strategies/基于多指标的数字货币量化策略Multi-Indicator-Quantitative-Strategy-for-Cryptocurrencies.md

Name

基于多指标的数字货币量化策略Multi-Indicator-Quantitative-Strategy-for-Cryptocurrencies

Author

ChaoZhang

Strategy Description

[trans]

本文将详细介绍一种针对数字货币设计的多指标量化交易策略。该策略综合使用均线、振荡器、通道等指标进行入场判断和风险控制。

一、策略原理

该策略主要应用以下几类指标:

1. ROC振荡器判断价格的超买超卖区间;

2. 唐奇安通道构建动态的支撑和阻力;

3. 熊力指标判断底部特征;

4. 平衡能量指标判断多空趋势;

5. 移动平均线进行趋势过滤。

只有当多个指标信号达成一致时,才会形成最终的入场判断。同时设置止盈止损点来控制单笔交易的风险。

二、策略优势

该策略最大的优势在于指标互补,从多个维度判断趋势和关键点位。

另一个优势是止盈止损设置直接合理,有助于积极的资金管理。

最后,参数空间广泛,可针对数字货币进行细致优化。

三、潜在风险

但该策略也存在以下问题:

首先,多指标组合增加了参数优化的难度。

其次,指标之间可能出现分歧,需要设定清晰的判断规则。

最后,需要针对特定品种进行参数优化。

四、内容总结

本文详细介绍了一种专门针对数字货币设计的多指标量化策略。它合理运用多种指标进行风险控制和获利管理。该策略可以通过参数优化获得稳定收益,但也需要注意防控优化难度及指标使用问题。

||

This article explains in detail a multi-indicator quantitative trading strategy designed for cryptocurrencies. It utilizes moving averages, oscillators, channels etc. for entry signals and risk control.

I. Strategy Logic

The main indicator categories used are:

1. ROC oscillator to gauge overbought/oversold levels.

2. Donchian Channel for dynamic support and resistance.

3. Bears Power identifying bottom characteristics.

4. Balance of Power for trend judgment.

5. Moving average for trend filtering.

Trades are only taken when multiple indicators agree. Profit targets and stop loss are also set to control single trade risks.

II. Advantages of the Strategy

The biggest advantage is the complementarity of indicators, judging from multiple dimensions.

Another advantage is the direct and sensible stop loss and take profit for prudent money management.

Finally, extensive parameter space allows fine tuning for cryptocurrencies.

III. Potential Risks

However, some risks exist:

Firstly, multi-indicator combinations increase optimization difficulty.

Secondly, discrepancies between indicators require clear logic rules.

Lastly, parameters need optimization for specific products.

IV. Summary

In summary, this article has explained a multi-indicator quantitative strategy tailored for cryptocurrencies. It intelligently combines indicators for risk and money management. Through parameter optimization it can achieve steady profits but needs to manage optimization difficulty and indicator usage.

[/trans]

Strategy Arguments

Argument	Default	Description
v_input_1	3000	Take Profit
v_input_2	3443	Stop Loss
v_input_3	185	ROC Length
v_input_4	49	Smoothing Length
v_input_5_close	0	Source: close
v_input_6	43	Upper Channel
v_input_7	43	Lower Channel
v_input_8	90	Offset Bars
v_input_9	61	BearsP WMA Period
v_input_10	15	BoP Exponential Smoothing
v_input_11	74	SMA Period
v_input_12	37	SMA Shift
v_input_13	false	My Price
v_input_14	0	Label Style: Lower Right

Source (PineScript)

/*backtest
start: 2023-09-07 00:00:00
end: 2023-09-14 00:00:00
period: 4m
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/
// © mbagheri746

//@version=4
strategy("Bagheri IG Ether", overlay=true, margin_long=100, margin_short=100)

TP = input(3000, minval = 1 , title ="Take Profit")
SL = input(3443, minval = 1 , title ="Stop Loss")


//_________________ RoC Definition _________________


rocLength = input(title="ROC Length", type=input.integer, minval=1, defval=185)
smoothingLength = input(title="Smoothing Length", type=input.integer, minval=1, defval=49)
src = input(title="Source", type=input.source, defval=close)

ma = ema(src, smoothingLength)
mom = change(ma, rocLength)

sroc = nz(ma[rocLength]) == 0
     ? 100
     : mom == 0
         ? 0
         : 100 * mom / ma[rocLength]

//srocColor = sroc >= 0 ? #0ebb23 : color.red
//plot(sroc, title="SROC", linewidth=2, color=srocColor, transp=0)
//hline(0, title="Zero Level", linestyle=hline.style_dotted, color=#989898)


//_________________ Donchian Channel _________________

length1 = input(43, minval=1, title="Upper Channel")
length2 = input(43, minval=1, title="Lower Channel")
offset_bar = input(90,minval=0, title ="Offset Bars")

upper = highest(length1)
lower = lowest(length2)

basis = avg(upper, lower)


