Trendline Breakout Strategy [KedArc Quant] Description
A single, rule-based system that builds two trendlines from confirmed swing pivots and trades their breakouts, with optional retest, trend-regime gates (EMA / HTF EMA), and ATR-based risk. All parts serve one decision flow: structure → breakout → gated entry → managed risk.
What it does (for traders)
Draws Up line (teal) through the last two Higher Lows and Down line (red) through the last two Lower Highs, then extends them forward.
Long when price breaks above red; Short when price breaks below teal.
Optional Retest entry: after a break, wait for a pullback toward the broken line within an ATR-scaled buffer.
Uses ATR stop and R-multiple target so risk is consistent across symbols/timeframes.
Labels HL1/HL2/LH1/LH2 so non-coders can verify which pivots built each line.
Why these components are combined
Pure breakout systems on trendlines suffer from three practical issues:
False breaks in chop → solved by trend-regime gates (EMA / HTF EMA) that only allow trades aligned with the prevailing trend.
Uneven volatility across markets/timeframes → solved by ATR-based stop/target, normalizing distance so R-multiples are comparable.
First break whipsaws near wedge apices → mitigated by the optional retest rule that demands a pullback/hold before entry.
These modules are not separate indicators with their own signals. They are support roles inside one method.
The pivot engine defines structure, the breakout detector defines signal, the regime gates decide if we’re allowed to take that signal, and the ATR module sizes risk.
Together they make the trendline breakout usable, testable, and explainable.
How it works (mechanism; each component explained)
1) Pivot engine (structure, non-repainting)
Swings are confirmed with ta.pivotlow/high(L, R). A pivot only exists after R bars (no look-ahead), so once plotted, the line built from those pivots will not repaint.
2) Trendline builder (geometry)
Teal line updates when two consecutive pivot lows satisfy HL2.price > HL1.price (and HL2 occurs after HL1).
Red line updates when two consecutive pivot highs satisfy LH2.price < LH1.price.
Lines are extended right and their current value is read every bar via line.get_price().
3) Breakout detector (signal)
On every bar, compute:
crossover(close, redLine) ⇒ Long breakout
crossunder(close, tealLine) ⇒ Short breakdown
4) Regime gates (trend filters, not separate signals)
EMA gate: allow longs only if close > EMA(len), shorts only if close < EMA(len).
HTF EMA gate (optional): same rule on a higher timeframe to avoid fighting the larger trend.
These do not create entries; they simply permit or block the breakout signal.
5) Retest module (optional confirmation)
After a breakout, record the line price. A valid retest occurs if price pulls back within an ATR-scaled buffer toward that broken line and then closes back in the breakout direction.
This reduces first-tick fakeouts.
6) Risk module (position exit)
Initial stop = ATR(len) × atrMult from entry.
Target = tpR × (ATR × atrMult) (e.g., 2R).
This keeps results consistent across instruments/timeframes.
Entries & exits
Long entry
Base: close breaks above red and passes EMA/HTF gates.
Retest (if enabled): after the break, price pulls back near the broken red line (within the ATR buffer) and holds; then enter.
Short entry
Mirror logic with teal (break below & gates), optionally with a retest.
Exit
strategy.exit places ATR stop & R-multiple target automatically.
Optional “flip”: close if the opposite base signal triggers.
How to use it (step-by-step)
Timeframe: 1–15m for intraday, 1–4h for swing.
Start defaults: Pivot L/R = 5, EMA len = 200, ATR len = 14, ATR mult = 2, TP = 2R, Retest = ON.
Tune sensitivity:
Faster lines (more trades): set L/R = 3–4.
Fewer counter-trend trades: enable HTF EMA (e.g., 60-min or Daily).
Visual audit: labels HL1/HL2 & LH1/LH2 show which pivots built each line—verify by eye.
Alerts: use Long breakout, Short breakdown, and Retest alerts to automate.
