Predicting Financial Returns
A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Financial Markets".
Deadline for manuscript submissions: closed (27 May 2022) | Viewed by 4677
Special Issue Editors
Interests: commodities modelling; financial econometrics; high frequency data; volatility modelling
Interests: econometrics: semiparametric and nonparametric estimation; time series econometrics: volatility and interest rates estimation; simulation and modelling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear colleagues,
A recurring question that arises in the financial literature is whether stock returns are predictable. Essentially, the debate is divided into studies searching for the best predictors of stock returns and studies stating their unpredictability. In addition, recent results have indicated that the predictability of stock returns significantly increases when the variance risk premium is considered in predictive models of stock market returns. Predictability rates are still small; however, they can often be increased by adding other predictors, such as short and long interest rate values, in the models. Further, new policies that are driven by climate change will likely affect financial markets whose risk assessment may benefit from incorporating new predictors, such as carbon emissions or electricity spot prices, into their models.
The aim of this Special Issue is to shed more light onto the problem of the predictability of stock returns by accumulating novel research on this matter. We are eager to receive new advances in modelling, estimation and forecasting that have been applied to the predictability of stock returns. We encourage submissions of theoretical and empirical research on these issues, including parametric, nonparametric and machine learning tools.
Dr. Helena Veiga
Dr. Isabel Casas
Guest Editors
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