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基于多重指标的趋势追踪策略Multi-Indicator-Trend-Tracking-Strategy.md

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Name

基于多重指标的趋势追踪策略Multi-Indicator-Trend-Tracking-Strategy

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

本策略名称为多指标组合趋势追踪策略(Multi-Indicator Trend Tracking Strategy),其利用Fisher变换指标、加权移动平均线(WMA)、相对强弱指标(RSI)以及均量线(OBV)等多个指标,判断市场趋势方向,实现趋势跟踪交易。

策略原理

  1. Fisher变换指标判断价格变化趋势和力度。当4个Fisher线同时变色时发出交易信号。
  2. WMA判断大趋势方向。RSI过滤假信号。
  3. OBV指标用于确认趋势。

具体来说,Fisher变换指标包含1倍、2倍、4倍和8倍4条线。当4条线同时向上翻绿时产生做多信号,4条线同时向下翻红时产生做空信号。WMA判断大趋势方向,如果指标向上则判断为看涨,向下则判断为看跌。OBV用于确认趋势方向。相对强弱指标RSI过滤假信号。

优势分析

本策略具有以下优势:

  1. Fisher变换指标判断力度强劲,当4个Fisher线同时变色时,确保趋势发生反转的可能性很大。
  2. WMA判断主要大趋势方向,避免逆势交易。
  3. OBV指标确认趋势,避免trendless市场的假突破。
  4. RSI指标过滤假信号,确保信号的可靠性。

通过多个指标的组合应用,既确保了交易信号的准确性和可靠性,又具有趋势跟踪的能力,可以获得较好的策略效果。

风险分析

本策略也存在一定的风险:

  1. 如果行情出现盘整,Fisher线容易产生假信号。这时需依赖RSI过滤。
  2. WMA参数设置不当也会影响判断 accurancy。
  3. Fisher变换指标对超短线行情判断较差。
  4. 若遇瀑布线,策略会产生巨额亏损。

为降低风险,可适当调整RSI参数,优化WMA周期参数。同时可设置止损点,避免出现超大亏损。

优化方向

本策略还可从以下方面进一步优化:

  1. 可测试不同周期参数下策略效果,找到最佳参数组合。
  2. 添加止损机制。当亏损达到一定比例时止损。
  3. 根据回测结果进一步调整Fisher变换指标的参数,找到指标判断最准确的参数组合。
  4. 尝试添加其他指标过滤,如强弱指标、Bias等。
  5. 测试不同的开仓仓位大小设置。

总结

本策略综合运用Fisher变换指标、WMA指标、OBV指标和RSI指标,判断市场的趋势方向。其判断信号精准,确认能力强,能够有效锁定趋势获利。通过参数优化,可进一步提高策略profit factor。总体来说,该策略通过指标组合判断,实现了高效的趋势跟踪交易,效果良好。

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Overview

The strategy is named Multi-Indicator Trend Tracking Strategy. It utilizes multiple indicators including Fisher Transform, Weighted Moving Average (WMA), Relative Strength Index (RSI) and On-Balance Volume (OBV) to determine the trend direction of the market and track the trend for trading.

Strategy Logic

  1. Fisher Transform to detect price change trend and momentum. Trading signals are generated when four Fisher lines change color synchronously .
  2. WMA to determine the major trend direction. RSI filters out fake signals.
  3. OBV to confirm the trend.

Specifically, Fisher Transform contains four lines - 1x, 2x, 4x and 8x. When four lines turn green simultaneously, a long signal is generated. When four lines turn red simultaneously, a short signal is generated. WMA determines if the major trend is bullish or bearish. OBV confirms the trend direction. RSI filters out false signals.

Advantage Analysis

The advantages of this strategy:

  1. Fisher Transform is momentum-sensitive, when four Fisher lines change color synchronously, it ensures a high probability of trend reversal.
  2. WMA determines the major trend to avoid trading against the trend.
  3. OBV confirms the real trend, avoids false breakout in trendless market.
  4. RSI filters out false signals to ensure reliability of trading signals.

Through the combination of multiple indicators, it ensures accuracy and reliability of trading signals and capable of catching trends, leading to good strategy performance.

Risk Analysis

Risks of this strategy:

  1. Fisher lines may generate false signals if market is in consolidation. RSI helps filter out false signals in this case.
  2. Improper WMA parameter setting may impact trend accuracy.
  3. Fisher Transform does not perform well in ultra short-term trends.
  4. Waterfall decline can lead to huge losses.

To mitigate the risks, RSI parameter can be adjusted accordingly. WMA period can be optimized. Stop loss can also be set to avoid huge losses.

Optimization Directions

This strategy can be further optimized from the following aspects:

  1. Test the effectiveness across different timeframes to find the optimal parameter combination.
  2. Add stop loss mechanism. Set stop loss when loss reaches a certain level.
  3. Further adjust Fisher Transform parameters based on backtest results to find the optimal parameter combination with best accuracy.
  4. Attempt to add other filtering indicators such as strength index, bias index etc.
  5. Test different strategies for setting position sizing.

