Abstract
In this paper, we analyze the role played by market liquidity and tradingrelated variables in forecasting one-day-ahead “value-at-risk” (VaR). We use the quantile-regression methodology, as this allows us to directly study the effects of the predictive variables on the tail distribution of returns. Our empirical setting builds on the so-called CAViaR model put forward by Engle and Manganelli (2004) and extends it empirically by incorporating further information beyond volatility. The backtesting VaR analysis, based on unconditional and conditional coverage tests, reveals that liquidity and trading variables considerably enhance the VaR performance.
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© 2011 Lidia Sanchis-Marco and Antonio Rubia
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Sanchis-Marco, L., Rubia, A. (2011). The Value of Liquidity and Trading Activity in Forecasting Downside Risk. In: Gregoriou, G.N., Pascalau, R. (eds) Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures. Palgrave Macmillan, London. https://doi.org/10.1057/9780230298101_8
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DOI: https://doi.org/10.1057/9780230298101_8
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-32890-1
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