Originality (why it merits publication)
Trades the visualization: many “auto-trendline” tools only draw lines; this one turns them into testable, alertable rules.
Integrated design: each component has a defined role in the same pipeline—no unrelated indicators bolted together.
Transparent & non-repainting: pivot confirmation removes look-ahead; labels let non-coders understand the setup that produced each signal.
Notes & limitations
Lines update only after pivot confirmation; that lag is intentional to avoid repainting.
Breakouts near an apex can whipsaw; prefer Retest and/or HTF gate in choppy regimes.
Backtests are idealized; forward-test and size risk appropriately.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Indicatori e strategie
BSL/SSL Sweep + FVG Strategy Jobin (c) The New York ATM Model is a structured intraday strategy designed to capture algorithmic stop-hunts and reversals during the New York session open. It focuses on liquidity sweeps—either Buy-Side or Sell-Side—followed by a confirmation using Fair Value Gaps (FVGs).
Enhanced TMA Strategy[BMM]This strategy combines multiple moving averages with pattern recognition and dynamic coloring to identify high-probability trades. It uses 3-line strike patterns, engulfing candles, and RSI-based trend analysis with proper risk management for consistent 75%+ win rates.
Ideal Settings by Timeframe
For clear signals strategy can be used with:
"The Arty" - The Moving Average Official Indicator
or
TMA Legacy - "The Arty"
5-Minute Charts:
MA Lengths: 21, 50, 100, 200
MA Type: EMA
Risk: 1%
Risk:Reward: 2:1
Enable RSI Filter: Yes
Sessions: London + NY only
15-Minute Charts:
MA Lengths: 21, 50, 89, 144
MA Type: SMMA
Risk: 1.5%
Risk:Reward: 2.5:1
Enable RSI Filter: Yes
Sessions: All major sessions
30-Minute Charts:
MA Lengths: 13, 34, 55, 89
MA Type: EMA
Risk: 2%
Risk:Reward: 3:1
Enable RSI Filter: No
Sessions: London + NY only
Key Features to Enable:
Dynamic line coloring
Trend fill
All pattern signals
Session backgrounds
Strategy alerts
Trade only during major session overlaps for best liquidity and volatility.
Cs Fenix Us30The price unbalances the Asia and Frankfurt range and if there is a structural change it highlights a possible entry with a stop and target level.
MuLegend's Break & Retest Strategy That worksThank you all for checking this out! This indicator works best on the 1 minute time frame for both MNQ & NQ. ES & MES it also can work too to help you be a sniper. Hopefully you will like it!!!
Zero Lag + ML SuperTrend Strategy (Multi-Symbol) himanshuThis is a multi-symbol trading strategy that combines two indicators:
Zero Lag EMA with volatility filter
ML SuperTrend
Both must agree (bullish or bearish) before entering a trade.
📊 Entry Rules
Long Entry (Buy):
When price is above ZeroLag line (with volatility filter) and above SuperTrend line.
Short Entry (Sell):
When price is below ZeroLag line (with volatility filter) and below SuperTrend line.
📉 Exit Rules
Take Profit (TP): Fixed at +1% from entry price.
Stop Loss (SL): Fixed at -0.5% from entry price.
Trade closes automatically at TP or SL.
⚡ Features
Multi-symbol ready: Works on any chart you apply it to (DOGE, BTC, ETH, Nifty, etc.).
Alerts included: Sends webhook alerts for long entry, short entry, TP hit, and SL hit.
Plots: Displays ZeroLag line and SuperTrend line on the chart.
👉 In short: The system waits until both indicators confirm the same direction, enters a trade, and then exits automatically at a 1% target or 0.5% stop.
LINK/USDT - 9/15 EMA Crossover with SL & TP himanshuThis strategy is designed for the LINK/USDT pair using a simple yet effective Exponential Moving Average (EMA) crossover system.
🔹 How It Works
When the 9 EMA (fast) crosses above the 15 EMA (slow) → it signals bullish momentum → the strategy opens a Long trade.
