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Multi-Indicator Synergistic Trading Strategy with Bollinger Bands, Fibonacci, MACD and RSI

Author: ChaoZhang, Date: 2024-12-12 17:20:26
Tags: BBMACDRSIFIBSMAEMASMMAWMAVWMA

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Overview

This strategy is a comprehensive trading system that combines multiple technical indicators including Bollinger Bands, Fibonacci retracement, MACD, and RSI. The strategy captures trading opportunities under different market conditions through multi-indicator coordination and applies maximum profit take-profit method for risk control. The system adopts a modular design with flexible indicator parameters, offering strong adaptability and practicality.

Strategy Principles

The strategy uses four main technical indicators to generate trading signals:

  1. Bollinger Bands signals: Price breaking below the lower band generates long signals, breaking above the upper band generates short signals
  2. Fibonacci signals: Price in 0-23.6% range generates long signals, in 61.8-100% range generates short signals
  3. MACD signals: MACD line crossing above signal line generates long signals, crossing below generates short signals
  4. RSI signals: RSI below oversold level generates long signals, above overbought level generates short signals Trading begins when any indicator generates a signal. The strategy also applies a maximum profit take-profit method, automatically closing positions when reaching preset profit targets or stop-loss levels.

Strategy Advantages

  1. Multi-indicator synergy: Improves signal reliability through integration of multiple technical indicators
  2. High flexibility: Indicator parameters can be adjusted for different market environments
  3. Comprehensive risk control: Combines maximum profit take-profit with fixed stop-loss
  4. Good adaptability: Strategy can adapt to different market cycles and volatility conditions
  5. High execution efficiency: Clear code structure with moderate computational load

Strategy Risks

  1. Signal overlap: Multiple indicators generating signals simultaneously may lead to overtrading
  2. Parameter sensitivity: Different parameter combinations may produce significantly different results
  3. Market adaptability: May underperform in certain market conditions
  4. Slippage impact: High-frequency trading may be affected by slippage
  5. Money management: Requires proper position sizing for risk control

Strategy Optimization

  1. Signal weighting: Add weights to different indicators to improve signal quality
  2. Market environment recognition: Add market environment recognition module to adjust strategy accordingly
  3. Dynamic parameters: Introduce adaptive parameter adjustment mechanism
  4. Trading costs: Optimize trading frequency to reduce costs
  5. Signal filtering: Add additional filtering conditions to reduce false signals

Summary

This strategy achieves trading efficiency while maintaining stability through multi-indicator coordination. Despite certain risks, it has practical value through proper risk control and continuous optimization. Thorough backtesting and parameter optimization are recommended before live trading.

/*backtest
start: 2024-12-04 00:00:00
end: 2024-12-11 00:00:00
period: 2h
basePeriod: 2h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Demo GPT Bollinger, Fibonacci, MACD & RSI with Max Profit Exit", overlay=true)

// === User Inputs for Bollinger Bands ===
length_bb = input.int(20, minval=1, title="Bollinger Bands Length")
maType_bb = input.string("SMA", title="Bollinger Bands MA Type", options=["SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA"])
src_bb = input(close, title="Bollinger Bands Source")
mult_bb = input.float(2.0, minval=0.001, maxval=50, title="Bollinger Bands StdDev")
offset_bb = input.int(0, title="Bollinger Bands Offset", minval=-500, maxval=500)

// === User Inputs for Fibonacci Levels ===
lookback_fib = input.int(50, minval=1, title="Fibonacci Lookback Period")

// === User Inputs for MACD ===
macd_fast = input.int(12, minval=1, title="MACD Fast Length")
macd_slow = input.int(26, minval=1, title="MACD Slow Length")
macd_signal = input.int(9, minval=1, title="MACD Signal Length")

// === User Inputs for RSI ===
rsi_length = input.int(14, title="RSI Length")
rsi_overbought = input.int(70, title="RSI Overbought Level")
rsi_oversold = input.int(30, title="RSI Oversold Level")

// === Start and End Date Inputs ===
start_date = input(timestamp("2023-01-01 00:00:00"), title="Start Date")
end_date = input(timestamp("2069-12-31 23:59:59"), title="End Date")

// === Moving Average Function ===
ma(source, length, _type) =>
    switch _type
        "SMA" => ta.sma(source, length)
        "EMA" => ta.ema(source, length)
        "SMMA (RMA)" => ta.rma(source, length)
        "WMA" => ta.wma(source, length)
        "VWMA" => ta.vwma(source, length)

