ianzeng123
Overview
This is an innovative quantitative trading strategy that provides a structured approach to trading by integrating liquidity zone entries, ATR volatility thresholds, and dynamic risk management. The strategy combines multiple technical analysis indicators to identify high-probability trading opportunities and automatically calculate take profit and stop loss levels.
Strategy Principles
The core principles of the strategy are based on the following key elements:
- Liquidity Zone Analysis: Identifying potential support and resistance areas by calculating the lowest and highest points over a specific period.
- ATR Volatility Filtering: Using Average True Range (ATR) as a dynamic threshold for entry and risk management.
- Trend Filtering: Combining 50-period Exponential Moving Average (EMA) and Relative Strength Index (RSI) to confirm market trend and momentum.
- Dynamic Risk Management: Automatically calculating take profit and stop loss levels based on ATR, with flexible risk/reward ratio adjustment.
Strategy Advantages
- Multi-Dimensional Signal Generation: Combining liquidity, volatility, and trend filtering to improve signal quality.
- Adaptive Risk Management: Dynamically adjusting take profit and stop loss to effectively control trading risk.
- Flexible Parameter Configuration: Customizable ATR length, liquidity period, and trading session.
- Visualization Support: Providing visualization of liquidity lines and first candle level.
- Performance Tracking: Built-in trading statistics table displaying win rate and trade outcomes directly on the chart.
Strategy Risks
- Parameter Sensitivity: Strategy performance highly depends on parameter selection, requiring continuous backtesting and optimization.
- Market Adaptability: Potential instability in markets with unclear trends or high volatility.
- False Breakout Risk: Potential for misreported liquidity zone breakouts.
- Trading Frequency: Session filtering and multiple conditions may reduce trading opportunities.
- Backtest Bias: The 64% historical win rate may not fully represent future performance.
Strategy Optimization Directions
- Machine Learning Integration: Introducing machine learning algorithms for dynamic parameter and signal generation adjustment.
- Multi-Market Adaptability: Developing more universal parameter settings applicable to different markets and instruments.
- Advanced Risk Management: Implementing more complex position sizing and risk allocation algorithms.
- Signal Confirmation Mechanism: Adding additional confirmation indicators like volume or other technical indicators.
- Real-Time Performance Monitoring: Developing real-time performance assessment and adaptive adjustment modules.
Summary
The ThinkTech AI Trading Strategy provides traders with a powerful quantitative trading tool through an innovative multi-factor approach. By leveraging liquidity analysis, volatility filtering, and dynamic risk management, the strategy aims to identify high-quality trading opportunities. However, traders must continuously backtest, optimize, and apply the strategy cautiously to fully realize its potential.
Strategy source code
/*backtest
start: 2025-01-01 00:00:00
end: 2025-03-30 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"ETH_USDT"}]
*/
if high > ta.highest(high[1], 5)
strategy.entry("Enter Long", strategy.long)
else if low < ta.lowest(low[1], 5)
strategy.entry("Enter Short", strategy.short)//@version=6
strategy("ThinkTech AI Signals", overlay=true, initial_capital=100000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)
//──────────────────────────────
// Input Settings
//──────────────────────────────
riskRewardRatio = input.float(title="Risk/Reward Ratio", defval=2.0, minval=1.0, step=0.1)
// Inputs from second script
liquidity_period = input.int(20, title="Liquidity Base Period")
atr_length = input.int(14, title="ATR Length")
atr_threshold = input.float(0.3, title="ATR Breakout Threshold")
take_profit_mult = input.float(0.25, title="Take-Profit Multiplier")
stop_loss_mult = input.float(0.75, title="Stop-Loss Multiplier")
vol_filter = input.bool(true, title="Enable Volume Filter")
session_filter = input.bool(true, title="Limit to Trading Session")
// Additional inputs for further filtering and settings
atrMultiplier = input.float(title="ATR Multiplier for Stop Loss", defval=1.5, minval=0.1, step=0.1)
retestCushionLong = input.float(title="Retest Cushion Factor for BUY", defval=1.0, minval=1.0, step=0.001)
retestCushionShort = input.float(title="Retest Cushion Factor for SELL", defval=1.0, minval=0.0, maxval=1.0, step=0.001)
useTrendFilter = input.bool(title="Use 50 EMA Trend Filter", defval=true)
