Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?
Alain-Philippe Fortin (),
Jean-Guy Simonato () and
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Alain-Philippe Fortin: HEC Montreal, Canada Research Chair in Risk Management
Jean-Guy Simonato: HEC Montreal, Department of Finance
No 18-4, Working Papers from HEC Montreal, Canada Research Chair in Risk Management
When forecasting the market risk of stock portfolios, is a univariate or a multivariate modeling approach more effective? This question is examined in the context of forecasting the one-week-ahead Expected Shortfall for a portfolio equally invested in the Fama-French and momentum factors. Applying extensive tests and comparisons, we find that in most cases there are no statistically significant differences between the forecasting accuracy of the two approaches. This suggests that univariate models, which are more parsimonious and simpler to implement than multivariate models, can be used to forecast the downsize risk of equity portfolios without losses in precision.
Keywords: Value-at-Risk; Expected Shortfall; Conditional Value-at-Risk; Elicitability; model comparison; backtesting; Fama-French and momentum factors (search for similar items in EconPapers)
JEL-codes: C22 C32 C52 C53 G17 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-fmk, nep-for, nep-knm and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:ris:crcrmw:2018_004
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