Moving Average Bollinger Band Fusion Trading Strategy
This strategy combines moving averages and Bollinger Bands for dual indicator signal validation to determine and trade trends. Fast and slow moving average crosses provide long/short signals, with Bollinger Band…
Overview
This strategy combines moving averages and Bollinger Bands for dual indicator signal validation to determine and trade trends. Fast and slow moving average crosses provide long/short signals, with Bollinger Band breaks as additional confirmation to improve stability.
Strategy Logic
Fast and slow moving averages are calculated. When the fast line crosses above the slow line, a long signal is generated. Below gives a short signal. Bollinger Band upper and lower bands are also calculated. Moving average signals are only confirmed when price also breaks the Bollinger Bands. This avoids whipsaws from false breakouts.
Advantages
- Dual indicator validation avoids false signals
- Moving averages determine main trend direction
- Bollinger Bands confirm quality of breakout
- Ability to go both long and short provides flexibility
Risks
- Moving averages and Bollinger Bands have lag
- Dual conditions limit trade frequency, unsuitable for high frequency trading
- Exact reversal points cannot be accurately determined
- Poor parameter tuning risks missing opportunities
Risks can be managed by shortening moving average and Bollinger periods or optimizing parameter combinations.
Enhancements
- Test different moving average and Bollinger parameter combinations
- Consider adding stop loss strategies to control losses
- Optimize logic rules for dual validation
- Test robustness across different products
Conclusion
This strategy validates signals with dual indicators to reduce false signals, suitable for medium/long-term holding. Further refinements like parameter optimization can improve performance.
Parameters
| Name | Default | What it controls |
|---|---|---|
| v_input_1 | 24 | Bollinger Period Length |
Source Pine Script
/*backtest
start: 2023-08-18 00:00:00
end: 2023-09-17 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=2
strategy("MA-Zorrillo",overlay=true)
ma_short= sma(close,8)
ma_long= sma(close,89)
entry_ma = crossover (ma_short,ma_long)
exit_ma = crossunder (ma_short,ma_long)
BBlength = input(24, minval=1,title="Bollinger Period Length")
BBmult = 2 // input(2.0, minval=0.001, maxval=50,title="Bollinger Bands Standard Deviation")
BBbasis = sma(close, BBlength)
BBdev = BBmult * stdev(close, BBlength)
BBupper = BBbasis + BBdev
BBlower = BBbasis - BBdev
source = close
entry_bb = crossover(source, BBlower)
exit_bb = crossunder(source, BBupper)
vs_entry = false
vs_exit = false
for i = 0 to 63
if (entry_bb[i])
vs_entry := true
if (exit_bb[i])
vs_exit := true
entry = entry_ma and vs_entry
exit = exit_ma and vs_exit
strategy.entry(id="long_ma",long=true,when=entry)
strategy.close(id="long_ma", when=exit)
strategy.entry(id="short_ma",long=false,when=exit)
strategy.close(id="short_ma",when=entry)
Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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