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Modeling and Predicting Stock Returns:The Rule of Parsimony
간결성의 법칙을 이용한 주식수익률 예측모형의 비교
- 곽승욱;
- 압둘라 알 마서드
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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 비율; 거시경제지표; 슈워츠 기준; GARCH 모형; 간결성의 법칙*; Valuation Ratios; Macroeconomic Variables; Schwartz Criterion; GARCH; Rule of Parsimony
- 제목
- Modeling and Predicting Stock Returns:The Rule of Parsimony
- 제목 (타언어)
- 간결성의 법칙을 이용한 주식수익률 예측모형의 비교
- 저자
- 곽승욱; 압둘라 알 마서드
- 발행일
- 2013-12
- 저널명
- POSRI경영경제연구
- 권
- 13
- 호
- 2
- 페이지
- 148 ~ 187