Modeling and Predicting Stock Returns:The Rule of Parsimony
간결성의 법칙을 이용한 주식수익률 예측모형의 비교
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초록

This study examines a variety of time-series forecasting models to uncover an economically effective forecasting model of stock returns using both valuation ratios and macroeconomic variables. We use the Schwarz criterion as a barometer of model selection and conclude that from the economic perspective as opposed to the statistical perspective the parsimonious multiple regression model with a select set of explanatory variables, mainly book-to-market ratio, default risk premium, and Treasury bill rate, shows as good a capacity to predict stock returns as more complicated forecasting models such as E-GARCH or I-GARCH. An out-of-sample test confirms our conclusion.

키워드

가치평가 비율거시경제지표슈워츠 기준GARCH 모형간결성의 법칙*Valuation RatiosMacroeconomic VariablesSchwartz CriterionGARCHRule of Parsimony
제목
Modeling and Predicting Stock Returns:The Rule of Parsimony
제목 (타언어)
간결성의 법칙을 이용한 주식수익률 예측모형의 비교
저자
곽승욱압둘라 알 마서드
발행일
2013-12
저널명
POSRI경영경제연구
13
2
페이지
148 ~ 187