measures
โข Range basis: True Range smoothed by ATR for stops and targets, length 14
โข Return basis: Not required for signals; residuals are absolute price distance to VWAP
Components
โข Daily Anchor VWAP Bands. VWAP with standard-deviation bands. Slope sign is used for trend confirmation on breakouts
โข Residual Percentiles. Rolling percentiles of close minus VWAP over Signal length. Identify location extremes inside the day
โข Expansion Ratio. Standard deviation of residuals divided by standard deviation of price over Signal length. Classifies balanced versus expanding day
โข Micro Flow. Net up minus down closes from 1 minute data across a short span, normalized to โ1..+1. Confirms direction and avoids fades against pressure
โข Session Window optional. Restricts trading to your configured hours to avoid thin periods
โข Cooldown optional. Bars to wait after a position closes to prevent immediate re-entry
Fusion rule
Gating rather than weighting. First choose regime by Expansion Ratio versus the Expansion gate. Inside each regime all listed conditions must be true: location test plus micro-flow threshold plus session window plus cooldown. Breakouts also require VWAP slope alignment.
Signal rule
โข Long suggestion on balanced day: residual at or below the lower percentile and micro flow positive above the gate while inside session and cooldown is satisfied
โข Short suggestion on balanced day: residual at or above the upper percentile and micro flow negative below the gate while inside session and cooldown is satisfied
โข Long suggestion on expanding day: close above the upper VWAP band, VWAP slope positive, micro flow positive, session and cooldown satisfied
โข Short suggestion on expanding day: close below the lower VWAP band, VWAP slope negative, micro flow negative, session and cooldown satisfied
โข Positions flip on opposite suggestions or exit by brackets
What you will see on the chart
โข Markers on suggestion bars: L for long, S for short
โข Exit occurs on reverse signal or when a bracket order is filled
โข Reference lines: daily anchored VWAP with upper and lower bands
โข Optional background: teal for balanced day, orange for expanding day
Inputs with guidance
Setup
โข Signal length. Residual and regime window. Typical 40 to 100. Higher smooths, lower reacts faster
Micro Flow
โข Micro TF. Lower timeframe used for micro flow, default 1 minute
โข Micro span bars. Count of lower-TF bars. Typical 5 to 20
โข Micro flow gate 0..1. Minimum absolute flow. Raising it demands stronger confirmation and reduces trade count
VWAP Bands
โข VWAP stdev multiplier. Band width. Typical 0.8 to 1.6. Wider bands reduce breakout frequency and increase fade distance
โข Expansion gate 0..3. Threshold to switch from fades to breakouts. Raising it favors fades, lowering it favors breakouts
Sessions
โข Use session filter. Enable to trade only inside your window
โข Trade window UTC. Default 07:00 to 17:00
Risk
โข ATR length. Stop and target basis. Typical 10 to 21
โข Stop ATR x. Initial stop distance in ATR multiples
โข Target ATR x. Profit target distance in ATR multiples
โข Cooldown bars after close. Wait bars before a new entry
โข Side. Both, long only, or short only
View
โข Show VWAP and bands
โข Color bars by residual regime
Properties visible in this publication
โข Initial capital 10000
โข Base currency Default
โข request.security uses lookahead off everywhere
โข Strategy: Percent of equity with value 3. Pyramiding 0. Commission cash per order 0.0001 USD. Slippage 3 ticks. Process orders on close ON. Bar magnifier ON. Recalculate after order is filled OFF. Calc on every tick OFF. Using standard OHLC fills ON.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Fills and slippage vary by venue. Shapes can move while a bar forms and settle on close. Strategies must run on standard candles for signals and orders.
Honest limitations and failure modes
High impact news, session opens, and thin liquidity can invalidate assumptions. Very quiet days can reduce contrast between residuals and price volatility. Session windows use the chart exchange time. If both stop and target are touched within a single bar, TradingViewโs standard OHLC price-movement model decides the outcome.
Expect different behavior on illiquid pairs or during holidays. The model is sensitive to session definitions and feed time. Past results never guarantee future outcomes.
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
saodisengxiaoyu-lianghua-2.1- This indicator is a modular, signal-building framework designed to generate long and short signals by combining a chosen leading indicator with selectable confirmation filters. It runs on Pine Script version 5, overlays directly on price, and is built to be highly configurable so traders can tailor the signal logic to their market, timeframe, and trading style. It includes a dashboard to visualize which conditions are active and whether they validate a signal, and it outputs clear buy/sell labels and alert conditions so you can automate or monitor trades with confidence.
Core Design
- Leading Indicator: You choose one primary signal generator from a broad list (for example, Range Filter, Supertrend, MACD, RSI, Ichimoku, and many others). This serves as the anchor of the system and determines when a preliminary long or short setup exists.
- Confirmation Filters: You can enable additional filters that validate the leading signal before it becomes actionable. Each โrespectโฆโ input toggles a filter on or off. These filters include popular tools like EMA, 2/3 EMA crosses, RQK (Nadaraya Watson), ADX/DMI, Bollinger-based oscillators, MACD variations, QQE, Hull, VWAP, Choppiness Index, Damiani Volatility, and more.
- Signal Expiry: To avoid waiting indefinitely for confirmations, the indicator counts how many consecutive bars the leading condition holds. If confirmations do not align within a defined number of bars, the setup expires. This controls latency and helps reduce late or stale entries.
- Alternating Signals: An optional mode enforces alternation (long must follow short and vice versa), helping avoid repeated entries in the same direction without a meaningful reset.
- Aggregation Logic: The final long/short conditions are formed by combining the leading condition with all selected confirmation filters through logical conjunction. Only if all enabled filters validate the signal (within expiry constraints) does the indicator consider it a confirmed long or short.
- Visualization and Alerts: The script plots buy/sell labels at signal points, provides alert conditions for automation, and displays a compact dashboard summarizing the leading indicatorโs status and each confirmationโs pass/fail result using checkmarks.
Leading Indicator Options
- The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include:
- Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative โDWโ mode.
- Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction.
- Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels.
- Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span.
- TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts.
- Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength.
- ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds.
- RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends.
- Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles.
- Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges.
Confirmation Filters
- Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples:
- EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels.
- 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment.
- RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern.
- RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories.
- Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade.
- VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts.
- ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades.
- Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup.
- By combining several filters you can create strict, conservative entries or looser setups depending on your goals.
Range Filter Engine
- A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types:
- Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges.
- Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments.
- The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation.
Signal Construction
- The script computes:
- leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator.
- longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition.
- Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined โSignal Expiry Candle Count,โ the setup is abandoned and the signal does not trigger.
- Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset.
- Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions.
Visualization
- Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (โlongโ vs. โshortโ).
- Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (โ๏ธ) or failed (โ) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning.
- Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. Itโs a helpful audit trail to understand missed trades or prevent โchasingโ invalid signals.
- Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates.
Inputs and Parameters
- You control the indicator from a comprehensive input panel:
- Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size).
- Leading Indicator: Choose the primary signal generator from the large list.
- Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior.
- Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales.
- Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes.
Alerts and Automation
- The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration.
Typical Workflow
- Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian.
- Add a few key Confirmation Filters that complement the leading signal. For example:
- Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum.
- Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions.
- Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough.
- Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly.
- Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed.
- For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot.
Strengths and Practical Notes
- Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately.
- Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code.
- Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset.
- Modular Design: The logical gates (โrespectโฆโ) make the behavior transparent: if a filter is on, it must pass; if itโs off, the signal ignores it. This keeps reasoning clean.
- Avoiding Overfitting: Because you can stack many filters, itโs tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes.
Limitations and Recommendations
- No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically.
- Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime.
- Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy.
- Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results.
Example Configurations
- Trend-Following Setup:
- Leading: Supertrend uptrend for longs and downtrend for shorts.
- Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA.
- Expiry: 3โ4 bars to keep entries timely.
- Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity.
- Mean-Reversion to Momentum Crossover:
- Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short).
- Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation.
- Expiry: 2โ3 bars for responsive re-entry.
- Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes.
- Range Breakout Focus:
- Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts.
- Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold.
- Expiry: 1โ3 bars to act on breakout windows.
- Result: Better alignment to breakout dynamics, gating trades by volatility and regime.
Conclusion
- This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. Itโs designed to help you build high-quality entry signals tailored to your approach, whether thatโs trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
ๅคๆๆ ้ๅไบคๆDIY- The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include:
- Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative โDWโ mode.
- Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction.
- Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels.
- Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span.
- TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts.
- Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength.
- ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds.
- RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends.
- Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles.
- Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges.
Confirmation Filters
- Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples:
- EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels.
- 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment.
- RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern.
- RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories.
- Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade.
- VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts.
- ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades.
- Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup.
- By combining several filters you can create strict, conservative entries or looser setups depending on your goals.
Range Filter Engine
- A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types:
- Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges.
- Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments.
- The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation.
Signal Construction
- The script computes:
- leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator.
- longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition.
- Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined โSignal Expiry Candle Count,โ the setup is abandoned and the signal does not trigger.
- Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset.
- Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions.
Visualization
- Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (โlongโ vs. โshortโ).
- Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (โ๏ธ) or failed (โ) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning.
- Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. Itโs a helpful audit trail to understand missed trades or prevent โchasingโ invalid signals.
- Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates.
Inputs and Parameters
- You control the indicator from a comprehensive input panel:
- Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size).
- Leading Indicator: Choose the primary signal generator from the large list.
- Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior.
- Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales.
- Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes.
Alerts and Automation
- The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration.
Typical Workflow
- Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian.
- Add a few key Confirmation Filters that complement the leading signal. For example:
- Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum.
- Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions.
- Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough.
- Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly.
- Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed.
- For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot.
Strengths and Practical Notes
- Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately.
- Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code.
- Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset.
- Modular Design: The logical gates (โrespectโฆโ) make the behavior transparent: if a filter is on, it must pass; if itโs off, the signal ignores it. This keeps reasoning clean.
- Avoiding Overfitting: Because you can stack many filters, itโs tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes.
Limitations and Recommendations
- No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically.
- Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime.
- Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy.
- Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results.
Example Configurations
- Trend-Following Setup:
- Leading: Supertrend uptrend for longs and downtrend for shorts.
- Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA.
- Expiry: 3โ4 bars to keep entries timely.
- Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity.
- Mean-Reversion to Momentum Crossover:
- Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short).
- Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation.
- Expiry: 2โ3 bars for responsive re-entry.
- Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes.
- Range Breakout Focus:
- Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts.
- Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold.
- Expiry: 1โ3 bars to act on breakout windows.
- Result: Better alignment to breakout dynamics, gating trades by volatility and regime.
Conclusion
- This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. Itโs designed to help you build high-quality entry signals tailored to your approach, whether thatโs trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
โข Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
โข Timeframes: one minute to daily
โข Default demo: BTC on 60 minute
โข Purpose: faster yet calmer PSAR that resists chop and improves short discipline
โข Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
โข Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
โข Addresses false flips in low volatility and weak downtrends
โข All controls are exposed in Inputs for testability
โข Yardstick: ATR normalizes drift so settings port across symbols
โข Open source. No links. No solicitation
Method overview
Components
โข Adaptive AF: base step plus boost factor times logistic strength
โข Trail inertia: one sided blend that keeps the SAR monotone
โข Flip hysteresis: price must clear SAR by a buffer times ATR
โข Volatility gate: ATR over its mean must exceed a ratio
โข Bear bias for shorts: price below EMA of length 91 with negative slope window 54
โข Cooldown bars optional after any entry
โข Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
โข Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
โข Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
โข Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
โข Start AF 0.02. Lower slows new trends. Higher reacts quicker
โข Max AF 1. Typical 0.2 to 1. Caps acceleration
โข Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
โข Strength window 18. Typical 10 to 40. Drift estimation window
โข ATR length 16. Typical 10 to 30. Volatility unit
โข Strength gain 4.5. Typical 2 to 6. Steepness of logistic
โข Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
โข Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
โข AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
โข Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
โข Allow Long, Allow Short toggles
Trade Filters
โข Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
โข Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
โข Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
โข Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
โข TP long ATR 1.0. Set to zero to disable
โข TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph
Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter.
Scope and intent
โข Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto
โข Timeframes: 5 min to 1 day
โข Default demo: SPY on 60 min
โข Purpose: fade stretched moves only when multi-anchor context and breadth agree
โข Limits: strategy uses standard candles for signals and orders only
Originality and usefulness
โข Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM
โข Failure mode addressed: chasing extended moves and fading during index-wide thrusts
โข Testability: each component is an input and visible in orders list via L and S tags
โข Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols
โข Open source: method and implementation are disclosed for community review
Method overview in plain language
Base measures
โข Range basis: ATR(length = atr_len) as the normalization unit
โข Return basis: not used directly; we use rank statistics for stability
Components
โข Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len
โข Robust Z of Close: median and MAD based Z to avoid outliers
โข Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts
โข Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided
โข Gap Shock: skip signals after large session gaps
Fusion rule
โข All required gates must be true: Energy โฅ energy_trig_prc, |Robust Z| โฅ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear
Signal rule
โข Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z โค โbreadth_z_ok
โข Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z โฅ +breadth_z_ok
What you will see on the chart
โข Standard strategy arrows for entries and exits
โข Optional short-side brackets: ATR stop and ATR take profit if enabled
Inputs with guidance
Setup
โข Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts.
โข ATR length: normalization unit. Typical 10 to 20. Higher reduces noise.
โข VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0.
โข Robust Z window: 40 to 100. Larger for stability.
โข Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only.
โข Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches.
โข Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs.
Regime and Breadth
โข Use breadth gate: on when trading indices or broad ETFs.
โข Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts.
โข Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade.
Risk โ Short only
โข Enable short SL TP: on to bracket shorts.
โข Short ATR stop mult: 1.0 to 3.0.
โข Short ATR take profit mult: 1.0 to 6.0.
