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on Econometric Time Series |
| By: | James H. Stock; Mark W. Watson |
| Abstract: | This paper considers VAR models incorporating many time series that interact through a few dynamic factors. Several econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions imposed on the VAR. Structural VAR identification based on timing restrictions, long run restrictions, and restrictions on factor loadings are discussed and practical computational methods suggested. Empirical analysis using U.S. data suggest several (7) dynamic factors, rejection of the exact dynamic factor model but support for an approximate factor model, and sensible results for a SVAR that identifies money policy shocks using timing restrictions. |
| JEL: | C32 E17 |
| Date: | 2005–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11467&r=ets |
| By: | John Y. Campbell; Samuel B. Thompson |
| Abstract: | A number of variables are correlated with subsequent returns on the aggregate US stock market in the 20th Century. Some of these variables are stock market valuation ratios, others reflect patterns in corporate finance or the levels of short- and long-term interest rates. Amit Goyal and Ivo Welch (2004) have argued that in-sample correlations conceal a systematic failure of these variables out of sample: None are able to beat a simple forecast based on the historical average stock return. In this note we show that forecasting variables with significant forecasting power in-sample generally have a better out-of-sample performance than a forecast based on the historical average return, once sensible restrictions are imposed on the signs of coefficients and return forecasts. The out-of-sample predictive power is small, but we find that it is economically meaningful. We also show that a variable is quite likely to have poor out-of-sample performance for an extended period of time even when the variable genuinely predicts returns with a stable coefficient. |
| JEL: | G1 |
| Date: | 2005–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11468&r=ets |
| By: | Ole E. Barndorff-Nielsen; Sven Erik Graversen; Jean Jacod; Neil Shephard |
| Abstract: | In this paper we provide an asymptotic analysis of generalised bipower measures of the variation of price processes in financial economics. These measures encompass the usual quadratic variation, power variation and bipower variations which have been highlighted in recent years in financial econometrics. The analysis is carried out under some rather general Brownian semimartingale assumptions, which allow for standard leverage effects. |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:sbs:wpsefe:2005fe09&r=ets |
| By: | Hsiang-Tai Lee (Washington State University); Jonathan Yoder (Washington State University) |
| Abstract: | This paper develops a new bivariate Markov regime switching BEKK-GARCH (RS-BEKK-GARCH) model. The model is a state-dependent bivariate BEKK- GARCH model, and an extension of Gray’s univariate generalized regime- switching (GRS) model to the bivariate case. To solve the path- dependency problem inherent in the bivariate regime switching BEKK-GARCH model, we propose a recombining method for the covariance term in the conditional variance-covariance matrix. The model is applied to estimate time-varying minimum variance hedge ratios for corn and nickel spot and futures prices. Out-of-sample point estimates of hedging portfolio variance show that compared to the state-independent BEKK-GARCH model, the RS-BEKK-GARCH model improves out-of-sample hedging effectiveness for both corn and nickel data. We perform White’s (2000) data-snooping reality check to test for predictive superiority of RS-BEKK-GARCH over the benchmark model, and find that the difference in variance reduction between BEKK-GARCH and RS-BEKK-GARCH is not statistically significant for either data set at conventional confidence levels. |
| Keywords: | bivariate GARCH, require switching, hedging |
| JEL: | D81 C53 |
| Date: | 2005–06–28 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0506009&r=ets |
| By: | Donggyu Sul (University of Auckland) |
| Abstract: | This paper studies the principle of common recursive mean adjustment and proposes a new detrending method in dynamic panel models. By utilizing recursive mean adjustment, this paper provides three unit root tests: a recursive mean adjusted (RMA) unit root test, a covariate RMA and a pooled RMA-feasible generalized least squares tests. The first two tests are designed for testing the cross sectional average of panel time series data to examine if the common factors in a panel are stationary or not. The third test is designed to test if the idiosyncratic errors are stationary or not. The proposed panel unit root test under cross section dependence is precise and powerful especially when T is larger than N |
| Keywords: | recursive detrending, panel unit root tests, cross section dependence |
| JEL: | C33 |
| Date: | 2005–06–29 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0506010&r=ets |
| By: | T. Bojdecki (Institute of Mathematics, University of Warsaw); Luis G. Gorostiza (Departamento de Mathematicas, Centro de Investigacion y de Estudios Avanzados, LRSP); A. Talarczyk (Institute of Mathematics, University of Warsaw) |
| Keywords: | Functional central limit theorem; Occupation time uctuation; Branching particle system; Distribution-valued Gaussian process; Fractional Brownian motion; Sub-fractional Brownian motion; Long-range dependence |
| JEL: | C10 C40 |
| Date: | 2004–07–05 |
| URL: | http://d.repec.org/n?u=RePEc:pqs:wpaper:0242005&r=ets |
| By: | Junsoo Lee; Mark C. Strazicich (Appalachian State University) |
| Abstract: | In this paper, we propose a minimum LM unit root test that endogenously determines a structural break in intercept and trend. Critical values are provided, and size and power properties are compared to the endogenous one-break unit root test of Zivot and Andrews (1992). Nunes, Newbold, and Kuan (1997) and Lee and Strazicich (2001) previously demonstrated that the Zivot and Andrews test exhibits size distortions in the presence of a break under the null. In contrast, the one-break minimum LM unit root test exhibits no size distortions in the presence of a break under the null. As such, rejection of the null unambiguously implies a trend stationary process. |
| Date: | 2004 |
| URL: | http://d.repec.org/n?u=RePEc:apl:wpaper:04-17&r=ets |