High frequency trading ničí finanční trhy

In a recent study, University of Michigan doctoral student Elaine Wah and I developed a simple model of latency arbitrage across two exchanges with a delayed public ticker. We found that the presence of high-frequency trading in this model takes profits away from regular investors and, moreover, reduces the overall profit of the system. This doesn’t even count all the direct costs of the latency arms race — all the resources dedicated to trimming microseconds. Our model can’t estimate the extent of the damage, but it does show that it degrades market performance.

Here’s why: High-frequency trading aggressively clears trades across exchanges, whereas the market sometimes performs better by letting orders accumulate for a while to better judge which ones should trade.

It might be in the nation’s best economic interest to eliminate this latency arms race. One way to do this would be to move to a system where all trades happen at discrete points in time — say once per second — rather than continuously. The interval is short enough so that markets can accurately track real-world events, but long enough so that shaving off tiny fractions of a second provides no significant advantage.

Our study showed that this market organization performs better by far than continuous trading. By placing a lower limit on time differences that matter for trading, we could create markets that can effectively keep up with even the fastest-moving world events, but no longer drive us to trade faster than reality itself.