Estimating stochastic volatility: the rough side to equity returns

Jonathan Haynes (), Daniel Schmitt () and Lukas Grimm ()
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Jonathan Haynes: Barcelona Graduate School of Economics
Daniel Schmitt: Barcelona Graduate School of Economics
Lukas Grimm: Barcelona Graduate School of Economics

Decisions in Economics and Finance, 2019, vol. 42, issue 2, No 6, 449-469

Abstract: Abstract This paper evaluates the forecasting performance of a Brownian semi-stationary (BSS) process in modelling the volatility of 21 equity indices. We implement a hybrid scheme to simulate BSS processes with high efficiency and precision. These simulations are useful to price derivatives, accounting for rough volatility. We then calibrate the BSS parameters for the realised kernel of 21 equity indices, using data from the Oxford-Man Institute. Finally, we conduct one-step and ten-step ahead forecasts on six indices and find that the BSS outperforms benchmarks, including a Log-HAR specification, in most cases.

Keywords: Asset pricing; Stochastic processes; Forecasting; Volatility; Derivatives (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 C58 G17 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10203-019-00261-y

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