Properties visible in this publication
โข Initial capital: 25000USD
โข Default order size: Percent of total equity 3%
โข Pyramiding: 0
โข Commission: 0.03 percent
โข Slippage: 5 ticks
โข Process orders on close: OFF
โข Bar magnifier: OFF
โข Recalculate after order is filled: OFF
โข Calc on every tick: OFF
โข request.security lookahead off where used
Realism and responsible publication
โข No performance claims. Past results never guarantee future outcomes
โข Fills and slippage vary by venue
โข Shapes can move during bar formation and settle on close
โข Standard candles only for strategies
Honest limitations and failure modes
โข Economic releases or very thin liquidity can overwhelm mean-reversion logic
โข Heavy gap regimes may require larger gap filter or TR-based tuning
โข Very quiet regimes reduce signal contrast; extend windows or raise thresholds
Open source reuse and credits
โข None
Strategy notice
Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution.
Entries and exits
โข Entry logic: as in Signal rule above
โข Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup
โข Risk model: ATR-based brackets on shorts when enabled
โข Tie handling: stop first when both could be touched inside one bar
Dataset and sample size
โข Test across your visible history. For robust inference prefer 100 plus trades.
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
โข Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
โข Timeframes. From one minute to daily
โข Default demo in this publication. SPY on one day timeframe
โข Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
โข Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
โข Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
โข Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
โข Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
โข Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
โข Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
โข Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
โข Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
โข Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
โข Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
โข Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
โข Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
โข Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
โข Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
โข Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
โข Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
โข Normalize the three drivers after removing overlap
โข Blend with weights that adapt to your aggression input
โข Multiply by the gates to respect path quality
โข Smooth just enough to avoid jitter while keeping timing responsive
โข Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
โข The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
โข A long suggestion appears when the long score crosses above its long threshold while all gates are active
โข A short suggestion appears when the short score crosses below its short threshold while all gates are active
โข If any required gate is missing the state is wait
โข When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
โข Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
โข Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
โข Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
โข Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
โข Entry mode. Both or Long only or Short only
Complementary risk engine
โข Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
โข ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
โข ATR length. Default fourteen
โข Stop multiple. Default one point five times the anchor ATR
โข Use take profit. On by default
โข Take profit in R. Default two R
โข Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
โข Entry mode Both
โข ATR anchor Week
โข Aggression Long zero point five Aggression Short zero point three
โข Stop multiple one point five Take profit two R
โข Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
โข Session windows optional if you add them in your copy
โข ATR anchor Day
โข Lower aggression both sides
โข Breakeven later and trailing later so the first bounce has room
โข This favors fade entries that still convert into trends when the path stays clean
Swing continuation
โข Signal timeframe four hours or one day
โข Confirm timeframe one day if you choose to include bias
โข ATR anchor Week or Month
โข Larger base windows and a steady two R target
โข This accepts fewer entries and aims for larger holds
Properties visible in this publication
โข Initial capital 25.000
โข Base currency USD
โข Default order size percent of equity value three - 3% of the total capital
โข Pyramiding zero
โข Commission zero point zero three percent - 0.03% of total capital
โข Slippage five ticks
โข Process orders on close off
โข Recalculate after order is filled off
โข Calc on every tick off
โข Bar magnifier off
โข Any request security calls use lookahead off everywhere
Realism and responsible publication
โข No performance promises. Past results never guarantee future outcomes
โข Fills and slippage vary by venue and feed
โข Strategies run on standard candles only
โข Shapes can update while a bar is forming and settle on close
โข Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
โข Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
โข Gap heavy symbols often behave better with a True Range basis for risk than a simple range
โข Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
โข Session windows follow the exchange time of the chart if you add them
โข If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
โข No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
ProbRSI Adaptive SPY and QQQ Swing One Hour Strategy Summary in one paragraph
A probabilistic RSI engine for large cap ETFs and index names on intraday and swing timeframes. It converts ATR scaled returns into a 0 to 100 probability line, adapts its smoothing from path efficiency, and gates flips with simple percent levels. It is original because it fuses three pieces that traders rarely combine in one signal line: ATR normalized return probability, curvature compression, and per bar adaptive EMA. Add it to a clean chart, keep the default one hour signal on QQQ, and read the entry and exit markers generated by the strategy. For conservative alerts select on bar close.
Scope and intent
โข Markets. Major ETFs and large cap equities. Index futures. Liquid crypto. Major FX pairs
โข Timeframes. One minute to daily. Defaults to one hour for swing pace
โข Default demo used in this publication. SPY/QQQ on one hour
โข Purpose. Reduce false flips by adapting to path efficiency and by gating long and short separately
โข Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
โข Unique fusion. Logistic probability of ATR scaled returns with arcsine pre transform, optional curvature compression, and per bar adaptive EMA steered by an efficiency ratio
โข Failure mode addressed. Fast whips in congestion and late entries after spikes
โข Testability. Each component has a named input and can be tuned directly. Entry names Long and Short are visible in the list of trades
โข Portable yardstick. ATR scaled return is a common unit across symbols and venues
โข Protected rationale. The code stays protected to preserve implementation details of the adaptive engine and curvature assist while the method and usage are fully explained here for community review
Method overview in plain language
You convert raw returns into a probability scale, adapt the smoothing to the straightness of the path, and only allow flips when a simple gate is satisfied. The probability line crosses its own EMA to generate signals. When the cross happens below a short gate or above a long gate, the flip is allowed. Otherwise it is ignored.
