Forecasting expected shortfall: Should we use a multivariate model for stock market factors?

Alain-Philippe Fortin, Jean-Guy Simonato and Georges Dionne ()

International Journal of Forecasting, 2023, vol. 39, issue 1, 314-331

Abstract: Is univariate or multivariate modeling more effective when forecasting the market risk of stock portfolios? We examine this question in the context of forecasting the one-week-ahead expected shortfall of a stock portfolio based on its exposure to 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 result suggests that univariate models, which are more parsimonious and simpler to implement than multivariate factor-based models, can be used to forecast the downside risk of equity portfolios without losses in precision.

Keywords: Fama–French and momentum factors; Value at risk; Expected shortfall; Conditional value at risk; Elicitability; Model comparison; Backtesting; Comparative predictive accuracy; Model confidence set (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:314-331

DOI: 10.1016/j.ijforecast.2021.11.010

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