Multi-Indicator Strategy By Arvind Dodke [EMA+MACD+RSI+ADX]This strategy is base on EMA+MACD+RSI+ADX.
You can backtest it.
Analisi trend
Range Breakout Strategy (AM/PM)Range breakout for back-testing on any asset pair for a give time range, for mechanical trading.
Trend-Following Strategy with Keltner ChannelsTrend Filter ( All Timeframes):
Price must be above the 200 EMA for a bullish setup
Price must be below the 200 EMA for a bearish setup
Keltner Channels for dynamic support/resistance
Buy when price pulls back to the midline or lower channel in an uptrend
Sell when price pulls back to the midline or upper channel in a downtrend
Entry trigger: Price pulls back to Keltner midline then crosses it
Exits: ATR-based SL & TP with optional trailing stops
YASINKARACAThe short-, medium-, and long-term indicator I have created is actually composed of moving averages, trend-following tools, Bollinger Bands, and various other indicators. You can use this indicator on any time frame.
If the turquoise moving average crosses above the orange moving average, it should be interpreted as a buy signal; if it crosses below, it should be interpreted as a sell signal.
Additionally, the white trend-following line indicates safety when the price is above it and risk when the price is below it.
The upper and lower lines of the Bollinger Bands are presented in gray. When the price approaches the lower Bollinger Band, it can be interpreted as a buying opportunity; when it reaches the upper band, it can be seen as a selling opportunity.
If the price is above the orange-colored slow moving average, the trend should be considered upward; if it is below, the trend is downward.
Wishing you success and a great day.
Yasin Karaca
EMA Crossover Strategy with Trailing Stop and AlertsPowerful EMA Crossover Strategy with Dynamic Trailing Stop and Real-Time Alerts
This strategy combines the simplicity and effectiveness of EMA crossovers with a dynamic trailing stop-loss mechanism for robust risk management.
**Key Features:**
* **EMA Crossover Signals:** Identifies potential trend changes using customizable short and long period Exponential Moving Averages.
* **Trailing Stop-Loss:** Automatically adjusts the stop-loss level as the price moves favorably, helping to protect profits and limit downside risk. The trailing stop percentage is fully adjustable.
* **Visual Buy/Sell Signals:** Clear buy (green upward label) and sell (red downward label) signals are plotted directly on the price chart.
* **Customizable Inputs:** Easily adjust the lengths of the short and long EMAs, as well as the trailing stop percentage, to optimize the strategy for different assets and timeframes.
* **Real-Time Alerts:** Receive instant alerts for buy and sell signals, ensuring you don't miss potential trading opportunities.
**How to Use:**
1. Add the strategy to your TradingView chart.
2. Customize the "Short EMA Length," "Long EMA Length," and "Trailing Stop Percentage" in the strategy's settings.
3. Enable alerts in TradingView to receive notifications when buy or sell signals are generated.
This strategy is intended to provide automated trading signals based on EMA crossovers with built-in risk management. Remember to backtest thoroughly on your chosen instruments and timeframes before using it for live trading.
#EMA
#Crossover
#TrailingStop
#Strategy
#TradingView
#TechnicalAnalysis
#Alerts
#TradingStrategy
W%R Zone Scalper[BullByte] v1.0W%R Zone Scalper Strategy - The Definitive Deep Dive
1. Introduction: The Philosophy Behind the Strategy
This script, W%R Zone Scalper , is not just another Williams %R-based trading system—it is a refined, multi-filtered scalping engine designed to maximize edge in trending markets while minimizing false signals in choppy conditions . Unlike most basic %R strategies that blindly trade crossovers, this system introduces a sophisticated confluence of trend, volatility, and momentum filters , making it a high-probability scalper for intraday traders .
What Makes This Script Different?
✅ Originality: Most %R strategies rely solely on overbought/oversold levels, leading to whipsaws in ranging markets. This script intelligently combines:
- Trend confirmation (MA, Supertrend)
- Volatility filters (BB Width, Choppiness Index)
- Volume validation (to ensure real participation)
- ADX trend strength (to avoid weak, fake trends)
✅ Smart Trade Execution:
- Not just %R crossovers —entries are only taken when multiple filters align, reducing noise.
- Optional ATR-based SL/TP for disciplined risk management.
- Dashboard integration for real-time trade monitoring.
✅ Adaptability:
- Works on crypto, forex, and stocks (optimized for high-liquidity assets like BTC).
- Scalable from 1-minute scalping to 1-hour swing trades (adjust filters accordingly).
2. Core Components: A Surgical Breakdown
A. Williams %R - The Trigger Mechanism
- Default Settings:
- Length = 14 (optimal balance between sensitivity and reliability).
- Long Entry : Cross above -80 (oversold bounce with momentum).
- Short Entry : Cross below -20 (overbought rejection).
Why This Matters:
- Unlike RSI or Stochastic, %R is more aggressive in detecting reversals, making it ideal for scalping fast moves.
- However, raw %R signals are noisy—hence the need for additional filters.
B. The Moving Average (MA) - Trend Filter
- Purpose: Ensures trades are only taken in the direction of the broader trend.
- Types Available:
- SMA (Simple MA) – Smooth but laggy.
- EMA (Exponential MA) – Faster, default choice.
- WMA (Weighted MA) – More responsive to recent prices.
- HMA (Hull MA) – Minimal lag, excellent for scalping.
Entry Logic:
- Long : Price must be above MA (confirms uptrend).
- Short : Price must be below MA (confirms downtrend).
Why This Matters:
- Prevents counter-trend trades , which are high-risk in scalping.
- Works as a dynamic support/resistance .
C. Advanced Filters - The Edge Enhancers
1. Choppiness Index (CI) - Avoiding Sideways Markets
- Default:
- Length = 12
- Threshold = 38.2 (below = trending, above = choppy).
Why This Matters:
- Eliminates false signals in ranging markets (where %R crossovers fail most).
- Inspired by market cycle theory—only trades when volatility is directional.
2. ADX (Average Directional Index) - Trend Strength
- Default:
- Length = 14
- Threshold = 25 (only trade if ADX > 25 = strong trend).
Why This Matters:
- Many traders ignore ADX and get fake breakouts—this ensures trades happen only in high-momentum conditions.
3. Volume Filter - Confirming Real Moves
- Logic: Volume must be above its 50-period MA.
- Why This Matters:
- Low-volume breakouts often fail—this ensures institutional participation.
4. Bollinger Band Width (BBW) - Volatility Check
- Logic: BBW must be above its moving average (expanding volatility = good for scalping).
Why This Matters:
- Avoids low-volatility traps where price moves are insignificant.
5. Supertrend - Dynamic Trend Confirmation
- Logic:
- Longs : Price must be above Supertrend line.
- Shorts : Price must be below Supertrend line.
Why This Matters:
- Acts as a secondary trend filter , reducing whipsaws.
---
3. Risk Management - Protecting Capital
A. Position Sizing (Flexible & Adaptive)
- Default: 30% of equity per trade(aggressive but adjustable).
- Initial Capital: $1,000(example—modify based on your account size).
B. Stop Loss & Take Profit (ATR-Based)
- SL = 1.5x ATR (protects against sudden reversals).
- TP = 2x ATR (locks in profits before pullbacks).
Why ATR?
- Dynamic adjustment —wider in volatile markets, tighter in calm ones.
C. Manual Adjustments Required
- Commission: Default 0.1% (adjust per your broker).
- Leverage: Not hardcoded —apply based on your risk tolerance.
4. Optimal Time Frame & Asset Selection
- Best for: 5M - 15M charts(scalping).
- Also works on: 1H-4H(swing trades with adjusted filters).
- Best Assets:
- High-liquidity cryptos (BTC, ETH, SOL)
- Forex majors (EUR/USD, GBP/USD)
- High-beta stocks (TSLA, NVDA)
5. The Dashboard - Real-Time Trade Intelligence
- PnL Tracking (profit/loss in $ and %).
- Position Status (Long/Short/Flat).
- Filter Status (which ones are active).
- Key Indicators (%R, MA, Volume).
Why This Matters:
- No guesswork—all critical info in one place.
6. Strong Disclaimer
⚠️ This is not financial advice. Trading carries risk of loss.
- Backtest thoroughly before live trading.
- Start with small capital to validate performance.
- Modify SL/TP, leverage, and position sizing based on your risk profile.
- The developer is not liable for any losses incurred.
7. Why This Strategy Stands Out
Most %R strategies fail in real markets because they ignore:
❌ Trend context (trading reversals blindly).
❌ Volatility cycles (getting chopped up in sideways action).
❌ Volume confirmation (falling for fake breakouts).
This script solves those problems by:
✅ Only trading when multiple high-probability factors align.
✅ Using adaptive risk management (ATR-based SL/TP).
✅ Providing a real-time dashboard for decision-making.
8.Important Note on Backtesting & Customization
The performance results displayed with this script are based on:
- Asset BTC/USD
- Timeframe : 5-minute chart
- Key Filters Enabled :
- Moving Average (Trend Confirmation)
- Choppiness Index (Sideways Market Filter)
- Volume (Participation Validation)
Your Trading Approach May Vary
This configuration represents just one possible way to deploy the strategy. You can:
- Test alternative settings (adjust lengths, thresholds, or filters)
- Apply to different assets (cryptos, forex pairs, stocks)
- Experiment with timeframes (1m for ultra-scalping, 15m/1H for swing trades)
Critical Reminder
Always conduct your own forward testing before live trading. Market conditions change, and past performance never guarantees future results.
All the best!
RSI + SuperTrend Filter Strategy (45m BTCUSDT)🧠 Strategy Breakdown: RSI + SuperTrend Filter (45m BTCUSDT)
This strategy is built on a simple yet powerful principle: don’t fight the trend — and never ignore momentum exhaustion.
At its core, this setup looks for RSI-based reversal entries, but only when price action aligns with the underlying trend structure, defined by a modified SuperTrend. This combo filters out a large chunk of noise you typically get with RSI alone on lower timeframes.
📊 How It Works
Longs trigger when RSI crosses up from oversold and SuperTrend confirms a bullish bias.
Shorts trigger when RSI crosses down from overbought and SuperTrend confirms a bearish structure.
Each entry is paired with a tight SL (1%) and dynamic TP (1.5%), offering favorable risk:reward setups.
The script includes clean chart visuals — background zones, SL/TP lines, and real-time trend bands — built for clarity and decision speed.
⚙️ Why It Works
Too many RSI strategies reverse blindly — this doesn’t. By combining RSI oversold/overbought conditions with a directional SuperTrend filter, you get higher-quality entries, especially during high-volatility phases.
This is not designed for sideways markets — it’s meant to catch clean swings in structured trends. The 45m TF adds breathing room for better signal quality while still allowing for decent trade frequency.
📈 Backtest Snapshot (3m logic on 45m BTCUSDT)
💰 +213,885 USDT total P&L
🧠 239 trades, with solid coverage across sessions
📉 15% max drawdown
⚖️ Profit factor: 1.12
🔁 Dynamic execution-ready — ideal for automation or manual confirmations
🔧 Built For Traders Who:
Want non-repainting structure they can trust
Prefer mechanical entries with visual context
Are experimenting with automation-ready setups
Need something they can tweak and expand on
🔥 If you're serious about combining clean signals with trend confirmation — this is a solid foundation. Drop a comment if you want the multi-timeframe version or ideas on adding volume-based confirmations.
TASC 2025.05 Trading The Channel█ OVERVIEW
This script implements channel-based trading strategies based on the concepts explained by Perry J. Kaufman in the article "A Test Of Three Approaches: Trading The Channel" from the May 2025 edition of TASC's Traders' Tips . The script explores three distinct trading methods for equities and futures using information from a linear regression channel. Each rule set corresponds to different market behaviors, offering flexibility for trend-following, breakout, and mean-reversion trading styles.
█ CONCEPTS
Linear regression
Linear regression is a model that estimates the relationship between a dependent variable and one or more independent variables by fitting a straight line to the observed data. In the context of financial time series, traders often use linear regression to estimate trends in price movements over time.
The slope of the linear regression line indicates the strength and direction of the price trend. For example, a larger positive slope indicates a stronger upward trend, and a larger negative slope indicates the opposite. Traders can look for shifts in the direction of a linear regression slope to identify potential trend trading signals, and they can analyze the magnitude of the slope to support trading decisions.
One caveat to linear regression is that most financial time series data does not follow a straight line, meaning a regression line cannot perfectly describe the relationships between values. Prices typically fluctuate around a regression line to some degree. As such, analysts often project ranges above and below regression lines, creating channels to model the expected extent of the data's variability. This strategy constructs a channel based on the method used in Kaufman's article. It measures the maximum distances from points on the linear regression line to historical price values, then adds those distances and the current slope to the regression points.
Depending on the trading style, traders might look for prices to move outside an established channel for breakout signals, or they might look for price action to reach extremes within the channel for potential mean reversion opportunities.
█ STRATEGY CALCULATIONS
Primary trade rules
This strategy implements three distinct sets of rules for trend, breakout, and mean-reversion trades based on the methods Kaufman describes in his article:
Trade the trend (Rule 1) : Open new positions when the sign of the slope changes, indicating a potential trend reversal. Close short trades and enter a long trade when the slope changes from negative to positive, and do the opposite when the slope changes from positive to negative.
Trade channel breakouts (Rule 2) : Open new positions when prices cross outside the linear regression channel for the current sample. Close short trades and enter a long trade when the price moves above the channel, and do the opposite when the price moves below the channel.
Trade within the channel (Rule 3) : Open new positions based on price values within the channel's range. Close short trades and enter a long trade when the price is near the channel's low, within a specified percentage of the channel's range, and do the opposite when the price is near the channel's high. With this rule, users can also filter the trades based on the channel's slope. When the filter is active, long positions are allowed only when the slope is positive, and short positions are allowed only when it is negative.
Position sizing
Kaufman's strategy uses specific trade sizes for equities and futures markets:
For an equities symbol, the number of shares traded is $10,000 divided by the current price.
For a futures symbol, the number of contracts traded is based on a volatility-adjusted formula that divides $25,000 by the product of the 20-bar average true range and the instrument's point value.
By default, this script automatically uses these sizes for its trade simulation on equities and futures symbols and does not simulate trading on other symbols. However, users can control position sizes from the "Settings/Properties" tab and enable trade simulation on other symbol types by selecting the "Manual" option in the script's "Position sizing" input.
Stop-loss
This strategy includes the option to place an accompanying stop-loss order for each trade, which users can enable from the "SL %" input in the "Settings/Inputs" tab. When enabled, the strategy places a stop-loss order at a specified percentage distance from the closing price where the entry order occurs, allowing users to compare how the strategy performs with added loss protection.
█ USAGE
This strategy adapts its display logic for the three trading approaches based on the rule selected in the "Trade rule" input:
For all rules, the script plots the linear regression slope in a separate pane. The plot is color-coded to indicate whether the current slope is positive or negative.
When the selected rule is "Trade the trend", the script plots triangles in the separate pane to indicate when the slope's direction changes from positive to negative or vice versa. Additionally, it plots a color-coded SMA on the main chart pane, allowing visual comparison of the slope to directional changes in a moving average.
When the rule is "Trade channel breakouts" or "Trade within the channel", the script draws the current period's linear regression channel on the main chart pane, and it plots bands representing the history of the channel values from the specified start time onward.
When the rule is "Trade within the channel", the script plots overbought and oversold zones between the bands based on a user-specified percentage of the channel range to indicate the value ranges where new trades are allowed.
Users can customize the strategy's calculations with the following additional inputs in the "Settings/Inputs" tab:
Start date : Sets the date and time when the strategy begins simulating trades. The script marks the specified point on the chart with a gray vertical line. The plots for rules 2 and 3 display the bands and trading zones from this point onward.
Period : Specifies the number of bars in the linear regression channel calculation. The default is 40.
Linreg source : Specifies the source series from which to calculate the linear regression values. The default is "close".
Range source : Specifies whether the script uses the distances from the linear regression line to closing prices or high and low prices to determine the channel's upper and lower ranges for rules 2 and 3. The default is "close".
Zone % : The percentage of the channel's overall range to use for trading zones with rule 3. The default is 20, meaning the width of the upper and lower zones is 20% of the range.
SL% : If the checkbox is selected, the strategy adds a stop-loss to each trade at the specified percentage distance away from the closing price where the entry order occurs. The checkbox is deselected by default, and the default percentage value is 5.
Position sizing : Determines whether the strategy uses Kaufman's predefined trade sizes ("Auto") or allows user-defined sizes from the "Settings/Properties" tab ("Manual"). The default is "Auto".
Long trades only : If selected, the strategy does not allow short positions. It is deselected by default.
Trend filter : If selected, the strategy filters positions for rule 3 based on the linear regression slope, allowing long positions only when the slope is positive and short positions only when the slope is negative. It is deselected by default.
NOTE: Because of this strategy's trading rules, the simulated results for a specific symbol or channel configuration might have significantly fewer than 100 trades. For meaningful results, we recommend adjusting the start date and other parameters to achieve a reasonable number of closed trades for analysis.
Additionally, this strategy does not specify commission and slippage amounts by default, because these values can vary across market types. Therefore, we recommend setting realistic values for these properties in the "Cost simulation" section of the "Settings/Properties" tab.
Weighted Ichimoku StrategyLSE:HSBA
The Ichimoku Kinko Hyo indicator is a comprehensive tool that combines multiple signals to identify market trends and potential buying/selling opportunities. My weighted variant of this strategy attempts to assign specific weights to each signal, allowing for a more nuanced and customizable approach to trend identification. The intent is to try and make a more informed trading decision based on the cumulative strength of various signals.
I've tried not to make it a mishmash of this and that + MACD + RSI and on and on; most people have their preferred indicator that focuses on just that that they can use in conjunction.
The signals used can be grouped into two groups the 'Core Ichimoku Signals' & the 'Additional Signals' (at the end you will find the signals and their assigned weights followed by the thresholds where they align).
The Core Ichimoku Signals are the primary signals used in Ichimoku analysis, including Kumo Breakout, Chikou Cross, Kijun Cross, Tenkan Cross, and Kumo Twist.
While the Additional Signals provide further insights and confirmations, such as Kijun Confirmation, Tenkan-Kijun Above Cloud, Chikou Above Cloud, Price-Kijun Cross, Chikou Span Signal, and Price Positioning.
Entries are triggered when the cumulative weight of bullish signals exceeds a specified buy threshold, indicating a strong uptrend or potential trend reversal.
Exits are initiated when the cumulative weight of bearish signals surpasses a specified sell threshold, or when additional conditions such as consolidation patterns or ATR-based targets are met.
There are various exit types that you can choose between, which can be used separately or in conjunction with one another. As an example you might want to exit on a different condition during consolidation periods than during other periods or just use ATR with some other backstop.
They are listed in evaluation order i.e. ATR trumps all, Consolidation exit trumps the regular Kumo sell and so on:
**ATR Sell**: Exits trades based on ATR-based profit targets and stop-losses.
**Consolidation Exit**: Exits trades during consolidation periods to reduce drawdown.
**Sell Below Kumo**: Exits trades when the price is below the Kumo, indicating a potential downtrend.
**Sell Threshold**: Exits trades when the cumulative weight of bearish signals surpasses a specified sell threshold.
There are various 'filters' which are really behavior modifiers:
**Kumo Breakout Filter**: Requires price to close above the Kumo for buy signals (essentially a entry delay).
**Whipsaw Filter**: Ensures trend strength over specified days to reduce false signals.
**Buy Cooldown**: Prevents new entries until half the Kijun period passes after an exit (prevents flapping).
**Chikou Filter**: Delays exits unless the previous close is below the Chikou Span.
**Consolidation Trend Filter**: Prevents consolidation exits if the trend is bullish (rare, but happens).
Then there are some debugging options. Ichimoku periods have some presets (personally I like 8/22/44/22) but are freely configurable, preset to the traditional values for purists.
The list of signals and most thresholds follow, play around with them. Thats all.
Cheers,
**Core Ichimoku Signals**
**Kumo Breakout**
- 30 (Bullish) / -30 (Bearish)
- Indicates a strong trend when the price breaks above (bullish) or below (bearish) the Kumo (cloud). This signal suggests a significant shift in market sentiment.
**Chikou Cross**
- 20 (Bullish) / -20 (Bearish)
- Shows the relationship between the Chikou Span (lagging span) and the current price. A bullish signal occurs when the Chikou Span is above the price, indicating a potential uptrend. Conversely, a bearish signal occurs when the Chikou Span is below the price, suggesting a downtrend.
**Kijun Cross**
- 15 (Bullish) / -15 (Bearish)
- Signals trend changes when the Tenkan-sen (conversion line) crosses above (bullish) or below (bearish) the Kijun-sen (base line). This crossover is often used to identify potential trend reversals.
**Tenkan Cross**
- 10 (Bullish) / -10 (Bearish)
- Indicates short-term trend changes when the price crosses above (bullish) or below (bearish) the Tenkan-sen. This signal helps identify minor trend shifts within the broader trend.
**Kumo Twist**
- 5 (Bullish) / -5 (Bearish)
- Shows changes in the Kumo's direction, indicating potential trend shifts. A bullish Kumo Twist occurs when Senkou Span A crosses above Senkou Span B, and a bearish twist occurs when Senkou Span A crosses below Senkou Span B.
**Additional Signals**
**Kijun Confirmation**
- 8 (Bullish) / -8 (Bearish)
- Confirms the trend based on the price's position relative to the Kijun-sen. A bullish signal occurs when the price is above the Kijun-sen, and a bearish signal occurs when the price is below it.
**Tenkan-Kijun Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Indicates a strong bullish trend when both the Tenkan-sen and Kijun-sen are above the Kumo. Conversely, a bearish signal occurs when both lines are below the Kumo.
**Chikou Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Shows the Chikou Span's position relative to the Kumo, indicating trend strength. A bullish signal occurs when the Chikou Span is above the Kumo, and a bearish signal occurs when it is below.
**Price-Kijun Cross**
- 2 (Bullish) / -2 (Bearish)
- Signals short-term trend changes when the price crosses above (bullish) or below (bearish) the Kijun-sen. This signal is similar to the Kijun Cross but focuses on the price's direct interaction with the Kijun-sen.
**Chikou Span Signal**
- 10 (Bullish) / -10 (Bearish)
- Indicates the trend based on the Chikou Span's position relative to past price highs and lows. A bullish signal occurs when the Chikou Span is above the highest high of the past period, and a bearish signal occurs when it is below the lowest low.
**Price Positioning**
- 10 (Bullish) / -10 (Bearish)
- Shows indecision when the price is between the Tenkan-sen and Kijun-sen, indicating a potential consolidation phase. A bullish signal occurs when the price is above both lines, and a bearish signal occurs when the price is below both lines.
**Confidence Level**: Highly Sensitive
- **Buy Threshold**: 50
- **Sell Threshold**: -50
- **Notes / Significance**: ~2–3 signals, very early trend detection. High sensitivity, may capture noise and false signals.
**Confidence Level**: Entry-Level
- **Buy Threshold**: 58
- **Sell Threshold**: -58
- **Notes / Significance**: ~3–4 signals, often Chikou Cross or Kumo Breakout. Very sensitive, risks noise (e.g., false buys in choppy markets).
**Confidence Level**: Entry-Level
- **Buy Threshold**: 60
- **Sell Threshold**: -60
- **Notes / Significance**: ~3–4 signals, Kumo Breakout or Chikou Cross anchors. Entry point for early trends.
**Confidence Level**: Moderate
- **Buy Threshold**: 65
- **Sell Threshold**: -65
- **Notes / Significance**: ~4–5 signals, balances sensitivity and reliability. Suitable for moderate risk tolerance.
**Confidence Level**: Conservative
- **Buy Threshold**: 70
- **Sell Threshold**: -70
- **Notes / Significance**: ~4–5 signals, emphasizes stronger confirmations. Reduces false signals but may miss some opportunities.
**Confidence Level**: Very Conservative
- **Buy Threshold**: 75
- **Sell Threshold**: -75
- **Notes / Significance**: ~5–6 signals, prioritizes high confidence. Minimizes risk but may enter trades late.
**Confidence Level**: High Confidence
- **Buy Threshold**: 80
- **Sell Threshold**: -80
- **Notes / Significance**: ~6–7 signals, very strong confirmations needed. Suitable for cautious traders.
**Confidence Level**: Very High Confidence
- **Buy Threshold**: 85
- **Sell Threshold**: -85
- **Notes / Significance**: ~7–8 signals, extremely high confidence required. Minimizes false signals significantly.
**Confidence Level**: Maximum Confidence
- **Buy Threshold**: 90
- **Sell Threshold**: -90
- **Notes / Significance**: ~8–9 signals, maximum confidence level. Ensures trades are highly reliable but may result in fewer trades.
**Confidence Level**: Ultra Conservative
- **Buy Threshold**: 100
- **Sell Threshold**: -100
- **Notes / Significance**: ~9–10 signals, ultra-high confidence. Trades are extremely reliable but opportunities are rare.
**Confidence Level**: Extreme Confidence
- **Buy Threshold**: 110
- **Sell Threshold**: -110
- **Notes / Significance**: All signals align, extreme confidence. Trades are almost certain but very few opportunities.
4 EMAs with Entry and Exit Strategy🔍 Purpose of the Script:
This strategy is designed to identify bullish trends using a combination of Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI), and execute long entries and exits accordingly.
📈 Key Technical Indicators Used:
EMAs (Exponential Moving Averages):
ema9, ema21, ema63, and ema200 are calculated to determine short-, mid-, and long-term trends.
An unused ema126 is mentioned but commented out.
RSI (Relative Strength Index):
A 14-period RSI is calculated and used to avoid entries when the stock is overbought.
🟢 Entry Logic (Long):
The strategy enters a long position when:
A bullish trend is confirmed by EMA alignment:
ema9 > ema21 > ema63 > ema200
The closing price is above ema9
RSI is ≤ 60, to avoid entering overbought conditions
🔴 Exit Logic (Long Exit):
The strategy exits a long position when:
ema21 crosses below ema63 (bearish signal)
There are commented-out conditions like:
RSI > 80 (overbought)
Close > 1.4 × ema126 (price extended far above average)
🎨 Visualization:
EMAs are plotted in different colors for trend visibility.
Background color turns:
Light green in bullish trend
Light red in bearish trend
⚙️ Strategy Configuration:
Capital: ₹10,00,000
Position size: 10% of equity
Commission: 0.75% per trade (roundtrip)
Overlay: true (indicators and trades plotted on price chart)
✅ Highlights:
Clear trend detection with layered EMA logic
Avoids overbought entries using RSI ≤ 60
Customizable and extendable (e.g., you can uncomment EMA126 and add price-overextension logic)
15Min Engulfing Break StrategyThe strategy involves the Engulfing Theory, Bullish and Bearish Engulfing patterns. Its specifically for 15 Minute chart. win ratio is 76%.
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
Dskyz (DAFE) MAtrix with ATR-Powered Precision Dskyz (DAFE) MAtrix with ATR-Powered Precision
This cutting‐edge futures trading strategy built to thrive in rapidly changing market conditions. Developed for high-frequency futures trading on instruments such as the CME Mini MNQ, this strategy leverages a matrix of sophisticated moving averages combined with ATR-based filters to pinpoint high-probability entries and exits. Its unique combination of adaptable technical indicators and multi-timeframe trend filtering sets it apart from standard strategies, providing enhanced precision and dynamic responsiveness.
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Core Functional Components
1. Advanced Moving Averages
A distinguishing feature of the DAFE strategy is its robust, multi-choice moving averages (MAs). Clients can choose from a wide array of MAs—each with specific strengths—in order to fine-tune their trading signals. The code includes user-defined functions for the following MAs:
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Hull Moving Average (HMA):
The hma(src, len) function calculates the HMA by using weighted moving averages (WMAs) to reduce lag considerably while smoothing price data. This function computes an intermediate WMA of half the specified length, then a full-length WMA, and finally applies a further WMA over the square root of the length. This design allows for rapid adaptation to price changes without the typical delays of traditional moving averages.
Triple Exponential Moving Average (TEMA):
Implemented via tema(src, len), TEMA uses three consecutive exponential moving averages (EMAs) to effectively cancel out lag and capture price momentum. The final formula—3 * (ema1 - ema2) + ema3—produces a highly responsive indicator that filters out short-term noise.
Double Exponential Moving Average (DEMA):
Through the dema(src, len) function, DEMA calculates an EMA and then a second EMA on top of it. Its simplified formula of 2 * ema1 - ema2 provides a smoother curve than a single EMA while maintaining enhanced responsiveness.
Volume Weighted Moving Average (VWMA):
With vwma(src, len), this MA accounts for trading volume by weighting the price, thereby offering a more contextual picture of market activity. This is crucial when volume spikes indicate significant moves.
Zero Lag EMA (ZLEMA):
The zlema(src, len) function applies a correction to reduce the inherent lag found in EMAs. By subtracting a calculated lag (based on half the moving average window), ZLEMA is exceptionally attuned to recent price movements.
Arnaud Legoux Moving Average (ALMA):
The alma(src, len, offset, sigma) function introduces ALMA—a type of moving average designed to be less affected by outliers. With parameters for offset and sigma, it allows customization of the degree to which the MA reacts to market noise.
Kaufman Adaptive Moving Average (KAMA):
The custom kama(src, len) function is noteworthy for its adaptive nature. It computes an efficiency ratio by comparing price change against volatility, then dynamically adjusts its smoothing constant. This results in an MA that quickly responds during trending periods while remaining smoothed during consolidation.
Each of these functions—integrated into the strategy—is selectable by the trader (via the fastMAType and slowMAType inputs). This flexibility permits the tailored application of the MA most suited to current market dynamics and individual risk management preferences.
2. ATR-Based Filters and Risk Controls
ATR Calculation and Volatility Filter:
The strategy computes the Average True Range (ATR) over a user-defined period (atrPeriod). ATR is then used to derive both:
Volatility Assessment: Expressed as a ratio of ATR to closing price, ensuring that trades are taken only when volatility remains within a safe, predefined threshold (volatilityThreshold).
ATR-Based Entry Filters: Implemented as atrFilterLong and atrFilterShort, these conditions ensure that for long entries the price is sufficiently above the slow MA and vice versa for shorts. This acts as an additional confirmation filter.
Dynamic Exit Management:
The exit logic employs a dual approach:
Fixed Stop and Profit Target: Stops and targets are set at multiples of ATR (fixedStopMultiplier and profitTargetATRMult), helping manage risk in volatile markets.
Trailing Stop Adjustments: A trailing stop is calculated using the ATR multiplied by a user-defined offset (trailOffset), which captures additional profits as the trade moves favorably while protecting against reversals.
3. Multi-Timeframe Trend Filtering
The strategy enhances its signal reliability by leveraging a secondary, higher timeframe analysis:
15-Minute Trend Analysis:
By retrieving 15-minute moving averages (fastMA15m and slowMA15m) via request.security, the strategy determines the broader market trend. This secondary filter (enabled or disabled through useTrendFilter) ensures that entries are aligned with the prevailing market direction, thereby reducing the incidence of false signals.
4. Signal and Execution Logic
Combined MA Alignment:
The entry conditions are based primarily on the alignment of the fast and slow MAs. A long condition is triggered when the current price is above both MAs and the fast MA is above the slow MA—complemented by the ATR filter and volume conditions. The reverse applies for a short condition.
Volume and Time Window Validation:
Trades are permitted only if the current volume exceeds a minimum (minVolume) and the current hour falls within the predefined trading window (tradingStartHour to tradingEndHour). An additional volume spike check (comparing current volume to a moving average of past volumes) further filters for optimal market conditions.
Comprehensive Order Execution:
The strategy utilizes flexible order execution functions that allow pyramiding (up to 10 positions), ensuring that it can scale into positions as favorable conditions persist. The use of both market entries and automated exits (with profit targets, stop-losses, and trailing stops) ensures that risk is managed at every step.
5. Integrated Dashboard and Metrics
For transparency and real-time analysis, the strategy includes:
On-Chart Visualizations:
Both fast and slow MAs are plotted on the chart, making it easy to see the market’s technical foundation.
Dynamic Metrics Dashboard:
A built-in table displays crucial performance statistics—including current profit/loss, equity, ATR (both raw and as a percentage), and the percentage gap between the moving averages. These metrics offer immediate insight into the health and performance of the strategy.
Input Parameters: Detailed Breakdown
Every input is meticulously designed to offer granular control:
Fast & Slow Lengths:
Determine the window size for the fast and slow moving averages. Smaller values yield more sensitivity, while larger values provide a smoother, delayed response.
Fast/Slow MA Types:
Choose the type of moving average for fast and slow signals. The versatility—from basic SMA and EMA to more complex ones like HMA, TEMA, ZLEMA, ALMA, and KAMA—allows customization to fit different market scenarios.
ATR Parameters:
atrPeriod and atrMultiplier shape the volatility assessment, directly affecting entry filters and risk management through stop-loss and profit target levels.
Trend and Volume Filters:
Inputs such as useTrendFilter, minVolume, and the volume spike condition help confirm that a trade occurs in active, trending markets rather than during periods of low liquidity or market noise.
Trading Hours:
Restricting trade execution to specific hours (tradingStartHour and tradingEndHour) helps avoid illiquid or choppy markets outside of prime trading sessions.
Exit Strategies:
Parameters like trailOffset, profitTargetATRMult, and fixedStopMultiplier provide multiple layers of risk management and profit protection by tailoring how exits are generated relative to current market conditions.
Pyramiding and Fixed Trade Quantity:
The strategy supports multiple entries within a trend (up to 10 positions) and sets a predefined trade quantity (fixedQuantity) to maintain consistent exposure and risk per trade.
Dashboard Controls:
The resetDashboard input allows for on-the-fly resetting of performance metrics, keeping the strategy’s performance dashboard accurate and up-to-date.
Why This Strategy is Truly Exceptional
Multi-Faceted Adaptability:
The ability to switch seamlessly between various moving average types—each suited to particular market conditions—enables the strategy to adapt dynamically. This is a testament to the high level of coding sophistication and market insight infused within the system.
Robust Risk Management:
The integration of ATR-based stops, profit targets, and trailing stops ensures that every trade is executed with well-defined risk parameters. The system is designed to mitigate unexpected market swings while optimizing profit capture.
Comprehensive Market Filtering:
By combining moving average crossovers with volume analysis, volatility thresholds, and multi-timeframe trend filters, the strategy only enters trades under the most favorable conditions. This multi-layered filtering reduces noise and enhances signal quality.
-Final Thoughts-
The Dskyz Adaptive Futures Elite (DAFE) MAtrix with ATR-Powered Precision strategy is not just another trading algorithm—it is a multi-dimensional, fully customizable system built on advanced technical principles and sophisticated risk management techniques. Every function and input parameter has been carefully engineered to provide traders with a system that is both powerful and transparent.
For clients seeking a state-of-the-art trading solution that adapts dynamically to market conditions while maintaining strict discipline in risk management, this strategy truly stands in a class of its own.
****Please show support if you enjoyed this strategy. I'll have more coming out in the near future!!
-Dskyz
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Heiken Ashi Supertrend ADX - StrategyHeiken Ashi Supertrend ADX Strategy
Overview
This strategy combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement.
Supertrend Filter : Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop : Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters: All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters: Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings: Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
Recommended Timeframes: Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Position Sizing: The strategy uses a percentage of equity approach (default: 3%) for position sizing
Performance Characteristics
When properly optimized, this strategy has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This strategy represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Dskyz Adaptive Futures Elite (DAFE)Dskyz Adaptive Futures Edge (DAFE)
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A Dynamic Futures Trading Strategy
DAFE adapts to market volatility and price action using technical indicators and advanced risk management. It’s built for high-stakes futures trading (e.g., MNQ, BTCUSDT.P), offering modular logic for scalpers and swing traders alike.
Key Features
Adaptive Moving Averages
Dynamic Logic: Fast and slow SMAs adjust lengths via ATR, reacting to momentum shifts and smoothing in calm markets.
Signals: Long entry on fast SMA crossing above slow SMA with price confirmation; short on cross below.
RSI Filtering (Optional)
Momentum Check: Confirms entries with RSI crossovers (e.g., above oversold for longs). Toggle on/off with custom levels.
Fine-Tuning: Adjustable lookback and thresholds (e.g., 60/40) for precision.
Candlestick Pattern Recognition
Eng|Enhanced Detection: Identifies strong bullish/bearish engulfing patterns, validated by volume and range strength (vs. 10-period SMA).
Conflict Avoidance: Skips trades if both patterns appear in the lookback window, reducing whipsaws.
Multi-Timeframe Trend Filter
15-Minute Alignment: Syncs intrabar trades with 15-minute SMA trends; optional for flexibility.
Dollar-Cost Averaging (DCA) New!
Scaling: Adds up to a set number of entries (e.g., 4) on pullbacks/rallies, spaced by ATR multiples.
Control: Caps exposure and resets on exit, enhancing trend-following potential.
Trade Execution & Risk Management
Entry Rules: Prioritizes moving averages or patterns (user choice), with volume, volatility, and time filters.
Stops & Trails:
Initial Stop: ATR-based (2–3.5x, volatility-adjusted).
Trailing Stop: Locks profits with configurable ATR offset and multiplier.
Discipline
Cooldown: Pauses post-exit (e.g., 0–5 minutes).
Min Hold: Ensures trades last a set number of bars (e.g., 2–10).
Visualization & Tools
Charts: Overlays MAs, stops, and signals; trend shaded in background.
Dashboard: Shows position, P&L, win rate, and more in real-time.
Debugging: Logs signal details for optimization.
Input Parameters
Parameter Purpose Suggested Use
Use RSI Filter - Toggle RSI confirmation *Disable 4 price-only
trading
RSI Length - RSI period (e.g., 14) *7–14 for sensitivity
RSI Overbought/Oversold - Adjust for market type *Set levels (e.g., 60/40)
Use Candlestick Patterns - Enables engulfing signals *Disable for MA focus
Pattern Lookback - Pattern window (e.g., 19) *10–20 bars for balance
Use 15m Trend Filter - Align with 15-min trend *Enable for trend trades
Fast/Slow MA Length - Base MA lengths (e.g., 9/19) *10–25 / 30–60 per
timeframe
Volatility Threshold - Filters volatile spikes *Max ATR/close (e.g., 1%)
Min Volume - Entry volume threshold *Avoid illiquid periods
(e.g., 10)
ATR Length - ATR period (e.g., 14) *Standard volatility
measure
Trailing Stop ATR Offset - Trail distance (e.g., 0.5) *0.5–1.5 for tightness
Trailing Stop ATR Multi - Trail multiplier (e.g., 1.0) *1–3 for trend room
Cooldown Minutes - Post-exit pause (e.g., 0–5) *Prevents overtrading
Min Bars to Hold - Min trade duration (e.g., 2) *5–10 for intraday
Trading Hours - Active window (e.g., 9–16) *Focus on key sessions
Use DCA - Toggle DCA *Enable for scaling
Max DCA Entries - Cap entries (e.g., 4) *Limit risk exposure
DCA ATR Multiplier Entry spacing (e.g., 1.0) *1–2 for wider gaps
Compliance
Realistic Testing: Fixed quantities, capital, and slippage for accurate backtests.
Transparency: All logic is user-visible and adjustable.
Risk Controls: Cooldowns, stops, and hold periods ensure stability.
Flexibility: Adapts to various futures and timeframes.
Summary
DAFE excels in volatile futures markets with adaptive logic, DCA scaling, and robust risk tools. Currently in prop account testing, it’s a powerful framework for precision trading.
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Follow Line Strategy Version 2.5 (React HTF)Follow Line Strategy v2.5 (React HTF) - TradingView Script Usage
This strategy utilizes a "Follow Line" concept based on Bollinger Bands and ATR to identify potential trading opportunities. It includes advanced features like optional working hours filtering, higher timeframe (HTF) trend confirmation, and improved trend-following entry/exit logic. Version 2.5 introduces reactivity to HTF trend changes for more adaptive trading.
Key Features:
Follow Line: The core of the strategy. It dynamically adjusts based on price breakouts beyond Bollinger Bands, using either the low/high or ATR-adjusted levels.
Bollinger Bands: Uses a standard Bollinger Bands setup to identify overbought/oversold conditions.
ATR Filter: Optionally uses the Average True Range (ATR) to adjust the Follow Line offset, providing a more dynamic and volatility-adjusted entry point.
Optional Trading Session Filter: Allows you to restrict trading to specific hours of the day.
Higher Timeframe (HTF) Confirmation: A significant feature that allows you to confirm trade signals with the trend on a higher timeframe. This can help to filter out false signals and improve the overall win rate.
HTF Selection Method: Choose between Auto and Manual HTF selection:
Auto: The script automatically determines the appropriate HTF based on the current chart timeframe (e.g., 1min -> 15min, 5min -> 4h, 1h -> 1D, Daily -> Monthly).
Manual: Allows you to select a specific HTF using the Manual Higher Timeframe input.
Trend-Following Entries/Exits: The strategy aims to enter trades in the direction of the established trend, using the Follow Line to define the trend.
Reactive HTF Trend Changes: v2.5 exits positions not only based on the trade timeframe (TTF) trend changing, but also when the higher timeframe trend reverses against the position. This makes the strategy more responsive to larger market movements.
Alerts: Provides buy and sell alerts for convenient trading signal notifications.
Visualizations: Plots the Follow Line for both the trade timeframe and the higher timeframe (optional), making it easy to understand the strategy's logic.
How to Use:
Add to Chart: Add the "Follow Line Strategy Version 2.5 (React HTF)" script to your TradingView chart.
Configure Settings: Customize the strategy's settings to match your trading style and preferences. Here's a breakdown of the key settings:
Indicator Settings:
ATR Period: The period used to calculate the ATR. A smaller period is more sensitive to recent price changes.
Bollinger Bands Period: The period used for the Bollinger Bands calculation. A longer period results in smoother bands.
Bollinger Bands Deviation: The number of standard deviations from the moving average that the Bollinger Bands are plotted. Higher deviations create wider bands.
Use ATR for Follow Line Offset?: Enable to use ATR to calculate the Follow Line offset. Disable to use the simple high/low.
Show Trade Signals on Chart?: Enable to show BUY/SELL labels on the chart.
Time Filter:
Use Trading Session Filter?: Enable to restrict trading to specific hours of the day.
Trading Session: The trading session to use (e.g., 0930-1600 for regular US stock market hours). Use 0000-2400 for all hours.
Higher Timeframe Confirmation:
Enable HTF Confirmation?: Enable to use the HTF trend to filter trade signals. If enabled, only trades in the direction of the HTF trend will be taken.
HTF Selection Method: Choose between "Auto" and "Manual" HTF selection.
Manual Higher Timeframe: If "Manual" is selected, choose the specific HTF (e.g., 240 for 4 hours, D for daily).
Show HTF Follow Line?: Enable to plot the HTF Follow Line on the chart.
Understanding the Signals:
Buy Signal: The price breaks above the upper Bollinger Band, and the HTF (if enabled) confirms the uptrend.
Sell Signal: The price breaks below the lower Bollinger Band, and the HTF (if enabled) confirms the downtrend.
Exit Long: The trade timeframe trend changes to downtrend or the higher timeframe trend changes to downtrend.
Exit Short: The trade timeframe trend changes to uptrend or the higher timeframe trend changes to uptrend.
Alerts:
The script includes alert conditions for buy and sell signals. To set up alerts, click the "Alerts" button in TradingView and select the desired alert condition from the script. The alert message provides the ticker and interval.
Backtesting and Optimization:
Use TradingView's Strategy Tester to backtest the strategy on different assets and timeframes.
Experiment with different settings to optimize the strategy for your specific trading style and risk tolerance. Pay close attention to the ATR Period, Bollinger Bands settings, and the HTF confirmation options.
Tips and Considerations:
HTF Confirmation: The HTF confirmation can significantly improve the strategy's performance by filtering out false signals. However, it can also reduce the number of trades.
Risk Management: Always use proper risk management techniques, such as stop-loss orders and position sizing, when trading any strategy.
Market Conditions: The strategy may perform differently in different market conditions. It's important to backtest and optimize the strategy for the specific markets you are trading.
Customization: Feel free to modify the script to suit your specific needs. For example, you could add additional filters or entry/exit conditions.
Pyramiding: The pyramiding = 0 setting prevents multiple entries in the same direction, ensuring the strategy doesn't compound losses. You can adjust this value if you prefer to pyramid into winning positions, but be cautious.
Lookahead: The lookahead = barmerge.lookahead_off setting ensures that the HTF data is calculated based on the current bar's closed data, preventing potential future peeking bias.
Trend Determination: The logic for determining the HTF trend and reacting to changes is critical. Carefully review the f_calculateHTFData function and the conditions for exiting positions to ensure you understand how the strategy responds to different market scenarios.
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice, and you should not trade based solely on the signals generated by this script. Always do your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred as a result of using this script.
Scalping 15min: EMA + MACD + RSI + ATR-based SL/TP📈 Strategy: 15-Minute Scalping — EMA + MACD + RSI + ATR-based SL/TP
This scalping strategy is designed for 15-minute charts and combines trend-following and momentum confirmation with dynamic stop loss and take profit levels based on volatility.
🔧 Indicators Used:
EMA 50 — identifies the main trend
MACD Histogram — confirms momentum direction
RSI (14) — filters overbought/oversold conditions
ATR (14) — dynamically sets SL and TP based on market volatility
📊 Entry Conditions:
Long Entry:
Price is above EMA 50
MACD histogram is positive
RSI is above 50 but below 70
Short Entry:
Price is below EMA 50
MACD histogram is negative
RSI is below 50 but above 30
🛑 Risk Management:
Stop Loss: 1×ATR (user-configurable)
Take Profit: 2×ATR (user-configurable)
These values can be adjusted in the script inputs depending on your risk/reward preference or market conditions.
⚠️ Notes:
Strategy is optimized for scalping fast-moving pairs (e.g. crypto, forex).
Works best in trending markets.
Use backtesting and forward testing before live trading.
EMA Crossover (Short Focus with Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The 100-period SMA and 200-period SMA serve as additional trend indicators to provide context for the market conditions. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
The strategy is designed to execute trades swiftly with an emphasis on entering positions when conditions align in real time. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A key feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves in favor of the trade, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing more flexibility in managing risk. This trailing stop mechanism helps to capture profits from favorable market moves while ensuring that positions are exited if the market moves against them.
This strategy works best on the daily timeframe and is optimized for major cryptocurrency pairs. The daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
Uptrick X PineIndicators: Z-Score Flow StrategyThis strategy is based on the Z-Score Flow Indicator developed by Uptrick. Full credit for the original concept and logic goes to Uptrick.
The Z-Score Flow Strategy combines statistical mean-reversion logic with trend filtering, RSI confirmation, and multi-mode trade execution, offering a flexible and structured approach to trading both reversals and trend continuations.
Core Concepts Behind Z-Score Flow
1. Z-Score Mean Reversion Logic
The Z-score measures how far current price deviates from its statistical mean, in standard deviations.
A high positive Z-score (e.g. > 2) suggests price is overbought and may revert downward.
A low negative Z-score (e.g. < -2) suggests price is oversold and may revert upward.
The strategy uses Z-score thresholds to trigger signals when price deviates far enough from its mean.
2. Trend Filtering with EMA
To prevent counter-trend entries, the strategy includes a trend filter based on a 50-period EMA:
Only allows long entries if price is below EMA (mean-reversion in downtrends).
Only allows short entries if price is above EMA (mean-reversion in uptrends).
3. RSI Confirmation and Lockout System
An RSI smoothing mechanism helps confirm signals and avoid whipsaws:
RSI must be below 30 and rising to allow buys.
RSI must be above 70 and falling to allow sells.
Once a signal occurs, it is "locked out" until RSI re-enters the neutral zone (30–70).
This avoids multiple signals in overextended zones and reduces overtrading.
Entry Signal Logic
A buy or sell is triggered when:
Z-score crosses below (buy) or above (sell) the threshold.
RSI smoothed condition is met (oversold and rising / overbought and falling).
The trend condition (EMA filter) aligns.
A cooldown period has passed since the last opposite trade.
This layered approach helps ensure signal quality and timing precision.
Trade Modes
The strategy includes three distinct trade modes to adapt to various market behaviors:
1. Standard Mode
Trades are opened using the Z-score + RSI + trend filter logic.
Each signal must pass all layered conditions.
2. Zero Cross Mode
Trades are based on the Z-score crossing zero.
This mode is useful in trend continuation setups, rather than mean reversion.
3. Trend Reversal Mode
Trades occur when the mean slope direction changes, i.e., basis line changes color.
Helps capture early trend shifts with less lag.
Each mode can be customized for long-only, short-only, or long & short execution.
Visual Components
1. Z-Score Mean Line
The basis (mean) line is colored based on slope direction.
Green = bullish slope, Purple = bearish slope, Gray = flat.
A wide shadow band underneath reflects current trend momentum.
2. Gradient Fill to Price
A gradient zone between price and the mean reflects:
Price above mean = bearish zone with purple overlay.
Price below mean = bullish zone with teal overlay.
This visual aid quickly reveals market positioning relative to equilibrium.
3. Signal Markers
"𝓤𝓹" labels appear for buy signals.
