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However, the trick is that you can often modify the basic strategy and make it profitable. 1), where it was claimed that it had a high Sharpe ratio. When I backtested the strategy, it turned out not to work as well as advertised. I then tried a few simple modifications, such as decreasing the holding period and entering and exiting at different times than suggested, and was able to turn this strategy into one of my main profit centers. If you are diligent and creative enough to try the multiple variations of a basic strategy, chances are you will find one of those variations that is highly profitable.

Whittle them down to just a handful based on your personal circumstances and requirements, and by applying the screening criteria (more accurately described as healthy skepticism) that I listed earlier: r How much time do you have for baby-sitting your trading programs? r How good a programmer are you? r How much capital do you have? r Is your goal to earn steady monthly income or to strive for a large, long-term capital gain? Even before doing an in-depth backtest of the strategy, you can quickly filter out some unsuitable strategies if they fail one or more of these tests: r Does it outperform a benchmark?

This leads us to consider the information ratio or Sharpe ratio (Sharpe, 1994), rather than returns, as the proper performance measurement of a quantitative trading strategy. Information ratio is the measure to use when you want to assess a long-only strategy. It is defined as Information Ratio = Average of Excess Returns Standard Deviation of Excess Returns where Excess Returns = Portfolio Returns − Benchmark Returns Now the benchmark is usually the market index to which the securities you are trading belong.

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A Critical Perspective of ISCT

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