Base measures
โข Return basis. Close minus prior close normalized by ATR, then arcsine to damp large steps. ATR window is set by ATR length. Sensitivity is adjusted by an ATR scale input
โข Probability map. A logistic function maps the normalized return to 0 to 1 which becomes 0 to 100 after scaling
Components
โข Probability core. Logistic probability of ATR scaled returns. Higher values imply upside pressure. Smoothed by an adaptive EMA
โข Curvature assist optional. A curvature proxy compresses extreme spikes toward neutral. Useful after news bars. Weight controls strength
โข Efficiency ratio. A path efficiency score from 0 to 1 extends the smoothing length during noisy paths and shortens it during directional paths
โข Signal line. An EMA of the probability line creates the reference for cross up and cross down
โข Gates. Two simple percent levels define when long and short flips are allowed
Fusion rule
โข The adaptive EMA length is computed as a linear map between a minimum and a maximum bound based on one minus efficiency
โข If curvature assist is enabled the probability is adjusted by a small counter spike term
โข Final probability is compared to its EMA
Signal rule
โข Long. A long entry is suggested when probability crosses above the signal line and the current probability is above the Long gate level
โข Short. A short entry is suggested when probability crosses below the signal line and the current probability is below the Short gate level
โข Exit and flip. When an opposite entry condition appears the current position is closed and a new position opens in the opposite direction
What you will see on the chart
โข Strategy markers on suggestion bars. Orders named Long and Short
โข Exit marker when the opposite signal closes the open side
โข No table by design. All tuning lives in Inputs for a clean chart
Inputs with guidance
Market TF
โข Symbol. Series used for oscillator computation. Use the instrument you trade or a close proxy
โข Signal timeframe. Timeframe where the oscillator is evaluated. Leave blank to follow the chart
Core
โข Price source. Series used for returns. Typical choice close
โข Base length. Fallback EMA length used when adaptation is off. Typical range 20 to 200. Larger smooths more
โข ATR length. Window for ATR that scales returns. Typical range 10 to 30. Larger normalizes more and lowers sensitivity
โข Logit sharpness. Steepness of the logistic link. Typical range 1 to 8. Raising it reacts more to the same input
โข ATR scale. Extra divisor on ATR. Typical range 0.5 to 2. Smaller is more sensitive
โข Signal length. EMA of the probability line. Typical range 5 to 20. Larger gives fewer flips
โข Long gate. Allow long flips only above this level. Typical range 20 to 40
โข Short gate. Allow short flips only below this level. Typical range 20 to 40
Adaptive
โข Adaptive smoothing. If on, the efficiency ratio controls the per bar EMA length
โข Min effective length. Lower bound of adaptive EMA. Typical range 5 to 50
โข Max effective length. Upper bound of adaptive EMA. Typical range 50 to 300
โข Efficiency window. Window for efficiency ratio. Typical range 30 to 100
Shape Assist
โข Curvature influence. If on, extreme spikes are nudged toward neutral
โข Curvature weight. Strength of compression. Typical range 0.1 to 0.3
Properties visible in this publication
โข Initial capital. 25000
โข Base currency. USD
โข request.security lookahead off everywhere
โข Commission. 0.03 percent
โข Slippage. 5 ticks
โข Default order size method percent of equity with value 3 for realistic testing
โข Pyramiding 0
โข Process orders on close ON
โข Bar magnifier OFF
โข Recalculate after order is filled OFF
โข Calc on every tick OFF
Realism and responsible publication
โข No performance claims. Past results never guarantee future outcomes
โข Shapes can move while a bar forms and settle on close
โข Strategies use standard candles for signals and orders only
Honest limitations and failure modes
โข Economic releases and thin liquidity can break assumptions behind the curvature assist
โข Gap heavy symbols may prefer a longer ATR window
โข Very quiet regimes can reduce signal contrast. Consider higher gates or longer signal length
โข Session time follows the exchange of the chart and can change symbol to symbol
โข Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
โข Past results never guarantee future outcomes
Open source reuse and credits
โข None
Mode
Public protected. Source is hidden while access is free. Implementation detail remains private. Method and use are fully disclosed here
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Moving Average Trend Strategy V4.1 โ Revised Version (Selectableโ
**Version Notes (V4.0)**
| Feature | Description |
| --------------------------------------- | -------------------------------------------------------- |
| ๐ง **Moving Average Type Options** | Choose from EMA / SMA / HMA / WMA |
| ๐งฑ **Take-Profit / Stop-Loss Switches** | Can be enabled or disabled independently |
| โ๏ธ **Add Position Function** | Can be enabled or disabled independently |
| ๐ **Add Position Signal Source** | Selectable between MA Crossover / MACD / RCI / RSI |
| ๐น **Adjustable Parameters** | All periods and percentages are customizable in settings |
---
โ
**Update Summary:**
| Function | Description |
| -------------------------------------- | --------------------------------------------------------------------- |
| **MA Type Selection** | Choose EMA / SMA / HMA / WMA in chart settings |
| **Take-Profit / Stop-Loss Percentage** | Configurable in the โTake-Profit & Stop-Lossโ group |
| **Add / Reduce Position Percentage** | Adjustable separately in the โAdd/Reduce Positionโ group |
| **MA Periods** | Customizable in the โMoving Average Parametersโ section |
| **Code Structure** | Logic unchanged โ only parameterization and selection functions added |
---
### **Strategy Recommendations:**
* **Trending Market:** Prefer EMA trend tracking or SAR indicators
* **Range-Bound Market:** Use ATR-based volatility stop-loss
* **Before Major Events:** Consider option hedging
* **Algorithmic Trading:** Recommend ATR + partial take-profit combination strategy
---
### **Key Parameter Optimization Logic:**
* Backtest different **ATR multipliers** (2โ3ร ATR)
* Test **EMA periods** (10โ50 periods)
* Optimize **partial take-profit ratios**
* Adjust **maximum drawdown tolerance** (typically 30โ50% of profit)
---
### **Risk Control Tips:**
* Avoid overly tight stop-losses that trigger too frequently
* During strong trends, consider widening take-profit targets
* Confirm trend continuation with **volume analysis**
* Adjust parameters based on **timeframe** (e.g., Daily vs Hourly)
---
### **Practical Example (Forex: EUR/USD):**
* **Entry:** Go long on breakout above 1.1200
* **Initial Stop-Loss:** 1.1150 (50 pips)
* **When profit reaches 1.1300:**
* Close 50% of position
* Move stop-loss to 1.1250 (lock in 50 pips profit)
* **When price rises to 1.1350:**
* Move stop-loss to 1.1300 (lock in 100 pips profit)
* **Final Outcome:**
* Price retraces to 1.1300, triggering take-profit
This method secured over **80% of trend profits** during the 2023 EUR rebound, capturing **23% more profit** compared to fixed take-profit strategies (based on backtest results).
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
โข Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
โข Timeframes. One minute to daily
โข Default demo used in the publication. QQQ on one hour
โข Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
โข Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
โข Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
โข What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
โข Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
โข Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
โข Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
โข Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
โข Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
โข Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
โข Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
โข Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
โข Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
โข Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
โข Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
โข The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
โข Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
โข Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
โข Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
โข When polarity flips from plus to minus, the strategy closes any long and enters a short.
โข When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
โข White polarity plot around the zero line
โข A dotted reference line at zero named Zen
โข Green background tint for positive polarity and red background tint for negative polarity
โข Strategy long and short markers placed by the TradingView engine at entry and at close conditions
โข No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
โข Price source. Default ohlc4. Stable for noisy symbols.