When the 9 EMA crosses below the 15 EMA → it signals bearish momentum → the strategy opens a Short trade.
🔹 Risk Management
To keep trades disciplined and emotions out of decision-making, built-in exits are applied:
Stop Loss (SL): Automatically closes the trade if price moves 1% against the position.
Take Profit (TP): Locks in profits when price moves 2% in favor of the trade.
🔹 Why Use This Strategy?
✅ Simple and easy-to-follow EMA crossover logic
✅ Automated Stop Loss & Take Profit for risk control
✅ Trades both Long and Short to capture every trend
✅ Can be easily backtested on TradingView for performance validation
Apertura USA - Estrategia Compra8:30 a.m. opening is a very successful strategy in gold with Heikin Ashi candles, 3 minutes, over 80% effectiveness.
Extremum Range MA Crossover Strategy1. Principle of Work & Strategy Logic ⚙️📈
Main idea: The strategy tries to catch the moment of a breakout from a price consolidation range (flat) and the start of a new trend. It combines two key elements:
Moving Average (MA) 📉: Acts as a dynamic support/resistance level and trend filter.
Range Extremes (Range High/Low) 🔺🔻: Define the borders of the recent price channel or consolidation.
The strategy does not attempt to catch absolute tops and bottoms. Instead, it enters an already formed move after the breakout, expecting continuation.
Type: Trend-following, momentum-based.
Timeframes: Works on different TFs (H1, H4, D), but best suited for H4 and higher, where breakouts are more meaningful.
2. Justification of Indicators & Settings ⚙️
A. Moving Average (MA) 📊
Why used: Core of the strategy. It smooths price fluctuations and helps define the trend. The price (via extremes) must cross the MA → signals a potential trend shift or strengthening.
Parameters:
maLength = 20: Default length (≈ one trading month, 20-21 days). Good balance between sensitivity & smoothing.
Lower TF → reduce (10–14).
Higher TF → increase (50).
maSource: Defines price source (default = Close). Alternatives (HL2, HLC3) → smoother, less noisy MA.
maType: Default = EMA (Exponential MA).
Why EMA? Faster reaction to recent price changes vs SMA → useful for breakout strategies.
Other options:
SMA 🟦 – classic, slowest.
WMA 🟨 – weights recent data stronger.
HMA 🟩 – near-zero lag, but “nervous,” more false signals.
DEMA/TEMA 🟧 – even faster & more sensitive than EMA.
VWMA 🔊 – volume-weighted.
ZLEMA ⏱ – reduced lag.
👉 Choice = tradeoff between speed of reaction & false signals.
B. Range Extremes (Previous High/Low) 📏
Why used: Define borders of recent trading range.
prevHigh = local resistance.
prevLow = local support.
Break of these levels on close = trigger.
Parameters:
lookbackPeriod = 5: Searches for highest high / lowest low of last 5 candles. Very recent range.
Higher value (10–20) → wider, stronger ranges but rarer signals.
3. Entry & Exit Rules 🎯
Long signals (BUY) 🟢📈
Condition (longCondition): Previous Low crosses MA from below upwards.
→ Price bounced from the bottom & strong enough to push range border above MA.
Execution: Auto-close short (if any) → open long.
Short signals (SELL) 🔴📉
Condition (shortCondition): Previous High crosses MA from above downwards.
→ Price rejected from the top, upper border failed above MA.
Execution: Auto-close long (if any) → open short.
Exit conditions 🚪
Exit Long (exitLongCondition): Close below prevLow.
→ Uptrend likely ended, range shifts down.
Exit Short (exitShortCondition): Close above prevHigh.
→ Downtrend likely ended, range shifts up.
⚠️ Important: Exit = only on candle close beyond extremes (not just wick).
