NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Anthony Tay

School of Economics
90 Stamford Road
Singapore
Tel: (65) 6828-0850
Fax: (65) 6828-0833

E-Mail: anthonytay@smu.edu.sg
Institutional Affiliation: Singapore Management University

NBER Working Papers and Publications

December 1998Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange
with Francis X. Diebold, Jinyong Hahn: w6845
We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving cross-variable interactions, such as time-varying conditional correlations. We also provide conditions under which a technique of density forecast forecasts. Finally by recent advances in financial risk management, we provide a detailed application to multivariate high-frequency exchange rate density forecasts.

Published: (Published as "Multivariate Density Forecast Evaluation and Calibration in Financial Risk Management: High Frequency Returns on Foreign Exchange") Review of Economics and Statistics, Vol. 81 (1999): 661-673.

October 1997Evaluating Density Forecasts of Inflation: The Survey of Professional Forecasters
with Francis X. Diebold, Kenneth F. Wallis: w6228
Since 1968, the Survey of Professional Forecasters has asked respondents to provide a" complete probability distribution of expected future inflation. We evaluate the adequacy of" those density forecasts using the framework of Diebold, Gunther and Tay (1997). The analysis" reveals several interesting features of the density forecasts in relation to realized inflation including several deficiencies of the forecasts. The probability of a large negative inflation" shock is generally overestimated, and in more recent years the probability of a large shock of" either sign is overestimated. Inflation surprises are serially correlated eventually adapt. Expectations of low inflation are associated with reduced uncertainty. The" results suggest several promising directions for future research.

Published: Cointegration, Causality and Forecasting: A Festschrift in Honor of Clive W. J. Granger, 76-90, Engleand, R. and H. Whie, eds., Oxford: Oxford University Press, 1999.

Evaluating Density Forecasts
with Francis X. Diebold, Todd A. Gunther: t0215
We propose methods for evaluating density forecasts. We focus primarily on methods" that are applicable regardless of the particular user's loss function. We illustrate the methods" with a detailed simulation example, and then we present an application to density forecasting of" daily stock market returns. We discuss extensions for improving suboptimal density forecasts multi-step-ahead density forecast evaluation, multivariate density forecast evaluation for structural change and its relationship to density forecasting, and density forecast evaluation" with known loss function.

Published: (newly titled "Evaluating Density Forecasts, with Applications to Financial Risk Management") International Economic Review, Vol. 39 (1998): 863-883.

 
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