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Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction

Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2018

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …

Persistent link: https://www.econbiz.de/10011775136

Nonparametric predictive regressions for stock return brediction

Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2019

Persistent link: https://www.econbiz.de/10012698837

Nonparametric predictive regressions for stock return prediction

Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2019

Persistent link: https://www.econbiz.de/10012592220

Time-varying predictability of the long horizon equity premium based on semiparametric regressions

Yu, Deshui; Li, Chen; Li, Luyang - In: Economics letters 224 (2023), pp. 1-6

Persistent link: https://www.econbiz.de/10014307887

Development of stock market trend prediction system using multiple regression

Asghar, Muhammad Zubair; Rahman, Fazal; Kundi, Fazal Masud - In: Computational and mathematical organization theory 25 (2019) 3, pp. 271-301

Persistent link: https://www.econbiz.de/10012098937

Quantile aggregation and combination for stock return prediction

Jiang, Chuanliang; Maasoumi, Esfandiar; Xiao, Zhijie - In: Econometric reviews 39 (2020) 7, pp. 715-743

Persistent link: https://www.econbiz.de/10012262517

Tales of tails : jumps in currency markets

Lee, Suzanne S.; Wang, Minho - In: Journal of financial markets 48 (2020), pp. 1-29

Persistent link: https://www.econbiz.de/10012631807

Semi-parametric single-index predictive regression models with cointegrated regressors

Zhou, Weilun; Gao, Jiti; Harris, David; Kew, Hsein - In: Journal of econometrics 238 (2024) 1, pp. 1-18

Persistent link: https://www.econbiz.de/10015073842

Data-driven jump detection thresholds for application in jump regressions

Davies, Robert; Tauchen, George Eugene - 2015

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

Persistent link: https://www.econbiz.de/10011524214

Generalized jump regressions for local moments

Bollerslev, Tim; Li, Jia; Chaves, Leonardo Salim Saker - In: Journal of business & economic statistics : JBES ; a … 39 (2021) 4, pp. 1015-1025

Persistent link: https://www.econbiz.de/10012653221

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