Christofferson, P. F., F. X. Diebold, and T. Schuermann (1998). Horizon problems and extreme events in financial risk management. Federal Reserve Bank of New York Economic Policy Review 4(3), 109--116. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Pricing Systemic Crises: Monetary and Fiscal Policy When.. - Lehnert, al. (1999) (Correct)
....assets widened dramatically, while asset return volatility also in 2 The CME QBI is a count, measured in thousands, of all new bankruptcy case filings in U.S. bankruptcy courts. For more information, see Chicago Mercantile Exchange (1999) 3 As a further example of this kind of uncertainty, Christofferson, Diebold, and Schuermann (1998) analyze the typical volatility forecast underpinning the popular Value at Risk risk management model and find that, beyond a ten day trading horizon, the volatility forecast is of very poor quality. 2 creased. Market participants reported that they were dissatisfied with their risk management ....
Christofferson, P. F., F. X. Diebold, and T. Schuermann (1998). Horizon problems and extreme events in financial risk management. Federal Reserve Bank of New York Economic Policy Review 4(3), 109--116.
Subordinated Debt and Bank Capital Reform - Evanoff, Wall (2000) (Correct)
....Thus, his analysis also overstates the amount of direct discipline arising from sub debt designed to qualify as capital under existing capital standards. 55. See for example Kupiec (1995) The difficulty of identifying the probability of extreme events with small samples is also highlighted by Christoffersen, Diebold and Schuermann (1998) who argue that for performing statistical inference on objects such as a once every hundred years quantile, the relevant measure of sample size is likely better approximated by the number of nonoverlapping hundred year intervals in the data set than by the actual number of data points. 56. ....
Christoffersen, P.F., F.X. Diebold, and T. Schuermann (1998). Horizon problems and extreme events in financial risk management. Economic Policy Review, Federal Reserve Bank of New York, 4.
Towards A Global Financial Architecture: Capital Mobility .. - Christoffersen, Errunza (1999) Self-citation (Christoffersen) (Correct)
.... returns properly modeled Is there an element of forecastability in financial crises If so, what is the optimal forecast methodology Arguably, capturing these extreme events is the single most important problem facing a risk manager, as these are events with the potential to bankrupt the firm (Christoffersen, Diebold and Schuermann, 1998). Traditional Value at Risk based risk measurement methodologies such as JP Morgan (1995) and Blejer and Schumacher (1998) are based on an assumption of conditional normality, and are therefore ill suited to capture the probability of a crisis outcome. Furthermore, they tend to be univariate in ....
....high. This volatility contained useful information, which would be completely ignored in forecasting models based purely on low frequency macroeconomic indicators. Further evidence on the usefulness of high frequency information in forecasting low frequency extreme events can be found in Christoffersen and Diebold (1998). Suggestion: Apply Forecast Combination Using Information in Derivatives Prices In addition to the macro based forecasting models outlined above, risk managers can rely on information in risk neutral probability distribution functions derived from observed options prices (Soderlind and ....
Christoffersen, P., F. Diebold, and T. Schuermann (1998) "Horizon Problems and Extreme Events in Financial Risk Management," Economic Policy Review, Federal Reserve Bank of New York, October 1998, 109-118.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC