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Why is it so hard to estimate expected returns?


Oct 18, 2013 - 12:00pm to 1:00pm


E1 104


John Dodson
Vice President, Quantitative Risk Management at Option Clearing Corporation


Abstract: A key part of experiment design is determining how much data to collect. When the data comes in the form of a time series, the sample size can be expressed by the count N of the observations and the duration T of the historical period. For forecasting the drift of an asset price process with continuous sample paths it turns out the duration is key. I generalize a result by Merton and demonstrate that the standard error of any unbiased estimator of the price of risk is bounded below by 1/\sqrt T, which I believe this is higher than many practitioners realize.

Event Type: 

Professional Mathematical Finance Seminar