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dc.contributor.authorBai, Jennieen_US
dc.date.accessioned2010-12-07en_US
dc.date.accessioned2012-08-17T14:33:32Z-
dc.date.available2012-08-17T14:33:32Z-
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/10419/60792-
dc.description.abstractFundamental economic conditions are crucial determinants of equity premia. However, commonly used predictors do not adequately capture the changing nature of economic conditions and hence have limited power in forecasting equity returns. To address the inadequacy, this paper constructs macro indexes from large data sets and adaptively chooses optimal indexes to predict stock returns. I find that adaptive macro indexes explain a substantial fraction of the short-term variation in future stock returns and have more forecasting power than both the historical average of stock returns and commonly used predictors. The forecasting power exhibits a strong cyclical pattern, implying the ability of adaptive macro indexes to capture time-varying economic conditions. This finding highlights the importance of using dynamically measured economic conditions to investigate empirical linkages between the equity premium and macroeconomic fundamentals.en_US
dc.language.isoengen_US
dc.publisherFederal Reserve Bank of New York New York, NYen_US
dc.relation.ispartofseriesStaff Report, Federal Reserve Bank of New York 475en_US
dc.subject.jelG17en_US
dc.subject.jelC58en_US
dc.subject.ddc330en_US
dc.subject.keywordAdaptive macro indexen_US
dc.subject.keywordforecastingen_US
dc.titleEquity premium predictions with adaptive macro indexesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn64119854Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Staff Reports, Federal Reserve Bank of New York

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