DC_UP_Band = upper[offset_bar]
DC_LW_Band = lower[offset_bar]

l = plot(DC_LW_Band, style=plot.style_line, linewidth=2, color=color.red)
u = plot(DC_UP_Band, style=plot.style_line, linewidth=2, color=color.aqua)

fill(l,u,color = color.new(color.aqua,transp = 90))

//_________________ Bears Power _________________


wmaBP_period = input(61,minval=1,title="BearsP WMA Period")
line_wma = ema(close, wmaBP_period)

BP = low - line_wma


//_________________ Balance of Power _________________

ES_BoP=input(15, title="BoP Exponential Smoothing")
BOP=(close - open) / (high - low)

SBOP = rma(BOP, ES_BoP)

//_________________ Alligator _________________

//_________________ CCI _________________

//_________________ Moving Average _________________

sma_period = input(74, minval = 1 , title = "SMA Period")
sma_shift = input(37, minval = 1 , title = "SMA Shift")

sma_primary = sma(close,sma_period)

SMA_sh = sma_primary[sma_shift]

plot(SMA_sh, style=plot.style_line, linewidth=2, color=color.yellow)

//_________________ Long Entry Conditions _________________//

MA_Lcnd = SMA_sh > low and SMA_sh < high

ROC_Lcnd = sroc < 0

DC_Lcnd = open < DC_LW_Band

BP_Lcnd = BP[1] < BP[0] and BP[1] < BP[2]

BOP_Lcnd = SBOP[1] < SBOP[0]

//_________________ Short Entry Conditions _________________//

MA_Scnd = SMA_sh > low and SMA_sh < high

ROC_Scnd = sroc > 0

DC_Scnd = open > DC_UP_Band

BP_Scnd = BP[1] > BP[0] and BP[1] > BP[2]

BOP_Scnd = SBOP[1] > SBOP[0]

//_________________ OPEN POSITION __________________//


strategy.entry(id = "BUY", long = true , when = MA_Lcnd and ROC_Lcnd and DC_Lcnd and BP_Lcnd and BOP_Lcnd)

strategy.entry(id = "SELL", long = false , when = MA_Scnd and ROC_Scnd and DC_Scnd and BP_Scnd and BOP_Scnd)

//_________________ CLOSE POSITION __________________//

strategy.exit(id = "CLOSE BUY", from_entry = "BUY", profit = TP , loss = SL)

strategy.exit(id = "CLOSE SELL", from_entry = "SELL" , profit = TP , loss = SL)


//_________________ TP and SL Plot __________________//

currentPL= strategy.openprofit
pos_price = strategy.position_avg_price
open_pos = strategy.position_size

TP_line = (strategy.position_size  > 0) ? (pos_price + TP/100) : strategy.position_size < 0 ? (pos_price - TP/100) : 0.0
SL_line = (strategy.position_size  > 0) ? (pos_price - SL/100) : strategy.position_size < 0 ? (pos_price + SL/100) : 0.0

// hline(TP_line, title = "Take Profit", color = color.green , linestyle = hline.style_dotted, editable = false)
// hline(SL_line, title = "Stop Loss", color = color.red , linestyle = hline.style_dotted, editable = false)


Tline = plot(TP_line != 0.0 ? TP_line : na , title="Take Profit", color=color.green, trackprice = true, show_last = 1)
Sline = plot(SL_line != 0.0 ? SL_line : na, title="Stop Loss", color=color.red, trackprice = true, show_last = 1)
Pline = plot(pos_price != 0.0 ? pos_price : na, title="Stop Loss", color=color.gray, trackprice = true, show_last = 1)


fill(Tline , Pline, color = color.new(color.green,transp = 90))
fill(Sline , Pline, color = color.new(color.red,transp = 90))



//_________________ Label __________________//


inMyPrice           = input(title="My Price", type=input.float, defval=0)
inLabelStyle        = input(title="Label Style", options=["Upper Right", "Lower Right"], defval="Lower Right")

posColor = color.new(color.green, 25)
negColor = color.new(color.red, 25)
dftColor = color.new(color.aqua, 25)
posPnL   = (strategy.position_size != 0) ? (close * 100 / strategy.position_avg_price - 100) : 0.0
posDir   = (strategy.position_size  > 0) ? "long" : strategy.position_size < 0 ? "short" : "flat"
posCol   = (posPnL > 0) ? posColor : (posPnL < 0) ? negColor : dftColor
myPnL    = (inMyPrice != 0) ? (close * 100 / inMyPrice - 100) : 0.0

var label lb = na
label.delete(lb)
lb := label.new(bar_index, close,
   color=posCol,
   style=inLabelStyle=="Lower Right"?label.style_label_upper_left:label.style_label_lower_left,
   text=
      "╔═══════╗" +"\n" + 
      "Pos: "  +posDir +"\n" +
      "Pos Price: "+tostring(strategy.position_avg_price) +"\n" +
      "Pos PnL: "  +tostring(posPnL, "0.00") + "%" +"\n" +
      "My Price: " +tostring(inMyPrice) +"\n" +
      "My PnL: "   +tostring(myPnL, "0.00") + "%" +"\n" +
      "╚═══════╝")

Detail

https://www.fmz.com/strategy/426889

Last Modified

2023-09-15 11:58:36