// === Bollinger Bands Calculation ===
basis_bb = ma(src_bb, length_bb, maType_bb)
dev_bb = mult_bb * ta.stdev(src_bb, length_bb)
upper_bb = basis_bb + dev_bb
lower_bb = basis_bb - dev_bb

// === Fibonacci Levels Calculation ===
highest_price = ta.highest(high, lookback_fib)
lowest_price = ta.lowest(low, lookback_fib)

fib_0 = lowest_price
fib_23 = lowest_price + 0.236 * (highest_price - lowest_price)
fib_38 = lowest_price + 0.382 * (highest_price - lowest_price)
fib_50 = lowest_price + 0.5 * (highest_price - lowest_price)
fib_61 = lowest_price + 0.618 * (highest_price - lowest_price)
fib_100 = highest_price

// === MACD Calculation ===
[macd_line, signal_line, _] = ta.macd(close, macd_fast, macd_slow, macd_signal)

// === RSI Calculation ===
rsi = ta.rsi(close, rsi_length)

// === Plotting for Reference ===
plot(basis_bb, "Bollinger Basis", color=color.blue, offset=offset_bb)
p1_bb = plot(upper_bb, "Bollinger Upper", color=color.red, offset=offset_bb)
p2_bb = plot(lower_bb, "Bollinger Lower", color=color.green, offset=offset_bb)
fill(p1_bb, p2_bb, title="Bollinger Bands Background", color=color.rgb(33, 150, 243, 95))

plot(fib_0, "Fib 0%", color=color.gray)
plot(fib_23, "Fib 23.6%", color=color.yellow)
plot(fib_38, "Fib 38.2%", color=color.orange)
plot(fib_50, "Fib 50%", color=color.blue)
plot(fib_61, "Fib 61.8%", color=color.green)
plot(fib_100, "Fib 100%", color=color.red)

hline(0, "MACD Zero Line", color=color.gray)
plot(macd_line, "MACD Line", color=color.blue)
plot(signal_line, "Signal Line", color=color.orange)

hline(rsi_overbought, "RSI Overbought", color=color.red)
hline(rsi_oversold, "RSI Oversold", color=color.green)
plot(rsi, "RSI", color=color.blue)

// === Combined Trading Logic ===
// Bollinger Bands Signals
long_bb = ta.crossover(close, lower_bb)
short_bb = ta.crossunder(close, upper_bb)

// Fibonacci Signals
long_fib = close <= fib_23 and close >= fib_0
short_fib = close >= fib_61 and close <= fib_100

// MACD Signals
long_macd = ta.crossover(macd_line, signal_line)
short_macd = ta.crossunder(macd_line, signal_line)

// RSI Signals
long_rsi = rsi < rsi_oversold
short_rsi = rsi > rsi_overbought

// Combined Long and Short Conditions
long_condition = (long_bb or long_fib or long_macd or long_rsi) 
short_condition = (short_bb or short_fib or short_macd or short_rsi) 
// === Max Profit Exit Logic ===
// Define the maximum profit exit percentage
take_profit_percentage = input.float(5.0, title="Take Profit (%)", minval=0.1, maxval=100) / 100
stop_loss_percentage = input.float(2.0, title="Stop Loss (%)", minval=0.1, maxval=100) / 100

// Track the highest price during the trade
var float max_profit_price = na
if (strategy.opentrades > 0)
    max_profit_price := na(max_profit_price) ? strategy.opentrades.entry_price(0) : math.max(max_profit_price, high)

// Calculate the take profit and stop loss levels based on the max profit price
take_profit_level = max_profit_price * (1 + take_profit_percentage)
stop_loss_level = max_profit_price * (1 - stop_loss_percentage)

// Exit the trade if the take profit or stop loss level is hit
if (strategy.opentrades > 0)
    if (close >= take_profit_level)
        strategy.exit("Take Profit", from_entry="Long", limit=take_profit_level)
    if (close <= stop_loss_level)
        strategy.exit("Stop Loss", from_entry="Long", stop=stop_loss_level)

if (strategy.opentrades > 0)
    if (close <= take_profit_level)
        strategy.exit("Take Profit", from_entry="Short", limit=take_profit_level)
    if (close >= stop_loss_level)
        strategy.exit("Stop Loss", from_entry="Short", stop=stop_loss_level)

// === Execute Trades ===
if (long_condition)
    strategy.entry("Long", strategy.long, when=not na(long_condition))

if (short_condition)
    strategy.entry("Short", strategy.short, when=not na(short_condition))
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