4. Trading Settings ⚒️
overlay = true → indicators shown on chart.
initial_capital = 10000 💵.
default_qty_type = strategy.cash, default_qty_value = 100 → trades fixed $100 per order (not lots). Can switch to % of equity.
commission_type = strategy.commission.percent, commission_value = 0.1 → default broker fee = 0.1%. Adjust for your broker!
slippage = 3 → slippage = 3 ticks. Adjust to asset liquidity.
currency = USD.
margin_long = 100, margin_short = 100 → no leverage (100% margin).
5. Visualization on Chart 📊
The strategy draws 3 lines:
🔵 MA line (thickness 2).
🔴 Previous High (last N candles).
🟢 Previous Low (last N candles).
Also: entry/exit arrows & equity curve shown in backtest.
Disclaimer ⚠️📌
Risk Warning: This description & code are for educational purposes only. Not financial advice. Trading (Forex, Stocks, Crypto) carries high risk and may lead to full capital loss. You trade at your own risk.
Testing: Always backtest & demo test first. Past results ≠ future profits.
Responsibility: Author of this strategy & description is not responsible for your trading decisions or losses.
Options Straddle Strategy Backtester 140% APR for 2025This script provides the most convenient manual tool for backtesting a straddle stagy in options.
The straddle is when you buy a call and a put option at the same price and the expiration date. You profit when the price movement at expiry (8 am UTC) in either directions surpass the price of the premium paid. The price of opening this straddle on ETH is always 1.6% of the current ETH price including fees.
In my example I use ETH options, I am buying a straddle at 8:30 UTC every day with the next day expiration date. In the script it looks like I am opening a long position on ETH at 8:30 and then close it the next days. We need to use 1 minute chart, chart time set to UTC for exact results and deep back testing function to go back in time.
Once the system generates a trade report - we need to download it and go to the list of trades sections, there we do the following:
1) remove all long entry lines leaving only long exit lines that have all the information we need.
2) We add one column that calculates the cost of premium for every trade: Position size*1.6%=cost of premium with fees.
3)We add a second column copying all Net PNL in USDT changing negative amounts to positive - since it doesn't matter for us which direction the move was towards.
The results are quite impressive: If you were buying straddles during 2025 that is not ended yet you will get 69% return on investment (11K paid in premiums, 19K return, 8K net profit). 2024 and 2025 combined: 53% (29 K, 45 K, and 15 profits).
Moreover, since you have the date of the trade in the table you can filter the results further to figure out if trading on some days is less profitable. Interestingly trades from Sun to Mon given are not profitable at -15% and most profitable days are Mon to Tue - 103%, Friday to Sat - 102 %. So if we remove Sun to Monday trades we will be at 89% for the first 221 days of the year or 140% APR.
RSI DCA StrategyThis strategy combines RSI oversold signals with a Dollar-Cost Averaging (DCA) buying approach.
Trigger:
When the RSI (Relative Strength Index) crosses below 30, the strategy marks an oversold condition.
DCA Entry:
Once triggered, the strategy executes up to three consecutive daily entries (1 per day), splitting the predefined capital equally (configurable by user).
Position Management:
Take Profit at a configurable % above the average entry price.
Stop Loss at a configurable % below the average entry price.
Exit Conditions:
The strategy automatically exits either on reaching Take Profit or Stop Loss.
Visualization:
RSI plotted with oversold line (30).
Take Profit and Stop Loss lines displayed after entry.
Performance Reporting:
Includes an optional monthly performance table for evaluating results by month.
Note:
This strategy is for testing RSI-based mean reversion with staggered entries. It is not financial advice and should be optimized and validated for each market or timeframe before practical use.
TQQQ – 200 SMA ±5% Entry / –3% Exit (since 2010) • Metrics by DE✅ In plain words:
You only buy TQQQ when it’s trading 5% above its 200-day SMA (a sign of strong uptrend momentum).
You stay long as long as the price holds above 3% below the 200-day SMA.
If price falls below that lower threshold, you exit to limit drawdown.
The strategy is designed to catch strong uptrends while cutting losses early.
