BP-CVaR: A novel model of estimating CVaR with back propagation algorithm

Gang-Jin Wang and Chun-Long Zhu

Economics Letters, 2021, vol. 209, issue C

Abstract: We propose a more flexible and useful model, BP-CVaR, to estimate conditional value-at-risk (CVaR) using back propagation (BP) algorithm, which can capture the change of markets and use the information to adjust the next CVaR result. We use three samples including S&P 500 index, Nasdaq index, DIJA index and compare the results by back-testing approaches. We find that (i) BP-CVaR is more reliable and has higher accuracy than Monte Carlo CVaR model and (ii) BP-CVaR can react to the change of markets more quickly than traditional CVaR model.

Keywords: Risk measure; CVaR; Back propagation; BP-CVaR; Back-testing (search for similar items in EconPapers)
JEL-codes: C58 G10 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:209:y:2021:i:c:s016517652100402x

DOI: 10.1016/j.econlet.2021.110125

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