Showing 1 - 10 of 17,228
We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...
Persistent link: https://www.econbiz.de/10011721618
This paper addresses the open debate about the effectiveness and practical relevance of high-frequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...
Persistent link: https://www.econbiz.de/10013120653
This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...
Persistent link: https://www.econbiz.de/10009306337
This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...
Persistent link: https://www.econbiz.de/10009308302
A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...
Persistent link: https://www.econbiz.de/10011563065
This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...
Persistent link: https://www.econbiz.de/10013085726
One of the challenging research problems in the domain of time series analysis and forecasting is making efficient and robust prediction of stock market prices. With rapid development and evolution of sophisticated algorithms and with the availability of extremely fast computing platforms, it...
Persistent link: https://www.econbiz.de/10012991826
This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...
Persistent link: https://www.econbiz.de/10013404229
Employing both the mean-variance framework and the common portfolio risk-optimization, this study adds to the investment research by examining how ideal holdings for emerging and frontier markets (EFM) of the four global regions (Asian, Europe, and Commonwealth of Independent States (Eastern +...
Persistent link: https://www.econbiz.de/10013391097
This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...
Persistent link: https://www.econbiz.de/10009714536