R&D Blog
Volume Filters: Part 3 | Trading Strategy (Entry & Exit)
I. Trading Strategy
Developer: Larry Williams (“All in one: Price, volume and open interest”, Futures, 2007); R. D. Donchian (Breakout Channels). Concept: Trading strategy based on price breakouts confirmed by POIV (Price, Open Interest, and Volume) filters. Research Question: Can combined filters improve price breakouts? Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Entry Setup: High[i] > EntryUpPriceChannel[i − 1]. Short Entry Setup: Low[i] < EntryDnPriceChannel[i − 1]. Index: i ~ Current Bar. Trade Filter: POIV Filter (Table 1). Trade Entry: Long Trade Entry: A buy at the open is placed after Long Entry Setup and Long Entry Filter. Short Trade Entry: A sell at the open is placed after Short Entry Setup and Short Entry Filter. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 37 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: Entry_Look_Back & Exit_Index (Definitions: Table 1):
Figure 1 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $0).
| STRATEGY | SPECIFICATION | PARAMETERS |
| Auxiliary Variables: | Price Channels: EntryUpPriceChannel(Entry_Look_Back) is the highest high over a period of Entry_Look_Back. EntryDnPriceChannel(Entry_Look_Back) is the lowest low over a period of Entry_Look_Back. ExitUpPriceChannel(Exit_Look_Back) is the highest high over a period of Exit_Look_Back. ExitDnPriceChannel(Exit_Look_Back) is the lowest low over a period of Exit_Look_Back. On-Balance Volume (OBV): If Close[i] > Close[i − 1] then OBV[i] = OBV[i − 1] + Volume[i]; If Close[i] < Close[i − 1] then OBV[i] = OBV[i − 1] − Volume[i]; If Close[i] = Close[i − 1] then OBV[i] = OBV[i − 1]; On-Balance Open Interest (OBOI): TrueHigh[i] = max(High[i], Close[i − 1]); TrueLow[i] = min(Low[i], Close[i − 1]); Ratio[i] = (Close[i] − Close[i − 1]) / (TrueHigh[i] − TrueLow[i]); OBOI[i] = OBOI[i − 1] + OpenInterest [i] * Ratio[i]; Price/Open Interest/Volume (POIV): POIV[i] = OBV[i] + OBOI[i]; Index: i ~ Current Bar. POIV Channels: EntryUpPOIVChannel(Entry_Look_Back) is the highest POIV over a period of Entry_Look_Back. EntryDnPOIVChannel(Entry_Look_Back) is the lowest POIV over a period of Entry_Look_Back. ExitUpPOIVChannel(Exit_Look_Back) is the highest POIV over a period of Exit_Look_Back. ExitDnPOIVChannel(Exit_Look_Back) is the lowest POIV over a period of Exit_Look_Back. | Entry_Look_Back = [5, 200], Step = 5 (bars); Exit_Index= [5, 100], Step = 5 (% of Entry_Look_Back); Exit_Look_Back = Entry_Look_Back * Exit_Index ÷ 100; |
| Setup: | Long Entry Setup: If High[i] > EntryUpPriceChannel[i − 1]; Short Entry Setup: If Low[i] < EntryDnPriceChannel[i − 1]; Long Exit Setup: If Low[i] < ExitDnPriceChannel[i − 1]; Short Exit Setup: If High[i] > ExitUpPriceChannel[i − 1]; Index: i ~ Current Bar. | |
| Filter: | Long Entry Filter: If POIV[i] > EntryUpPOIVChannel[i − 1]; Short Entry Filter: If POIV[i] < EntryDnPOIVChannel[i − 1]; Long Exit Filter: If POIV[i] < ExitDnPOIVChannel[i − 1]; Short Exit Filter: If POIV[i] > ExitUpPOIVChannel[i − 1]; Index: i ~ Current Bar. | |
| Entry: | Long Trades: A buy at the open is placed after Long Entry Setup (i.e. Long Price Breakout) and Long Entry Filter (i.e. Long POIV Breakout). Short Trades: A sell at the open is placed after Short Entry Setup (i.e. Short Price Breakout) and Short Entry Filter (i.e. Short POIV Breakout). | |
| Exit: | Channel Exit: Long Trades: A sell at the open is placed after Long Exit Setup and Long Exit Filter. Short Trades: A sell at the open is placed after Short Exit Setup and Short Exit Filter. 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]. Stop Loss Exit is used to normalize risk via position sizing. | ATR_Length = 20; ATR_Stop = 6; |
| Sensitivity Test: | Entry_Look_Back = [5, 200], Step = 5 (bars) Exit_Index = [5, 100], Step = 5 (% of Entry_Look_Back) Exit_Look_Back = Entry_Look_Back * Exit_Index ÷ 100 | |
| 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; 37 years (1980/01/01−2017/07/31) |
Table 1 | Specification of Trading Strategy.
