Equity Premium Predictions with Adaptive Macro Indexes

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in 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.

Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages

“…Moreover, it is also preferred particularly in the regarding stock return predictabilities. Some recent works in the literature show that prediction about excess stock returns can be improved by exploiting the factors obtained from a large set of macroeconomic and financial variables through factor models, as argued by Bai (2010), Neely et al (2014, Ç akmaklı and van Dijk (2016).…”

Getting the Most Out of Macroeconomic Information for Predicting Stock Returns and Volatility

“…We use a utility based metric to evaluate how much the investor would be willing to pay to use the predictions from the factoraugmented models rather than those from the benchmarks. Specifically, we employ the procedure proposed in West et al (1993), which is frequently used for measuring the economic value of dynamic investment strategies, see Fleming et al (2001Fleming et al ( , 2003, Marquering and Verbeek (2004a), De Pooter et al (2008), and Della Corte et al (2009, 2010, among others.…”

“…1 We only became aware of this project while completing the current work. Several features distinguish our paper from Bai (2010). First, Bai (2010) only considers predictive regressions for excess return, while we also use macro factors for volatility.…”

“…Several features distinguish our paper from Bai (2010). First, Bai (2010) only considers predictive regressions for excess return, while we also use macro factors for volatility. Second, we examine the possibility of pre-selection of macro variables that are used in the factor construction, while Bai (2010) does not.…”

“…First, Bai (2010) only considers predictive regressions for excess return, while we also use macro factors for volatility. Second, we examine the possibility of pre-selection of macro variables that are used in the factor construction, while Bai (2010) does not. (She instead examines the possibility to select the most informative factors after their construction.…”