Volatility Bands and VWAP Multi Timeframe Stock Trend Trading Strategy

Pine ScriptTrend following Volatility Multi-timeframe SMA ATR VWAP

Author: ChaoZhang
Complexity: Intermediate · 91 lines
Parameters: 9
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

This strategy calculates the ATR volatility of price and combines different period VWAP to set long entry and exit conditions for stock trend trading.

Strategy Overview

The strategy is mainly used for trend tracking of stock products. By calculating the ATR volatility and combining VWAP prices of different periods, it sets buy and sell conditions to judge and track trends. The strategy is flexible enough to switch between long term and short term, suitable for capturing medium and long term trends.

Strategy Logic

The strategy uses the ATR indicator to calculate price volatility and judges the trend direction based on whether the price breaks through the volatility channel. At the same time, it introduces VWAP prices of different cycles to determine the consistency of long and short term trends. The specific logic is as follows:

Calculate the ATR volatility channel of the price
Judge if the price breaks through the volatility channel
1. Breaking through the upper rail indicates a bullish trend
2. Breaking through the lower rail indicates a bearish trend
Introduce weekly and daily VWAP prices
1. When the price breaks through the upper volatility rail, if both daily and weekly VWAPs are above the price, a long signal is generated
2. When the price breaks through the lower volatility rail, if both daily and weekly VWAPs are below the price, a short signal is generated

The above is the core logic of the strategy. The ATR volatility judges the short-term trend and the VWAP price judges the long-term trend. The two are combined to determine the consistency of the trend and thus generate trading signals.

Advantages of the Strategy

Use a combination of ATR and VWAP to judge trends, more reliable
Customizable ATR period parameter to adjust strategy sensitivity
Introducing multi-timeframe VWAP to determine long and short term trend consistency
Flexible to switch between long term and short term
Suitable for tracking medium and long term stock trends

Risks and Optimization

As a trend following strategy, it may generate more trades during consolidation, bringing slippage risks
ATR and VWAP parameter settings impact strategy performance, require careful testing against different products
Consider adding stop loss to control single trade loss
Can combine with MA and other indicators to filter entry signals and reduce unnecessary trades

Summary

The strategy realizes stock trend tracking through dual confirmation of ATR volatility and VWAP. There is ample room for optimization by adjusting parameters or incorporating other technical indicators. Overall, the strategy logic is clear and robust for tracking medium to long term trends.

Parameters

Name	Default	What it controls
v_input_1	27	length
v_input_2	false	mult
v_input_3	true	From Day
v_input_4	true	From Month
v_input_5	2000	From Year
v_input_6	31	To Day
v_input_7	12	To Month
v_input_8	2021	To Year
v_input_9_ohlc4	0	srcX: ohlc4 \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| close

Source Pine Script

/*backtest
start: 2023-12-17 00:00:00
end: 2024-01-16 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/
// © exlux99

//@version=4
strategy(title="VWAP MTF STOCK STRATEGY", overlay=true )

// high^2 / 2 - low^2 -2

h=pow(high,2) / 2
l=pow(low,2) / 2

o=pow(open,2) /2
c=pow(close,2) /2


x=(h+l+o+c) / 4
y= sqrt(x)

source = y
useTrueRange = false
length = input(27, minval=1)
mult = input(0, step=0.1)
ma = sma(source, length)
range = useTrueRange ? tr : high - low
rangema = sma(range, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
crossUpper = crossover(source, upper)
crossLower = crossunder(source, lower)
bprice = 0.0
bprice := crossUpper ? high+syminfo.mintick : nz(bprice[1])
sprice = 0.0
sprice := crossLower ? low -syminfo.mintick : nz(sprice[1])
crossBcond = false
crossBcond := crossUpper ? true
     : na(crossBcond[1]) ? false : crossBcond[1]
crossScond = false
crossScond := crossLower ? true
     : na(crossScond[1]) ? false : crossScond[1]
cancelBcond = crossBcond and (source < ma or high >= bprice )
cancelScond = crossScond and (source > ma or low <= sprice )

longOnly = true

fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
fromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
fromYear = input(defval = 2000, title = "From Year", minval = 1970)
 //monday and session 
// To Date Inputs
toDay = input(defval = 31, title = "To Day", minval = 1, maxval = 31)
toMonth = input(defval = 12, title = "To Month", minval = 1, maxval = 12)
toYear = input(defval = 2021, title = "To Year", minval = 1970)

startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00)
finishDate = timestamp(toYear, toMonth, toDay, 00, 00)
time_cond = true

srcX = input(ohlc4)
t = time("W")
start = na(t[1]) or t > t[1]

sumSrc = srcX * volume
sumVol = volume
sumSrc := start ? sumSrc : sumSrc + sumSrc[1]
sumVol := start ? sumVol : sumVol + sumVol[1]

vwapW= sumSrc / sumVol

 
//crossUpper = crossover(source, upper)
//crossLower = crossunder(source, lower)
shortCondition = close < vwap and time_cond and (close < vwapW)
longCondition = close > vwap and time_cond and (close > vwapW)

 


if(longOnly and time_cond)
    if (crossLower and close < vwapW )
        strategy.close("long")
    if (crossUpper and close>vwapW)
        strategy.entry("long", strategy.long, stop=bprice)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-17. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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