FARVaR: Functional Autoregressive Value-at-Risk

Journal of Financial Econometrics, forthcoming

81 Pages Posted: 23 Mar 2014 Last revised: 5 Mar 2019

See all articles by Charlie X. Cai

Charlie X. Cai

University of Liverpool Management School

Minjoo Kim

University of Liverpool - Accounting and Finance Division

Yongcheol Shin

University of York (UK) - Department of Economics and Related Studies

Qi Zhang

Independent

Date Written: November 15, 2018

Abstract

Motivated by the stylized fact that intraday returns can provide additional information on the tail behaviour of daily returns, we propose a functional autoregressive value-at-risk approach which can directly incorporate such informational advantage into the daily value-at-risk forecast. Our approach leads to greater flexibility in modelling the dynamic evolution of the density function of intraday returns and the ability to capture substantial swings in the tails following major events. We comprehensively evaluate our proposed model using intraday transaction data and demonstrate that it can improve coverage ability, reduce economic cost and enhance statistical reliability in market risk management.

Keywords: density forecasts; financial risk management; functional autoregressive model

JEL Classification: G17, C53

Suggested Citation

Cai, Charlie Xiaowu and Kim, Minjoo and Shin, Yongcheol and Zhang, Qi, FARVaR: Functional Autoregressive Value-at-Risk (November 15, 2018). Journal of Financial Econometrics, forthcoming. Available at SSRN: https://ssrn.com/abstract=2412635 or http://dx.doi.org/10.2139/ssrn.2412635

Charlie Xiaowu Cai

University of Liverpool Management School ( email )

University of Liverpool
Liverpool, L69 7ZA
United Kingdom

Minjoo Kim (Contact Author)

University of Liverpool - Accounting and Finance Division ( email )

227 Grove
Management School
Liverpool, Liverpool L69 3BX
United Kingdom

HOME PAGE: http://https://www.liverpool.ac.uk/management/staff/minjoo-kim/

Yongcheol Shin

University of York (UK) - Department of Economics and Related Studies ( email )

Heslington
York, YO1 5DD
United Kingdom

Qi Zhang

Independent

No Address Available

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