You also goes to Dave Lowdon of Logical Systems Inc. for programming support and to Mark Wiemeler and Ken McGahan for the charts presented in the book. Thanks are also due to graduate assistants Daniel Snyder and V. Anand for their untiring efforts. Special thanks are due to John Oleson for introducing me to chart-based risk and reward estimation techniques. My debt to these individuals parallels the enormous debt I owe to Dean Olga Engelhardt for encouraging me to write the book and Associate Dean Kathleen Carlson for providing valuable administrative support. My chairperson, Professor C. T. Chen, deserves special commendation for creating an environment conducive to thinking and writing. I also
wish to thank the Northeastern Illinois University Foundation for its generous support of my research endeavors.

In a sense, every successful trader employs money management principles in the course of futures trading, even if only unconsciously. The goal of this book is to facilitate a more conscious and rigorous adoption of these principles in everyday trading. This chapter outlines the money management process in terms of market selection, exposure control, trade-specific risk assessment, and the allocation of capital across competing opportunities. In doing so, it gives the reader a broad overview of the book. A signal to buy or sell a commodity may be generated by a technical or chart-based study of historical data. Fundamental analysis, or a study of demand and supply forces influencing the price of a commodity, could also be used to generate trading signals. Important as signal generation is, it is not the focus of this book. The focus of this book is on the decision-making process that follows a signal.

First, the trader must decide whether or not to proceed with the signal. This is a particularly serious problem when two or more commodities are vying for limited funds in the account. Next, for every signal accepted, the trader must decide on the fraction of the trading capital that he or she is willing to risk. The goal is to maximize profits while protecting the bankroll against undue loss and overexposure, to ensure participation in future major moves. An obvious choice is to risk a fixed dollar amount every time.

More simply, the trader might elect to trade an equal number of contracts of every commodity traded. However, the resulting allocation of capital is likely to be suboptimal. For each signal pursued, the trader must determine the price that unequivocally confirms that the trade is not measuring up to expectations. This price is known as the stop-loss price, or simply the stop price. The dollar value of the difference between the entry price and the stop price defines the maximum permissible risk per contract. The risk capital allocated to the trade divided by the maximum permissible risk per contract determines the number of contracts to be traded. Money management encompasses the following steps:

1. Ranking available opportunities against an objective yardstick of desirability
2. Deciding on the fraction of capital to be exposed to trading at any given time
3. Allocating risk capital across opportunities
4. Assessing the permissible level of loss for each opportunity accepted for trading
5. Deciding on the number of contracts of a commodity to be traded, using the information from steps 3 and 4

The following paragraphs outline the salient features of each of these
steps.

There are over 50 different futures contracts currently traded, making it difficult to concentrate on all commodities. Superimpose the practical constraint of limited funds, and selection assumes special significance. Ranking of competing opportunities against an objective yardstick of desirability seeks to alleviate the problem of virtually unlimited opportunities competing for limited funds. The desirability of a trade is measured in terms of (a) its expected profits , (b) the risk associated with earning those profits, and (c) the investment required to initiate the trade. The higher the expected profit for a given level of risk, the more desirable the trade. Similarly, the lower the investment needed to initiate a trade, the more desirable the trade. In Chapter 3, we discuss chart-based approaches to estimating risk and reward. Chapter 5 discusses alternative approaches to commodity selection.

Having evaluated competing opportunities against an objective yardstick of desirability, the next step is to decide upon a cutoff point or benchmark level so as to short-list potential trades. Opportunities that fail to measure up to this cutoff point will not qualify for further consideration. Overall exposure refers to the fraction of total capital that is risked across all trading opportunities. Risking 100 percent of the balance in the account could be ruinous if every single trade ends up a loser. At the other extreme, risking only 1 percent of capital mitigates the risk of bankruptcy, but the resulting profits are likely to be inconsequential.
The fraction of capital to be exposed to trading is dependent upon the returns expected to accrue from a portfolio of commodities. In general, the higher the expected returns, the greater the recommended level of exposure. The optimal exposure fraction would maximize the overall expected return on a portfolio of commodities. In order to facilitate the analysis, data on completed trade returns may be used as a proxy for expected returns. This analysis is discussed at length in Chapter 7.

Another relevant factor is the correlation between commodity returns. TWO commodities are said to be positively correlated if a change in one is accompanied by a similar change in the other. Conversely, two commodities are negatively correlated if a change in one is accompanied by an opposite change in the other. The strength of the correlation depends on the magnitude of the relative changes in the two commodities. In general, the greater the positive correlation across commodities in a portfolio, the lower the theoretically safe overall exposure level. This safeguards against multiple losses on positively correlated commodities. By the same logic, the greater the negative correlation between commodities in a portfolio, the higher the recommended overall optimal exposure. Chapter 4 discusses the concept *of correlations and their role in reducing overall portfolio risk.

The overall exposure could be a fixed fraction of available funds.
Alternatively, the exposure fraction could fluctuate in line with changes
in trading account balance. For example, an aggressive trader might
want to increase overall exposure consequent upon a decrease in account
balance. A defensive trader might disagree, choosing to increase overall
exposure only after witnessing an increase in account balance. These
issues are discussed in Chapter 7.

Finally, I wish to thank Karl Weber, Associate Publisher, John Wiley & Sons, for his infinite patience with and support of a first-time writer.