Search Results
Working Paper
Optimal prediction under asymmetric loss
Prediction problems involving asymmetric loss functions arise routinely in many fields, yet the theory of optimal prediction under asymmetric loss is not well developed. We study the optimal prediction problem under general loss structures and characterize the optimal predictor. We compute it numerically in less tractable cases. A key theme is that the conditionally optimal forecast is biased under asymmetric loss and that the conditionally optimal amount of bias is time-varying in general and depends on higher-order conditional moments. Thus, for example, volatility dynamics (e.g., GARCH ...
Journal Article
Horizon problems and extreme events in financial risk management
This paper was presented at the conference "Financial services at the crossroads: capital regulation in the twenty-first century" as part of session 3, "Issues in value-at-risk modeling and evaluation." The conference, held at the Federal Reserve Bank of New York on February 26-27, 1998, was designed to encourage a consensus between the public and private sectors on an agenda for capital regulation in the new century.
Working Paper
Cointegration and long-horizon forecasting
It is widely believed that imposing cointegration on a forecasting system, if cointegration is, in fact, present, will improve long-horizon forecasts. The authors show that, contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. The authors' results highlight a potentially important deficiency of standard forecast accuracy measures--they fail to value the maintenance of cointegrating relationships among ...