High-Frequency Trading Sharpe Ratio [ZT]# Stock
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How Profitable Are High-Frequency Trading Strategies?
Oct 2 2009 | 9:25am ET
By Irene Aldridge -- High-frequency trading has been taking Wall Street by
storm. While no institution thoroughly tracks the performance of high-
frequency funds, colloquial evidence suggests that the majority of high-
frequency managers delivered positive returns in 2008, while 70% of low-
frequency practitioners lost money, according to The New York Times.
The discourse on the profitability of high-frequency trading strategies
always runs into the question of availability of performance data on returns
realized at different frequencies. Hard data on performance of high-
frequency strategies is indeed hard to find. Hedge funds successfully
running high-frequency strategies tend to shun the public limelight. Others
produce data from questionable sources.
Yet, performance at different frequencies can be compared using publicly
available data by estimating the maximum potential profitability.
Profitability of trading strategies is often measured by Sharpe ratios, a
risk-adjusted return metric first proposed by a Nobel Prize winner, William
Sharpe. A Sharpe ratio measures return per unit of risk; a Sharpe ratio of
2 means that the average annualized return on the strategy twice exceeds the
annualized standard deviation of strategy returns: if the annualized return
of a strategy is 12%, the standard deviation of returns is 6%. The Sharpe
ratio further implies the distribution of returns: statistically, in 95% of
cases, the annual returns are likely stay within 2 standard deviations from
the average. In other words, in any given year, the strategy of Sharpe
ratio of 2 and annualized return of 12% is expected to generate returns from
0% to 24% with 95% statistical confidence, or 95% of time.
The maximum possible Sharpe ratio for a given trading frequency is computed
as a sample period’s average range (High – Low) divided by the sample
period’s standard deviation of the range, adjusted by square root of the
number of observations in a year. Note that high-frequency strategies
normally do not carry overnight positions, and, therefore, do not incur the
overnight carry cost often proxied by the risk-free rate in Sharpe ratios of
longer-term investments.
The table below compares the maximum Sharpe Ratios that could be attained at
10-second, 1-minute, 10-minute, 1-hour and 1-day frequencies in EUR/USD.
The results are computed ex-post with perfect 20/20 hindsight on the data
for 30 trading days from February 9, 2009 through March 22, 2009. The
return is calculated as the maximum return attainable during the observation
period within each interval at different frequencies. Thus, the average 10
-second return is calculated as the average of ranges (high-low) of EUR/USD
prices in all 10-second intervals from February 9, 2009 through March 22,
2009. The standard deviation is then calculated as the standard deviation
of all price ranges at a given frequency within the sample.
Time Period
Average Max. Gain (Range) per Period Range Standard Deviation per
Period Number of observations in the sample period Maximum
Annualized Sharpe Ratio
10 seconds 0.04% 0.01% 2,592,000 5879.8
1 minute 0.06% 0.02% 43,200 1860.1
10 minutes 0.12% 0.09% 4,320 246.4
1 hour 0.30% 0.19% 720 122.13
1 day 1.79% 0.76% 30 37.3
As the table above shows, the maximum profitability of trading strategies
measured using Sharpe ratios increases with increases in trading frequencies
. From February 9, 2009 through March 22, 2009, the maximum possible
annualized Sharpe ratio for EUR/USD trading strategies with daily position
rebalancing was 37.3, while EUR/USD trading strategies that held positions
for 10 seconds could potentially score Sharpe ratios well over 5,000 (five
thousand) mark.
In practice, well-designed and implemented strategies trading at the highest
frequencies tend to produce double-digit Sharpe ratios. Real-life Sharpe
ratios for well-executed daily strategies tend to fall in the 1-2 range.
How Profitable Are High-Frequency Trading Strategies?
Oct 2 2009 | 9:25am ET
By Irene Aldridge -- High-frequency trading has been taking Wall Street by
storm. While no institution thoroughly tracks the performance of high-
frequency funds, colloquial evidence suggests that the majority of high-
frequency managers delivered positive returns in 2008, while 70% of low-
frequency practitioners lost money, according to The New York Times.
The discourse on the profitability of high-frequency trading strategies
always runs into the question of availability of performance data on returns
realized at different frequencies. Hard data on performance of high-
frequency strategies is indeed hard to find. Hedge funds successfully
running high-frequency strategies tend to shun the public limelight. Others
produce data from questionable sources.
Yet, performance at different frequencies can be compared using publicly
available data by estimating the maximum potential profitability.
Profitability of trading strategies is often measured by Sharpe ratios, a
risk-adjusted return metric first proposed by a Nobel Prize winner, William
Sharpe. A Sharpe ratio measures return per unit of risk; a Sharpe ratio of
2 means that the average annualized return on the strategy twice exceeds the
annualized standard deviation of strategy returns: if the annualized return
of a strategy is 12%, the standard deviation of returns is 6%. The Sharpe
ratio further implies the distribution of returns: statistically, in 95% of
cases, the annual returns are likely stay within 2 standard deviations from
the average. In other words, in any given year, the strategy of Sharpe
ratio of 2 and annualized return of 12% is expected to generate returns from
0% to 24% with 95% statistical confidence, or 95% of time.
The maximum possible Sharpe ratio for a given trading frequency is computed
as a sample period’s average range (High – Low) divided by the sample
period’s standard deviation of the range, adjusted by square root of the
number of observations in a year. Note that high-frequency strategies
normally do not carry overnight positions, and, therefore, do not incur the
overnight carry cost often proxied by the risk-free rate in Sharpe ratios of
longer-term investments.
The table below compares the maximum Sharpe Ratios that could be attained at
10-second, 1-minute, 10-minute, 1-hour and 1-day frequencies in EUR/USD.
The results are computed ex-post with perfect 20/20 hindsight on the data
for 30 trading days from February 9, 2009 through March 22, 2009. The
return is calculated as the maximum return attainable during the observation
period within each interval at different frequencies. Thus, the average 10
-second return is calculated as the average of ranges (high-low) of EUR/USD
prices in all 10-second intervals from February 9, 2009 through March 22,
2009. The standard deviation is then calculated as the standard deviation
of all price ranges at a given frequency within the sample.
Time Period
Average Max. Gain (Range) per Period Range Standard Deviation per
Period Number of observations in the sample period Maximum
Annualized Sharpe Ratio
10 seconds 0.04% 0.01% 2,592,000 5879.8
1 minute 0.06% 0.02% 43,200 1860.1
10 minutes 0.12% 0.09% 4,320 246.4
1 hour 0.30% 0.19% 720 122.13
1 day 1.79% 0.76% 30 37.3
As the table above shows, the maximum profitability of trading strategies
measured using Sharpe ratios increases with increases in trading frequencies
. From February 9, 2009 through March 22, 2009, the maximum possible
annualized Sharpe ratio for EUR/USD trading strategies with daily position
rebalancing was 37.3, while EUR/USD trading strategies that held positions
for 10 seconds could potentially score Sharpe ratios well over 5,000 (five
thousand) mark.
In practice, well-designed and implemented strategies trading at the highest
frequencies tend to produce double-digit Sharpe ratios. Real-life Sharpe
ratios for well-executed daily strategies tend to fall in the 1-2 range.