Forecasting Value-at-Risk under Temporal and Portfolio Aggregation

Erik Kole (), Thijs Markwat, Anne Opschoor and Dick van Dijk

Journal of Financial Econometrics, 2017, vol. 15, issue 4, 649-677

Abstract: We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of 10 trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly, or biweekly returns of all constituent assets separately, gathered into portfolios based on asset class, or into a single portfolio. We compare the impact of aggregation with that of choosing a model for the conditional volatilities and correlations, the distribution for the innovations, and the method of forecast construction. We find that the level of temporal aggregation is most important. Daily returns form the best basis for VaR forecasts. Modeling the portfolio at the asset or asset class level works better than complete portfolio aggregation, but differences are smaller. The differences from the model, distribution, and forecast choices are also smaller compared with temporal aggregation.

Keywords: aggregation; forecast evaluation; model comparison; value-at-risk (search for similar items in EconPapers)
JEL-codes: C22 C32 C52 C53 G17 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (9)

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