Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe
This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice.
0. Publication mode and rationale
This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible.
Why Protected
The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users.
Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results.
1. What the strategy does in one paragraph
Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity.
Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor.
Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal.
2. Why it is original and useful
It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance.
The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise.
Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants.
Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates.
The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about.
3. Plain language overview of the math
Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural.
Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases.
Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one.
Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow.
Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band.
4. Entries, exits, and position sizing
Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs.
Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate.
Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active.
Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn.
Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts.
5. Inputs quick guide with recommended ranges
Every input has a tooltip in the script. The same guidance appears here for fast reading.
Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing.
Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55.
Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more.
Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence.
Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical.
Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets.
Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts.
Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more.
Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes.
AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes.
Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70.
Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20.
Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2.
Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts.
Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior.
Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits.
Background heat opacity . Cosmetic. Set to taste. Zero disables it.
6. Properties used on the published chart
The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results.
Initial capital 100000
Base currency USD
Order size 2 percent of equity coming from our risk management inputs.
Pyramiding 0
Commission 0.05 percent
Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research.
Recalculate after order is filled off. On every tick off.
Using bar magnifier on. On bar close on.
Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1.
7. Visual elements and alerts
The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan.
8. How to reproduce the example
Open a BTCUSD daily chart with regular candles.
Add the strategy and load the defaults that match the values above.
Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on.
Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown.
9. Practical tuning recipes
Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions.
Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar.
Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday.
Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions.
Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it.
10. Strengths and limitations
Strengths
Self scaling unit through AAR makes the tool portable across markets and timeframes.
Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align.
Adaptive centering reduces structural bias at the score level which helps during regime flips.
Limitations
In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable.
Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate.
Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research.
The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases.
11. Realism and responsible publication
No promises or projections of performance are made. Past results never guarantee future outcomes.
Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange.
Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model.
Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size.
Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders.
12. Suggested research workflow
Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history.
Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value.
Try one higher timeframe blend with a modest weight. Large weights can drown the signal.
Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop.
Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy.
Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods.
13. How to read the HUD and heat map
The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty.
14. Frequently asked questions
Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch.
Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly.
Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off.
Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown.
Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing.
Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context.
15. Concepts glossary
AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops.
Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity.
Geometric mean growth . Rate that preserves the effect of compounding over many bars.
Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound.
Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale.
Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew.
16. Educational notice and risk statement
Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results.
17. Final notes for readers and moderators
The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments.
Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence.
Thank you for your time to read all of this
Indicatori e strategie
Turtle Strategy - Triple EMA Trend with ADX and ATRDescription
The Triple EMA Trend strategy is a directional momentum system built on the alignment of three exponential moving averages and a strong ADX confirmation filter. It is designed to capture established trends while maintaining disciplined risk management through ATR-based stops and targets.
Core Logic
The system activates only under high-trend conditions, defined by the Average Directional Index (ADX) exceeding a configurable threshold (default: 43).
A bullish setup occurs when the short-term EMA is above the mid-term EMA, which in turn is above the long-term EMA, and price trades above the fastest EMA.
A bearish setup is the mirror condition.
Execution Rules
Entry:
• Long when ADX confirms trend strength and EMA alignment is bullish.
• Short when ADX confirms trend strength and EMA alignment is bearish.
Exit:
• Stop Loss: 1.8 × ATR below (for longs) or above (for shorts) the entry price.
• Take Profit: 3.3 × ATR in the direction of the trade.
Both parameters are configurable.
Additional Features
• Start/end date inputs for controlled backtesting.
• Selective activation of long or short trades.
• Built-in commission and position sizing (percent of equity).
• Full visual representation of EMAs, ADX, stop-loss, and target levels.
This strategy emphasizes clean trend participation, strict entry qualification, and consistent reward-to-risk structure. Ideal for swing or medium-term testing across trending assets.
Fury by Tetrad Fury by Tetrad
What it is:
A rules-based Bollinger+RSI strategy that fades extremes: it looks for price stretching beyond Bollinger Bands while RSI confirms exhaustion, enters countertrend, then exits at predefined profit multipliers or optional stoploss. “Ultra Glow” visuals are purely cosmetic.
How it works — logic at a glance
Framework: Classic Bollinger Bands (SMA basis; configurable length & multiplier) + RSI (configurable length).
