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基于资金曲线的仓位管理策略Dynamic-Position-Sizing-Strategy-Based-on-Equity-Curve.md

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Name

基于资金曲线的仓位管理策略Dynamic-Position-Sizing-Strategy-Based-on-Equity-Curve

Author

ChaoZhang

Strategy Description

IMG [trans]

策略概述

本策略的核心思路是根据资金曲线的走势来动态调整仓位大小,在盈利时加大仓位,在亏损时减小仓位,以控制整体风险。该策略同时结合了Chande动量指标、SuperTrend指标和动量指标来识别交易信号。

策略原理

该策略使用两种方式判断资金曲线是否处于下行趋势:1)计算资金曲线的快速和慢速简单移动平均线,如果快速SMA低于慢速SMA,则判断为下行;2)计算资金曲线与其本身较长周期的简单移动平均线,如果资金曲线低于该移动平均线,则判断为下行。

当判断资金曲线下行时,仓位会根据设定减少或增加一定比例。例如,如果设定减少50%,则原先10%的仓位会减少至5%。该策略使得盈利时加大仓位规模,亏损时减小仓位规模,以控制整体风险。

策略优势

  • 利用资金曲线判断系统整体盈亏情况,动态调整仓位有助于控制风险
  • 结合多个指标判断入场,可提高获利概率
  • 可自定义仓位调整的参数,适应不同风险偏好

策略风险

  • 仓位放大时亏损也会被放大
  • 参数设置不当可能导致仓位调整过于激进
  • 仓位管理并不能完全规避系统性风险

优化思路

  • 测试不同仓位调整参数的效果
  • 尝试其他指标组合判断资金曲线走势
  • 优化入场条件,提高胜率

总结

本策略总体思路清晰,利用资金曲线动态调整仓位,可有效控制风险,值得进一步测试与优化。参数设置和止损策略也需要充分考虑,避免激进操作带来的风险。

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Strategy Overview

The core idea of this strategy is to dynamically adjust position size based on the trend of the equity curve - increase position size during profit and decrease size during loss to control overall risk. The strategy also combines Chande Momentum indicator, SuperTrend indicator and Momentum indicator to identify trading signals.

Strategy Name

Dynamic Position Sizing Strategy Based on Equity Curve

Strategy Logic

The strategy uses two methods to determine if the equity curve is in a downtrend: 1) Calculate fast and slow simple moving averages of the equity curve, if the fast SMA is below the slow one, it is considered a downtrend; 2) Calculate the equity curve against its own longer period simple moving average, if the equity is below the moving average line, it is considered a downtrend.

When equity curve downtrend is determined, the position size will be reduced or increased by a certain percentage based on the settings. For example, if 50% reduction is set, the original 10% position size will be reduced to 5%. This mechanism increases position size during profit and decreases size during loss to control overall risk.

Advantages

  • Uses equity curve to judge the overall profit/loss and dynamically adjusts position size to control risk
  • Combining multiple indicators to identify entry signals can improve win rate
  • Customizable parameters for position adjustment suit different risk appetites

Risks

  • Loss can be amplified with increased position size during profit
  • Aggressive adjustment due to improper parameter settings
  • Position sizing alone cannot completely avoid system risk

Enhancement Directions

  • Test effectiveness of different position adjustment parameters
  • Try other indicators to determine equity curve trend
  • Optimize entry conditions to improve win rate

Conclusion

The overall logic of this strategy is clear - it dynamically adjusts position size based on equity curve, which helps effectively control risk. Further testing and optimization of parameters and stop loss strategies are needed to avoid the risk of aggressive maneuvers.

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Strategy Arguments

Argument Default Description
v_input_bool_1 true Use Trading the Equity Curve Position Sizing
v_input_float_1 10 Initial % Equity
v_input_int_1 25 Slow SMA Period
v_input_int_2 9 Fast SMA Period
v_input_bool_2 true Use Fast/Slow Avg
v_input_string_1 0 Position Size Adjustment: Reduce size by (%)
v_input_int_3 50 Increase/Decrease % Equity by:
v_input_int_4 9 Chande Momentum Length
v_input_int_5 10 Chande Momentum Signal
v_input_int_6 10 SuperTrend ATR Length
v_input_float_2 3 SuperTrend Factor
v_input_int_7 12 Momentum Length

Source (PineScript)

/*backtest
start: 2024-01-08 00:00:00
end: 2024-01-15 00:00:00
period: 3m
basePeriod: 1m
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/
// © shardison
//@version=5