III. Sensitivity Test with Commission & Slippage
Tested Variables: Entry_Look_Back & Exit_Index (Definitions: Table 1):
Figure 2 | Portfolio Performance (Inputs: Table 1; Commission & Slippage: $100 Round Turn).
IV. Benchmarking
We benchmark the base case strategy (i.e. POIV filters turned off; Table 2) against the same strategy using POIV filters (i.e. POIV filters turned on; Table 3):
Case #1a: Entry_Look_Back = 200 (bars); Exit_Index = 50 (%); POIV Filters: Off.
Case #2a: Entry_Look_Back = 150 (bars); Exit_Index = 50 (%); POIV Filters: Off.
Case #3a: Entry_Look_Back = 100 (bars); Exit_Index = 50 (%); POIV Filters: Off.
Case #4a: Entry_Look_Back = 50 (bars); Exit_Index = 50 (%); POIV Filters: Off.
| POIV Filers: Off | Case #1a | Case #2a | Case #3a | Case #4a |
| Net Profit ($) | 440,110,888 | 152,729,764 | 177,143,846 | 19,227,786 |
| Sharpe Ratio | 0.95 | 0.78 | 0.78 | 0.49 |
| Ulcer Performance Index (UPI) | 1.22 | 0.83 | 0.93 | 0.34 |
| Profit Factor | 1.45 | 1.25 | 1.22 | 1.05 |
| CAGR (%) | 17.77 | 14.40 | 14.79 | 8.33 |
| Max. Drawdown (%) | (46.35) | (53.84) | (44.92) | (57.34) |
| Percent Profitable Trades (%) | 42.80 | 40.98 | 40.59 | 37.35 |
| Avg. Win / Avg. Loss Ratio | 1.93 | 1.80 | 1.79 | 1.76 |
Table 2 | Inputs: Table 1; Fixed Fractional Sizing: 1%; Commission & Slippage: $100 Round Turn.
Case #1b: Entry_Look_Back = 200 (bars); Exit_Index = 50 (%); POIV Filters: On.
Case #2b: Entry_Look_Back = 150 (bars); Exit_Index = 50 (%); POIV Filters: On.
Case #3b: Entry_Look_Back = 100 (bars); Exit_Index = 50 (%); POIV Filters: On.
Case #4b: Entry_Look_Back = 50 (bars); Exit_Index = 50 (%); POIV Filters: On.
| POIV Filters: On | Case #1b | Case #2b | Case #3b | Case #4b |
| Net Profit ($) | 381,486,161 | 329,089,430 | 492,907,902 | 75,105,971 |
| Sharpe Ratio | 0.97 | 0.91 | 0.93 | 0.68 |
| Ulcer Performance Index (UPI) | 1.29 | 1.19 | 1.38 | 0.64 |
| Profit Factor | 1.48 | 1.38 | 1.34 | 1.11 |
| CAGR (%) | 17.32 | 16.76 | 17.95 | 12.22 |
| Max. Drawdown (%) | (44.81) | (45.54) | (40.23) | (50.53) |
| Percent Profitable Trades (%) | 40.16 | 39.46 | 41.21 | 39.32 |
| Avg. Win / Avg. Loss Ratio | 2.20 | 2.12 | 1.91 | 1.72 |
Table 3 | Inputs: Table 1; Fixed Fractional Sizing: 1%; Commission & Slippage: $100 Round Turn.
V. Rating: Volume Filters (Part 3) | Trading Strategy
A/B/C/D
VI. Summary
(a) The POIV (Price, Open Interest, and Volume) filters improve risk adjusted returns for shorter look backs; (b) The POIV filters do not add value for longer look backs (Table 2 vs. Table 3).
L. Williams, All in one: Price, volume and open interest (2007):
ISSUES WITH VOLUME
[…] there are real problems when we use volume. Problems for stock traders arise when a huge block of stock is swapped from fund to fund; this is not real buying and selling pressure. An even greater problem crept in with the advent of arbitrage programs, whose trades do not necessarily represent supply and demand but minute price differences that are being bought and sold in huge chunks to lock in gains.
Futures traders have different problems with volume in that the largest players, commercial firms that have a business reason for trading the derivative, are usually hedging positions. So, they are not taking on speculative positions that represent buying and selling pressures. These hedges also may become spread buying/selling in the same item or spreads between, say, silver and gold, corn and wheat, or live cattle and feeders.
Related Entries: Volume Filters: Part 1 (Entry & Exit) | Volume Filters: Part 2 (Entry & Exit) | Donchian’s 20 Guides To Trading Commodities
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/VolOI/3/channels