It is a commonplace that risk management is critical to trading success. What constitutes good risk management, however, is anything but commonplace knowledge. Was VaR the number that killed us, as Pablo Triana claimed, or is it a useful, perhaps even indispensable, tool? Should risk management teams have their separate turf or should they be integrated with the trading desks? And what do you have to know to be a risk manager?

Davis W. Edwards addresses all of these questions, with particular emphasis on the third, in *Risk Management in Trading: Techniques to Drive Profitability of Hedge Funds and Trading Desks* (Wiley, 2014). The book is a useful self-study guide for those who aspire to become risk managers; each chapter ends with a set of questions to test the reader’s knowledge, and there is an answer key at the back of the book. It also goes a long way toward satisfying the curiosity of those who want to know just what it is that risk managers really do. It does not, however, directly address the concerns of the individual trader who wants to incorporate sound risk management principles into his business model.

After three preliminary chapters (on trading and hedge funds, financial markets, and financial mathematics) Edwards gets to the heart of the matter. He discusses backtesting and trade forensics; mark-to-market accounting; value-at-risk; hedging; options, Greeks, and non-linear risks; and credit value adjustments (CVA).

To give you a better sense of the level of the book—and so you can test your own skills—here are a few questions from the quizzes.

“Chang, a trader at a hedge fund, is examining two trading strategies. Strategy A has a 2.0 Sharpe ratio, Strategy B has a -0.1 Sharpe ratio, and the strategies have a -1.0 correlation. What is the best combination of strategies?” (p. 119)

“Angela, a risk manager at a mining company, wants to hedge the output of copper ore using exchange traded copper futures. What is the minimum variance hedge ratio if both copper and copper ore have 17 percent volatility and are 85 percent correlated?” (p. 195)

“Richard, a risk manager at a bank, wants to estimate the loss caused by owning a long put option given a $2 per unit rise in price of the underlying. The option is for 100,000 units, the delta is -0.6, gamma is 0.1, and interest rates are zero. Using a second-order approximation (a delta/gamma approximation) what is the expected profit or loss?” (p. 235)

“Benjamin, a credit analyst at a hedge fund, is trying to calculate the default probability of a company that doesn’t have traded CDS spreads. The company issued bonds at 6 percent. At the time of issuance, risk-free rates were 3.5 percent and the spread for liquidity risk was 50 basis points. The estimated recovery rate in event of a default is 40 percent.” (p. 264)

I’m not providing the answers. If you’re either supremely confident in your responses or you haven’t a clue, this book probably isn’t for you. If, however, you’re somewhere in between, Edwards’ book may help you gain some skills.