Long entries:
Price closes below the lower band and RSI < Long RSI threshold (default 28.3) → open LONG (subject to your “Market Direction” setting).
Short entries:
Price closes above the upper band and RSI > Short RSI threshold (default 88.4) → open SHORT.
Profit exits (price targets):
Uses simple multipliers of the strategy’s average entry price:
Long exit = `entry × Long Exit Multiplier` (default 1.14).
Short exit = `entry × Short Exit Multiplier` (default 0.915).
Risk controls:
Optional pricebased stoploss (disabled by default) via:
Long stop = `entry × Long Stop Factor` (default 0.73).
Short stop = `entry × Short Stop Factor` (default 1.05).
Directional filter:
“Market Direction” input lets you constrain entries to Market Neutral, Long Only, or Short Only.
Visuals:
“Ultra Glow” draws thin layered bands around upper/basis/lower; these do not affect signals.
> Note: Inputs exist for a timebased stop tracker in code, but this version exits via targets and (optional) price stop only.
Why it’s different / original
Explicit extreme + momentum pairing: Entries require simultaneous band breach and RSI exhaustion, aiming to avoid entries on gardenvariety volatility pokes.
Deterministic exits: Multiplier-based targets keep results auditable and reproducible across datasets and assets.
Minimal, unobtrusive visuals: Thin, layered glow preserves chart readability while communicating regime around the Bollinger structure.
Inputs you can tune
Bollinger: Length (default 205), Multiplier (default 2.2).
RSI: Length (default 23), Long/Short thresholds (28.3 / 88.4).
Targets: Long Exit Mult (1.14), Short Exit Mult (0.915).
Stops (optional): Enable/disable; Long/Short Stop Factors (0.73 / 1.05).
Market Direction: Market Neutral / Long Only / Short Only.
Visuals: Ultra Glow on/off, light bar tint, trade labels on/off.
How to use it
1. Timeframe & assets: Works on any symbol/timeframe; start with liquid majors and 60m–1D to establish baseline behavior, then adapt.
2. Calibrate thresholds:
Narrow/meanreverting markets often tolerate tighter RSI thresholds.
Fast/volatile markets may need wider RSI thresholds and stronger stop factors.
3. Pick realistic targets: The default multipliers are illustrative; tune them to reflect typical mean reversion distance for your instrument/timeframe (e.g., ATRinformed profiling).
4. Risk: If enabling stops, size positions so risk per trade ≤ 1–2% of equity (max 5–10% is a commonly cited upper bound).
5. Mode: Use Long Only or Short Only when your discretionary bias or higher timeframe model favors one side; otherwise Market Neutral.
Recommended publication properties (for backtests that don’t mislead)
When you publish, set your strategy’s Properties to realistic values and keep them consistent with this description:
Initial capital: 10,000 (typical retail baseline).
Commission: ≥ 0.05% (adjust for your venue).
Slippage: ≥ 2–3 ticks (or a conservative pertrade value).
Position sizing: Avoid risking > 5–10% equity per trade; fixedfractional sizing ≤ 10% or fixedcash sizing is recommended.
Dataset / sample size: Prefer symbols/timeframes yielding 100+ trades over the tested period for statistical relevance. If you deviate, say why.
> If you choose different defaults (e.g., capital, commission, slippage, sizing), explain and justify them here, and use the same settings in your publication.
Interpreting results & limitations
This is a countertrend approach; it can struggle in strong trends where band breaches compound.
Parameter sensitivity is real: thresholds and multipliers materially change trade frequency and expectancy.
No predictive claims: Past performance is not indicative of future results. The future is unknowable; treat outputs as decision support, not guarantees.
Suggested validation workflow
Try different assets. (TSLA, AAPL, BTC, SOL, XRP)
Run a walkforward across multiple years and market regimes.
Test several timeframes and multiple instruments. (30m Suggested)
Compare different commission/slippage assumptions.
Inspect distribution of returns, max drawdown, win/loss expectancy, and exposure.
Confirm behavior during trend vs. range segments.
Alerts & automation
This release focuses on chart execution and visualization. If you plan to automate, create alerts at your entry/exit conditions and ensure your broker/venue fills reflect your slippage/fees assumptions.
Disclaimer
This script is provided for educational and research purposes. It is not investment advice. Trading involves risk, including the possible loss of principal. © Tetrad Protocol.
