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Improve volatility forecasting with realized semivariance-evidences from intra-day large data sets in Chinese

Yin, Lianqian; Liu, Bo; Du, Zhen - In: International journal of economics and finance 6 (2014) 12, pp. 64-70

Persistent link: https://www.econbiz.de/10010460882

Estimation and updating methods for hedonic valuation

Mayer, Michael; Bourassa, Steven C.; Hoesli, Martin; … - 2018

models.Design/methodology/approach – We apply six estimation methods (linear least squares, robust regression, mixed effects …

Persistent link: https://www.econbiz.de/10011976945

Linear time-varying regression with Copula-DCC-GARCH models for volatility

Kim, Jong-Min; Jung, Hojin - In: Economics letters 145 (2016), pp. 262-265

Persistent link: https://www.econbiz.de/10011618857

Predicting stock return volatility : can we benefit from regression models for return intervals?

Fischer, Henning; Blanco-Fernández, Ángela; Winker, Peter - In: Journal of forecasting 35 (2016) 2, pp. 113-146

Persistent link: https://www.econbiz.de/10011580244

A reexamination of stock return predictability

Choi, Yongok; Jacewitz, Stefan; Park, Joon Y. - In: Journal of econometrics 192 (2016) 1, pp. 168-189

Persistent link: https://www.econbiz.de/10011617132

Predicting exchange rate volatility in Brazil : an approach using quantile autoregression

Viola, Alessandra Pasqualina; Klotzle, Marcelo Cabus; … - 2017

Persistent link: https://www.econbiz.de/10011944952

Consistent inference for predictive regressions in persistent economic systems

Andersen, Torben; Varneskov, Rasmus Tangsgaard - In: Journal of econometrics 224 (2021) 1, pp. 215-244

Persistent link: https://www.econbiz.de/10013275373

Forecasting the equity premium using weighted regressions : Does the jump variation help?

Zhang, Zhikai; Zhang, Yaojie; Wang, Yudong - In: Empirical economics : a quarterly journal of the … 66 (2024) 5, pp. 2049-2082

Persistent link: https://www.econbiz.de/10014520108

Predicting volatility based on interval regression models

Qu, Hui; He, Mengying - In: Journal of risk and financial management : JRFM 15 (2022) 12, pp. 1-21

Considering the inferior volatility tracking capability of the point-data-based models, we propose using the more informative price interval data and building interval regression models for volatility forecasting. To characterize the heterogeneity of the market and the nonlinearity of...

Persistent link: https://www.econbiz.de/10014284403

Mixed-Frequency Predictive Regressions with Parameter Learning

Leippold, Markus; Yang, Hanlin - 2023

Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions …

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