//EXPLANATION
//"Trading the equity curve" as a risk management method is the 
//process of acting on trade signals depending on whether a system’s performance
//is indicating the strategy is in a profitable or losing phase.
//The point of managing equity curve is to minimize risk in trading when the equity curve is  in a downtrend. 
//This strategy has two modes to determine the equity curve downtrend:
//By creating two simple moving averages of a portfolio's equity curve - a short-term
//and a longer-term one - and acting on their crossings. If the fast SMA is below
//the slow SMA, equity downtrend is detected (smafastequity < smaslowequity).
//The second method is by using the crossings of equity itself with the longer-period SMA (equity < smasloweequity).
//When "Reduce size by %" is active, the position size will be reduced by a specified percentage
//if the equity is "under water" according to a selected rule. If you're a risk seeker, select "Increase size by %"
//- for some robust systems, it could help overcome their small drawdowns quicker.

strategy("Use Trading the Equity Curve Postion Sizing", shorttitle="TEC", default_qty_type = strategy.percent_of_equity, default_qty_value = 10, initial_capital = 100000)

//TRADING THE EQUITY CURVE INPUTS
useTEC           = input.bool(true, title="Use Trading the Equity Curve Position Sizing")
defulttraderule  = useTEC ? false: true
initialsize      = input.float(defval=10.0, title="Initial % Equity")
slowequitylength = input.int(25, title="Slow SMA Period")
fastequitylength = input.int(9, title="Fast SMA Period")
seedequity = 100000 * .10
if strategy.equity == 0
    seedequity
else
    strategy.equity
slowequityseed   = strategy.equity > seedequity ? strategy.equity : seedequity
fastequityseed   = strategy.equity > seedequity ? strategy.equity : seedequity
smaslowequity    = ta.sma(slowequityseed, slowequitylength)
smafastequity    = ta.sma(fastequityseed, fastequitylength)
equitycalc       = input.bool(true, title="Use Fast/Slow Avg", tooltip="Fast Equity Avg is below Slow---otherwise if unchecked uses Slow Equity Avg below Equity")
sizeadjstring    = input.string("Reduce size by (%)", title="Position Size Adjustment", options=["Reduce size by (%)","Increase size by (%)"])
sizeadjint       = input.int(50, title="Increase/Decrease % Equity by:")
equitydowntrendavgs = smafastequity < smaslowequity
slowequitylessequity = strategy.equity < smaslowequity

equitymethod = equitycalc ? equitydowntrendavgs : slowequitylessequity

if sizeadjstring == ("Reduce size by (%)")
    sizeadjdown = initialsize * (1 - (sizeadjint/100))
else
    sizeadjup = initialsize * (1 + (sizeadjint/100))
c = close
qty = 100000 * (initialsize / 100) / c
if useTEC and equitymethod
    if sizeadjstring == "Reduce size by (%)"
        qty := (strategy.equity * (initialsize / 100) * (1 - (sizeadjint/100))) / c
    else
        qty := (strategy.equity * (initialsize / 100) * (1 + (sizeadjint/100))) / c
    
//EXAMPLE TRADING STRATEGY INPUTS
CMO_Length = input.int(defval=9, minval=1, title='Chande Momentum Length')
CMO_Signal = input.int(defval=10, minval=1, title='Chande Momentum Signal')

chandeMO = ta.cmo(close, CMO_Length)
cmosignal = ta.sma(chandeMO, CMO_Signal)

SuperTrend_atrPeriod = input.int(10, "SuperTrend ATR Length")
SuperTrend_Factor = input.float(3.0, "SuperTrend Factor", step = 0.01)
Momentum_Length = input.int(12, "Momentum Length")
price = close

mom0 = ta.mom(price, Momentum_Length)
mom1 = ta.mom( mom0, 1)
[supertrend, direction] = ta.supertrend(SuperTrend_Factor, SuperTrend_atrPeriod)
stupind = (direction < 0 ? supertrend : na)
stdownind = (direction < 0? na : supertrend)

//TRADING CONDITIONS
longConditiondefault = ta.crossover(chandeMO, cmosignal) and (mom0 > 0 and mom1 > 0 and close > stupind) and defulttraderule
if (longConditiondefault)
    strategy.entry("DefLong", strategy.long, qty=qty)

shortConditiondefault = ta.crossunder(chandeMO, cmosignal) and (mom0 < 0 and mom1 < 0 and close < stdownind) and defulttraderule
if (shortConditiondefault)
    strategy.entry("DefShort", strategy.short, qty=qty)
    
longCondition = ta.crossover(chandeMO, cmosignal) and (mom0 > 0 and mom1 > 0 and close > stupind) and useTEC
if (longCondition)
    strategy.entry("AdjLong", strategy.long, qty = qty)

shortCondition = ta.crossunder(chandeMO, cmosignal) and (mom0 < 0 and mom1 < 0 and close < stdownind) and useTEC
if (shortCondition)
    strategy.entry("AdjShort", strategy.short, qty = qty)
plot(strategy.equity)
plot(smaslowequity, color=color.new(color.red, 0))
plot(smafastequity, color=color.new(color.green, 0))

Detail

https://www.fmz.com/strategy/438939

Last Modified

2024-01-16 15:06:39