Solana 4H RSI->MACD — Counter-Trend By TetradTetrad RSI→RSI Cross→MACD (Sequenced) — Counter-Trend (SL-Only)
Category: Market-neutral, counter-trend, sequenced entries
Timeframe default: Works on any TF; designed around 4H On Solana
Markets: Any (spot, perp, futures); parameterize to your asset
What it does
This strategy hunts reversals using a 3-step sequence on RSI and MACD, then optionally restricts entries by market regime and a price gate. It shows stop-loss lines only when hit (clean chart), and paints a Donchian glow for quick read of backdrop conditions.
Entry logic (sequenced)
1. RSI Extreme:
Long path activates when RSI < Oversold (default 27.5).
Short path activates when RSI > Overbought (default 74).
2. RSI Cross confirmation:
Long path: RSI crosses up back above the oversold level.
Short path: RSI crosses down back below the overbought level.
Each step has a max bar lookback so stale signals time out.
3. MACD Cross trigger:
Long: MACD line crosses above Signal.
Short: MACD line crosses below Signal.
→ When step 3 fires and gates are satisfied, a trade is entered.
Optional gates & filters
Regime Filter (Counter-Trend):
Longs allowed in **Range / Short Trend / Short Parabolic** regimes.
Shorts allowed in **Range / Long Trend / Long Parabolic** regimes.
Based on ADX/DI and ATR% intensity.
* Price Gate (Long Ceiling):
Toggle to **disable new longs above a chosen price (default 209.0 For SOL).
Useful for assets like SOL where you want longs only below a cap.
Exits / Risk
* Stop-Loss (% of entry):** default **14%**, toggleable.
* SL visualization:** plots a **thin dashed red line only on the bar it’s hit**.
* (No take-profit or time-based exit in this version—keep it pure to the sequence and regime. Add TP/time exits if desired.)
Visuals
* Donchian Glow (50): background band only (upper/lower lines hidden).
* Regime HUD: compact table (top-right) highlighting the active regime.
* Minimal marks: no entry/exit “arms” clutter; only SL-hit lines render.
Inputs (key)
* Core: RSI Length, Oversold/Overbought, MACD Fast/Slow/Signal.
* Sequence: Max bars from Extreme→RSI Cross and RSI Cross→MACD Cross.
* Regime: ADX Length, Trend/Parabolic thresholds, ATR length & floor.
* Stops: Enable/disable; SL %.
* Price Gate: Enable; Long ceiling price.
Alerts
Sequenced Long (CT): RSIhigh → RSI cross down → MACD bear cross.
## Notes & Tips
Designed for counter-trend fades that become trend rides. The regime filter helps avoid fading true parabolics and aligns entries with safer contexts.
The sequence is stateful (steps must occur in order). If a step times out, the path resets.
Works on lower TFs, but the 4H baseline reduces noise and over-trading.
Consider pairing with volume or structure filters if you want fewer but higher-conviction entries.
Past performance ≠ future results. **Educational use only. Not financial advice.
Pump-Smart Shorting StrategyThis strategy is built to keep your portfolio hedged as much as possible while maximizing profitability. Shorts are opened after pumps cool off and on new highs (when safe), and closed quickly during strong upward moves or if stop loss/profit targets are hit. It uses visual overlays to clearly show when hedging is on, off, or blocked due to momentum, ensuring you’re protected in most market conditions but never short against the pump. Fast re-entry keeps the hedge active with minimal downtime.
Pump Detection:
RSI (Relative Strength Index): Calculated over a custom period (default 14 bars). If RSI rises above a threshold (default 70), the strategy considers the market to be in a pump (strong upward momentum).
Volume Spike: The current volume is compared to a 20-bar simple moving average of volume. If it exceeds the average by 1.5× and price increases at least 5% in one bar, pump conditions are triggered.
Price Jump: Measured by (close - close ) / close . A single-bar change > 5% helps confirm rapid momentum.
Pump Zone (No Short): If any of these conditions is true, an orange or red background is shown and shorts are blocked.
Cooldown and Re-Entry:
Cooldown Detection: After the pump ends, RSI must fall below a set value (default ≤ 60), and either volume returns towards average or price momentum is less than half the original spike (oneBarUp <= pctUp/2).
barsWait Parameter: You can specify a waiting period after cooldown before a short is allowed.
