Trading System : Risk Control, Money Management, and Portfolio Design

Risk Control, Money Management, and Portfolio Design

All traders have accounts of finite size as well as written or unwritten guidelines for expected performance over the immediate future. These performance guidelines have a great influence on the existence and longevity of an account. For example, consider a trading system that produces a 30 percent loss over five months. The same trading system then goes on to perform extremely well. One person may close the account after the 30 percent drawdown. Another may go on to reap excellent returns. Your money management rules could cause you to close out an account too soon, or keep it open too long. Thus, money management guidelines are crucial to trading success.

Given performance expectations and the finite size of the trading account, it is essential to maintain good risk control, sensible money management, and good portfolio design. Risk control is the process of managing open trades with predefined exit orders. Money management rules determine how many contracts to trade in a given market and the amount of money to risk in particular positions. Portfolio-level issues must be considered to obtain a smoother equity curve.

Table 2.7 illustrates the effects of not using an initial money management stop versus adding an initial money management stop of $2,000. The trading system, a “canned” system using four consecutive up or down closes to initiate a trade, comes with the Omega Research’s System Writer Plus™.

As expected, the largest losing trade can be horrifying, and most real-world accounts would probably close before swallowing such huge losses. Of course, recent headlines of billion-dollar-plus losses in sophisticated trading firms illustrate that trading without adequate risk control is not uncommon.

Adding a money management stop constrains the worst initial loss to predictable levels.

Even with slippage, the largest loss is usually lower than trading without any stop at all. Thus, your profitability is likely to improve with improved risk control. Observe that average net profits improved from a loss of -$5,085 with no stop to a loss of -$424 using risk control. The maximum drawdown also improved with the added risk control. The lesson from this comparison is clear. There is much to gain if you use proper risk control.


Table 2.7 Effect of adding an initial money management stop, May 1989-June 1995 (dollars)

You can reduce swings inequity and improve account longevity if you combine risk control with sound money management ideas. Your money management guidelines will specify how much of your equity to risk on any trade. These guidelines convert the initial stop into a specific percentage of your equity. One common rule of thumb is to risk or “bet” just 2 percent of your account equity per trade.

The 2-percent rule converts into a $1,000 initial stop for a $50,000 account.

This $1,000 initial stop is often called a “hard dollar stop,” applied to the entire position. A position could have one or more contracts. Thus, if you had two contracts, you would protect the position with a stop-loss order placed $500 away from the entry price. Chapter 7 discusses the bet size issue in detail.
Overtrading an account is a common problem cited by analysts for many account closures. For example, if you consistently bet more than 2 percent per trade, you are overtrading an account. If you do not use any initial money management stop, then the risk could be much greater than 2 percent of equity. In the worst case, you risk your entire account equity. Some extra risk, say up to 5 percent of equity, may be justified if the market presents an extraordinary market opportunity (see chapter 4). However, consistently exceeding the 2 percent limit can cause large and unforeseen swings in account equity.

As another rule of thumb, you are overtrading an account if the monthly equity swings are often greater than 20 percent. Again, there may be an occasional exception due to extraordinary market conditions.

You must also consider the benefits and problems of diversification, that is, trading many different markets in a single account. The main advantage of trading many markets is that it increases the odds of participating in major moves. The main problem is that many of the markets respond to the same or similar fundamental forces, so their price moves are highly correlated in time. Therefore, trading many correlated markets is similar to trading multiple contracts in one market.

For example

The Swiss franc (SF) and Deutsche mark (DM) often move together, and trading both these markets is equivalent to trading multiple contracts in either the franc or the mark. Let us look specifically at SF and DM continuous contracts from May 26, 1989, through June 30, 1995, with a dual moving average system using a $1,500 stop and $100 for slippage and commissions. The two moving averages were 7 and 65 days. As Figure 2.9 shows, the equity curves have a correlation of 83 percent. For example, you would have made $60,619 trading one contract each of SF and DM, but your profits would have been $63,850 trading two contracts of DM and $57,388 trading two contracts of SF.

Figure 2.9 Swiss franc and Deutsche mark equity curves are highly correlated at 83 percent.

Note one important difference between the two cases. Since the two markets may have a negative correlation from time to time, the drawdown for both SF and DM together maybe in between trading two contracts of just DM or SF. For example, the drawdown for SF and DM, in this case, was -$10,186 versus -$22,375 for two DM contracts and -$9,950 for two SF contracts. Hence, the benefits of trading correlated markets are relatively small. Thus, it may be better to trade uncorrelated or weakly correlated markets in the same portfolio.


Figure 2.10 Adding 10-year T-note (TY) and cotton to the portfolio trading just Swiss francs provides a smoother equity curve versus trading three SF contracts.

The benefits of adding usually unrelated markets to a portfolio can be illustrated by an example of trading the Swiss franc (SF), cotton (CT) and 10-year Treasury note (TY) in a single account, using the same dual moving average system as above. The paper profits from trading three SF contracts add up to $86,801 versus $85,683 for SF plus TY and CT. The equity curve for the two combinations is shown in Figure 2.10. The smoothness of the two curves can be compared by using linear regression analysis to calculate the standard error (SE) of the daily equity curve. The SE for trading three SF contracts in $6238 and the SE for SF and TY plus CT is just $4,902, a reduction of 21 percent. Thus, adding TY and CT to a portfolio of SF produced a smoother equity curve with essentially the same nominal profits.

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Figure 2.11 This contrived jagged equity curve has a standard error of 2.25. The perfectly smooth equity curve has a SE of zero. The standard deviation of monthly returns is 33 percent.

The relevance of the standard error is illustrated in Figure 2.11, which shows a contrived equity curve.

The SE for that curve was 2.25 since it was quite “jagged.” Perfectly smooth equity would have a SE reading of zero.

Diversification can be more than just adding markets. You can also trade multiple trading systems and multiple time frames within a single account. You should try to use uncorrelated or weakly correlated systems. In summary, risk control, money management, and portfolio design are important issues in designing trading systems.