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Strategy vault / Trend following

Volume Weighted Dual Trend Detection System

This is a trend detection system that combines trading volume weighting and price movement. The system calculates the difference between opening and closing prices (Delta value), weighted by trading volume, to form a…

Pine ScriptTrend followingMean reversionMomentumEMASMAVolume
Author
ChaoZhang
Complexity
Starter · 59 lines
Parameters
0
Backtest bar
1d · swing
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

IMG

Overview

This is a trend detection system that combines trading volume weighting and price movement. The system calculates the difference between opening and closing prices (Delta value), weighted by trading volume, to form a unique trend indicator. The system also integrates a Simple Moving Average (SMA) for signal confirmation, determining market trends by comparing the Delta value with its SMA. Additionally, the system incorporates EMA as an auxiliary indicator, forming a multi-dimensional analytical framework.

Strategy Principles

  1. Delta Value Calculation: Uses the difference between opening and closing prices within a specific period, weighted by trading volume
  2. Signal Generation Mechanism:
    • When Delta crosses above its SMA, the system identifies a bearish signal
    • When Delta crosses below its SMA, the system identifies a bullish signal
  3. EMA Integration:
    • System uses 20-period EMA for trend confirmation
    • EMA color changes based on Delta value's position relative to its SMA
  4. Volume Filter: Sets volume threshold to ensure trading occurs under sufficient liquidity conditions

Strategy Advantages

  1. Multi-dimensional Analysis: Combines price, volume, and moving average systems for a more comprehensive market perspective
  2. Signal Reliability: Reduces random price fluctuation effects through volume weighting
  3. Strong Adaptability: Operates effectively across multiple timeframes, including 4-hour and daily
  4. Parameter Flexibility: Offers multiple adjustable parameters for optimization across different market characteristics
  5. Risk Control: Built-in volume filtering mechanism effectively avoids low liquidity environments

Strategy Risks

  1. Trend Reversal Risk: May generate false signals in volatile markets
  2. Parameter Sensitivity: Different parameter combinations may lead to significant strategy performance variations
  3. Time Lag Risk: Inherent lag in moving average systems may delay entry timing
  4. Market Environment Dependency: May generate frequent trading signals in sideways markets

Strategy Optimization Directions

  1. Introduce Dynamic Parameters:
    • Automatically adjust Delta calculation period based on market volatility
    • Dynamically adjust volume threshold based on volume changes
  2. Enhance Signal Filtering:
    • Add trend strength confirmation indicators
    • Integrate price pattern recognition systems
  3. Improve Risk Management:
    • Establish dynamic stop-loss mechanism
    • Introduce position management system

Summary

This is a systematic strategy that organically combines price momentum, trading volume, and trend indicators. Through multi-dimensional analysis and strict trading condition screening, the strategy maintains high reliability while demonstrating good adaptability and scalability. The core advantage lies in its three-dimensional judgment of market trends, while its greatest development potential lies in dynamic parameter optimization and risk management system improvement.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-09 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Volume-Weighted Delta Strategy", overlay=true)

// Input-parametrit
length_delta = input.int(5, minval=1, title="Delta Length")
length_ma = input.int(5, minval=1, title="MA Length")
length_sma = input.int(5, minval=1, title="MA Length")
volume_threshold = input.float(100000, title="Volume Threshold")

// Funktio delta-arvojen laskemiseksi ja volyymin mukaan painottamiseksi
calculate_volume_weighted_delta(delta_length) =>
    delta_sum = 0.0
    for i = 0 to delta_length - 1
        delta_sum := delta_sum + ((close[i] - open[i]) * volume[i])
    delta_sum







// Laskenta
delta_value = calculate_volume_weighted_delta(length_delta)
ma_value = ta.sma(delta_value, length_sma)


ema20 = ta.ema(close, 20)
// EMA:n värin määrittely
ema_color = delta_value  > ma_value ? color.green : color.red

positive = ta.crossover(delta_value, ma_value)
negative = ta.crossunder(delta_value, ma_value)

// Piirretään graafit

plot(ema20, color=ema_color, title="20 EMA")


BullishCond = ta.crossover(ma_value, delta_value)
BearishCond = ta.crossunder(ma_value, delta_value)


if (BullishCond)
    strategy.entry("Sell", strategy.short)




if (BearishCond)
    strategy.entry("Buy", strategy.long)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-12-11. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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