Short Entry After Pump/Cooldown: When these cooldown conditions are met, and no short is active, a blue background is shown and a short position is opened at the next signal.
New High Entry:
Lookback New High: If the current high is greater than the highest high in the last N bars (default 20), and pump is NOT active, a short can be opened.
Take Profit (TP) & Stop Loss (SL):
Take Profit: Short is closed if price falls to a threshold below the entry (minProfitPerc, default 2%).
Stop Loss: Short is closed if price rises to a threshold above the entry (stopLossPerc, default 6%).
Preemptive Exit:
Any time a pump is detected while a short position is open, the strategy closes the short immediately to avoid losses.
Visual Feedback:
Orange Background: Market is pumping, do not short.
Red Background: Other conditions block shorts (cooldown or waiting).
Blue Background: Shorts allowed.
Triangles/Circles: Mark entries, pump start/end, for clear trading signals.
Seykota EMA Crossover with ATR Risk Sizing 📈 A Tribute to Ed Seykota’s Timeless Trend-Following and Risk Discipline
Overview
This strategy is inspired by the trading principles of Ed Seykota, one of the most influential trend followers in modern market history.
It combines a classic exponential moving average (EMA) crossover system with ATR-based risk sizing and optional trailing stops, closely modeled on the ideas and system examples Seykota published on his website.
The strategy enters long positions when a short-term EMA crosses above a longer-term EMA (confirming an uptrend), and exits either on a bearish crossover or when price closes below an ATR-based trailing stop.
⚙️ Core Components
1. EMA Trend System
Buy Signal: Fast EMA crosses above Slow EMA → establishes trend direction
Sell Signal: Fast EMA crosses below Slow EMA → trend reverses
Typical defaults:
Fast EMA = 20
Slow EMA = 200
This aligns with Seykota’s timeless philosophy:
“Follow the trend. Ride winners. Cut losses.”
2. ATR Risk Sizing (The 1% Rule)
When the “Enable ATR Position Sizing” box is checked, the system applies Seykota’s version of risk-based position sizing:
Each trade risks a fixed percent of account equity (default = 1%).
Risk per trade = (Account Equity × Risk %) ÷ (ATR × Multiplier).
Stop distance = ATR × Multiplier (default = 5×).
ATR defines volatility — higher volatility leads to smaller positions — keeping risk consistent across changing market conditions.
When the checkbox is off, the strategy uses your default TradingView position sizing (for example, 100% of equity per trade).
3. ATR Trailing Stop (Optional – Not Seykota’s Original Method)
This feature is available in this script, but it is not the exact exit logic Seykota used in his original trading systems.
Seykota’s trend-following systems typically exited trades based on support/resistance breaks or moving average reversals, not a continuously updating volatility-based stop.
He managed trades using trend structure and long-term signals, rather than a mechanical trailing formula.
However, the ATR trailing stop is included here as a modern optional enhancement for users who prefer smoother, automatic exits.
When enabled, the stop automatically trails the price according to:
Stop = Close – (ATR × Multiplier)
As price rises, the stop ratchets upward — locking in gains while giving the trade enough room to breathe.
This reflects Seykota’s broader risk principle:
“The elements of good trading are: (1) cutting losses, (2) cutting losses, and (3) cutting losses.”
While practical and popular today, this ATR-based trailing stop was not part of Seykota’s original mechanical systems.
If you prefer to stay closer to his authentic approach, you can simply disable this option and rely on EMA crossovers (or a longer-term filter) for exits.
4. About Dynamic Risk Scaling
Seykota practiced what he called dynamic risk control or “heat management” — adjusting exposure based on portfolio equity and drawdown:
New equity highs → full risk (e.g., 1%)
10% drawdown → reduce exposure (e.g., 0.9%)
25% drawdown → reduce further (e.g., 0.75%)
Never below a “heat floor” (e.g., 0.25%)
However, TradingView cannot dynamically resize open positions based on drawdown. This feature does not affect open trades or past results.
Therefore, this script focuses on ATR-based risk sizing only.
Dynamic risk scaling should be calculated externally, before placing trades.
