FARVaR: Functional Autoregressive Value-at-Risk.
Motivated by the stylized fact that intraday returns can provide additional information on the tail behavior of daily returns, we propose a functional autoregressive value-at-risk (VaR) approach which can directly incorporate such informational advantage into the daily VaR forecast. Our approach lea...
| Published in: | Journal of Financial Econometrics Vol. 17; no. 2; pp. 284 - 338 |
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| Main Authors: | , , , |
| Format: | Article |
| Published: |
Oxford University Press / USA
Spring2019
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=135916665&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 135916665 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 14798409 T2Y jtl: Journal of Financial Econometrics issn: 14798409 maglogo: N pubinfo: dt: Spring2019 vid: 17 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 135916665 10.1093/jjfinec/nby031 ppf: 284 ppct: 54 formats: tig: atl: FARVaR: Functional Autoregressive Value-at-Risk. aug: au: Cai, Charlie X Kim, Minjoo Shin, Yongcheol Zhang, Qi affil: The University of Liverpool Management School University of York Durham University Business School su: Value at risk Autoregressive models Stock exchanges Density functionals Rate of return sug: subj: Securities and Commodity Exchanges Value at risk Autoregressive models Stock exchanges Density functionals Rate of return keyword: density forecasts functional autoregressive model covariance market risk management density forecasts functional autoregressive model covariance market risk management ab: Motivated by the stylized fact that intraday returns can provide additional information on the tail behavior of daily returns, we propose a functional autoregressive value-at-risk (VaR) approach which can directly incorporate such informational advantage into the daily VaR forecast. Our approach leads to greater flexibility in modeling 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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