Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn? Export

@article{citeulike:1325150, abstract = {Statistical model selection criteria provide an informed choice of the model with best external (i.e., out-of-sample) validity. Therefore they guard against overfitting (\"data snooping\"). We implement several model selection criteria in order to verify recent evidence of predictability in excess stock returns and to determine which variables are valuable predictors. We confirm the presence of in-sample predictability in an international stock market dataset, but discover that even the best prediction models have no out-of-sample forecasting power. The failure to detect out-of-sample predictability is not due to lack of power.}, author = {Bossaerts, Peter and Hillion, Pierre}, citeulike-article-id = {1325150}, citeulike-linkout-0 = {http://www.jstor.org/stable/2646023}, journal = {The Review of Financial Studies}, keywords = {finance, forecast}, number = {2}, pages = {405--428}, posted-at = {2007-05-24 14:48:56}, priority = {3}, title = {Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?}, url = {http://www.jstor.org/stable/2646023}, volume = {12}, year = {1999} }

TY - JOUR ID - citeulike:1325150 L3 - citeulike-article-id:1325150 N2 - Statistical model selection criteria provide an informed choice of the model with best external (i.e., out-of-sample) validity. Therefore they guard against overfitting ("data snooping"). We implement several model selection criteria in order to verify recent evidence of predictability in excess stock returns and to determine which variables are valuable predictors. We confirm the presence of in-sample predictability in an international stock market dataset, but discover that even the best prediction models have no out-of-sample forecasting power. The failure to detect out-of-sample predictability is not due to lack of power. IS - 2 JF - The Review of Financial Studies EP - 428 TI - Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn? VL - 12 SP - 405 KW - finance KW - forecast AU - Bossaerts, Peter AU - Hillion, Pierre PY - 1999/// UR - http://www.jstor.org/stable/2646023 ER -