PENN AUTOMATED TRADING PROJECT
HISTORICAL DATA COMPETITION RESULTS, DECEMBER 2002
SIMULATION DAYS: DECEMBER 7-12, 2002
HISTORICAL TRADING DAYS: NOVEMBER 13, 19, 25
STOCK TRADED ON PXS: MSFT
BRIEF DESCRIPTION: Each team was given 3 of the 6 days during which they were allowed to run only one simulation at any time. Since each simulation takes between 8 and 12 hours of real time, there was limited opportunity for teams to get multiple runs on each day and report their best results. Each team was required to remain inside a 100,000 share position limit at all times, and teams were required to trade the strategies they had previously developed and described in advance of the historical dates being chosen and announced, and the data released.
BRIEF ANALYSIS: Perhaps the most interesting outcome was the overall strength of strategies that in some way used the order books in the computation of when to place orders, and/or in what volume. The top four strategies all shared this property, though their uses of the order book data was varied. There were a number of variants of the SOBI (Static Order Book Imbalance) strategy we studied earlier in the term. Some of these variants used a SOBI-like strategy as their main approach, while others used quartile averages as a modifying factor on top of some other strategy (such as market-making).
A number of more traditional technical trading strategies, such as those computing breakouts from moving averages, were also profitable overall. Perhaps the most common source of underperformance was the failure to saturate the allowed risk, which is discussed in the News and Notes.
KEY AND COMMENTS:
RANK | TEAM MEMBERS | DESCRIPTION | NOV 13 VALUE (MAX SHARES ) | NOV 19 VALUE (MAX SHARES) | NOV 25 VALUE (MAX SHARES) | 3-DAY VALUE | COMMENTS |
1 | Mahesh | SOBI variant: uses standard deviation of buy and sell queues | 15.1 (70.0) | 66.1 (80.0) | 44.3 (45.0) | 125.5 | A simple strategy with a good story; decent risk saturation |
2 | Lowenstein, Rowin, Schwartz, Skolnick | Market-maker with volume moderated by SOBI signal | 22.0 (80.0) | 30.0 (105.0) | 70.0 (99.0) | 122.0 | More SOBI than MM?; good (over)saturation of risk |
3 | Lao, Leung, Wong | Case-based learning on top of basic SOBI | 42.7 (47.1) | 16.2 (16.1) | 11.8 (30.9) | 70.7 | Closest to original SOBI; could have won with better risk saturation? |
4 | Yu, Zhang | Short-term trend tracking, long-term breakouts moderated by SOBI | 47.3 (72.5) | 21.1 (41.0) | -19.9 (112.0) | 48.5 | Interesting mixture of approaches; did queue info help here? |
5 | Morgovsky, Sharma | Moving average trends | 39.7 (60.0) | 13.3 (80.0) | -7.7 (60.0) | 45.3 | Highest-ranking strategy not looking at queues |
6 | Jawaid, Shah | Conjunction of range breakout and moving average crossovers | 40.8 (110.9) | -6.2 (107.1) | -0.8 (100.2) | 33.8 | Combo of two common tech trading strategies |
7 | Kadakia, Vora | Market-maker adjusted by volatility | 12.5 (57.4) | 3.6 (40.0) | 9.0 (82.0) | 25.1 | Might be only "true" market maker in group |
8 | Yu (U. Texas) | Simple trend strategy | -2.7 (90.0) | 6.9 (90.0) | 20.7 (40.0) | 24.8 | Not bad for such a simple idea |
9 | Angel, Hausman | Intersecting geometric trend lines | 3.8 (13.0) | 0.4 (5.8) | 3.1 (12.3) | 7.3 | Positive earnings each day, but greatly undersaturated risk |
10 | Chi, Koltunov, Luss, Trinh | SOBI moderated by volatility | -5.8 (55.0) | -0.1 (1.4) | -0.1 (0.9) | -6.0 | Poor saturation on last two days |
11 | Chavez | Crossover moving average with added features | -5.9 (3.5) | -1.7 (3.0) | -1.2 (2.5) | -8.8 | Plots show extreme volatility in position; very low saturation |