R&D Blog
Wide Range N-Day Pattern | Trading Strategy (Setup)
I. Trading Strategy
Developer: Toby Crabel (Narrow Range N-Day Pattern; Note: Wide Range N-Day Pattern applies a reverse logic of Narrow Range N-Day Pattern). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility cycles (expansion-contraction) with different look back periods. Research Goal: Performance verification of Wide Range N-Day patterns. Specification: Table 1. Results: Figure 1-2. Trade Setup: Wide Range N-Day pattern is defined as the widest range from high to low of any N-day period relative to any N-day period within the previous 20 market days. Trade Entry: Opening Range Breakout (ORB). A trade is taken at a predetermined amount above/below the open. The predetermined amount is called the stretch. Long Trades: A buy stop is placed at [Open + Stretch]. Short Trades: A sell stop is placed at [Open − Stretch]. The first stop that is traded is the position. The other stop is the protective stop. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 39 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: N & Look_Back (Definitions: Table 1):
Figure 1 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $0).
| STRATEGY | SPECIFICATION | PARAMETERS |
| Auxiliary Variables: | Noise: The difference between the open for each day and the closest extreme to the open on each day (Noise[i] = min(High[i] − Open[i], Open[i] − Low[i])). Average_Noise: The simple moving average of Noise over a period of Stretch_Length. Stretch[i] = Average_Noise[i] * Stretch_Multiple. Index: i ~ Current Bar. | Stretch_Length = 10; Stretch_Multiple = 2; |
| Setup: | Wide Range N-Day pattern is defined as the widest range from high to low of any N-day period relative to any N-day period within the previous 20 market days (Look_Back). In the sensitivity test, we research the size of the wide range (N) and look back period (Look_Back). | N = [2, 19], Step = 1; Look_Back = [20, 50], Step = 1; |
| Filter: | N/A | |
| Entry: | Opening Range Breakout (ORB). A trade is taken at a predetermined amount above/below the open. The predetermined amount is called the stretch (defined above). Long Trades: A buy stop is placed at [Open + Stretch]. Short Trades: A sell stop is placed at [Open − Stretch]. The first stop that is traded is the position. The other stop is the protective stop. If both stops are triggered during the same day, we account only for one entry and one exit (no reversals) and assume the trade was a loser. | |
| Exit: | Time Exit: nth day at the close, n = Time_Index. Stretch Exit: Long Trades: A sell stop is placed at [Open − Stretch]. Short Trades: A buy stop is placed at [Open + Stretch]. The values are calculated at the day of entry. 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 = 10; ATR_Length = 20; ATR_Stop = 6; |
| Sensitivity Test: | N = [2, 19], Step = 1 Look_Back = [20, 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; 39 years (1980/01/01−2019/07/31) |
Table 1 | Specification: Trading Strategy.
III. Sensitivity Test with Commission & Slippage
Tested Variables: N & Look_Back (Definitions: Table 1):
Figure 2 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $50 Round Turn).
IV. Benchmarking
We benchmark Wide Range N-Day Patterns (Table 2) against Narrow Range N-Day Patterns (Table 3):
Case #1: N = 2; Look_Back = 20 (Base Case).
Case #2: N = 2; Look_Back = 30.
Case #3: N = 2; Look_Back = 40.
Case #4: N = 2; Look_Back = 50.
| Wide Range | Case #1 | Case #2 | Case #3 | Case #4 |
| Net Profit ($) | (873,375) | (828,372) | (783,222) | (744,736) |
| Sharpe Ratio | (1.45) | (1.37) | (1.26) | (1.18) |
| Ulcer Performance Index (UPI) | (0.07) | (0.07) | (0.06) | (0.06) |
| Profit Factor | 0.74 | 0.73 | 0.72 | 0.72 |
| CAGR (%) | (5.09) | (4.37) | (3.79) | (3.39) |
| Max. Drawdown (%) | (88.33) | (84.56) | (80.60) | (76.88) |
| Percent Profitable Trades (%) | 23.82 | 22.78 | 22.44 | 22.14 |
| Avg. Win / Avg. Loss Ratio | 2.38 | 2.48 | 2.50 | 2.52 |
Table 2 | Inputs: Table 1; Fixed Fractional Sizing: 1%; Commission & Slippage: $50 Round Turn.
| Narrow Range | Case #1 | Case #2 | Case #3 | Case #4 |
| Net Profit ($) | 404,740 | 624,920 | 380,268 | 625,868 |
| Sharpe Ratio | 0.18 | 0.29 | 0.23 | 0.36 |
| Ulcer Performance Index (UPI) | 0.10 | 0.24 | 0.13 | 0.27 |
| Profit Factor | 1.02 | 1.05 | 1.05 | 1.09 |
| CAGR (%) | 0.86 | 1.23 | 0.82 | 1.24 |
| Max. Drawdown (%) | (19.97) | (13.50) | (15.60) | (13.62) |
| Percent Profitable Trades (%) | 30.38 | 30.27 | 30.19 | 30.44 |
| Avg. Win / Avg. Loss Ratio | 2.34 | 2.42 | 2.42 | 2.48 |
Table 3 | Inputs: Table 1; Fixed Fractional Sizing: 1%; Commission & Slippage: $50 Round Turn.
V. Rating: Wide Range N-Day Pattern | Trading Strategy
A/B/C/D
VI. Summary
Narrow Range N-Day Patterns (Table 3) perform better than Wide Range N-Day Patterns (Table 2).
Related Entries: Narrow Range N-Day Pattern | 2-Bar Narrow Range Pattern (Setup & Exit) | 2-Bar Narrow Range Pattern (Exits) | NR7 Pattern (Setup & 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/crabel/2bar-wr