The third principle of modern quantitative risk management was an antisurprise, which we called “risk ignition.” This is an idea that traces back to John Kelly—who we met briefly in Chapter 1—in 1956. He discovered that if you take an optimal amount of risk—not more and not less—you can be certain of exponentially growing success, which will always leave you better off than any other strategy. Instead of gains and losses bobbing you up and down, you can take off like a rocket to astronomical success.
Taking less risk than is optimal is not safer; it just locks in a worse outcome. In competitive fields, doing less than the best often means failing completely. Taking more risk than is optimal also results in a worse outcome, and often leads to complete disaster.
In theory. It turned out that risk duality was the concept necessary to make risk ignition work in practice.
Consider, for example, a casino. Thousands of people are in there betting red or black in roulette, laying chips on pass or don't pass in craps, spinning slot machines, and making other wagers. None of this represents risk to the casino, as it has both sides of most bets, plus an edge such that it pays out winners less than it collects from losers. There is some unmatched risk, but it averages out very quickly.
When analyzing these games, most quantitative people focus on the house edge, the fraction of each dollar bet the casino gets on average. But a casino cares about something different: ...