Frontiers in VaR forecasting and backtesting
By M. Nieto, Esther Ruiz. 2016
128 citations recorded by the source corpus.
The interest in forecasting the Value at Risk (VaR) has been growing over the last two decades, due to the practical relevance of this risk measure for financial and insurance institutions. Furthermore, VaR forecasts are often used as a testing ground when fitting alternative models for representing the dynamic evolution of time series of financial returns. There are vast numbers of alternative methods for constructing and evaluating VaR forecasts. In this paper, we survey the new benchmarks proposed in the recent literature.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/76b4b0e2993dc0fc911ebcd4901202f139398519
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- James W. Taylor
- M. Nieto
- Zhijie Xiao
- Esther Ruiz
- Roger W. Koenker
- E.J. Candes
- Thomas Kneib
- Matteo Sesia
In Finance
- James W. Taylor
- M. Nieto
- Esther Ruiz
- Zhijie Xiao
- Roger W. Koenker
- E.J. Candes
- Thomas Kneib
- Matteo Sesia
Citations in the corpus
- Forecast combinations for value at risk and expected shortfall (2020, background): “In their recent review of the VaR literature, Nieto and Ruiz (2016) report just a handful of studies on combining.”