Stepwise Multiple Testing as Formalized Data Snooping

Stepwise Multiple Testing as Formalized Data Snooping

It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. This paper suggests a stepwise multiple testing procedure which asymptotically controls the familywise error rate at a desired level. Compared to related singlestep methods, the procedur...

Stewise Multiple Testing as Formalized Data Snooping

It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. In this paper, we suggest a stepwise multiple testing procedure which asymptotically controls the familywise error rate at a desired level. Compared to related single-step methods, our p...

Formalized Data Snooping Based on Generalized Error Rates

It is common in econometric applications that several hypothesis tests are carried out simultaneously. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. The classical approach is to control the familywise error rate (FWE) which is the probability of one or more false rejections. But when the number of hypotheses under consideration is larg...

Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias

Article history: Received 25 October 2008 Received in revised form 19 July 2009 Accepted 5 January 2010 Available online 18 January 2010 In the finance literature, statistical inferences for large-scale testing problems usually suffer from data snooping bias. In this paper we extend the “superior predictive ability” (SPA) test of Hansen (2005, JBES) to a stepwise SPA test that can identify pred...

A Reality Check For Data Snooping