General Financial Market Measurement, Modeling and Forecasting

Diebold, F.X. and Yilmaz, K. (2008), "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," NBER Working Paper No. 13811, forthcoming in The Economic Journal.

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes, including trends and bursts in spillovers, and both turn out to be empirically important. In particular, in an analysis of nineteen global equity markets from the early 1990s to the present, we find striking evidence of divergent behavior in the dynamics of return spillovers vs. volatility spillovers: Return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts.

Click here for weekly updates of the Diebold-Yilmaz Spillover Index, reported weekly by the Turkish Economic Research Forum.

Christoffersen, P.F., Diebold, F.X., Mariano, R.S., Tay, A.S. and Tse, Y.K. (2007), "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence," Journal of Financial Forecasting, 1(2), 3-24.

We generalize the Christoffersen-Diebold (2006) direction-of-change forecasting framework to incorporate conditional moments beyond the variance, and we examine its performance in the context of Asian equity markets. The results are mixed but encouraging.

Campbell, S.D. and Diebold, F.X. (Forthcoming), "Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence," Journal of Business and Economic Statistics.

Using half a century of Livingston expected business conditions data, we characterize directly the impact of expected business conditions on expected excess stock returns. Expected business conditions consistently affect expected excess returns in a statistically and economically significant counter-cyclical fashion: depressed expected business conditions are associated with high expected excess returns. Moreover, inclusion of expected business conditions in otherwise-standard predictive return regressions substantially reduces the explanatory power of the conventional financial predictors, including the dividend yield, default premium, and term premium, while simultaneously increasing R squared. Interestingly, one important and recently introduced non-financial predictor, the generalized consumption/wealth ratio ("CAY"), retains its predictive power even when controlling for expected business conditions, which accords with the view that the consumption/wealth ratio plays a role in asset pricing different from and complementary to that of expected business conditions. We argue that time-varying expected business conditions likely captures time-varying risk, while time-varying consumption/wealth captures time-varying risk aversion.

Christoffersen, P.F. and Diebold, F.X. (2006), "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, 52, 1273-1288.

We consider three sets of phenomena that feature prominently in the financial economics literature: conditional mean dependence (or lack thereof) in asset returns, dependence (and hence forecastability) in asset return signs, and dependence (and hence forecastability) in asset return volatilities. We show that they are very much interrelated, and we explore the relationships in detail.

Diebold, F.X. and Kilian, L. (2001), "Measuring Predictability: Theory and Macroeconomic Applications," Journal of Applied Econometrics, 16, 657-669.

Diebold, F.X. and Kilian, L. (2000), "Unit Root Tests are Useful for Selecting Forecasting Models," Journal of Business and Economic Statistics, 18, 265-273.

Diebold, F.X., Hahn, J. and Tay, A. (1999), "Multivariate Density Forecast Evaluation and Calibration in Financial Risk Management: High-Frequency Returns on Foreign Exchange," Review of Economics and Statistics, 81, 661-673.

Diebold, F.X., Tay, A. and Wallis, K. (1999), "Evaluating Density Forecasts of Inflation: The Survey of Professional Forecasters," in R. Engle and H. White (eds.), Festschrift in Honor of C.W.J. Granger, 76-90. Oxford: Oxford University Press.

Christoffersen, P. and Diebold, F.X. (1998), "Cointegration and Long-Horizon Forecasting," Journal of Business and Economic Statistics, 16, 450-458.

Diebold, F.X., Gunther, T. and Tay, A. (1998), "Evaluating Density Forecasts, with Applications to Financial Risk Management," International Economic Review, 39, 863-883.

Christoffersen, P. and Diebold, F.X. (1997), "Optimal Prediction Under Asymmetric Loss," Econometric Theory, 13, 808-817.