useRSIFilter = input.bool(title="Use RSI Filter", defval=false)
rsiPeriod = input.int(title="RSI Period", defval=14, minval=1)
rsiOversold = input.float(title="RSI Oversold Level", defval=30.0, minval=1, maxval=50)
rsiOverbought = input.float(title="RSI Overbought Level", defval=70.0, minval=50, maxval=100)
// Option to remove plotted lines
showLiquidityLines = input.bool(true, title="Show Liquidity Lines")
showFirstCandleLines = input.bool(true, title="Show First Candle Level Lines")
//──────────────────────────────
// Calculations & Variables (Liquidity & ATR Based)
//──────────────────────────────
price = close
atr = ta.atr(atr_length)
vol_condition = volume > ta.sma(volume, 20)
// Define Liquidity Base and Apex for support/resistance
liquidity_base = ta.lowest(low, liquidity_period)
apex = ta.highest(high, liquidity_period)
// Track recent highs and lows for filtering
hh = ta.highest(high, 30)
ll = ta.lowest(low, 30)
//──────────────────────────────
// Trade Stats Variables
//──────────────────────────────
var float take_profit = na
var float stop_loss = na
var bool in_trade = false
var int win_count = 0
var int loss_count = 0
//──────────────────────────────
// ENTRY LOGIC (BUY) Based on Liquidity & ATR
//──────────────────────────────
breakout_up = price > liquidity_base + (atr * atr_threshold)
point_of_release = ta.crossover(price, liquidity_base) and breakout_up
retest_buy = price > liquidity_base and price < hh and not in_trade
// Session condition (e.g. trading between 9AM–12PM)
session_condition = (hour >= 9 and hour <= 12) or not session_filter
if (point_of_release or retest_buy) and (vol_condition or not vol_filter) and session_condition
strategy.entry("Buy", strategy.long)
take_profit := price + (atr * take_profit_mult)
stop_loss := liquidity_base - (atr * stop_loss_mult)
in_trade := true
alert("Buy Signal - Price: " + str.tostring(price), alert.freq_once_per_bar)
//──────────────────────────────
// ENTRY LOGIC (SELL) Based on Liquidity & ATR
//──────────────────────────────
breakout_down = price < apex - (atr * atr_threshold)
clean_break = ta.crossunder(price, apex) and breakout_down
retest_sell = price < apex and price > ll and not in_trade
if (clean_break or retest_sell) and (vol_condition or not vol_filter) and session_condition
strategy.entry("Sell", strategy.short)
take_profit := price - (atr * take_profit_mult)
stop_loss := apex + (atr * stop_loss_mult)
in_trade := true
alert("Sell Signal - Price: " + str.tostring(price), alert.freq_once_per_bar)
//──────────────────────────────
// EXIT LOGIC (For BUY & SELL)
//──────────────────────────────
if strategy.position_size > 0
if price >= take_profit
strategy.close("Buy", comment="Take Profit")
win_count += 1
in_trade := false
if price <= stop_loss
strategy.close("Buy", comment="Stop Loss")
loss_count += 1
in_trade := false
if strategy.position_size < 0
if price <= take_profit
strategy.close("Sell", comment="Take Profit")
win_count += 1
in_trade := false
if price >= stop_loss
strategy.close("Sell", comment="Stop Loss")
loss_count += 1
in_trade := false
//──────────────────────────────
// Plot Liquidity Lines (Support/Resistance)
//──────────────────────────────
plot(showLiquidityLines ? liquidity_base : na, color=color.green, title="Liquidity Base (Support)")
plot(showLiquidityLines ? apex : na, color=color.red, title="Apex (Resistance)")
//──────────────────────────────
// Debugging Signal Shapes
//──────────────────────────────
plotshape(series=point_of_release, location=location.belowbar, color=color.green, style=shape.triangleup, title="Buy Signal")
plotshape(series=clean_break, location=location.abovebar, color=color.red, style=shape.triangledown, title="Sell Signal")
//──────────────────────────────
// Win/Loss Table Display
//──────────────────────────────
var table t = table.new(position.top_right, 1, 2)
if bar_index == last_bar_index
table.cell(t, 0, 0, "Wins: " + str.tostring(win_count), bgcolor=color.new(color.green, 80))
table.cell(t, 0, 1, "Losses: " + str.tostring(loss_count), bgcolor=color.new(color.red, 80))
//──────────────────────────────
// Alert Conditions for Entries and Exits
//──────────────────────────────
alertcondition(point_of_release, title="Buy Alert", message="Buy Signal Triggered")
alertcondition(clean_break, title="Sell Alert", message="Sell Signal Triggered")
var int lastClosedTrades = 0
var bool exitSignal = false
if strategy.closedtrades > lastClosedTrades
exitSignal := true
lastClosedTrades := strategy.closedtrades
alertcondition(exitSignal, title="EXIT Signal", message="EXIT signal triggered: Trade has closed (TP or SL reached).")