I’ll soon publish a simple calculator (Google Sheets or web tool) that automatically computes the adjusted risk percentage and position size based on your account equity and drawdown level — so you can apply Seykota’s true “heat control” method in your portfolio tracking.
🧭 How to Use This Strategy
Apply to any trending instrument (e.g., QQQ, SPY, CL1!, GC1!, BTCUSD).
Set your preferred parameters:
Fast EMA = 20
Slow EMA = 200
ATR Period = 20
ATR Multiplier = 5
Check “Enable ATR Position Sizing” to use the 1% risk rule.
Optionally enable “Use ATR Trailing Stop Exit” for automatic volatility-based exits.
Run the backtest and fine-tune parameters for your instrument and timeframe.
🏁 Philosophy
This strategy captures the essence of Seykota’s trading wisdom:
“The trend is your friend — until the end, when it bends.”
It’s not about prediction — it’s about process, discipline, and letting winners run while controlling risk.
ATR sizing and optional trailing stops simply automate the timeless rules that made Seykota a legend.
ATR + VIX Breakout StrategyChange the symbol to UVXY. Work great for option l long and S short. Take profits before it closes the trade. Pls remember you are using it at your own risk.
DK Fractals (Strategy)Convert to strategy. Introduce the first 2 trading models (Still heavily in development) The reversal and continuation models. More to come.
If you still want to use as an indicator, just disable the two trading models.
Moon Phases Long/Short StrategyThis is an experiment of Moon Phases, likely buy when full moon and sell when new moon with few changes, like it would buy a day ahead or sometimes sell a day post these events, with Stop loss and take profits, 50% profitable so sounds good to me
Long only good for bitcoin gold, both modes(L+S) better for stocks and alt coins
SPY200SMA (+4%/-3%) TQQQ/QQQ STRATEGYSummary of the Improved Strategy: When the price of AMEX:SPY is +4% above the 200SMA BUY NASDAQ:TQQQ and when the price of SPY drops to -3% under the SPY 200SMA SELL everything and slowly DCA into NASDAQ:QQQ over the next 6-12 months or until price returns to +4% above the SPY 200SMA at which point you will go back into 100% TQQQ.
Note: (if the price of QQQ goes 30% above the 200SMA of QQQ deleverage to QQQ or Sell to protect yourself from dot com level event)
More info and stats -https://www.reddit.com/r/LETFs/comments/1nhye66/spy_200sma_43_tqqqqqq_long_term_investment/
超趨勢策略 (中文)-Caelusif ta.change(direction) < 0
strategy.entry("My Long Entry Id", strategy.long)
if ta.change(direction) > 0
strategy.entry("My Short Entry Id", strategy.short)
Gaussian MACD RSI v2Gaussian Filter MACD Strategy (Zero Cross + RSI Gate)
What it does
This strategy evaluates momentum using a Gaussian-smoothed MACD and requires a MACD zero-line cross to confirm trend initiation. A configurable RSI threshold filters weak signals, aiming to reduce whipsaws around the zero line. Entries occur only when momentum and baseline strength agree; exits are triggered by MACD crossing below its signal to capture the meat of the move while avoiding discretionary overrides.
How it works (concepts, not code)
Gaussian MACD: The fast/slow components are smoothed with a Gaussian-style filter to reduce noise relative to standard EMA MACD.
Zero-line confirmation: Longs require MACD to cross above zero, aligning entries with positive momentum regimes.
RSI gate: A threshold (default 50) further filters entries so that only setups with baseline strength qualify.
Exit logic: Positions close when MACD crosses below its signal line, providing an objective exit without trailing logic.
Sources: The script supports standard and Heikin-Ashi-derived sources for traders who prefer alternate preprocessing.
How to use it
Add the strategy to a clean chart.
Keep default settings for initial testing; then adjust the RSI threshold and symbol/timeframe for your market.
Favor liquid instruments where slippage and fills are reliable.
Forward-test and walk-forward before any live use.
Default Properties (used for this publication)
Initial Capital: $25,000
Order Size: 100% of equity per trade (no leverage).
Commission: 0.02% per side.
Slippage: 2 ticks (or 0.02% on percent-based markets).
Timeframe used for the published chart: 15-minute (example)
Dataset: SPY/QQQ/large-cap equities (2+ years) producing 100+ trades in sample.
