Tags: SMA

This strategy is based on the Bollinger Bands indicator. It enters a long position when the closing price breaks above the upper band and enters a short position when the closing price breaks below the lower band. The exit condition for the long position is when the price falls below the middle band, and the exit condition for the short position is when the price breaks above the middle band. The strategy uses the position of the price relative to the upper and lower bands of the Bollinger Bands to determine the trend direction and the timing of entries and exits.

- Calculate the upper, middle, and lower bands of the Bollinger Bands. The middle band is the simple moving average of the closing price, and the upper and lower bands are the middle band plus or minus a certain multiple of the standard deviation.
- When the closing price breaks above the upper band, enter a long position.
- When the closing price breaks below the lower band, enter a short position.
- When holding a long position, if the closing price falls below the middle band, close the long position.
- When holding a short position, if the closing price breaks above the middle band, close the short position.

- The Bollinger Bands can effectively reflect the price volatility range and trend direction. Using the position of the price relative to the Bollinger Bands for entries and exits can capture trending markets.
- The distance between the upper and lower bands and the middle band is a certain standard deviation, which can adapt to changes in price volatility. The larger the standard deviation, the farther the upper and lower bands are from the middle band.
- The exit condition uses the middle band instead of a reverse break of the upper or lower bands, allowing for early stop-loss and profit-taking.
- The parameters are adjustable, allowing for optimization of the Bollinger Band period, standard deviation multiplier, and other parameters to adapt to different symbols and timeframes.

- In a ranging market, prices may oscillate repeatedly near the upper and lower bands, potentially causing frequent entries and exits, leading to increased transaction costs.
- When the price accelerates in a trending movement, the entry point is relatively lagging, and the trend-following ability is weaker.
- At the beginning of a trend reversal, a retracement touching the middle band will trigger an exit, missing out on subsequent price movements if the trend continues to develop.

- ATR or other stop-loss indicators can be incorporated to control drawdowns.
- Dynamic position sizing for long and short positions can be used to flexibly allocate positions based on trend strength.
- More filtering conditions, such as volume and price indicators, can be added to the entry conditions to improve the reliability of entry signals.

This strategy is a classic trend-following strategy that captures trending markets using Bollinger Bands. The strategy logic is clear, and the advantages are obvious, but it also has certain risks. By optimizing stop-loss, profit-taking, position management, and entry filters, the strategy performance can be improved, and adaptability can be enhanced. However, every strategy has its limitations and needs to be flexibly applied in conjunction with actual market conditions.

/*backtest start: 2024-03-01 00:00:00 end: 2024-03-31 23:59:59 period: 1h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 // Bollinger Bands: Madrid : 14/SEP/2014 11:07 : 2.0 // This displays the traditional Bollinger Bands, the difference is // that the 1st and 2nd StdDev are outlined with two colors and two // different levels, one for each Standard Deviation strategy(shorttitle='MBB', title='Bollinger Bands', overlay=true) src = input(close) length = input.int(20, minval=1, title = "Length") mult = input.float(2.0, minval=0.001, maxval=50, title = "Multiplier") basis = ta.sma(src, length) dev = ta.stdev(src, length) dev2 = mult * dev upper1 = basis + dev lower1 = basis - dev upper2 = basis + dev2 lower2 = basis - dev2 // Strategy long_condition = ta.crossover(close, upper1) short_condition = ta.crossunder(close, lower1) if (long_condition) strategy.entry("Long", strategy.long) if (short_condition) strategy.entry("Short", strategy.short) // Exit conditions exit_long_condition = ta.crossunder(close, basis) exit_short_condition = ta.crossover(close, basis) if (exit_long_condition) strategy.close("Long") if (exit_short_condition) strategy.close("Short") colorBasis = src >= basis ? color.blue : color.orange pBasis = plot(basis, linewidth=2, color=colorBasis) pUpper1 = plot(upper1, color=color.new(color.blue, 0), style=plot.style_circles) pUpper2 = plot(upper2, color=color.new(color.blue, 0)) pLower1 = plot(lower1, color=color.new(color.orange, 0), style=plot.style_circles) pLower2 = plot(lower2, color=color.new(color.orange, 0)) fill(pBasis, pUpper2, color=color.new(color.blue, 80)) fill(pUpper1, pUpper2, color=color.new(color.blue, 80)) fill(pBasis, pLower2, color=color.new(color.orange, 80)) fill(pLower1, pLower2, color=color.new(color.orange, 80))

- Zero Lag MACD Dual Crossover Trading Strategy - High-Frequency Trading Based on Short-Term Trend Capture
- Dynamic Take Profit Bollinger Bands Strategy
- Short-term Short Selling Strategy for High-liquidity Currency Pairs
- MOST Indicator Dual Position Adaptive Strategy
- Bollinger Bands RSI Trading Strategy
- Buy and Sell Volume Heatmap with Real-Time Price Strategy
- Multi-Indicator Quantitative Trading Strategy - Super Indicator 7-in-1 Strategy
- SMK ULTRA TREND Dual Moving Average Crossover Strategy
- Quintuple Strong Moving Average Strategy
- EMA-SMA Crossover Bull Market Support Band Strategy
- Ichimoku Cloud and ATR Strategy

- Dynamic Take Profit and Stop Loss Trading Strategy Based on Three Consecutive Bearish Candles and Moving Averages
- MOST and Dual Moving Average Crossover Strategy
- Bollinger Bands Stochastic Oscillator Strategy
- MACD RSI Ichimoku Momentum Trend Following Long Strategy
- Dual Moving Average Crossover Entry Strategy
- Moving Average Crossover Strategy
- RSI Direction Change Strategy
- Trading Strategy Based on Consecutive MACD Golden and Death Crosses
- Bollinger Bands Breakout Strategy
- Enhanced Bollinger Bands RSI Trading Strategy
- Stochastic Oscillator and Moving Average Strategy
- Pivot and Momentum Strategy
- Triple EMA Crossover Strategy
- Moving Average and RSI Comprehensive Trading Strategy
- Exponential Moving Average Crossover Leverage Strategy
- Price Action, Pyramiding, 5% Profit Target, 3% Stop Loss
- Turnaround Tuesday Strategy (Weekend Filter)
- Bollinger Bands Double Standard Deviation Filtering 5-Minute Quantitative Trading Strategy
- Pivot Reversal Strategy with Pivot Exit
- Khaled Tamim's Avellaneda-Stoikov Strategy