//──────────────────────────────
// FIRST 15-MINUTE CANDLE CAPTURE (9:30–9:45 AM EST)
//──────────────────────────────
newDay = dayofmonth != dayofmonth[1]
var float fHigh = na
var float fLow = na
var bool firstCandleCaptured = false
if newDay
fHigh := high
fLow := low
firstCandleCaptured := true
//──────────────────────────────
// Additional Filters & Calculations
//──────────────────────────────
// Trend Filter: 50 EMA
ema50 = ta.ema(close, 50)
longFilter = not useTrendFilter or (close > ema50)
shortFilter = not useTrendFilter or (close < ema50)
// ATR-Based Stop Loss Buffer
atrValue = ta.atr(14)
stopLossBuffer = atrValue * atrMultiplier
// RSI Calculation (if enabled)
rsiValue = ta.rsi(close, rsiPeriod)
//──────────────────────────────
// ENTRY CONDITIONS (15-Minute Candle Retest)
//──────────────────────────────
// Breakout/Breakdown based on the first candle levels
buyBreakout = firstCandleCaptured and ta.crossover(close, fHigh)
sellBreakdown = firstCandleCaptured and ta.crossunder(close, fLow)
// Retest conditions: price must retest the level after the breakout/breakdown
buyRetest = firstCandleCaptured and (low <= fHigh) and (close > fHigh)
sellRetest = firstCandleCaptured and (high >= fLow) and (close < fLow)
// Final entry signals (with optional RSI filter)
buySignal = buyBreakout and buyRetest and longFilter and (strategy.position_size == 0) and (not useRSIFilter or (rsiValue < rsiOversold))
sellSignal = sellBreakdown and sellRetest and shortFilter and (strategy.position_size == 0) and (not useRSIFilter or (rsiValue > rsiOverbought))
//──────────────────────────────
// Trade Parameters for 15-Minute Candle Retest
//──────────────────────────────
candleRange = fHigh - fLow
stopLossBuy = fLow - stopLossBuffer
takeProfitBuy = fHigh + (candleRange * riskRewardRatio)
stopLossSell = fHigh + stopLossBuffer
takeProfitSell = fLow - (candleRange * riskRewardRatio)
//──────────────────────────────
// Execute Trades for 15-Minute Candle Retest
//──────────────────────────────
if buySignal
strategy.entry("BUY", strategy.long)
strategy.exit("TP/SL BUY", "BUY", stop=stopLossBuy, limit=takeProfitBuy)
if sellSignal
strategy.entry("SELL", strategy.short)
strategy.exit("TP/SL SELL", "SELL", stop=stopLossSell, limit=takeProfitSell)
//──────────────────────────────
// Plot First Candle Level Lines (Optional)
//──────────────────────────────
plot(showFirstCandleLines and firstCandleCaptured ? fHigh : na, title="First Candle High", color=color.blue, linewidth=2)
plot(showFirstCandleLines and firstCandleCaptured ? fLow : na, title="First Candle Low", color=color.red, linewidth=2)