โข Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
โข Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
โข Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
โข Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
โข Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
โข Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
โข Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
โข Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
โข Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
โข Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
โข Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
โข Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
โข Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
โข Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
โข Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
โข This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
โข Initial capital 25000
โข Base currency Default
โข Default order size method percent of equity with value 5
โข Pyramiding 1
โข Commission 0.05 percent
โข Slippage 10 ticks
โข Process orders on close ON
โข Bar magnifier ON
โข Recalculate after order is filled OFF
โข Calc on every tick OFF
Honest limitations and failure modes
โข Past results do not guarantee future outcomes
โข Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
โข Gap heavy symbols may benefit from the MAD Z normalization
โข Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
โข Session time is the exchange time of the chart
โข If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
โข None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
โข Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
โข Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
โข Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
โข Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
โข Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
โข Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
โข Initial capital 25000
โข Base currency Default
โข Default order size percent of equity with value 5
โข Pyramiding 1
โข Commission 0.05 percent
โข Slippage 10 ticks
โข Process orders on close ON
โข Bar magnifier ON
โข Recalculate after order is filled OFF
โข Calc on every tick OFF
Dataset and sample size
โข Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
โข Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
โข Add alertcondition lines for long, short, and exit short
โข Add optional table with component readouts
โข Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Ekoparaloji Cyrpto StrategyEkoparaloji Crypto Strategy - User Information Document
๐ Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
๐ฏ Key Features
โ
Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
๐ Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
๐ฐ Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
๐ Visual Tracking System
The following information is displayed in real-time on the chart:
โ
Average cost level
โ
Profit target level
โ
Stop loss level (if active)
โ
Next pyramiding level
โ
Liquidation (capital reset) level
โ
Trend indicator
๐ก๏ธ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
๐ฑ Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
โ๏ธ Adjustable Parameters
Customizable by user:
๐ต Capital Amount: Base amount to be used for each position
๐ Profit Target: Profit percentage at which to exit
๐ Stop Loss: Usage status and maximum loss percentage
๐
Time Filter: Start and end dates for testing
๐ฌ Trade Comments: Custom labels for each trade
๐ Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
โ ๏ธ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
โ ๏ธ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
๐ How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Happy trading! ๐
Ekoparaloji Strategy Crypto Ekoparaloji Crypto Strategy - User Information Document
๐ Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
๐ฏ Key Features
โ
Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
๐ Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
๐ฐ Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
๐ Visual Tracking System
The following information is displayed in real-time on the chart:
โ
Average cost level
โ
Profit target level
โ
Stop loss level (if active)
โ
Next pyramiding level
โ
Liquidation (capital reset) level
โ
Trend indicator
๐ก๏ธ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
๐ฑ Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
โ๏ธ Adjustable Parameters
Customizable by user:
๐ต Capital Amount: Base amount to be used for each position
๐ Profit Target: Profit percentage at which to exit
๐ Stop Loss: Usage status and maximum loss percentage
๐
Time Filter: Start and end dates for testing
๐ฌ Trade Comments: Custom labels for each trade
๐ Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
โ ๏ธ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
โ ๏ธ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
๐ How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Ajay R5.41๐ป Ajay Gold 3H Sell Power Indicator ๐ป
Precision-Based Smart Sell System for Gold (XAU/USD)
๐ก Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
โ๏ธ Technical Foundation
The indicator uses multiple advanced confirmations:
๐ EMA Trend Filter โ Confirms downtrend
๐ช RSI Overbought Rejection โ Momentum reversal signal
๐ MACD Bearish Cross โ Confirms trend strength
๐ฏ๏ธ Bearish Candle Structure โ Price action validation
When all conditions align, a clear ๐ป Sell Signal is plotted on the chart.
๐ Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart โ fully automated internal logic.
๐ Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
๐ How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the ๐ป Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
โ ๏ธ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate โ always backtest and demo trade before using in real trading.
๐ฌ Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Ajay R5.41๐ป Ajay Gold 3H Power Indicator ๐ป
Precision-Based Smart Sell System for Gold (XAU/USD)
๐ก Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
โ๏ธ Technical Foundation
The indicator uses multiple advanced confirmations:
๐ EMA Trend Filter โ Confirms downtrend
๐ช RSI Overbought Rejection โ Momentum reversal signal
๐ MACD Bearish Cross โ Confirms trend strength
๐ฏ๏ธ Bearish Candle Structure โ Price action validation
When all conditions align, a clear ๐ป Sell Signal is plotted on the chart.
๐ Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart โ fully automated internal logic.
๐ Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
๐ How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the ๐ป Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
โ ๏ธ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate โ always backtest and demo trade before using in real trading.
๐ฌ Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Nemesis Strategy MLWinning That's all I know
Years of research been done to this strategy It's based on algorithm that detects where the markets are going Works on crypto this strategy his excellent indicators and it can generate a lot of money if you know what you are doing and depending on the fees of the exchanges as well So be smart and be kind God bless you all
Kz GC1! ORBStrategy that trades breakouts on GC1! futures on the 5min timeframe. It also works on MGC1! for lower drawdown and to manage Apex and Top Step accounts with the lower risk.
Risk Disclaimer:
Past results as well as strategy tester reports do not indicate future performance. Guarantees do not exist in trading. By using this strategy you risk losing all your money.
Important:
It trades all days that markets are open. Set times may be seen on settings. Trades multiple times a day sometimes.
It works on the 5 and 15min timeframe only. Results are better on 5min timeframe.
The settings are optimized already for GC1! on the 5min timeframe.
How it works:
Every trading day it measures the range of the first 15min candle of pre-selected hours. As soon as price closes above or below on the 15min timeframe, it will trade the breakout targeting a set risk to reward ratio. SL on the opposite side of the range.
Settings:
Hourly Trading Hours: These are the times that worked best for this strategy. All boxes should be checked for best results. Excluded times were when it performed bad which is why those times have been left out.
ORB Formation Period: This setting determines on which timeframe candle has to close outside the opening range box in order to take a trade. It's set to 15min by default because this is what worked by far the best
Entry Type: Entries are immediate instead of waiting for a pull back to enter on a limit order.
Limit Orders: If enabled, the strategy will place a pending order x points from the current price, instead of a market order. Immediate orders are enabled by default for a better performance. Important: It doesn't actually place a limit order. The strategy will just wait for a pullback and then enter with a market order. It's more like a hidden limit order.
Limit Order Offset Points: If you have limit orders enabled, this setting determines how many points from the current price the limit order will be placed.
FVG Detection Type: How fast it detects the fair value gaps. Standard detection over immediate had better performance
Risk Type: You can chose either between Fixed USD Amount, Risk per Trade in % or Fixed Contract Size. By default it's set to fixed contract size.
Risk Amount (USD or Contracts): This setting is to set how many USD or how many contracts you want to risk per trade. Make sure to check which risk type you have selected before you choose the risk amount.
Take Profit Multiplier: This is simply the total SL size in points multiplied by x.
Example: If you put 2, you get a 2:1 Risk to Reward Ratio. By Default it's set to 2.5 because this gave the best results in backtests.
Stop Loss Padding: This is simply the buffer in points that is added to the SL for safety reasons. If you have it on 0, the SL will be at the exact price of the opposite side of the range. By default it's set to 5 because this is what delivered the best results in backtests.
Stop Loss Placement: This determines where the stop loss gets placed for the order. It has been set to ORB Range by default as this delivered the best results.
Max Trades Per Hour: This allows the user to decide how many trades are taken an hour. 1 is been set to default for best results
Visual Settings: Check boxes to show orb range, FVG's, Entry points, and trade visualization boxes.
Backtest Settings:
For the backtest the commissions were set to 1.29USD per contract and .35USD for micros which is the highest amount Tradovate charges Margin was not accounted for because typically on prop accounts you can use way more contracts than you need for the extremely low max drawdown. Margin would be important on personal accounts but even there typically it's not an issue at all especially because this strategy runs on the 15min timeframe so it won't use a lot of contracts anyways.
Why the source code is hidden:
The source code is hidden because I invested a lot of time and money into developing this strategy and optimizing it with paid 3rd party software.
Longโonly Swing/ScalpThis is a basic scalper stategy for algos or crypto bots, tested on BNB, not the best backtest but you can tweak and get better results. Take profit at 1% and Sl at 2% , adjust those settings first to see different back test resutls.
