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Tests of investor learning models using earnings innovations and implied volatilities

Neururer, Thaddeus; Papadakis, George; Riedl, Edward J. - In: Review of accounting studies 21 (2016) 2, pp. 400-437

Persistent link: https://www.econbiz.de/10011488222

Learning to smile : can rational learning explain predictable dynamics in the implied volatility surface?

Bernales, Alejandro; Guidolin, Massimo - In: Journal of financial markets 26 (2015), pp. 1-37

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Sequential learning of cryptocurrency volatility dynamics : evidence based on a stochastic volatility model with jumps in returns and volatility

Huang, Jing-Zhi; Huang, Zhijian; Xu, Li - In: The quarterly journal of finance 11 (2021) 2, pp. 1-37

Persistent link: https://www.econbiz.de/10012649885

Perceived uncertainty shocks, excess optimism-pessimism, and learning in the business cycle

Chatterjee, Pratiti; Milani, Fabio - In: Journal of economic behavior & organization : JEBO 179 (2020), pp. 342-360

Persistent link: https://www.econbiz.de/10012486782

Learning to smile : can rational learning explain predictable dynamics in the implied volatility surface?

Bernales, Alejandro; Guidolin, Massimo - 2015 - This version: December, 2015

Persistent link: https://www.econbiz.de/10011809309

Sequential bayesian learning for stochastic volatility with variance-gamma jumps in returns

Warty, Samir P.; Lopes, Hehibert F.; Polson, Nicholas G. - 2014

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Nonparametric Bayesian Volatility Learning Under Microstructure Noise

Gugushvili, Shota; van der Meulen, Frank; Schauer, Moritz; … - 2018

Aiming at financial applications, we study the problem of learning the volatility under market microstructure noise. Specifically, we consider noisy discrete time observations from a stochastic differential equation and develop a novel computational method to learn the diffusion coefficient of...

Persistent link: https://www.econbiz.de/10014113947