R&D Blog
Bollinger Bands %b | Trading Strategy (Setup & Filter)
I. Trading Strategy
Developer: Connors Group. Concept: Mean-reversion trading strategy based on Bollinger Bands %b. Research Goal: Performance verification of the pattern setup and trend filter. Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: (Close[i − 1] > MA_Trend[i − 1]) & (%b[i − 1] < 0.2) & (%b[i − 2] < 0.2) & (%b[i − 3] < 0.2). Short Trades: (Close[i − 1] < MA_Trend[i − 1]) & (%b[i − 1] > 0.8) & (%b[i − 2] > 0.8) & (%b[i − 3] > 0.8). 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: 32 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 & MA_Trend_Length (Definitions: Table 1):
Figure 1 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $0).
| STRATEGY | SPECIFICATION | PARAMETERS |
| Auxiliary Variables: | MA_Trend(Close, MA_TrendLength) is a simple moving average of the close price over a period of MA_TrendLength. The default value for MA_TrendLength is 200. MA(Close, MA_Length) is a simple moving average of the close price over a period of MA_Length. The default value for MA_Length is 5. Std(MA_Length) is a sample standard deviation over a period of MA_Length. St_Dev is a number of standard deviations to include in the price envelope. The default value for St_Dev is 1. UpperBand[i] = MA[i] + St_Dev * Std[i]. LowerBand[i] = MA[i] − St_Dev * Std[i]. %b[i] = (Close[i] − LowerBand[i]) / (UpperBand[i] − LowerBand[i]). The lower the %b is, the more “oversold” the market is relative to recent history. The higher the %b is, the more “overbought” the market is relative to recent history. Index: i ~ Current Bar. | MA_TrendLength = [80, 250], Step = 5; MA_Length = [5, 60], Step = 1; St_Dev = 1; |
| Setup: | Long Trades: (Close[i − 1] > MA_Trend[i − 1]) & (%b[i − 1] < 0.2) & (%b[i − 2] < 0.2) & (%b[i − 3] < 0.2). Short Trades: (Close[i − 1] < MA_Trend[i − 1]) & (%b[i − 1] > 0.8) & (%b[i − 2] > 0.8) & (%b[i − 3] > 0.8). 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 close is placed after %b > 0.8. Short Trades: A buy at the close is placed after %b < 0.2. 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_TrendLength = [80, 250], Step = 5 MA_Length = [5, 60], Step = 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; 32 years (1980/01/01−2011/12/31) |
Table 1 | Specification: Trading Strategy.
III. Sensitivity Test with Commission & Slippage
Tested Variables: MA_Length & MA_Trend_Length (Definitions: Table 1):
Figure 2 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $50 Round Turn).
IV. Rating: Bollinger Bands %b | Trading Strategy
A/B/C/D
Related Posts: Bollinger Bands %b (Setup)
Related Topics: (Public) Trading Strategies
Proprietary 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/connors/%b/