strategies/基于Z距离的VWAP策略ZVWAP-Strategy-Based-on-Z-Distance-from-VWAP.md

Name

基于Z距离的VWAP策略ZVWAP-Strategy-Based-on-Z-Distance-from-VWAP

Author

ChaoZhang

Strategy Description

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概述

该策略基于LazyBear的Z距离VWAP指标,通过计算价格与VWAP的Z距离来判断是否超买超卖,以及进行入场出场。策略加入EMA均线以及Z距离回归0轴的判断,可过滤掉部分噪声信号。

策略原理

1. 计算VWAP的值
2. 计算价格与VWAP的Z距离
3. 设置超买线(2.5)和超卖线(-0.5)
4. 当快线大于慢线,Z距离低于超卖线,且Z距离上穿0轴时做多
5. 当Z距离超过超买线时平仓
6. 加入止损逻辑

关键函数:

• calc_zvwap:计算价格与VWAP的Z距离
• VWAP值:vwap(hlc3)
• 快线:ema(close,fastEma)
• 慢线:ema(close,slowEma)

优势分析

1. 使用Z距离更直观判断超买超卖
2. 结合EMA过滤假突破,避免被套
3. 允许加仓,可以利用趋势获利
4. 有止损逻辑,可以控制风险

风险分析

1. 需确保参数设置合理,如超买超卖线位置,EMA周期等
2. Z距离指标有滞后,可能错过关键买卖点
3. 允许加仓会增大损失风险
4. 止损位置需要合理设置

解决方法:

1. 通过回测优化参数设置
2. 结合额外指标过滤信号
3. 合理设置加仓条件
4. 动态调整止损位置

优化方向

1. 优化EMA周期参数
2. 测试不同的超买超卖判断标准
3. 加入其他指标过滤信号噪音
4. 测试不同的止损方式
5. 优化入场、加仓和止损逻辑

总结

该策略利用Z距离判定价格与VWAP的关系,结合EMA过滤噪音信号,以捕捉趋势机会。策略允许加仓追踪趋势,同时设置止损控制风险。通过参数优化及加入其他指标可以提高策略稳定性。但Z距离指标存在滞后问题,在优化时需考量。总体来说,该策略以简单清晰的逻辑捕捉趋势,经过充分优化后可成为高效的趋势跟踪策略。

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Overview

This strategy is based on the Z-distance from VWAP indicator by LazyBear. It uses the Z-distance between price and VWAP to determine overbought and oversold conditions, as well as entries and exits. The strategy incorporates EMA lines and Z-distance crossing 0 level to filter out some noise.

Strategy Logic

1. Calculate VWAP value
2. Calculate Z-distance between price and VWAP
3. Set overbought line (2.5) and oversold line (-0.5)
4. Go long when fast EMA > slow EMA, Z-distance < oversold line and Z-distance crosses above 0
5. Close position when Z-distance > overbought line
6. Incorporate stop loss logic

Key Functions:

• calc_zvwap: Calculate Z-distance between price and VWAP
• VWAP value: vwap(hlc3)
• Fast EMA: ema(close,fastEma)
• Slow EMA: ema(close,slowEma)

Advantage Analysis

1. Z-distance intuitively shows overbought/oversold levels
2. EMA filters out false breakouts
3. Allows pyramiding to capitalize on trends
4. Has stop loss logic to control risk

Risk Analysis

1. Need to ensure parameters like lines, EMA periods are set properly
2. Z-distance indicator lags, may miss key turning points
3. Pyramiding can increase loss if trend reverses
4. Stop loss needs to be set reasonably

Solutions:

1. Optimize parameters via backtesting
2. Add other indicators to filter signals
3. Set proper conditions for pyramiding
4. Use dynamic stop loss

Optimization Directions

1. Optimize EMA periods
2. Test different overbought/oversold criteria
3. Add other indicators to filter noise
4. Test different stop loss techniques
5. Optimize entry, pyramiding and stop loss logic

Summary

The strategy uses Z-distance to determine price-VWAP relationship and adds EMA to filter signals, aiming to capture trend opportunities. It allows pyramiding to follow trends and has a stop loss to control risk. Optimization and adding other indicators can improve robustness. However, lagging issue of Z-distance should be considered during optimization. Overall, this is a trend-following strategy with simple, clear logic. When fully optimized, it can be an efficient tool to trade trends.

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Strategy Arguments

Argument	Default	Description
v_input_1	13	length
v_input_2	-0.5	OverSold Line
v_input_3	2	OverBought Line
v_input_4	13	Fast EMA
v_input_5	55	Slow EMA
v_input_6	5	Stop Loss

Source (PineScript)

/*backtest
start: 2022-11-03 00:00:00
end: 2023-11-09 00:00:00
period: 1d
basePeriod: 1h
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/
// © mohanee

//@version=4
//This is based on Z distance from VWAP by Lazybear
strategy(title="ZVWAP[LB] strategy", overlay=false,pyramiding=2, default_qty_type=strategy.fixed, default_qty_value=3,    initial_capital=10000, currency=currency.USD)
length=input(13,"length")

calc_zvwap(pds, source1) =>
	mean = sum(volume*source1,pds)/sum(volume,pds)
	vwapsd = sqrt(sma(pow(source1-mean, 2), pds) )
	(close-mean)/vwapsd


upperTop=2.5  //input(2.5)
upperBottom=2.0  //input(2.0)
lowerTop=-0.5  //input(-0.5)
lowerBottom=-2.0 //input(-2.0)

buyLine=input(-0.5, title="OverSold Line",minval=-2, maxval=3)
sellLine=input(2.0, title="OverBought Line",minval=-2, maxval=3)

fastEma=input(13, title="Fast EMA",minval=1, maxval=50)
slowEma=input(55, title="Slow EMA",minval=10, maxval=200)

stopLoss =input(5, title="Stop Loss",minval=1) 

hline(0, title="Middle Line", linestyle=hline.style_dotted, color=color.green)

ul1=plot(upperTop, "OB High")
ul2=plot(upperBottom, "OB Low")
fill(ul1,ul2, color=color.red)
ll1=plot(lowerTop, "OS High")
ll2=plot(lowerBottom, "OS Low")
fill(ll1,ll2, color=color.green)
zvwapVal=calc_zvwap(length,close)
plot(zvwapVal,title="ZVWAP",color=color.purple, linewidth=2)


longEmaVal=ema(close,slowEma)
shortEmaVal=ema(close,fastEma)  

vwapVal=vwap(hlc3)


zvwapDipped=false

for i = 1 to 10
    zvwapDipped := zvwapDipped or zvwapVal[i]<=buyLine

longCondition=  shortEmaVal > longEmaVal  and zvwapDipped and  crossover(zvwapVal,0)

barcolor(longCondition ? color.yellow: na)

strategy.entry(id="ZVWAPLE", long=true,  when= longCondition  and strategy.position_size<1) 


//Add
strategy.entry(id="ZVWAPLE", comment="Add", long=true,  when= strategy.position_size>1 and close<strategy.position_avg_price and crossover(zvwapVal,0)) 


//calculate stop Loss
stopLossVal =  strategy.position_avg_price -  (strategy.position_avg_price*stopLoss*0.01)

strategy.close(id="ZVWAPLE",comment="SL Exit",    when=close<stopLossVal)   //close all on stop loss

strategy.close(id="ZVWAPLE",comment="TPExitAll",    qty=strategy.position_size ,   when= crossunder(zvwapVal,sellLine))   //close all      zvwapVal>sellLine

Detail

https://www.fmz.com/strategy/431669

Last Modified

2023-11-10 12:02:19