How Relevant is Volatility Forecasting for Financial Risk Management?

By Peter F. Christoffersen, Francis X. Diebold. Review of Economics and Statistics, 2000

397 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/fefd1ffa61debee04c904e36a8c35d76bb597644

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Citations in the corpus

Market risk models for intraday data (2005, background): “As indicated in Christoffersen and Diebold (2000) , volatility forecastability (such as featured by conditional volatility models) decays quickly with the time horizon of the forecasts.”
Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach (2010, neutral): “The extensive body of research on volatility modeling and forecasting (Anderson, Bollerslev, & Lange, 1999; Blair, Poon, & Taylor, 2001; Engle, 2002; Hamid, 2004; Noh, Engle, & Kane, 1994; Poon & Granger, 2003) has reflected the importance of financial volatility to investment decision-making (Busse”
Risk Measurement Performance of Alternative Distribution Functions (2008, methodology): “…We calculated the LRind and LRcc statistics for all the distribution functions considered in the article.17 We also computed the first-order serial correlation coefficient corr(Et,Et−1), a diagnostic suggested by Christoffersen and Diebold (2000), and tested its statistical significance.”
What Ties Return Volatilities to Price Valuations and Fundamentals? (2013, neutral): “, Diebold and Christoffersen (2000), who question the relevance of lag-based models for intermediate term decisions and risk management.”
How Accurate are Value-at-Risk Models at Commercial Banks (2001, neutral): “corr(It,It-1), a diagnostic suggested by Christoffersen and Diebold (2000) .”
MODELING AND FORECASTING REALIZED VOLATILITY (2003, neutral): “Second, although the lognormal-normal mixture distribution works very well in the present context, the predictive distribution could be refined and adapted to more challenging contexts using the numerical simulation methods of Geweke (1989), the Cornish-Fisher expansion of Baillie and Bollerslev (19”
An Application of Extreme Value Theory for Measuring Financial Risk (2006, background): “Indeed, as Christoffersen and Diebold (2000) notice, conditional volatility forecasting is not indicated for multiple day predictions.”