Quantitative Trading Strategy Based on 5 day Moving Average Band and GBS Buy Sell Signals

Pine ScriptMachine learning Breakout Mean reversion RSI MACD SMA Pivots / S&R

Author: ChaoZhang
Complexity: Starter · 45 lines
Parameters: 1
Backtest bar: 4h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines the 5-day moving average band and GBS buy/sell signals to identify trend direction and generate trading signals. The moving average band is used to judge the trend direction and major support/resistance levels, while the GBS buy/sell signals are used to find precise entry timing under the trend direction. This strategy is suitable for medium-term trend trading and can achieve excess returns in range-bound markets.

Strategy Principles

Calculate the simple moving average of 5-day high and low prices to obtain the 5-day moving average band
When the closing price breaks through the moving average band, it indicates a trend reversal
When an uptrend is identified, long positions are taken if GBS buy signals are triggered; When a downtrend is identified, short positions are taken if GBS sell signals are triggered
Set stop loss/take profit exit mechanisms, exit when drawdown exceeds certain threshold

Advantages of the Strategy

The moving average band accurately judges the major trend direction
GBS buy/sell signals have a relatively high winning rate
The stop loss mechanism effectively controls risks and limits losses

Risks and Solutions

False breakouts may occur frequently in range-bound markets, causing trading mistakes
- Solution: Widen the moving average band to ensure operations only during clear trends
Risks relying on single indicator
- Solution: Add validation from other indicators e.g. MACD, RSI to avoid missing reversal signals
Backtest overfitting risks
- Solution: Expand backtest timeframe, compare results across different products and parameters

Directions for Strategy Optimization

Parameter optimization to find optimum parameter combinations
Add validation signals from other indicators
Develop adaptive moving average mechanisms
Adjust stop loss level based on market conditions
Add machine learning algorithms to automatically optimize the strategy

Conclusion

This strategy integrates the moving average band and GBS buy/sell signals, operating with high confidence after identifying a clear trend direction to filter out market noise. It can lock in medium-term profits and exit timely. The strategy is simple and efficient in capital utilization, providing stable profits for quant traders. Continuous optimizations and iterations can further improve the win rate and profitability.

Parameters

Name	Default	What it controls
v_input_1	5	Number of Candles for Average

Source Pine Script

/*backtest
start: 2024-01-05 00:00:00
end: 2024-02-04 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("5MABAND + GBS Buy & Sell Strategy", overlay=true)

// Command 1 - 5MABAND Calculation
length = input(5, title="Number of Candles for Average")
avgHigh = ta.sma(high, length)
avgLow = ta.sma(low, length)

// Plotting 5MABAND Bands
plot(avgHigh, color=color.green, title="5MABAND High Line", linewidth=1)
plot(avgLow, color=color.red, title="5MABAND Low Line", linewidth=1)

// Command 2 - GBS concept Buy Entry
gbsBuyCondition = close > open and high - close < close - open and open - low < close - open and close - open > close[1] - open[1] and close - open > close[2] - open[2] and close - open > close[3] - open[3] and close[1] < avgHigh and close[2] < avgHigh and close[3] < avgHigh and open[1] < avgHigh and open[2] < avgHigh and open[3] < avgHigh

// Command 3 - GBS Concept Sell Entry
gbsSellCondition = open - close > open[1] - close[1] and open - close > open[2] - close[2] and open - close > open[3] - close[3] and open[1] > avgLow and open[2] > avgLow and open[3] > avgLow and open - close > open - low and open - close > high - open

// Command 6 - 5MABAND Exit Trigger
exitTriggerCandle_5MABAND_Buy = low < avgLow
exitTriggerCandle_5MABAND_Sell = high > avgHigh

// Exit Signals for 5MABAND
exitBuySignal_5MABAND = close < avgLow
exitSellSignal_5MABAND = close > avgHigh

// Execute Buy and Sell Orders
strategy.entry("Buy", strategy.long, when = gbsBuyCondition)
strategy.close("Buy", when = exitBuySignal_5MABAND)

strategy.entry("Sell", strategy.short, when = gbsSellCondition)
strategy.close("Sell", when = exitSellSignal_5MABAND)

// Exit Buy and Sell Orders for 5MABAND
strategy.close("Buy", when = exitTriggerCandle_5MABAND_Buy)
strategy.close("Sell", when = exitTriggerCandle_5MABAND_Sell)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-05. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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