"𝓓𝓸𝔀𝓷" labels appear for sell signals.
These are colored and positioned according to trend context.
Customization Options
Z-Score Period & Thresholds: Define sensitivity to price deviations.
EMA Trend Filter Length: Filter entries with long-term bias.
RSI & Smoothing Periods: Fine-tune RSI confirmation conditions.
Cooldown Period: Prevent signal spam and enforce timing gaps.
Slope Index: Adjust how far back to compare mean slope.
Visual Settings: Toggle mean lines, gradients, and more.
Use Cases & Strategy Strengths
1. Mean-Reversion Trading
Ideal for catching pullbacks in trending markets or fading overextended price moves.
2. Trend Continuation or Reversal
With multiple trade modes, traders can choose between fading price extremes or trading slope momentum.
3. Signal Clarity and Risk Control
The combination of Z-score, RSI, EMA trend, and cooldown logic provides high-confidence signals with built-in filters.
Conclusion
The Z-Score Flow Strategy by Uptrick X PineIndicators is a versatile and structured trading system that:
Fuses statistical deviation (Z-score) with technical filters.
Provides both mean-reversion and trend-based entry logic.
Uses visual overlays and signal labels for clarity.
Prevents noise-driven trades via cooldown and lockout systems.
This strategy is well-suited for traders seeking a data-driven, multi-condition entry framework that can adapt to various market types.
Full credit for the original concept and indicator goes to Uptrick.
Smart Money Pivot Strategy [Jason Kasei]This strategy is designed to identify key pivot points (Pivot High and Pivot Low) in the market and leverage the "Smart Money" concept to capture price breakout opportunities. It supports both long and short trades, offering customizable stop-loss (SL) and take-profit (TP) settings, while visually plotting pivot points and breakout signals on the chart.
Core Features
Pivot Point Detection:
Utilizes ta.pivothigh and ta.pivotlow functions to detect the highest (Pivot High) and lowest (Pivot Low) points within a specified period (default: 20 bars).
Trading Signals:
Long Signal: Triggered when the price breaks above a previous Pivot High, indicating a potential uptrend.
Short Signal: Triggered when the price breaks below a previous Pivot Low, indicating a potential downtrend.
How It Works
Detects Pivot High (PH) and Pivot Low (PL) over the specified period and records their price and time.
Triggers a long entry when the price breaks above a Pivot High and a short entry when it falls below a Pivot Low.
Sets exit conditions automatically based on predefined SL and TP percentages after entry.
Plots breakout points and levels on the chart for analysis.
Considerations
The strategy relies on accurate pivot point detection; adjust the period parameter based on market volatility.
In highly volatile markets, consider widening the stop loss to avoid frequent triggering.
Combine with other indicators or analysis methods to validate signals and avoid blind trading.
Multi-EMA Crossover StrategyMulti-EMA Crossover Strategy
This strategy uses multiple exponential moving average (EMA) crossovers to identify bullish trends and execute long trades. The approach involves progressively stronger signals as different EMA pairs cross, indicating increasing bullish momentum. Each crossover triggers a long entry, and the intensity of bullish sentiment is reflected in the color of the bars on the chart. Conversely, bearish trends are represented by red bars.
Strategy Logic:
First Long Entry: When the 1-day EMA crosses above the 5-day EMA, it signals initial bullish momentum.
Second Long Entry: When the 3-day EMA crosses above the 10-day EMA, it confirms stronger bullish sentiment.
Third Long Entry: When the 5-day EMA crosses above the 20-day EMA, it indicates further trend strength.
Fourth Long Entry: When the 10-day EMA crosses above the 40-day EMA, it suggests robust long-term bullish momentum.
The bar colors reflect these conditions:
More blue bars indicate stronger bullish sentiment as more short-term EMAs are above their longer-term counterparts.
Red bars represent bearish conditions when short-term EMAs are below longer-term ones.
Example: Bitcoin Trading on a Daily Timeframe
Bullish Scenario:
Imagine Bitcoin is trading at $30,000 on March 31, 2025:
First Signal: The 1-day EMA crosses above the 5-day EMA at $30,000. This suggests initial upward momentum, prompting a small long entry.
Second Signal: A few days later, the 3-day EMA crosses above the 10-day EMA at $31,000. This confirms strengthening bullish sentiment; another long position is added.
Third Signal: The 5-day EMA crosses above the 20-day EMA at $32,500, indicating further upward trend development; a third long entry is executed.
Fourth Signal: Finally, the 10-day EMA crosses above the 40-day EMA at $34,000. This signals robust long-term bullish momentum; a fourth long position is entered.
Bearish Scenario:
Suppose Bitcoin reverses from $34,000 to $28,000:
The 1-day EMA crosses below the 5-day EMA at $33,500.
The 3-day EMA dips below the 10-day EMA at $32,000.
The 5-day EMA falls below the 20-day EMA at $30,000.
The final bearish signal occurs when the 10-day EMA drops below the 40-day EMA at $28,000.
The bars turn increasingly red as bearish conditions strengthen.
Advantages of This Strategy:
Progressive Confirmation: Multiple crossovers provide layered confirmation of trend strength.
Visual Feedback: Bar colors help traders quickly assess market sentiment and adjust positions accordingly.
Flexibility: Suitable for trending markets like Bitcoin during strong rallies or downturns.
Limitations:
Lagging Signals: EMAs are lagging indicators and may react slowly to sudden price changes.
False Breakouts: Crossovers in choppy markets can lead to whipsaws or false signals.
This strategy works best in trending markets and should be combined with additional risk management techniques, e.g., stop loss or optimal position sizes (Kelly Criterion).
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
EMA 10/55/200 - LONG ONLY MTF (4h with 1D & 1W confirmation)Title: EMA 10/55/200 - Long Only Multi-Timeframe Strategy (4h with 1D & 1W confirmation)
Description:
This strategy is designed for trend-following long entries using a combination of exponential moving averages (EMAs) on the 4-hour chart, confirmed by higher timeframe trends from the daily (1D) and weekly (1W) charts.
🔍 How It Works
🔹 Entry Conditions (4h chart):
EMA 10 crosses above EMA 55 and price is above EMA 55
OR
EMA 55 crosses above EMA 200
OR
EMA 10 crosses above EMA 500
These entries indicate short-term momentum aligning with medium/long-term trend strength.
🔹 Confirmation (multi-timeframe alignment):
Daily (1D): EMA 55 is above EMA 200
Weekly (1W): EMA 55 is above EMA 200
This ensures that we only enter long trades when the higher timeframes support an uptrend, reducing false signals during sideways or bearish markets.
🛑 Exit Conditions
Bearish crossover of EMA 10 below EMA 200 or EMA 500
Stop Loss: 5% below entry price
⚙️ Backtest Settings
Capital allocation per trade: 10% of equity
Commission: 0.1%
Slippage: 2 ticks
These are realistic conditions for crypto, forex, and stocks.
📈 Best Used On
Timeframe: 4h
Instruments: Trending markets like BTC/ETH, FX majors, or growth stocks
Works best in volatile or trending environments
⚠️ Disclaimer
This is a backtest tool and educational resource. Always validate on demo accounts before applying to real capital. Do your own due diligence.