Note: This strategy does not use hard stops by default. If you prefer risk caps ≤ 5–10% per trade, add a stop in the Inputs and re-publish; otherwise, this description explains the deviation per House Rules.
Disclosures
Backtest results are estimates; real-world fills, slippage, and availability may differ. No guarantee of performance. Use prudent position sizing and independent verification.
PropvaultSignals Clean Combined Labels Best Tested 91%PropvaultSignals Clean Single Label with best session
Ekoparaloji Cyrpto StrategyEkoparaloji Crypto Strategy - User Information Document
📊 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.
🎯 Key Features
✅ 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
📈 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
💰 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
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ 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
📱 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
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 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
⚠️ 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!
⚠️ 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
🎓 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! 📊
MAUL RSI Gaussian Filter MACD Gaussian Filter MACD — Strategy (with RSI Gate)
A momentum-first, chop-aware strategy built on a Gaussian-smoothed MACD with an optional RSI threshold filter. It looks for clean transitions in trend and ignores half-hearted wiggles around the zero line. You choose how signals are confirmed and whether shorts are allowed—no clutter, just deliberate entries and exits.
What it does (at a glance)
Confirms momentum using a smoothed MACD and a selectable signal mode.
Optional RSI gate to avoid low-quality breakouts.
Flexible source options (incl. Heikin-Ashi families) to match your charting style.
Long-only by default; shorts are an option.
Built-in alerts for entries/exits.
How to use
Add to chart and select your preferred signal mode.
Toggle the RSI gate and set your threshold to filter weak setups.
Forward-test across symbols/timeframes; then walk it into live with conservative sizing.
Notes
The parameters and internals are intentionally locked to protect IP and avoid over-fitting by casual copycats.
Works best on liquid symbols with consistent session structure.
Risk
Backtests are not a promise. Markets are noisy, slippage is real, and capital at risk should be sized accordingly. Use with sound risk management and a clear exit plan.
Ekoparaloji Strategy Crypto Ekoparaloji Crypto Strategy - User Information Document
📊 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.
🎯 Key Features
✅ 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
📈 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
💰 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
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ 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
📱 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
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 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
⚠️ 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!
⚠️ 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
🎓 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.
DCA Test Daily / Weekly / Monthly1.Input daily, weekly or monthly preferance of DCA
2.Select how much to DCA
3.Use the slider on the indicator down to select from where to DCA
Important: Don't use a higher timeframe chart than the desired DCA frequency, or all the DCA buys won't get executed.
(5m) EMA Cross + RSI + Stoch + ATR Strategy Psammodromus1979Indicators
EMA4
EMA9
EMA20
EMA50
RSI
STOCHASTIC
ATR
With buy/sell indicators directly on main chart
It worked for me when waited for retracement on EMA50
Didn't work when on accumulation.
Confluence Dashboard + Strategy [Daily + Weekly Adaptive]Removed duplicate strategy() declarations
Scoped getWeeklyBias() safely with correct request.security() usage
Ensured all variables are declared before use
Aligned background shading with bias logic
Streamlined signal tier logic to avoid overlap
Integrated strategy entries/exits cleanly
4hr / BTCBTCUSDT.P / 4hr
趨勢線交易策略
設定可以如我圖表
也可以自己找合適的
測試請用最大虧損的三倍金額下去打
圖以含手續費(0.06%)
可以用小金額去打
最大淨利與最大虧損績效比 1:10
平均獲利/虧損盈虧比 2.135
長期放保證獲利
沒獲利或獲利較小的那年通常是大事件
如2022
有問題私訊 謝謝
BTCUSDT.P / 4hr
Trendline Trading Strategy
You can set it up the same way as shown on my chart,
or find your own suitable setup.
For testing, please use three times the maximum loss as your trading capital.
The chart should include fees (0.06%).
You can trade with a small amount.
Performance:
Maximum profit to maximum loss ratio: 1:10
Average profit/loss ratio: 2.135
Guaranteed profit in the long term
Years with no profit or smaller profit are usually caused by major events,
such as 2022.
If you have any questions, please DM me. Thank you.
MACD Master Strategy Suite🧩 Overview
The MACD Master Strategy Suite is not a basic MACD crossover system, but a complete backtesting tool designed for traders who want to explore and optimize MACD-based logic.