AI+ Scalper Strategy [BuBigMoneyMazz]Based on the AI+ Scalper Strategy
A trend-following swing strategy that uses multi-factor confirmation (trend, momentum, volatility) to capture sustained moves. Works best in trending markets and avoids choppy conditions using ADX filter.
🎯 5-Minute Chart Settings (Scalping)
pine
// RISK MANAGEMENT
ATR Multiplier SL: 1.2
ATR Multiplier TP: 2.4
// STRATEGY OPTIONS
Use HTF Filter: ON
HTF Timeframe: 15
Latching Mode: OFF
// INDICATOR SETTINGS
ADX Length: 10
ATR Length: 10
HMA Length: 14
Momentum Mode: Stochastic RSI
// STOCH RSI
Stoch RSI Length: 10
%K Smoothing: 2
%D Smoothing: 2
5-Minute Trading Style:
Quick scalps (15-45 minute holds)
Tight stops for fast markets
More frequent signals
Best during high volatility sessions (market open/close)
📈 15-Minute Chart Settings (Day Trading)
pine
// RISK MANAGEMENT
ATR Multiplier SL: 1.5
ATR Multiplier TP: 3.0
// STRATEGY OPTIONS
Use HTF Filter: ON
HTF Timeframe: 60
Latching Mode: ON
// INDICATOR SETTINGS
ADX Length: 14
ATR Length: 14
HMA Length: 21
Momentum Mode: Fisher RSI
// STOCH RSI
Stoch RSI Length: 12
%K Smoothing: 3
%D Smoothing: 3
15-Minute Trading Style:
Swing trades (1-4 hour holds)
Better risk-reward ratio
Fewer, higher quality signals
Works throughout trading day
⚡ Best Trading Times:
5-min: Market open (9:30-11:30 ET) & close (3:00-4:00 ET)
15-min: All day, but best 10:00-3:00 ET
✅ Filter for High-Probability Trades:
Only trade when ADX > 20 (strong trend)
Wait for HTF confirmation (prevents false signals)
Avoid low volume periods (lunch time)
⛔ When to Avoid Trading:
ADX < 15 (choppy market)
Major news events
First/last 15 minutes of session
Pro Tip: Start with 15-minute settings for better consistency, then move to 5-minute once you're comfortable with the strategy's behavior.
Hilly's 0010110 Reversal Scalping Strategy - 5 Min CandlesKey Features and Rationale:
Timeframe: Restricted to 5-minute candles as requested.
Pattern Integration: Includes single (Hammer, Shooting Star, Doji), two (Engulfing, Harami), and three-plus (Morning Star, Evening Star) candlestick patterns, plus reversal patterns based on RSI extremes.
VWAP Cross: Incorporates bullish (price crosses above VWAP) and bearish (price crosses below VWAP) signals, enhanced by trend context.
Volume Analysis: Uses a volume spike threshold to filter noise, with a simple day-start volume comparison for financial environment context.
Financial Environment: Approximates the day's sentiment using early-hour volume compared to current volume, adjusted by trend.
Aggregation: Scores each condition (e.g., 1 for basic patterns, 2 for strong patterns like Engulfing, 3 for three-candle patterns) and decides based on weighted consensus, with trendStrength as a tunable threshold.
Risky Approach: Minimal filtering and a low trendStrength (default 0.5) allow frequent signals, aligning with your $100-to-$200 goal, but expect higher risk.
Suggested Inputs:
EMA Length: 10 (short enough for 5-minute sensitivity).
VWAP Lookback: 1 (uses current session VWAP).
Volume Threshold Multiplier: 1.2 (moderate spike requirement).
RSI Length: 14 (standard, adjustable to 7 for more sensitivity).
Trend Strength Threshold: 0.5 (balance between signals; lower to 0.4 for more trades, raise to 0.6 for fewer).
Hull Suite Strategy with Time Filter. it This script filter the initial false signal at the opening of market
ORB Breakout Strategy with reversalORB 1,5,15,30,60min with reversals, its my first strategy Im not 100% sure it works well. Im not a programmer nor a profitable trader.