Conclusion

This strategy integrates Fisher Transform, WMA, OBV and RSI to determine the trend direction. It generates precise trading signals with strong confirmation capability, allowing to effectively lock in profits along the trend. With further parameter optimization, profit factor can be improved. In conclusion, through the combination of multiple indicators, this strategy effectively tracks the trend with good performance.

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Strategy Arguments

Argument Default Description
v_input_int_1 10 (?Fisher Transform)Len
v_input_int_2 true mult1
v_input_int_3 2 mult2
v_input_int_4 4 mult3
v_input_int_5 8 mult4
v_input_int_6 14 (?Moving Averages)rsiLength
v_input_int_7 10 WMA Length
v_input_int_8 20 (?On-Balance Volume)OBV Length
v_input_float_1 0.1 OBV Bullish minimum value
v_input_float_2 -0.1 OBV Bearish minimum value
v_input_float_3 -0.7 (?RSI Level Filters)Reversal Down TP Filter
v_input_float_4 0.7 Reversal Up TP Filter
v_input_float_5 1.66 RSI Level Buy Filter
v_input_float_6 true RSI Level Sell Filter

Source (PineScript)

/*backtest
start: 2022-12-20 00:00:00
end: 2023-12-26 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
//author Sdover0123
strategy(title='FTR, WMA, OBV & RSI Strat', shorttitle='FTR WMA, OBV, RSI',overlay=false, default_qty_type=strategy.percent_of_equity, initial_capital = 100, default_qty_value=100, commission_value = 0.06, pyramiding = 3)
Len = input.int(10, minval=1, group ="Fisher Transform")
mult1 = input.int(1, minval=1, group ="Fisher Transform")
mult2 = input.int(2, minval=1, group ="Fisher Transform")
mult3 = input.int(4, minval=1, group ="Fisher Transform")
mult4 = input.int(8, minval=1, group ="Fisher Transform")
fish(Length, timeMultiplier) =>
    var nValue1 = 0.0
    var nValue2 = 0.0
    var nFish = 0.0
    xHL2 = hl2
    xMaxH = ta.highest(xHL2, Length * timeMultiplier)
    xMinL = ta.lowest(xHL2, Length * timeMultiplier)
    nValue1 := 0.33 * 2 * ((xHL2 - xMinL) / (xMaxH - xMinL) - 0.5) + 0.67 * nz(nValue1[1])
    if nValue1 > .99
        nValue2 := .999
        nValue2
    else if nValue1 < -.99
        nValue2 := -.999
        nValue2
    else
        nValue2 := nValue1
        nValue2
    nFish := 0.5 * math.log((1 + nValue2) / (1 - nValue2)) + 0.5 * nz(nFish[1])
    nFish
Fisher1 = fish(Len, mult1)
Fisher2 = fish(Len, mult2)
Fisher4 = fish(Len, mult3)
Fisher8 = fish(Len, mult4)

rsiLength = input.int(14, minval=1, group ="Moving Averages")
rsiVal = (ta.rsi(close, rsiLength) - 50) / 10
avg = strategy.position_avg_price

wma(source, length) =>
    sum = 0.0
    for i = 0 to length - 1
        sum := sum + source[i] * (length - i)
    wma = sum / (length * (length + 1) / 2)
    wma

wmaLength = input.int(10, "WMA Length", minval=1, group ="Moving Averages")
wmaClose = wma(close, wmaLength)
// Determine if WMA is bullish or bearish
isWmaBullish = wmaClose > wmaClose[1]
isWmaBearish = wmaClose < wmaClose[1]

//OBV 
src = close
length = input.int(20, title="OBV Length", group="On-Balance Volume")
obv1(src) =>
    change_1 = ta.change(src)
    ta.cum(ta.change(src) > 0 ? volume : change_1 < 0 ? -volume : 0 * volume)*0.01
os = obv1(src)
obv_osc = os - ta.ema(os, length)
obc_color = (obv_osc > 0 ? color.rgb(0, 255, 8) : color.rgb(255, 0, 0))
plot(obv_osc, color=obc_color, style=plot.style_line, title='OBV-Points', linewidth=2)
plot(obv_osc, color=color.new(#b2b5be, 70), title='OBV', style=plot.style_area)
obvBullFilter = input.float(0.1, minval = 0, maxval = 5, step = 0.01, title ="OBV Bullish minimum value", group="On-Balance Volume")
obvBearFilter = input.float(-0.1, minval = -5, maxval = 0, step = 0.01, title ="OBV Bearish minimum value", group="On-Balance Volume")
obvBull = obv_osc > obvBullFilter
obvBear = obv_osc < obvBearFilter