This suite offers a host of configurable options that transform the standard MACD into a powerful research framework. You can test multiple entry styles, apply trend filters, run contrarian setups, and study seasonality — all from one script.
⚙️ Key Features
Multiple MACD entry modes: classic cross, zero-line flip, pullback, momentum burst, divergence, and more.
Dual-EMA trend filter with optional Contrarian Mode.
Higher-timeframe trend confirmation.
Calendar filters for weekday, month, and day-of-month testing.
Realistic trade management: stop/target exits, cooldowns, and same-bar recalculation guard.
Adjustable position sizing and leverage for accurate SPY-style backtests.
🧠 How It Differs From TradingView’s Built-In MACD Strategy
The built-in MACD strategy uses only histogram zero-cross entries with no filters or risk controls.
The MACD Master Strategy Suite expands this into a fully modular testing environment, allowing you to analyze how different MACD behaviors perform under diverse market conditions — turning MACD from a simple signal into a measurable system.
⚖️ Disclaimer
For research and educational use only. This script does not constitute financial advice or guarantee performance.
ALMASTO – Pro Trend & Momentum (v1.1)ALMASTO — Pro Trend & Momentum Strategy
Description:
This strategy is designed for precision trading in both Forex (FX) and Crypto markets.
It combines multi-timeframe trend confirmation (EMA200), momentum filters (RSI, MACD, ADX), and ATR-based dynamic risk management.
ALMASTO — Pro Trend & Momentum Strategy automatically manages take-profit levels, stop-loss, and breakeven adjustments once TP1 is reached — providing a structured and emotion-free trading approach.
Optimal Use
Works best on lower timeframes (5m–15m) with strong liquidity sessions.
Optimized for pairs like EURUSD, XAUUSD, and BTCUSDT.
Built for trend-following setups and momentum reversals with high volatility confirmation.
Recommended Settings
🔹 Forex – 5m
EMA Fast = 34, EMA Slow = 200, HTF = 1H
RSI (14): Long ≥ 55 / Short ≤ 45
MACD (8 / 21 / 5), ADX Len 10 / Min 27
ATR Len 7, Stop Loss = ATR × 2.1
TP1 = 1.1 RR, TP2 = 2.3 RR
Session = 07:00–11:00 & 12:30–16:00 (Exchange Time)
Risk = 0.8% per trade
🔹 Forex – 15m
EMA Fast = 50, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 53 / Short ≤ 47
MACD (12 / 26 / 9), ADX Min 24
ATR Len 10, SL = ATR × 1.9
TP1 = 1.2 RR, TP2 = 2.6 RR
Risk = 1.0% per trade
🔹 Crypto – 5m (BTC/USDT)
EMA Fast = 34, EMA Slow = 200, HTF = 4H
RSI (14): Long ≥ 56 / Short ≤ 44
MACD (8 / 21 / 5), ADX Min 30
ATR Len 7, SL = ATR × 2.2
TP1 = 1.0 RR, TP2 = 2.5 RR
Session = 00:00–06:00 & 12:00–22:00 (UTC)
Risk = 0.5% per trade
Core Features
✅ Auto breakeven after TP1
✅ Dual take-profit system (1:1 & 1:2 RR)
✅ ATR-based stop & trailing logic
✅ Filters for session time, volume, and volatility
✅ Candle-body vs ATR size filter to avoid noise
✅ Optional cooldown between trades
Important Notes
Use bar close confirmation only (barstate.isconfirmed) to avoid repainting on lower timeframes.
Adjust commission (0.01–0.03%) and slippage (1–2 ticks) in Strategy Tester for realistic results.
Avoid low-liquidity hours (after 21:00 UTC for FX / after midnight for crypto).
Backtest using realistic broker data (e.g., BlackBull Markets / Bybit / Binance Futures).
Best results occur during London & New York sessions with moderate volatility.
⚠️ Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice.
Use proper risk management and test thoroughly before using on live accounts.
Developed by KING FX Labs
Built and optimized by Yousef Almasto — combining advanced price-action logic, multi-timeframe EMA structure, and volatility-adaptive ATR management.
Tested across Forex, Gold, and Crypto markets to ensure consistent performance and minimal drawdown.
📈 “Precision Trading. Zero Emotion. Pure Momentum.”
