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Dual Momentum Strategy

Author: ChaoZhang, Date: 2023-09-28 15:03:57
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Overview

The Dual Momentum strategy uses fast and slow momentum indicators to generate entry and exit signals. It is a fast-reacting strategy well-suited for trending instruments on the daily and 4-hour timeframes. This implementation is based on the QuantCT app.

The strategy allows configuring long/short or long-only mode. It also allows enabling fixed stop loss or ignoring it so that the strategy acts solely on entry and exit signals.

Strategy Logic

The strategy uses fast period momentum (default 5 days) and slow period momentum (default 10 days).

When slow momentum and fast momentum are both above 0, a long entry signal is generated.

When slow momentum or fast momentum goes below 0, an exit signal is generated.

Similarly, when slow momentum and fast momentum are both below 0, a short entry signal is generated. When slow momentum or fast momentum goes above 0, an exit signal is generated.

Thus, the strategy captures trend changes using the crossover of two momentum indicators with different periods.

Advantage Analysis

  • Using dual momentum provides more accurate trend change detection and fewer false signals.

  • Fast period momentum reacts quickly to market changes, while slow period filters out noise.

  • Flexible long/short or long-only modes suit different trading preferences.

  • Optional stop loss controls risk.

  • Fast-reacting nature makes it suitable for trend trading on daily or higher timeframes for outsized gains.

Risk Analysis

  • Dual momentum relies on indicator values above/below 0, which has some lag.

  • The strategy is more trend-dependent and may underperform in range-bound markets with more whipsaws.

  • Not using stop loss risks large losses.

  • Wrong choice of symbols or timeframes can lead to poor results.

To control risks, tune the momentum periods, use reasonable fixed stop loss percentage, select strongly trending symbols and run on daily or higher timeframes.

Enhancement Opportunities

The strategy can be enhanced in several ways:

  1. Add filters like MACD or RSI to avoid wrong trades at trend turning points.

  2. Add adaptive stop loss to adjust stop distance based on market volatility.

  3. Optimize momentum parameters for different symbols via stepwise optimization, walk forward analysis etc.

  4. Add position sizing rules to adjust new position size based on past performance.

  5. Differentiate long and short market conditions for asymmetric entries and exits.

Conclusion

The Dual Momentum strategy captures trend direction using fast and slow momentum crossover. Using simple indicators to detect trend changes, it is suitable for riding intraday or multi-day trends and generating excess returns. Proper risk control via stop loss, symbol/parameter optimization can improve consistency.


/*backtest
start: 2023-08-28 00:00:00
end: 2023-09-27 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © QuantCT

//@version=4
strategy("Momentum Strategy Idea",
         shorttitle="Momentum", 
         overlay=false,
         pyramiding=0,     
         default_qty_type=strategy.percent_of_equity, 
         default_qty_value=100, 
         initial_capital=1000,           
         commission_type=strategy.commission.percent, 
         commission_value=0.075)

// ____ Inputs

fast_period = input(title="Fast Period", defval=5) 
slow_period = input(title="Slow Period", defval=10)
long_only = input(title="Long Only", defval=false)
slp = input(title="Stop-loss (%)", minval=1.0, maxval=25.0, defval=5.0)
use_sl = input(title="Use Stop-Loss", defval=false)

// ____ Logic

mom_fast = mom(close, fast_period)
mom_slow = mom(close, slow_period)
    
enter_long = (mom_slow > 0 and mom_fast > 0)
exit_long = (mom_slow < 0 or mom_fast < 0)
enter_short = (mom_slow < 0 and mom_fast < 0)
exit_short = (mom_slow > 0 or mom_fast > 0)

strategy.entry("Long", strategy.long, when=enter_long)
strategy.close("Long", when=exit_long) 
if (not long_only)
    strategy.entry("Short", strategy.short, when=enter_short)
    strategy.close("Short", when=exit_short) 
   
// ____ SL

sl_long = strategy.position_avg_price * (1- (slp/100))
sl_short = strategy.position_avg_price * (1 + (slp/100))
if (use_sl)
    strategy.exit(id="SL", from_entry="Long", stop=sl_long)
    strategy.exit(id="SL", from_entry="Short", stop=sl_short)
    
// ____ Plots

colors = 
 enter_long ? #27D600 :
 enter_short ? #E30202 :
 color.orange

mom_fast_plot = plot(mom_fast, color=colors)
mom_slow_plot = plot(mom_slow, color=colors)
fill(mom_fast_plot, mom_slow_plot, color=colors, transp=50)








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