Anomalies and Multiple Hypothesis Testing

 

Topic: Anomalies and Multiple Hypothesis Testing: Evidence from Two Million Trading Strategies

 

Speaker: Amit Goyal, University of Lausanne

 

 We use a large laboratory of over two million trading strategies to provide thresholds for statistical significance based on multiple hypothesis testing as well as estimates of the cost (in terms of falsely rejecting a null) of evaluating hypothesis based on classical hypothesis testing. We refer to the latter as the proportion of lucky rejections (i.e., strategies that survive classical hypothesis testing but fail multiple hypothesis testing thresholds). We estimate the proportion of lucky discoveries to be around 60% and find that our estimate of optimal multiple hypothesis thresholds is higher than previously reported.

Time: 12.00 – 1.00 p.m.

Venue: University of Technology, Sydney

             Building 8, Room 8.002, Dr Chau Chak Wing Building
             Dr Chau Chak Wing Building

            14 - 28 Ultimo Road, Ultimo

 

 

Enquiries: Mala Kapahi (Ph: +61 2 9514 7777)