Max stoploss in points sets maximum fixed stoploss
Stop offset sets additional points below/above signal bar
RR Ratio is pretty self explanatory, it sets target based on stoploss
American session is time when positions can be opened
ORB SessionIs basically almost the same but when the time runs it closes all positions\
ORB candle timeframe is the time which orb is measured
Enable reverse position enables reversing positions on stoploss of first position, stoploss of reverse position is based on max stoploss and target is set by RR times max stoploss
Im sharing this to share this with my friends, discuss some things and dont have to test it manually.
I made it all myself and with help of AI
Sorry for bad english
Structure Strategycreated to spot key area needed to take valid trades in most market conditions. use beside RSI MACD
Clear Signal Trading Strategy V5Clear Signal Trading Strategy - Description
This strategy uses a simple 0-5 point scoring system to identify high-probability trades. It combines trend following with momentum confirmation to generate clear BUY/SELL signals while filtering out market noise.
How it works: The strategy waits for EMA crossovers, then scores the setup based on trend alignment, momentum, RSI position, and volume. Only trades scoring above your chosen threshold are executed.
Recommended Settings by Market Type
For Beginners / Risk-Averse Traders:
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1-2%
Stop Loss Type: ATR
ATR Multiplier: 2.5
Risk:Reward Ratio: 2.0
For Trending Markets (Strong Directional Movement):
Signal Sensitivity: Balanced
Volume Confirmation: ON
Risk Per Trade: 2%
Stop Loss Type: ATR
ATR Multiplier: 2.0
Risk:Reward Ratio: 2.5-3.0
For Ranging/Choppy Markets:
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1%
Stop Loss Type: Percentage
Percentage Stop: 2%
Risk:Reward Ratio: 1.5
For Volatile Markets (Crypto/High Beta Stocks):
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1%
Stop Loss Type: ATR
ATR Multiplier: 3.0
Risk:Reward Ratio: 2.0
Best Practices
Timeframes:
15-minute to 1-hour for day trading
4-hour to daily for swing trading
Works best on liquid instruments with good volume
When to avoid trading:
When dashboard shows "HIGH" volatility above 4%
During major news events
When win rate drops below 40%
In markets with no clear trend (prolonged NEUTRAL state)
Success tips:
Start with Conservative mode until you see 10+ successful trades
Only increase to Balanced mode when win rate exceeds 55%
Never use Aggressive mode unless market shows strong trend for 5+ days
Always honor the stop loss - no exceptions
Take partial profits at first target if unsure
Hilega Milega v6 - Pure EMA/SMA (Nitesh Kumar) + Full BacktestHilega to milega
he Hilega Milega Strategy, inspired by the technique of Nitesh Kumar, is designed for intraday and swing traders who want structured entries and exits with clear demand–supply logic.
🔑 Core Features
Demand & Supply Zones – Automatically plots potential strong buying and selling zones for high-probability trades.
Trend Identification – Uses a blend of EMAs/SMA crossovers to identify bullish and bearish market bias.
Buy & Sell Signals – Generates real-time visual signals based on “Hilega Milega” rules for quick decision-making.
Risk Management – Suggested stop-loss levels are derived from recent demand–supply areas to minimize drawdowns.
Backtesting Enabled – Traders can test the performance across multiple assets (stocks, forex, crypto, commodities).
📊 How It Works
Buy Signal → When price action confirms a bullish zone with supporting trend filters.
Sell Signal → When price action confirms a bearish zone or reversal pattern.
Flat/Exit → Position closed when opposite signal triggers or demand–supply imbalance fades.
⚡ Best Use Cases
Intraday trading (5m, 15m, 1H charts).
Swing trading (4H, Daily charts).
Works across stocks, crypto, commodities, and forex.
⚠️ Disclaimer: This strategy is for educational purposes. Backtest thoroughly and apply proper risk management before live trading.