3-Bar Momentum Pattern | Trading Strategy (Filter & Exit)

I. Trading Strategy

Concept: Short-term momentum patterns with a trend filter. Source: Hill, J. R. (1977). Stock & Commodity Market Trend Trading by Advanced Technical Analysis. Hendersonville, N.C.: Commodity Research Institute, Ltd.  Research Goal: Performance verification of the 3-Bar Momentum Pattern. Specification: Table 1. Results: Figure 1-2. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 35 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: Filter_Look_Back & Time_Index (Definitions: Table 1):

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

STRATEGY	SPECIFICATION	PARAMETERS
Auxiliary Variables:	TrueHigh[i] = max(High[i], Close[i − 1]); TrueLow[i] = min(Low[i], Close[i − 1]); TrueRange[i] = TrueHigh[i] − TrueLow[i]. Index: i ~ Current Bar.
Setup:	Long 3-Bar Momentum Pattern: A] (TrueRange[i] > TrueRange[i − 1]) & (TrueRange[i − 1] > TrueRange[i − 2]); B] (Close[i] > Open[i]) & (Close[i − 1] > Open[i − 1]) & (Close[i − 2] > Open[i − 2]); C] (Close[i] > Close[i − 1]) & (Close[i − 1] > Close[i − 2]); D] (Close[i] − Close[i − 1]) > (Close[i − 1] − Close[i − 2]); E] (High[i] − High[i − 1]) > (High[i − 1] − High[i − 2]); F] (Low[i] > Low[i − 1]) & (Low[i − 1] > Low[i − 2]). Index: i ~ Current Bar. Short 3-Bar Momentum Pattern: A] (TrueRange[i] > TrueRange[i − 1]) & (TrueRange[i − 1] > TrueRange[i − 2]); B] (Close[i] < Open[i]) & (Close[i − 1] < Open[i − 1]) & (Close[i − 2] < Open[i − 2]); C] (Close[i] < Close[i − 1]) & (Close[i − 1] < Close[i − 2]); D] (Close[i − 1] − Close[i]) > (Close[i − 2] − Close[i − 1]); E] (Low[i − 1] − Low[i]) > (Low[i − 2] − Low[i − 1]); F] (High[i] < High[i − 1]) & (High[i − 1] < High[i − 2]). Index: i ~ Current Bar.
Filter:	UpperChannel(Filter_Look_Back) is the highest high over a period of Filter_Look_Back. LowerChannel(Filter_Look_Back) is the lowest low over a period of Filter_Look_Back. Long Trend Filter: If High[i] > UpperChannel[i − 1] then the trend is “long” (only long trades are accepted). Short Trend Filter: If Low[i] < LowerChannel[i − 1] then the trend is “short” (only short trades are accepted). Index: i ~ Current Bar. Note: When Filter_Look_Back = 2, all trades are accepted since the pattern has three bars only.	Filter_Look_Back = [2, 100], Step = 2;
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:	Time Exit: nth day at the close, n = Time_Index. Pattern Exit: Long Trades: A sell stop is placed at the lowest low of the pattern minus one tick. Short Trades: A buy stop is placed at the highest high of the pattern plus one tick. 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].	Time_Index = [1, 50], Step = 1; ATR_Length = 20; ATR_Stop = 6;
Sensitivity Test:	Filter_Look_Back = [2, 100], Step = 2 Time_Index = [1, 50], 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; 35 years (1980/01/01−2015/07/31)

Table 1 | Specification: Trading Strategy.

III. Sensitivity Test with Commission & Slippage

Tested Variables: Filter_Look_Back & Time_Index (Definitions: Table 1):

Figure 2 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $50 Round Turn).

IV. Rating: 3-Bar Momentum Pattern | Trading Strategy

A/B/C/D

V. Summary

(i) The trend filter defined by the variable “Filter_Look_Back” improves performance of the 3-Bar Momentum Pattern (Figure 1-2); (ii) The longer holding period defined by the variable “Time_Index” is preferred (Figure 1-2); (iii) The pattern deteriorated since 2007.

Related Entries: Hikkake Pattern (Filter & Exit) | Price Momentum Model (Benchmark)
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/oxfordstrat/hill/3-bar-momentum