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Mechanical trading systems - Weissman R.L.

Weissman R.L. Mechanical trading systems - Wiley publishing , 2005 . - 240 p.
ISBN 0-471-65435-3
Download (direct link): mechanicaltradingsystems2005.pdf
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• Stop losses. Without disclosing the detailed mechanics of our trading system, the philosophy statement should let potential investors know
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MECHANICAL TRADING SYSTEMS
how stops are triggered (e.g., based on a percentage of asset value at time of entry, fixed dollar amounts, etc.). Traders using fixed dollar amounts must include a detailed review process for adjusting these amounts as volatility of the portfolio (or asset) rises/falls.
• Maximum consecutive losses. Inclusion of this number psychologically prepares investors for weathering the inevitable string of losses inherent in execution of any trading strategy. It can also clue traders in to a shift in market dynamics so that we can adjust or possibly abandon our trading system.
• Price risk management. This section should include assumptions regarding worst peak-to-valley drawdowns in equity, allowances for exceeding worst peak-to-valley drawdown assumptions (typically a 50 percent increase over the largest historical drawdown), and a stop loss for the trading system. Chapter 8 addresses the issue of trading system stop losses in greater detail; the basic idea is adherence to a maximum peak-to-valley drawdown for the trading system (37.5 percent of equity under management is a popular system stop-loss level for trading systems). Violation of this peak-to-valley drawdown percentage will result in liquidation of the fund (or trading account).
The worst peak-to-valley drawdown number should be broken down into two subcategories—worst monthly peak-to-valley drawdown and maximum peak-to-valley drawdown—which could encompass several calendar months. Exclusion of this second measurement masks the true risk of the trading system.
Finally, this section should include the maximum duration of drawdowns. This performance measure psychologically clues investors in to the amount of time that they can expect to hold their investment without experiencing a new high water mark in account equity. As with many of the other measures covered in the philosophy statement, significant deviations in durations of drawdowns are also instructive as they can alert traders to fundamental shifts in market behavior.
MEASURING TRADING SYSTEM PERFORMANCE

The Sharpe ratio continues to be the traditional and standard measure of performance of both managed funds and trading systems. This ratio is defined as the expected return minus the risk-free interest rate (e.g., treasury bills20) divided by the standard deviation of returns. The “expected return” is defined as the average past return of the entire data sampling in question. Standard deviation is a statistical measure of volatility of the entire data history. It measures the degree of dispersion of the individual data points in the history from the mean (or average) of that history. High standard deviation
System Development and Analysis
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(high volatility) occurs when many of the individual time intervals within the history deviate dramatically from the average past return for the period.
My objective is not to provide a comprehensive exposition of all the shortcomings of the Sharpe ratio, but rather to outline some of the most dangerous flaws in utilizing this ratio to the exclusion of other measures of system performance.21 The basic premise of the Sharpe ratio is that the wider dispersal of individual returns from the average past return, the riskier the investment. Although it is true that a wider dispersal of individual returns from the average past return does suggest higher volatility, because the Sharpe ratio makes no distinction between profits and losses in the composition of its measure of volatility, high volatility of returns does not necessarily equate to a riskier investment. Because the ratio cannot distinguish between upside and downside fluctuations in performance histories, it tends to penalize successful trend traders, because typically they experience dramatic increases in account equity followed by small retracements.
In addition, the Sharpe ratio does not distinguish between intermittent losses and consecutive losses; instead, it measures only the standard deviation of returns for the period analyzed. For example, say Trading System A generates three consecutive monthly losses of $4,000, followed by nine consecutive monthly gains of $3,500 for a total annual profit of $19,500, and Trading System B alternates between monthly profits of $7,500 and losses of $3,750 for a total annual profit of $22,500. Because the Sharpe ratio does not distinguish between intermittent and consecutive losses and because it cannot distinguish between upside and downside fluctuations in the performance history, it will show Trading System A as the superior trading vehicle despite the fact that System A had to endure a $12,000 drawdown in equity and enjoyed a lower average annualized return on investment.
By contrast, the profit to maximum drawdown ratio (P:MD) utilized throughout this book does distinguish between upside and downside volatility while simultaneously punishing systems (and managers) that endure large consecutive losses. Despite the superiority of the profit to maximum drawdown ratio as a measure of system performance, Sharpe ratio continues to be the industrywide standard.
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