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Strategy vault / Trend following

Trend Following Strategy Based on Bollinger Bands RSI and Moving Average

This strategy integrates Bollinger Bands, Relative Strength Index (RSI) and Moving Average (MA) to identify potential entry and exit points in the market. It can generate buy and sell signals (alerts) that can be…

Pine ScriptTrend followingBreakoutMean reversionRSISMABollinger BandsADX / DMI
Author
ChaoZhang
Complexity
Intermediate · 75 lines
Parameters
9
Backtest bar
1d · swing
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

IMG

Overview

This strategy integrates Bollinger Bands, Relative Strength Index (RSI) and Moving Average (MA) to identify potential entry and exit points in the market. It can generate buy and sell signals (alerts) that can be executed manually or via automated trading systems.

Strategy Logic

The strategy uses two Bollinger Bands with different parameters to create price channels. The default parameters are length of 20 periods and standard deviation of 2. The upper and lower bands serve as dynamic resistance and support levels.

The RSI indicator gauges price momentum strength. Its values are used to determine if overbought or oversold conditions exist.

A 50-period moving average is incorporated to identify the overall trend direction. When price is above the MA, it suggests an uptrend. When price is below the MA, it suggests a downtrend.

Entry conditions for long trades are when RSI goes above overbought level and Bollinger Bands are not contracting. For short trades, it is when RSI goes below oversold level and Bollinger Bands are not contracting.

Exit conditions for long trades are when RSI drops below overbought level or when price closes below 50-period MA. For short trades it is when RSI rises above oversold level or when price closes above 50-period MA.

Advantages

  1. Combining Bollinger Bands, RSI and MA avoids generating false signals by cross validating signals.

  2. Bollinger Bands identify local highs/lows and confirm breakouts. RSI filters false breakouts. MA determines overall trend. Signals are verified.

  3. Optimized parameters of Bollinger Bands using two standard deviations more accurately depict price channels.

Risks

  1. Bollinger Bands may generate false signals when contracting. RSI is also neutral and trading should be avoided.

  2. RSI and MA may generate incorrect signals during ranging markets. Ranging conditions should be identified beforehand.

  3. Price gaps cannot be effectively handled. Other indicators should confirm true breakouts.

Enhancement Opportunities

  1. Optimize parameters of Bollinger Bands and RSI for different products and timeframes.

  2. Add stop loss orders that trigger automatically when price breaches stop level.

  3. Add trend filter like ADX to avoid inefficient trades during ranging markets.

  4. Integrate with automated trading system to execute signals automatically without manual intervention.

Conclusion

This strategy combines the strengths of Bollinger Bands, RSI and MA with optimized parameters to improve signal accuracy. It can automatically generate trade alerts for execution. Main risks come from false signals during ranging markets. Adding a trend filter can reduce inefficient trades. Overall, by using parameter optimization and integrating multiple indicators, this strategy improves signal quality and is worth validating in live markets for usage.

Parameters

NameDefaultWhat it controls
v_input_120BB Length
v_input_22BB Standard Deviation
v_input_3trueBB Deviation 1
v_input_414RSI Length
v_input_570Overbought RSI Level
v_input_630Oversold RSI Level
v_input_750MA Length
v_input_8trueStop Loss Percentage
v_input_9_close0Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4

Source Pine Script

/*backtest
start: 2023-01-26 00:00:00
end: 2024-02-01 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Bollinger Bands, RSI, and MA Strategy", overlay=true)

// Define input variables
b_len = input(20, title="BB Length")
bb_mult = input(2.0, title="BB Standard Deviation")
bb_deviation1 = input(1.0, title="BB Deviation 1")
rsi_len = input(14, title="RSI Length")
overbought = input(70, title="Overbought RSI Level")
oversold = input(30, title="Oversold RSI Level")
ma_len = input(50, title="MA Length")
stop_loss_percent = input(1.0, title="Stop Loss Percentage")
source = input(close, title="Source")

// Calculate Bollinger Bands
bb_upper = ta.sma(source, b_len) + bb_mult * ta.stdev(source, b_len)
bb_lower = ta.sma(source, b_len) - bb_mult * ta.stdev(source, b_len)
bb_upper1 = ta.sma(source, b_len) + bb_deviation1 * ta.stdev(source, b_len)
bb_lower1 = ta.sma(source, b_len) - bb_deviation1 * ta.stdev(source, b_len)

// Calculate RSI
rsi = ta.rsi(source, rsi_len)

// Calculate Moving Average
ma = ta.sma(source, ma_len)

// Determine if Bollinger Bands are contracting
bb_contracting = ta.stdev(source, b_len) < ta.stdev(source, b_len)[1]

// Entry conditions
enterLong = rsi > overbought and not bb_contracting
enterShort = rsi < oversold and not bb_contracting

// Exit conditions
exitLong = close < ma
exitShort = close > ma

// Exit trades and generate alerts
if strategy.position_size > 0 and exitLong
    strategy.close("Long") // Exit the long trade
    alert("Long Exit", alert.freq_once_per_bar_close)
if strategy.position_size < 0 and exitShort
    strategy.close("Short") // Exit the short trade
    alert("Short Exit", alert.freq_once_per_bar_close)

// Strategy orders
if enterLong
    strategy.entry("Long", strategy.long)
if enterShort
    strategy.entry("Short", strategy.short)
if exitLong
    strategy.close("Long")
if exitShort
    strategy.close("Short")

// Plotting Bollinger Bands
plot(bb_upper, color=color.blue, title="BB Upper 2")
plot(bb_lower, color=color.blue, title="BB Lower 2")
plot(bb_upper1, color=color.red, title="BB Upper 1")
plot(bb_lower1, color=color.red, title="BB Lower 1")

// Plotting RSI
plot(rsi, color=color.orange, title="RSI")

// Plotting Moving Average
plot(ma, color=color.green, title="Moving Average")

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

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