TradeMastersAlgoOur strategy is a long only algorithm that has produced repeatable positive results in both back testing and live testing. The code is our proprietary IP. Users may have a 30 free trial to experiment with our strategy.
Results are not guaranteed.
This strategy was created for automated day trading a fully funded margin account. Please exercise caution and discipline when using any strategy. We've had the most positive results with heavy diversification (40 tickers trading 5% equity each).
Ticker selection, timeframe, and chart type ( we use standard candles ) are up to the user.
We encourage you to keep your own method to your self to prevent the dilution of your strategy.
Extremum Range MA Crossover Strategy1. Principle of Work & Strategy Logic โ๏ธ๐
Main idea: The strategy tries to catch the moment of a breakout from a price consolidation range (flat) and the start of a new trend. It combines two key elements:
Moving Average (MA) ๐: Acts as a dynamic support/resistance level and trend filter.
Range Extremes (Range High/Low) ๐บ๐ป: Define the borders of the recent price channel or consolidation.
The strategy does not attempt to catch absolute tops and bottoms. Instead, it enters an already formed move after the breakout, expecting continuation.
Type: Trend-following, momentum-based.
Timeframes: Works on different TFs (H1, H4, D), but best suited for H4 and higher, where breakouts are more meaningful.
2. Justification of Indicators & Settings โ๏ธ
A. Moving Average (MA) ๐
Why used: Core of the strategy. It smooths price fluctuations and helps define the trend. The price (via extremes) must cross the MA โ signals a potential trend shift or strengthening.
Parameters:
maLength = 20: Default length (โ one trading month, 20-21 days). Good balance between sensitivity & smoothing.
Lower TF โ reduce (10โ14).
Higher TF โ increase (50).
maSource: Defines price source (default = Close). Alternatives (HL2, HLC3) โ smoother, less noisy MA.
maType: Default = EMA (Exponential MA).
Why EMA? Faster reaction to recent price changes vs SMA โ useful for breakout strategies.
Other options:
SMA ๐ฆ โ classic, slowest.
WMA ๐จ โ weights recent data stronger.
HMA ๐ฉ โ near-zero lag, but โnervous,โ more false signals.
DEMA/TEMA ๐ง โ even faster & more sensitive than EMA.
VWMA ๐ โ volume-weighted.
ZLEMA โฑ โ reduced lag.
๐ Choice = tradeoff between speed of reaction & false signals.
B. Range Extremes (Previous High/Low) ๐
Why used: Define borders of recent trading range.
prevHigh = local resistance.
prevLow = local support.
Break of these levels on close = trigger.
Parameters:
lookbackPeriod = 5: Searches for highest high / lowest low of last 5 candles. Very recent range.
Higher value (10โ20) โ wider, stronger ranges but rarer signals.
3. Entry & Exit Rules ๐ฏ
Long signals (BUY) ๐ข๐
Condition (longCondition): Previous Low crosses MA from below upwards.
โ Price bounced from the bottom & strong enough to push range border above MA.
Execution: Auto-close short (if any) โ open long.
Short signals (SELL) ๐ด๐
Condition (shortCondition): Previous High crosses MA from above downwards.
โ Price rejected from the top, upper border failed above MA.
Execution: Auto-close long (if any) โ open short.
Exit conditions ๐ช
Exit Long (exitLongCondition): Close below prevLow.
โ Uptrend likely ended, range shifts down.
Exit Short (exitShortCondition): Close above prevHigh.
โ Downtrend likely ended, range shifts up.
โ ๏ธ Important: Exit = only on candle close beyond extremes (not just wick).
4. Trading Settings โ๏ธ
overlay = true โ indicators shown on chart.
initial_capital = 10000 ๐ต.
default_qty_type = strategy.cash, default_qty_value = 100 โ trades fixed $100 per order (not lots). Can switch to % of equity.
commission_type = strategy.commission.percent, commission_value = 0.1 โ default broker fee = 0.1%. Adjust for your broker!
slippage = 3 โ slippage = 3 ticks. Adjust to asset liquidity.
currency = USD.
margin_long = 100, margin_short = 100 โ no leverage (100% margin).
5. Visualization on Chart ๐
The strategy draws 3 lines:
๐ต MA line (thickness 2).
๐ด Previous High (last N candles).
๐ข Previous Low (last N candles).
Also: entry/exit arrows & equity curve shown in backtest.
Disclaimer โ ๏ธ๐
Risk Warning: This description & code are for educational purposes only. Not financial advice. Trading (Forex, Stocks, Crypto) carries high risk and may lead to full capital loss. You trade at your own risk.
Testing: Always backtest & demo test first. Past results โ future profits.
Responsibility: Author of this strategy & description is not responsible for your trading decisions or losses.
BSL/SSL Sweep + FVG Strategy Jobin (c) The New York ATM Model is a structured intraday strategy designed to capture algorithmic stop-hunts and reversals during the New York session open. It focuses on liquidity sweepsโeither Buy-Side or Sell-Sideโfollowed by a confirmation using Fair Value Gaps (FVGs).
My Backtest Module### ๐ Universal Backtest Module - Pro Structure
**A Fully Customizable Strategy Framework for Advanced Backtesting & Signal Analysis**
This powerful Pine Script strategy is designed as a **universal testing module** for traders and developers who want to evaluate custom trading logic across multiple conditions, timeframes, and risk parameters โ all within a single, flexible structure.
> โ ๏ธ **Note:** This script is intended for **educational and backtesting purposes only**. It does **not** provide financial advice, nor does it guarantee profits. Always test strategies thoroughly before applying them to live markets.
---
### ๐ง Key Features
โ
**Multi-Source Entry Signals**
Combine up to two independent buy/sell signals using flexible logic:
- **OR Logic**: Trigger on any signal (edge-based).
- **AND Logic (Latched)**: Requires both signals at any point (flip-flop style).
- **AND No Latch**: Both signals must be active simultaneously.
โ
**Dynamic Trade Direction Control**
Choose between:
- Long & Short (Both)
- Long Only
- Short Only
With optional **close-on-opposite-signal** and **wait-for-opposite-reentry** logic.
