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Predictive Regressions under Arbitrary Persistence and Stock Return Predictability

Borup, Daniel; Christensen, Bent Jesper; Ergemen, Yunus Emre - 2021

standard inference from least-squares estimation of a suitably adjusted predictive regression. We analyze US and international …

Persistent link: https://www.econbiz.de/10013238244

Sparse Multivariate Modeling for Stock Returns Predictability

Bernardi, Mauro; Bianchi, Daniele; Bianco, Nicolas - 2021

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with …, both in simulation and when forecasting a large cross section of industry portfolios spanning almost a hundred years of …

Persistent link: https://www.econbiz.de/10013239660

Observation-driven hierarchical density models for missing data imputation

Khanna, Yonas; Lucas, André - 2025

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel data. The model exploits both serial and cross-sectional information in the data and can easily cope with time-variation in conditional means and variances, as well as with either...

Persistent link: https://www.econbiz.de/10015373862

The contribution of realized covariance models to the economic value of volatility timing

Bauwens, Luc; Xu, Yongdeng - 2023

realized covariance matrices through a GARCH-type structure. We compare the forecasting performance of several such models in …

Persistent link: https://www.econbiz.de/10014434629

Bivariate volatility modeling with high-frequency data

Matei, Marius; Rovira, Xari; Agell, Núria - In: Econometrics : open access journal 7 (2019) 3/41, pp. 1-15

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate … leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that …

Persistent link: https://www.econbiz.de/10012160811

Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions

Szubzda, Filip; Chlebus, Marcin - In: Central European economic journal 6 (2019) 53, pp. 70-85

. Two approaches based on the extreme value theory were compared: Block Maxima and the Peaks Over Threshold. Forecasts were …

Persistent link: https://www.econbiz.de/10012302139

DCC-HEAVY : a multivariate GARCH model with realized measures of variance and correlation

Xu, Yongdeng - 2019

realized correlations in the DCC-HEAVY model. The new model removes well known asymptotic bias in DCC-GARCH model estimation … and has more desirable asymptotic properties. We also derive a Quasi-maximum likelihood estimation and provide closed …

Persistent link: https://www.econbiz.de/10012009351

Forecasting the Equity Risk Premium : The Importance of Regime-Dependent Evaluation

Baltas, Nick - 2020

recently introduced ERP forecasting models, which have been shown to generate econometrically superior ERP forecasts, and find … that their forecasting ability is regime-dependent. They give rise to significant relative losses during market downturns …

Persistent link: https://www.econbiz.de/10012855775

Predicting the Stock Market Index Using Stochastic Time Series Arima Modelling : The Sample of BSE and NSE

C, Viswanatha Reedy - 2019

design their trading strategies. An intelligent forecasting will certainly abet to yield significant profits. Many important … ARIMA modelling. The best fit ARIMA (0,1,0) model was chosen for forecasting the values of time series, viz., BSE_CLOSE and …

Persistent link: https://www.econbiz.de/10012863169

The Term Structure of Volatility Predictability

Li, Xingyi - 2019

Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities …

Persistent link: https://www.econbiz.de/10012890910