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Bollinger Bands – Momentum Model | Trading Strategy (Setup)

I. Trading Strategy

Developer: John Bollinger (Bollinger Bands®). Concept: Trend-following trading strategy based on Bollinger Bands. Research Goal: Performance verification of the 3-phase model (long/short/neutral). Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: Close[i − 1] > Upper_Band[i − 1]. Short Trades: Close[i − 1] < Lower_Band[i − 1]. Index: i ~ Current Bar. Trade Entry: Long Trades: A buy at the open is placed after a bullish Setup. Short Trades: A sell at the open is placed after a bearish Setup. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 36 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

All 3-D charts are followed by 2-D contour charts for Profit Factor, Sharpe Ratio, Ulcer Performance Index, CAGR, Maximum Drawdown, Percent Profitable Trades, and Avg. Win / Avg. Loss Ratio. The final picture shows sensitivity of Equity Curve.

Tested Variables: MA_Length & St_Dev (Definitions: Table 1):

Bollinger Bands: Profit Factor
Bollinger Bands: Profit Factor
Bollinger Bands: Sharpe Ratio
Bollinger Bands: Sharpe Ratio
Bollinger Bands: UPI
Bollinger Bands: UPI
Bollinger Bands: CAGR
Bollinger Bands: CAGR
Bollinger Bands: Max. Drawdown
Bollinger Bands: Max. Drawdown
Bollinger Bands: Percent Profitable Trades
Bollinger Bands: Percent Profitable Trades
Bollinger Bands: Avg. Win / Avg. Loss Ratio
Bollinger Bands: Avg. Win / Avg. Loss Ratio
Bollinger Bands: Equity

Figure 1 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $0).

STRATEGYSPECIFICATIONPARAMETERS
Auxiliary Variables:MA(Close, MA_Length) is a simple moving average of the close price over a period of MA_Length.
Std(MA_Length) is a standard deviation over a period of MA_Length.
St_Dev is a number of standard deviations to include in the envelope.
Upper_Band[i] = MA[i] + St_Dev * Std[i]
Lower_Band[i] = MA[i] − St_Dev * Std[i]
Index: i ~ Current Bar.
MA_Length = [10, 200], Step = 5;
St_Dev = [0.0, 3.0], Step = 0.1;
Setup:Long Trades: Close[i − 1] > Upper_Band[i − 1]
Short Trades: Close[i − 1] < Lower_Band[i − 1]
Index: i ~ Current Bar.
Filter:N/A
Entry:Long Trades: A buy at the open is placed after a bullish Setup.
Short Trades: A sell at the open is placed after a bearish Setup.
Exit:Trend Exit: Long Trades: A sell at the open is placed if Close[i − 1] < MA[i − 1]. Short Trades: A buy at the open is placed if Close[i − 1] > MA[i − 1]. Index: i ~ Current Bar.
Stop Loss Exit: ATR(ATR_Length) is the Average True Range over a period of ATR_Length. ATR_Stop is a multiple of ATR(ATR_Length). Long Trades: A sell stop is placed at [Entry − ATR(ATR_Length) * ATR_Stop]. Short Trades: A buy stop is placed at [Entry + ATR(ATR_Length) * ATR_Stop].
ATR_Length = 20;
ATR_Stop = 6;
Sensitivity Test:MA_Length = [10, 200], Step = 5
St_Dev = [0.0, 3.0], Step = 0.1
Position Sizing:Initial_Capital = $1,000,000
Fixed_Fractional = 1%
Portfolio = 42 US Futures
ATR_Stop = 6 (ATR ~ Average True Range)
ATR_Length = 20
Data:42 futures markets; 36 years (1980/01/01−2016/02/29)

Table 1 | Specification: Trading Strategy.

III. Sensitivity Test with Commission & Slippage

Tested Variables: MA_Length & St_Dev (Definitions: Table 1):

Bollinger Bands: Profit Factor
Bollinger Bands: Profit Factor
Bollinger Bands: Sharpe Ratio
Bollinger Bands: Sharpe Ratio
Bollinger Bands: UPI
Bollinger Bands: UPI
Bollinger Bands: CAGR
Bollinger Bands: CAGR
Bollinger Bands: Max. Drawdown
Bollinger Bands: Max. Drawdown
Bollinger Bands: Percent Profitable Trades
Bollinger Bands: Percent Profitable Trades
Bollinger Bands: Avg. Win / Avg. Loss Ratio
Bollinger Bands: Avg. Win / Avg. Loss Ratio
Bollinger Bands: Equity

Figure 2 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $100 Round Turn).

IV. Rating: Bollinger Bands – Momentum Model | Trading Strategy

A/B/C/D

V. Summary

(i) The default Bollinger Bands setup (MA_Length = 20) is not optimal and the lower frequency of trading is preferred (i.e. MA_Length > 60; Figure 1-2); (ii) The volatility envelope improves performance (i.e. St_Dev > 0; Figure 2); (iii) The strategy recovered from the recent drawdown.

Related Entries: Combined Donchian Channels (Entry & Exit) | Bollinger Bands %b (Setup) | Bollinger Bands %b (Setup & Filter) | Dow Theory – Trend (Entry & Exit)
Related Topics: (Public) Trading Strategies

CFTC RULE 4.41: HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN.

RISK DISCLOSURE: U.S. GOVERNMENT REQUIRED DISCLAIMER | CFTC RULE 4.41

Codes: matlab/bollinger/trend-following/

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