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Strategy vault / Trend following

Multi Timeframe Volume and Trend Confluence Trading Strategy

This is a complex multi-indicator trading strategy that combines Volume Weighted Average Price (AVWAP), Fixed Range Volume Profile (FRVP), Exponential Moving Average (EMA), Relative Strength Index (RSI), Average…

Author
ianzeng123
Complexity
Starter · 81 lines
Parameters
0
Backtest bar
1d · swing
Tested on
DOGE/USDT · futures

IMG IMG

Overview

This is a complex multi-indicator trading strategy that combines Volume Weighted Average Price (AVWAP), Fixed Range Volume Profile (FRVP), Exponential Moving Average (EMA), Relative Strength Index (RSI), Average Directional Index (ADX), and Moving Average Convergence Divergence (MACD) to identify high-probability trading opportunities through indicator confluence.

Strategy Principle

The strategy determines entry signals through multiple conditions:

  1. Price crossing with AVWAP
  2. Price position relative to EMA
  3. RSI strength assessment
  4. MACD trend momentum
  5. ADX trend strength confirmation
  6. Volume filter

The strategy focuses on Asian, London, and New York trading sessions, which typically have better liquidity and more reliable trading signals. Entry logic includes both long and short modes, with a gradient take-profit and stop-loss mechanism.

Strategy Advantages

  1. Multi-indicator combination improving signal accuracy
  2. Dynamic volume filtering to avoid low-liquidity trades
  3. Flexible take-profit and stop-loss strategy
  4. Optimization based on different trading sessions
  5. Dynamic risk management mechanism
  6. Visualization signals to assist decision-making

Strategy Risks

  1. Increased signal complexity due to multiple indicators
  2. Potential overfitting in backtesting data
  3. Potential performance instability under different market conditions
  4. Trading costs and slippage may affect actual returns

Strategy Optimization Directions

  1. Introduce machine learning algorithms for dynamic parameter adjustment
  2. Increase trading session adaptability
  3. Optimize take-profit and stop-loss strategies
  4. Add more filtering conditions
  5. Develop a universal strategy model across different instruments

Summary

This is a highly customized and multi-dimensional trading strategy that attempts to improve trading signal quality and accuracy by integrating multiple technical indicators and trading session characteristics. The strategy demonstrates the complexity of indicator confluence and dynamic risk management in quantitative trading.

Source Pine Script

/*backtest
start: 2024-04-02 00:00:00
end: 2024-12-31 00:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"DOGE_USDT"}]
*/

//@version=6
strategy("FRVP + AVWAP by Grok", overlay=true, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)

// User Inputs
frvpLength = input.int(20, title="FRVP Length", minval=1)
emaLength = input.int(75, title="EMA Length", minval=1) // Adjusted for stronger trend confirmation
rsiLength = input.int(14, title="RSI Length", minval=1)
adxThreshold = input.int(20, title="ADX Strength Threshold", minval=0, maxval=100)
volumeMultiplier = input.float(1.0, title="Volume Multiplier", minval=0.1)

// Stop Loss & Take Profit for XAUUSD
stopLossPips = 25 // 25 pips SL for Asian, London, NY Sessions
takeProfit1Pips = 35 // TP1 at 35 pips
takeProfit2Pips = 80 // Final TP at 80 pips

// Stop-Loss & Take-Profit Multipliers (XAUUSD: 1 pip = 0.1 points on most platforms)
stopMultiplier = float(stopLossPips) * 0.1
tp1Multiplier = float(takeProfit1Pips) * 0.1
tp2Multiplier = float(takeProfit2Pips) * 0.1

// Indicators
avwap = ta.vwap(close)  // Volume Weighted Average Price (VWAP)
ema = ta.ema(close, emaLength)     // Exponential Moving Average
rsi = ta.rsi(close, rsiLength)     // Relative Strength Index
macdLine = ta.ema(close, 12) - ta.ema(close, 26)  // MACD Line
signalLine = ta.ema(macdLine, 9)   // MACD Signal Line
atr = ta.atr(14)                   // Average True Range

// Average Directional Index (ADX)
adxSmoothing = 14
[diplus, diminus, adx] = ta.dmi(14, adxSmoothing)  // Corrected syntax for ta.dmi()

// Volume Profile (FRVP - Fixed Range Volume Profile Midpoint)
highestHigh = ta.highest(high, frvpLength)
lowestLow = ta.lowest(low, frvpLength)
frvpMid = (highestHigh + lowestLow) / 2  // Midpoint of the range

// Detect Trading Sessions
currentHour = hour(time, "UTC")  // Renamed to avoid shadowing built-in 'hour'
isAsianSession = currentHour >= 0 and currentHour < 8
isLondonSession = currentHour >= 8 and currentHour < 16
isNYSession = currentHour >= 16 and currentHour < 23

// Entry Conditions
longCondition = ta.crossover(close, avwap) and close > ema and rsi > 30 and macdLine > signalLine and adx > adxThreshold
shortCondition = ta.crossunder(close, avwap) and close < ema and rsi < 70 and macdLine < signalLine and adx > adxThreshold

// Volume Filter
avgVolume = ta.sma(volume, 20)     // 20-period Simple Moving Average of volume
volumeFilter = volume > avgVolume * volumeMultiplier  // Trade only when volume exceeds its moving average

// Trade Execution with SL/TP for Sessions
if (longCondition and volumeFilter and (isAsianSession or isLondonSession or isNYSession))
    strategy.entry("LongEntry", strategy.long, qty=100)
    strategy.exit("LongTP1", from_entry="LongEntry", limit=close + tp1Multiplier)
    strategy.exit("LongExit", from_entry="LongEntry", stop=close - stopMultiplier, limit=close + tp2Multiplier)

if (shortCondition and volumeFilter and (isAsianSession or isLondonSession or isNYSession))
    strategy.entry("ShortEntry", strategy.short, qty=100)
    strategy.exit("ShortTP1", from_entry="ShortEntry", limit=close - tp1Multiplier)
    strategy.exit("ShortExit", from_entry="ShortEntry", stop=close + stopMultiplier, limit=close - tp2Multiplier)

// Plotting for Debugging and Visualization
plot(avwap, "AVWAP", color=color.purple, style=plot.style_line, offset=0)
plot(ema, "EMA", color=color.orange, style=plot.style_line, offset=0)
// plot(rsi, "RSI", color=color.yellow, style=plot.style_histogram, offset=0)  // Better in a separate pane
// plot(macdLine, "MACD Line", color=color.blue, style=plot.style_histogram, offset=0)  // Better in a separate pane
// plot(signalLine, "Signal Line", color=color.red, style=plot.style_histogram, offset=0)  // Better in a separate pane
plot(adx, "ADX", color=color.green, style=plot.style_line, offset=0)

// Optional: Plot entry/exit signals for visualization
plotshape(longCondition and volumeFilter ? close : na, title="Long Signal", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.tiny)
plotshape(shortCondition and volumeFilter ? close : na, title="Short Signal", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.tiny)

Published by ianzeng123 on the FMZ strategy square · last modified 2025-04-02. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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