Exploring Non Linear Structures in Range-Based Volatility Time Series

Michele La Rocca () and Cira Perna
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Michele La Rocca: University of Salerno

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2022, pp 315-320 from Springer

Abstract: Abstract In this paper we focus on the use of Extreme Learning Machines (ELMs) to appropriately capture the nonlinear dynamics of the range based estimators. The results on all the assets in the S&P500 index show that ELMs produce residuals without neglected nonlinearities

Keywords: Extreme learning machines; Nonlinear dynamics; Range based estimators (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-99638-3_51

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DOI: 10.1007/978-3-030-99638-3_51

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