VWAP Trading Strategy

Pine ScriptBreakout Momentum Trend following RSI EMA ATR VWAP

Author: ChaoZhang
Complexity: Starter · 51 lines
Parameters: 6
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a trading strategy based on EMA, VWAP, and volume. The main idea is to generate opening signals when the closing price breaks through VWAP and EMA, and the trading volume is greater than the previous candle's volume within a specific trading time. It also sets stop loss and take profit, as well as conditions for closing positions within a specific time period.

Strategy Principle

Calculate EMA and VWAP indicators.
Determine whether it is within the specified trading time.
Long entry condition: closing price is greater than VWAP and EMA, volume is greater than the previous candle, and closing price is greater than opening price.
Short entry condition: closing price is less than VWAP and EMA, volume is greater than the previous candle, and opening price is greater than closing price.
Long exit condition: closing price falls below VWAP or EMA, reaches stop loss or take profit levels, or reaches the specified exit time.
Short exit condition: closing price breaks above VWAP or EMA, reaches stop loss or take profit levels, or reaches the specified exit time.

Strategy Advantages

It considers price trend (EMA), market fair value (VWAP), and trading volume simultaneously, making the opening conditions more strict, which helps to improve the strategy's win rate.
It sets stop loss and take profit to control risk and lock in profits.
It limits trading time and exit time to avoid risks during non-trading hours and overnight holding.

Strategy Risks

The strategy may not perform well in a volatile market, as frequent breakthroughs and pullbacks may lead to multiple openings and closings, increasing transaction costs and slippage.
The stop loss level is fixed, which may be triggered prematurely when the market fluctuates violently, causing the strategy to suffer significant losses.
The strategy does not consider actual market depth and order status, which may face issues such as slippage and opening failures in real trading.

Strategy Optimization Direction

Consider adding more filtering conditions, such as ATR and RSI indicators, to further confirm the strength of the trend and momentum.
Stop loss and take profit levels can be set dynamically, such as following ATR or percentage stop loss, to adapt to different market volatilities.
Optimize parameters, such as EMA length, VWAP source, stop loss and take profit levels, etc., to improve the stability and profitability of the strategy.
Consider adding position management, such as adjusting the opening volume according to volatility or capital ratio, to control overall risk.

Summary

By comprehensively considering price trends, market fair value, and trading volume, this strategy trades within a specific trading time. Although stop loss, take profit, and limited trading time are set, it still needs to pay attention to risks such as volatile markets and slippage in actual application. In the future, the strategy's robustness and profitability can be improved by adding more filtering conditions, optimizing parameters, and managing positions.

Parameters

Name	Default	What it controls
v_input_int_1	21	EMA Length
v_input_source_1_hlc3	0	VWAP Source: hlc3 \| high \| low \| open \| hl2 \| close \| hlcc4 \| ohlc4
v_input_float_1	100	Stop Loss (points)
v_input_float_2	200	Target (points)
v_input_1	0950-1430	Only take entry during
v_input_2	1515-1525	Exit Trade

Source Pine Script

/*backtest
start: 2024-04-27 00:00:00
end: 2024-04-28 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("EMA, VWAP, Volume Strategy", overlay=true, process_orders_on_close=true)

// Inputs
emaLength = input.int(21, title="EMA Length")
vwapSource = input.source(defval=hlc3, title='VWAP Source')
stopLossPoints = input.float(100, title="Stop Loss (points)")
targetPoints = input.float(200, title="Target (points)")
session = input("0950-1430", title='Only take entry during')
exit = input(defval='1515-1525', title='Exit Trade')

tradein = not na(time(timeframe.period, session))
exit_time = not na(time(timeframe.period, exit))

// Calculate indicators
ema = ta.ema(close, emaLength)
vwapValue = ta.vwap(vwapSource)

// Entry Conditions
longCondition = close > vwapValue and close > ema and volume > volume[1] and close > open and tradein
shortCondition = close < vwapValue and close < ema and volume > volume[1] and open > close and tradein

// Exit Conditions
longExitCondition = ta.crossunder(close, vwapValue) or ta.crossunder(close, ema) or close - strategy.position_avg_price >= targetPoints or close - strategy.position_avg_price <= -stopLossPoints or exit_time
shortExitCondition = ta.crossover(close, vwapValue) or ta.crossover(close, ema) or strategy.position_avg_price - close >= targetPoints or strategy.position_avg_price - close <= -stopLossPoints or exit_time

// Plotting
plot(vwapValue, color=color.blue, title="VWAP")
plot(ema, color=color.green, title="EMA")

// Strategy
if longCondition
    strategy.entry("Long", strategy.long)

if shortCondition
    strategy.entry("Short", strategy.short)

if longExitCondition
    strategy.close('Long', immediately=true)

if shortExitCondition
    strategy.close("Short", immediately=true)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-04-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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