Forecasting value at risk and conditional value at risk using option market data

Annalisa Molino, Carlo Sala

Producció científica: Article en revista indexadaArticleAvaluat per experts

3 Cites (Scopus)

Resum

We forecast monthly value at risk (VaR) and conditional value at risk (CVaR) using option market data and four different econometric techniques. Independent from the econometric approach used, all models produce quick to estimate forward-looking risk measures that do not depend from the amount of historical data used and that, through the implied moments of options, better reflect the ever-changing market scenario. All proposed option-based approaches outperform or are equally good to different “traditional” forecasts that use historical returns as input. The extensive robustness of our results shows that the real driver of the better forecasts is the use of option market data as inputs for the analysis, more than the type of econometric approach implemented.

Idioma originalAnglès
Pàgines (de-a)1190-1213
Nombre de pàgines24
RevistaJournal of Forecasting
Volum40
Número7
DOIs
Estat de la publicacióPublicada - de nov. 2021
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