Similar Search Results

Mixed-Frequency Predictive Regressions with Parameter Learning

Leippold, Markus; Yang, Hanlin - 2023

We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models...

Persistent link: https://www.econbiz.de/10014348997

It Takes Two to Tango : Economic Theory and Model Uncertainty for Equity Premium Prediction

Bianchi, Daniele; Rubesam, Alexandre; Tamoni, Andrea - 2023

-step procedure that (1) imposes a dogmatic view on a given economic theory to forecast the equity premium, and (2) exploits the … motivated predictors rather than dilute the importance of economic theory for equity premium predictability. Yet, each predictor …

Persistent link: https://www.econbiz.de/10014349549

Forecasting Stock Returns

Rapach, David; Zhou, Guofu - 2023

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...

Persistent link: https://www.econbiz.de/10014351279

Application of Persistent Homology in Forecasting Realized Volatility

Gobato Souto, Hugo - 2023

This paper proposes a novel algorithm called Persistent Homology for Realized Volatility (PH-RV), which aims to effectively incorporate persistent homology (PH) into neural network models to increase their forecast accuracy in predicting realized volatility (RV). This paper also proposes a novel...

Persistent link: https://www.econbiz.de/10014354048

Predicting the Equity Premium with Combination Forecasts : A Reappraisal

Denk, Sebastian; Löffler, Gunter - 2022

This paper reappraises the usefulness of forecast combination for predicting the US equity premium. For comparison, we also include penalized regression and dimension reduction approaches. We fail to find evidence of predictive ability in recent decades, regardless of the forecasting method...

Persistent link: https://www.econbiz.de/10013406380

Bespoke Realized Volatility : Tailored Measures of Risk for Volatility Prediction

Patton, Andrew J.; Zhang, Haozhe - 2023

Standard realized volatility (RV) measures estimate the latent volatility of an asset price using high frequency data …

Persistent link: https://www.econbiz.de/10014255167

Volatility Forecasting and Explanatory Variables : A Tractable Bayesian Approach to Stochastic Volatility

Dorion, Christian; Chapados, Nicolas - 2013

We provide a formulation of stochastic volatility (SV) based on Gaussian process regression (GPR). Forecasting volatility out-of-sample, both simulation and empirical analyses show that our GPR-based stochastic volatility (GPSV) model clearly outperforms SV and GARCH benchmarks, especially at...

Persistent link: https://www.econbiz.de/10014186681

Sum-of-the-parts revised : economic regimes and flexible probabilities

Haase, Felix - 2024 - First Draft: September 9, 2024

price-earnings multiple to form the sum-of-the-parts forecast. Our results demonstrate significant predictability from a …

Persistent link: https://www.econbiz.de/10015062491

Gold returns

Barro, Robert J.; Misra, Sanjay - 2013

Persistent link: https://www.econbiz.de/10009715114

Gold Returns

Barro, Robert J. - 2013

From 1836 to 2011, the average real rate of price change for gold in the United States is 1.1% per year and the … gold's real rate of price change with consumption and GDP growth rates are small and statistically insignificantly … between gold services and ordinary consumption, the model can generate a mean real rate of price change within the (0.1%, 2 …

Persistent link: https://www.econbiz.de/10013087443