// Add buy/sell signals
ReversalFilterDown = input.float(-0.7, 'Reversal Down TP Filter', -4, 4, step = 0.01, group = "RSI Level Filters", tooltip = "This is defined by taking the RSI value -50 and /10. When all Fisher lines are changing colour, this will SL/TP the long")
ReversalFilterUp = input.float(0.7, 'Reversal Up TP Filter', -4, 4, step = 0.01, group = "RSI Level Filters", tooltip = "This is defined by taking the RSI value -50 and /10. When all Fisher lines are changing colour, this will SL/TP the short")
RSILevelBuyFilter = input.float(1.66, 'RSI Level Buy Filter', -4, 4, step = 0.01, group = "RSI Level Filters", tooltip = "This is defined by taking the RSI value -50 and /10. Consider negative values")
RSILevelSellFilter = input.float(1, 'RSI Level Sell Filter', -4, 4, step = 0.01, group = "RSI Level Filters", tooltip = "This is defined by taking the RSI value -50 and /10. Consider negative values")
//buys - if breaking out and all Fisher are green and RSI filter value is met 
buySignal = Fisher1 > Fisher1[1] and Fisher2 > Fisher2[1] and Fisher4 > Fisher4[1] and Fisher8 > Fisher8[1] and rsiVal > RSILevelBuyFilter and isWmaBullish and obvBull
ReversalUp = Fisher1 > Fisher1[1] and Fisher2 > Fisher2[1] and Fisher4 > Fisher4[1] and Fisher8 > Fisher8[1] and rsiVal > ReversalFilterUp
//sells - if breaking down and all Fisher are green and RSI filter value is met 
sellSignal = Fisher1 < Fisher1[1] and Fisher2 < Fisher2[1] and Fisher4 < Fisher4[1] and Fisher8 < Fisher8[1] and rsiVal < RSILevelSellFilter and isWmaBearish and obvBear
ReversalDown = Fisher1 < Fisher1[1] and Fisher2 < Fisher2[1] and Fisher4 < Fisher4[1] and Fisher8 < Fisher8[1] and rsiVal < ReversalFilterDown


// Buy and Sell conditions
if buySignal and time>timestamp(2022, 06, 01, 09, 30) and barstate.isconfirmed
    strategy.close("Sell", comment = "Close Short")
    strategy.entry("Buy", strategy.long, comment = "Long")

if sellSignal and time>timestamp(2022, 06, 01, 09, 30) and barstate.isconfirmed
    strategy.close("Buy", comment = "Close Long")
    strategy.entry("Sell", strategy.short, comment = "Short")

if ReversalDown
    strategy.close("Buy", comment = "Close Long")

if ReversalUp
    strategy.close("Sell", comment = "Close Short")

//Plotting
//Fisher
plot(Fisher1, color=Fisher1 > nz(Fisher1[1]) ? color.green : color.rgb(255, 0, 0), title='Fisher TF:1')
plot(Fisher2, color=Fisher2 > nz(Fisher2[1]) ? color.green : color.rgb(255, 0, 0), title='Fisher TF:1', linewidth=2)
plot(Fisher4, color=Fisher4 > nz(Fisher4[1]) ? #008000 : #b60000, title='Fisher TF:1', linewidth=3)
plot(Fisher8, color=Fisher8 > nz(Fisher8[1]) ? #004f00 : #b60000, title='Fisher TF:1', linewidth=3)
//RSI
plot(rsiVal, color=rsiVal < 0 ? color.purple : color.yellow, linewidth=2, title='RSI')

//WMA
plot(isWmaBullish ? -2 : na, color=color.rgb(76, 175, 79, 20), linewidth=3, style=plot.style_linebr, title="WMA Bullish")
plot(isWmaBearish ? -2 : na, color=color.rgb(255, 82, 82, 20), linewidth=3, style=plot.style_linebr, title="WMA Bearish")

//Buy/Sell Signals
plotshape(buySignal, title='Buy Signal', location=location.bottom, color=color.new(color.lime, 0), style=shape.triangleup, size=size.small)
plotshape(sellSignal, title='Sell Signal', location=location.top, color=color.new(color.red, 0), style=shape.triangledown, size=size.small)

//Orientation
hline(RSILevelBuyFilter, color=color.rgb(25, 36, 99, 20), linestyle=hline.style_dotted, linewidth=2)
hline(RSILevelSellFilter, color=color.rgb(111, 27, 27, 20), linestyle=hline.style_dotted, linewidth=2)
hline(0, color=color.rgb(181, 166, 144, 39), linestyle=hline.style_dashed, linewidth=2, title = "Zero Line")
hline(1.5, color=color.rgb(217, 219, 220, 50), linestyle=hline.style_dotted, linewidth=2, title = "1.5 // 65 Line")
hline(-1.5, color=color.rgb(217, 219, 220, 50), linestyle=hline.style_dotted, linewidth=2, title = "-1.5 // 35 Line")

Detail

https://www.fmz.com/strategy/436789

Last Modified

2023-12-27 17:15:45