In the wake of the economic scandals of 2008-2009 and more recent events like the JP Morgan’s “London Whale” losses the media has directed substantial scrutiny at trader compensation and the role it plays in trading losses. This discussion has focused on one point: traders who are paid primarily via bonuses are paid both for performance (which is arguably good) and for volatility (which can cause havoc).
Consider a trader managing a $100M portfolio who is paid $300K per year plus 15% of each year’s profits. Clearly this trader has what amounts to a cash settled call option on the portfolio. If the portfolio makes money, he gets 15%. If it loses money, he loses nothing. It’s easy to see how this could warp the trader’s behavior in the direction of taking excessive risk anytime the portfolio was close to break-even as the year end approached. Taking a 20% coin flip at the end of a break-even year would result in an expected profit of $1.5M for the trader (half the time he wins $3M, half the time he gets no bonus) and an expected loss of $1.5M for his employer/investors (who would win $17M after fees half the time, and lose $20M the other half of the time).
This phenomenon is undeniably real, and anyone designing the compensation packages for traders would be wise to take it into account. But I would argue the media discussion of the topic misses one central fact: traders don’t like to get fired. This rather common-sense aversion on their part goes a long ways towards explaining certain market events. More importantly it can directly put money in your pocket once you know what to look for. Continue reading
Somewhere along the way someone probably told you not to play the lottery – that it’s a dumb idea. And this is true. The typical state lottery pays out about 50% of the money it takes in as prizes. The other 50% is retained by the state to build parks or educate kids or some such nonsense 😉 It’s no exaggeration to say that lotteries are a tax on people that are bad at math – a sort of tax I heartily approve of.
There’s an interesting intersection between trading and lotteries you may not have thought about. One aspect of a lottery is the deficient payout – in the typical case $0.50 is paid out for every $1 payed in. In other words playing the lottery has a profit factor of 0.5. Another aspect is the extreme imbalance of payouts – infrequent huge wins paired with frequent small losses. This later aspect is what I want to investigate today – especially the idea of lotteries where the payoff is greater than pay-in. In other words, “good” lotteries.
If you’ve read my about page, you know I have some ill-defined ambitions to eventually create a proprietary trading firm. This is probably a five to ten years out kind of thing, so there are essentially no details around the idea. Just some broad philosophies, a few lessons learned from the failures of other firms, and a belief that trading in groups is better than trading alone. But there’s one thing about this hypothetical firm that I have already decided – what poster I’ll have on my office wall. I’m going to have to have it custom made, but that’s OK. It’ll be worth it. The picture will be the rather nerdy looking Bell Labs engineer you see at right – John L. Kelly. The text on the poster will be:
Maximize The Expected Value Of The Logarithm Of Your Wealth. Then reduce your bet size by a factor of 5.
Here’s another little short piece of advice that can save you some pain: Don’t use market orders. Instead use a limit order across the bid-ask gap. Under normal conditions you will get exactly the same result, but in abnormal circumstances you can avoid big trouble. Continue reading
Many of my posts are marathon length, but this one will be short and to the point. I want to teach you a useful heuristic about risk. The issue is, for any given trade you put on, how much risk should you be willing to take. The risk you take on a given position is related to two things: the size of the position you take (in shares, contracts, etc.) and the amount you’re willing to let the position move against you before exiting via a stop order. Generally the amount you’ll let the position move against you is determined by your trading strategy, so position size is the variable you want to adjust to keep your risk under control. The rule of thumb has three parts: Continue reading
In order to evaluate trading strategies, it’s very handy to have one number that represents how good a given strategy is – bigger is better. I’ve suggested a couple of ways of doing that – win rate and expectation. Both are uselful, but both also have substantial limitations that render them problematic in the real world. What I want to do here is briefly describe those limitations, and then suggest an alternate mathematical construct called “profit factor” you can use for evaluating systems. Continue reading
I rarely comment on current events, but today I’m going to make an exception. We’ve had enough time since the explosion of MF Global to get a pretty good understanding of what happened. This is a “teachable moment” about the dangers of counterparty risk and things you can do to avoid it. Continue reading