Finding Alphas, 2nd Edition

7Turnover

By Pratik Patel

We generally measure the accuracy and quality of an alpha's predictions by metrics such as the information ratio (IR) and the information coefficient (IC). The IR is the ratio of excess returns over a benchmark to the variability of those returns; the idea behind it is that an alpha with high excess returns and low variability consistently predicts future returns over a given time period. The IC measures the correlation between the predicted and actual values, in which a value of 1.0 represents perfect forecasting ability.

In the context of evaluating the strength of an alpha, a high IR and a high IC are obviously desirable, but we usually measure an alpha's return prediction ability irrespective of real-world constraints. We assume liquidity is endless, trading is free, and there are no other market participants but ourselves. However, as actual trading strategies must abide by certain constraints, an alpha that often makes predictions correctly will be more easily leveraged if it also satisfies reasonable assumptions about market conditions.

ALPHA HORIZON

Predictions change as new information becomes available. Whether a stock moved one tick, an analyst revised his recommendation, or a company released earnings, this change in information can be a catalyst for trading activity. We measure this trading via turnover: the total value traded divided by the total value held. A company's stock price changes much more often than its earnings per share, ...