A Flow-Based Explanation for Return Predictability
نویسندگان
چکیده
منابع مشابه
A Flow-Based Explanation for Return Predictability
This paper proposes and tests a flow-based explanation for three important empirical findings on return predictability – the persistence of mutual fund performance, the “smart money” effect, and stock price momentum. Since mutual fund managers generally scale up or down their existing positions in response to investment flows, and since the portfolios of funds receiving capital generally differ...
متن کاملCommodity Market Capital Flow and Asset Return Predictability ∗
We establish several new findings on the relation between capital flow in commodity markets and asset returns. Capital flowing into commodity markets, as measured by high open-interest growth, predicts high commodity returns and low bond returns. Open-interest growth is a more powerful and robust predictor of commodity returns than other known predictors such as the short rate, the yield spread...
متن کاملPredictability of Stock Return and Volatility: A Factor Based Approach
Using factor based approaches, we investigate a return and volatility forecasting procedure that exploits all the available information by still keeping the econometric framework at considerable size. Our findings demonstrate that factor based approaches provide substantial gains when predicting the sign of the excess returns and state of the volatility separately as well as jointly. A striking...
متن کاملElusive Return Predictability∗
Investors’ search for successful forecasting models leads the data generating process for financial returns to change over time which means that individual return forecasting models can at best hope to uncover evidence of ‘local’ predictability. We illustrate this point on a suite of forecasting models used to predict US stock returns and propose an adaptive forecast combination approach. Most ...
متن کاملBreaks in Return Predictability
We propose a new approach to forecasting stock returns in the presence of structural breaks that simultaneously affect the parameters of multiple portfolios. Exploiting information in the cross-section increases our ability to identify breaks in return prediction models and enables us to detect breaks more rapidly in real time, thereby allowing the parameters of the predictive return regression...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2010
ISSN: 1556-5068
DOI: 10.2139/ssrn.1468382