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on Econometric Time Series |
| By: | Kenichiro Shiraya; Kanji Suzuki; Tomohisa Yamakami |
| Abstract: | Two formulations are proposed to filter out correlations in the residuals of the multivariate GARCH model. The first approach is to estimate the correlation matrix as a parameter and transform any joint distribution to have an arbitrary correlation matrix. The second approach transforms time series data into an uncorrelated residual based on the eigenvalue decomposition of a correlation matrix. The empirical performance of these methods is examined through a prediction task for foreign exchange rates and compared with other methodologies in terms of the out-of-sample likelihood. By using these approaches, the DCC-GARCH residual can be almost independent. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.08246 |
| By: | Jihyun Park; Andrey Sarantsev |
| Abstract: | We apply Principal Component Analysis for zero-coupon Treasury bonds to get level, slope, and curvature series. We model these as autoregressions of order 1, and analyze their innovations. For slope, but not for level and curvature, dividing these innovations by the Volatility Index VIX made for Standard \& Poor 500 makes them closer to independent identically distributed normal. We state and prove stability results for bond returns based on this observation. We chose zero-coupon as opposed to classic coupon Treasury bonds because it is much easier to compute returns for these. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.03699 |
| By: | Gabriel Rodriguez-Rondon; Jean-Marie Dufour |
| Abstract: | We present the R package MSTest, which implements hypothesis testing procedures to identify the number of regimes in Markov switching models. These models have wide-ranging applications in economics, finance, and numerous other fields. The MSTest package includes the Monte Carlo likelihood ratio test procedures proposed by Rodriguez-Rondon and Dufour (2024), the moment-based tests of Dufour and Luger (2017), the parameter stability tests of Carrasco, Hu, and Ploberger (2014), and the likelihood ratio test of Hansen (1992). Additionally, the package enables users to simulate and estimate univariate and multivariate Markov switching and hidden Markov processes, using the expectation-maximization (EM) algorithm or maximum likelihood estimation (MLE). We demonstrate the functionality of the MSTest package through both simulation experiments and an application to U.S. GNP growth data. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.08188 |
| By: | Kranz, Sebastian |
| Abstract: | We compare heteroskedasticity-robust inference methods with a large-scale Monte Carlo study based on regressions from 155 reproduction packages of leading economic journals. The results confirm established wisdom and uncover new insights. Among well established methods HC2 standard errors with the degree of freedom specification proposed by Bell and McCaffrey (2002) perform best. To further improve the accuracy of t-tests, we propose a novel degree-of-freedom specification based on partial leverages. We also show how HC2 to HC4 standard errors can be refined by more effectively addressing the 15.6% of cases where at least one observation exhibits a leverage of one. |
| Keywords: | hetereoskedasticity, robust standard errors, meta study, replications, degree of freedom correction |
| JEL: | C1 C12 C15 C87 |
| Date: | 2024–11–19 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:122724 |
| By: | Wenchao Xu; Xinyu Zhang |
| Abstract: | Asymptotic optimality is a key theoretical property in model averaging. Due to technical difficulties, existing studies rely on restricted weight sets or the assumption that there is no true model with fixed dimensions in the candidate set. The focus of this paper is to overcome these difficulties. Surprisingly, we discover that when the penalty factor in the weight selection criterion diverges with a certain order and the true model dimension is fixed, asymptotic loss optimality does not hold, but asymptotic risk optimality does. This result differs from the corresponding result of Fang et al. (2023, Econometric Theory 39, 412-441) and reveals that using the discrete weight set of Hansen (2007, Econometrica 75, 1175-1189) can yield opposite asymptotic properties compared to using the usual weight set. Simulation studies illustrate the theoretical findings in a variety of settings. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.09258 |