โ
**Precision Timing Filters**
- Date range filtering (start/end dates)
- Intraday session control (supports up to 3 custom sessions)
- Visual session shading for clarity
โ
**Advanced Risk Management**
- Multiple Stop Loss types:
- Fixed Points / Percent
- ATR-based (adjustable multiplier)
- Swing-based (automatically detects pivots)
- External SL source
- Dynamic position sizing:
- Fixed lot
- % of equity risk (with max fallback)
โ
**Smart Take Profit Options**
- Fixed Points, Percent, RR Ratio, ATR, Fibonacci extensions
- Support for **external TP levels** (user-defined sources)
- Optional **multiple partial exits** with customizable size distribution
- Fibonacci TP levels (1.0, 1.618, 2.618, 4.236) based on SL distance
โ
**Flexible Exit Tools**
- Breakeven stop activation after TP1 hit
- Internal swing-based trailing stop
- External trailing stop (custom source)
- Max holding time (auto-close after X candles)
- Custom close conditions via user-defined logic
- Close & reverse functionality
โ
**Visual Clarity & Feedback**
- Clear visual markers for Buy/Sell signals
- Real-time SL, Entry, and TP lines with color-coded risk/reward zones
- On-chart TP level labels showing prices and allocation percentages
- Session background highlighting
- Trade statistics summary label
---
### ๐ ๏ธ Ideal For:
- Testing new indicator combinations
- Validating entry/exit logic under various market filters
- Comparing signal fusion methods (OR vs AND)
- Simulating professional-grade risk management rules
- Educational demonstrations in algorithmic trading
---
### โ ๏ธ Important Notes
- This is a **backtesting tool**, not a live trading bot.
- Past performance is **not indicative of future results**.
- Strategy performance depends entirely on the quality of input signals.
- Always validate results across multiple assets and timeframes.
- Use in conjunction with sound money management principles.
---
### ๐ How to Use
1. Attach the script to your chart.
2. Configure **Buy/Sell Signal Sources** (e.g., RSI crossovers, moving averages, etc.)
3. Set your preferred **trade direction, session, and date filters**
4. Define **stop loss and take profit rules**
5. Adjust position sizing and exit behavior
6. Run the backtest and analyze results in the **Strategy Tester tab**
๐ก *Tip: Combine with other indicators by referencing their output values as signal sources.*
---
### โ Disclaimer
This script is shared for **informational and educational purposes only**. By using it, you agree that:
- The author is **not responsible** for any financial losses.
- Trading involves significant risk; only risk capital should be used.
- You are solely responsible for your trading decisions.
๐ซ **This script does not promote get-rich-quick schemes, guaranteed profits, or unverified performance claims.**
---
๐ **Version:** 5 (Pine Script v5)
๐ฆ **Category:** Strategy
๐ **Overlay:** Yes
๐งช **Purpose:** Backtesting, Signal Validation, Risk Modeling
---
โ
**Safe for Public Sharing**
โ Complies with TradingViewโs community standards
โ No misleading performance claims
โ No automated trading promises
โ No copyrighted or plagiarized content
---
> ๐ฌ *"Knowledge is power โ test wisely, trade responsibly."*
---
Let me know if you'd like a **short version** for the script's header comment or a **public post summary** for the TradingView feed!
EMA inFusion Pro - Multiple SourcesEMA Fusion Pro: Dynamic Trend & Momentum Strategy with Three Exit Modes
EMA Fusion Pro is a highly customizable, multi-exit trend-following strategy designed for traders who value both precision and flexibility. By leveraging exponential moving averages (EMA), average directional index (ADX), and volume analysis, this strategy aims to capture trending market moves while offering three distinct exit modes for optimal risk management across varying market conditions.
Strategy Overview
This strategy systematically identifies potential entry points using a moving average crossover with highly configurable data sources (including price, volume, rate of change, or their Heikin Ashi versions) and filters signal quality with ADX trend strength and volume spikes. Each trade is managed with one of three advanced exit methodologiesโreverse signal, ATR-based stop/take profit, or fixed percentageโgiving you the control to adapt your risk profile to different market regimes.
Key Features
Customizable EMA Source: Calculate the core trend-filtering EMA from price (default), volume, rate of change, or their Heikin Ashi counterparts for unique market perspectives.
Trend Filter with ADX: Confirm entries only when the trend is strong, as measured by the user-adjustable ADX threshold.
Volume Spike Confirmation: Optional filter to only take trades with above-average volume activity, reducing false signals.
Three Exit Modes:
Reverse Signal: Exit trades when a new, opposite entry signal occurs.
ATR-Based Stop/Take Profit: Dynamic risk management using multiples of the average true range (ATR) for both take profit and stop loss.
Percent-Based Stop/Take Profit: Fixed-percentage risk management with user-defined thresholds.
Visual Annotations: Signal markers, EMA line color-coded by source, trend background coloring, and optional ATR/percent-based TP/SL levels.
Info Panel: Real-time display of all core indicators, current trading mode, exit parameters, and position status for quick oversight.
How It Works
Entry Logic: A crossover signal (above/below the EMA) triggers a new entry, but only if both ADX trend strength and (optionally) volume spike conditions are met.
Exit Logic: Three selectable modes allow you to exit trades on reverse signals, at a dynamic ATR-based profit or loss, or at a fixed percentage gain/loss.
Flexible Data Analysis: The EMA source can be chosen from six optionsโstandard price, volume, rate of change, or their Heikin Ashi variantsโallowing experimentation with different market dimensions.
Risk Management: All exits are precisely controlled, either by the next opposing signal, by volatility-adjusted levels, or by fixed risk/reward ratios.
Backtest & Optimization: The strategy is fully backtestable within TradingViewโs Strategy Tester, with adjustable parameters for optimization.
Customization & Usage
Indicator Source: Select your preferred data type for EMA calculation, opening the door to creative strategy variations (e.g., volume momentum, pure price trend, rate of change divergence).
Filter Toggles: Enable/disable ADX and volume filters as desiredโuseful for different market environments.
Exit Mode Selection: Switch between reverse, ATR, or percent-based exits with a single parameterโideal for adapting to ranging vs. trending markets.
Visual Clarity: The EMA line color reflects its underlying source, and the info panel summarizes all critical values for easy monitoring.
Who Should Use This Strategy?
Trend Followers seeking to ride strong moves with multiple exit options.
Experienced Traders who want to experiment with different data types (volume, momentum, Heikin Ashi) for trend analysis.
Algorithmic Traders looking for a robust, flexible base to build upon with their own ideas.
Getting Started
Apply the script to your chart and review default settings.
Customize parametersโEMA length, ADX threshold, volume settings, exit typeโas desired.
Backtest on multiple instruments and timeframes to evaluate performance.
Optimize filters, exit rules, and risk parameters for your preferred trading style.
Monitor with the real-time info panel and trade alerts.
Disclaimer
This script is for educational and entertainment purposes only. It is not financial advice. Past performance is not indicative of future results. Always conduct thorough testing and consider your risk tolerance before trading real capital.
โ Happy Trading โ
Feel free to adapt, share, and contribute to this open-source strategy!
BRT T3 for BTC 1h [STRATEGY]## ๐ BRT T3 Adaptive Strategy for BTC 1H
STRATEGY DESCRIPTION
Professional trading strategy based on the adaptive T3 (Tillson T3) indicator with dynamic length controlled by the Relative Strength Index (RSI) . The strategy is specifically designed for Bitcoin trading on the hourly timeframe and includes a comprehensive filter system to minimize false signals.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ฅ UNIQUE CODE FEATURES
1. RSI-Adaptive Architecture:
โข Innovative Approach: Unlike standard MA strategies with fixed periods, our code dynamically adjusts the moving average length based on RSI
โข Smart Formula: len = minLen + (maxLen - minLen) * (1 - RSI/100) - automatically accelerates response in extreme zones
โข Result: Strategy adapts to market conditions without manual reconfiguration
2. Modified Ichimoku Cloud:
โข Unique Calculation: Instead of classic high/low, uses ATR-based method
โข Dynamic Levels: Cloud is built based on volatility, not fixed periods
โข Advantage: More accurate trend determination in highly volatile cryptocurrency markets
3. Hybrid Signal System:
โข Dual-mode Generation: Switch between classic MA crossovers and volatility band breakouts
โข Multi-stage Confirmation: Optional signal verification across N forward bars
โข Effect: 40-60% reduction in false signals compared to simple MA strategies
4. All-in-One Solution:
โข 8 MA Types in One Code: The only strategy on TradingView with complete implementation of T3, EMA, SMA, WMA, VWMA, HMA, RMA, DEMA
โข Custom Functions: All MAs calculated through custom functions supporting series int
โข Versatility: One code replaces 8 different strategies
5. Intelligent Filtering:
Combination of 4 independent filters:
โโโ Volume Filter (dynamic multiplier)
โโโ Trend Filter (adaptive period)
โโโ ATR Filter (volatility)
โโโ Ichimoku Filter (cloud trend)
โข Unique Logic: Each filter can work independently or in combination
โข Master Switch: Single control for all filters
6. Advanced Risk Management:
โข Smart Stops: SL/TP levels are stored in variables and not recalculated on every bar
โข Slippage Protection: Checks both close and high/low for stop triggers
โข Visualization: Dynamic display of levels only for active positions
7. Performance Optimization:
โข Efficient Loops: Minimized calculations through intermediate result storage
โข Conditional Visualization: Element rendering only when necessary
โข Clean Code: Structured organization with clear logical block separation
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ TECHNICAL INNOVATIONS
Adaptation Algorithm (exclusive development):
// Dynamic length based on RSI
rsi_scale = 1.0 - rsi / 100.0
len_adaptive = minLen + (maxLen - minLen) * rsi_scale
ATR-based Ichimoku (unique modification):
// Instead of classic (highest + lowest) / 2
// Using ATR for dynamic levels
upper := close < upper ? min(hl2 + atr*mult, upper ) : hl2 + atr*mult
lower := close > lower ? max(hl2 - atr*mult, lower ) : hl2 - atr*mult
Multi-MA Architecture (complete implementation):
โข Each MA type has its own optimized function
โข Support for series int for dynamic length
โข Unified selection interface via switch statement
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ฏ KEY FEATURES
โข Adaptive System: Moving average length automatically adjusts based on RSI, providing quick response in trending movements and stability in sideways markets
โข 8 Moving Average Types: T3, EMA, SMA, WMA, VWMA, HMA, RMA, DEMA - ability to choose the optimal type for different market conditions
โข Multi-level Filtering:
- Volume Filter - signal confirmation with increased activity
- Trend Filter - trading in the direction of the main trend
- ATR Filter - accounting for market volatility
- Ichimoku Cloud - additional trend direction confirmation
โข Professional Risk Management: Customizable stop-loss and take-profit levels
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ๏ธ HOW IT WORKS
1. Signal Generation:
โข Original Mode: Classic MA crossover signals with lagged version
โข Band Break Mode: Volatility band breakouts (based on standard deviation)
2. RSI Adaptation:
โข High RSI (overbought) โ uses short MA length for quick response
โข Low RSI (oversold) โ uses long MA for noise smoothing
โข Adaptation range is configured by Min/Max length parameters
3. Filter System:
โข Each filter can be enabled/disabled independently
โข Signal is generated only when passing all active filters
โข Ichimoku filter blocks counter-trend trades
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ STRATEGY PARAMETERS
Main Settings:
โข Strategy Type: Long Only / Short Only / Both
โข Data Source: Close, Open, High, Low, HL2, HLC3, OHLC4
RSI Settings:
โข RSI Length: Calculation period (default 14)
โข RSI Smoothing: Smoothing to reduce noise
T3/MA Settings:
โข Min/Max Length: Adaptive length range (5-50)
โข Volume Factor: T3 smoothing coefficient (0.7)
โข MA Type: Moving average type selection
Filters:
โข Volume Filter: Volume multiplier (1.5x average)
โข Trend Filter: Trend MA period (200)
โข ATR Filter: Minimum volatility for entry
โข Ichimoku Filter: Cloud for trend determination
Risk Management:
โข Stop Loss: Percentage from entry price (1.2%)
โข Take Profit: Percentage from entry price (5.9%)
โข Position Size: 50,000 USDT (effective leverage 5x)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ก USAGE RECOMMENDATIONS
Optimal Conditions:
โข Timeframe: 1H (developed and optimized)
โข Instrument: BTC/USDT and other liquid cryptocurrencies
โข Market Conditions: Trending and moderately volatile markets
Customize to Your Style:
1. Conservative: Increase signal confirmation period, enable all filters
2. Aggressive: Reduce filters, use Band Break mode
3. Scalping: Decrease Min/Max length, disable trend filter
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ VISUALIZATION
Strategy displays:
โข Main MA Line - changes color depending on direction
โข Lag Line - for visualizing crossover moment
โข Volatility Bands - upper and lower boundaries
โข Trend MA - orange line (200 periods)
โข SL/TP Levels - red and green lines for open positions
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ ALERTS
Strategy supports alert configuration for:
โข Long position entry signals
โข Short position entry signals
โข Position exit signals
โข Ichimoku line crossings
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ ๏ธ RISK WARNING
IMPORTANT NOTICE: Trading in financial markets involves substantial risk of capital loss. Past performance presented in this strategy is based solely on historical data and under no circumstances constitutes a guarantee of future returns.
The strategy author is not responsible for:
โข Any direct or indirect financial losses resulting from the use of this strategy
โข Trading decisions made based on strategy signals
โข Interpretation of backtesting results as a forecast of future performance
This strategy is provided exclusively for educational and research purposes. Backtesting results are affected by numerous factors including but not limited to: slippage, spread, commissions, market liquidity, and technical failures.
Before using the strategy in live trading:
โข Conduct your own testing on a demo account
โข Ensure understanding of all parameters and logic
โข Only use funds you can afford to lose
โข Consider consulting with a qualified financial advisor
DISCLAIMER: By using this strategy, you acknowledge and accept all risks associated with financial market trading and confirm that the author does not provide investment advice and bears no fiduciary responsibility to users.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ TECHNICAL SUPPORT
For questions about setup and optimization:
โข Leave comments under the publication
โข Follow strategy updates
โข Study the code for deep understanding of logic
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ VERSION AND UPDATES
Version: 1.0.0
Pine Script: v6
Last Updated: 2025
Changelog:
โข Added support for 8 MA types
โข Integrated Ichimoku Cloud filter
โข Optimized risk management system
โข Improved signal visualization
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ยฉ 2025 BRT Trading Systems
Strategy is protected by copyright. Commercial use without author's permission is prohibited.






















