arXiv 11 Mar 2020 · Econometrics · publishedStudies in Nonlinear Dynamics and Econometrics (2021) · 5 citations (OpenAlex)
arXiv:2003.05221 · PDF · DOI · OpenAlex · Extracted main text
We introduce a new mixture autoregressive model which combines Gaussian and Student's $t$ mixture components. The model has very attractive properties analogous to the Gaussian and Student's $t$ mixture autoregressive models, but it is more flexible as it enables to model series which consist of both conditionally homoscedastic Gaussian regimes and conditionally heteroscedastic Student's $t$ regimes. The usefulness of our model is demonstrated in an empirical application to the monthly U.S. interest rate spread between the 3-month Treasury bill rate and the effective federal funds rate.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Kalliovirta, L (2012) Misspecification tests based on quantile residuals | 1.000 | 19 | 3 | 100% |
| 2 | Virolainen, S (2020) uGMAR: Estimate Univariate Gaussian or Student's $t$ Mixture Autoregressive Model self | 0.928 | 5 | 5 | 80% |
| 3 | Meitz, M., Preve, D., and Saikkonen, P (2018) A mixture autoregressive model based on student's $t$-distribution | 0.909 | 16 | 7 | 75% |
| 4 | Dorsey, R. and Mayer, W (1995) Genetic algorithms for estimation problems with multiple optima, nondifferentiability, and other irregular features | 0.894 | 7 | 3 | 71% |
| 5 | Kalliovirta, L., Meitz, M., and Saikkonen, P (2015) A gaussian mixture autoregressive model for univariate time series | 0.885 | 13 | 6 | 69% |
| 6 | Sarno, L. and Thornton, D (2003) The dynamic relationship between the federal funds rate and the treasury bill rate: An empirical investigation | 0.874 | 8 | 2 | 100% |
| 7 | Meitz, M., Preve, D., and Saikkonen, P (2018) StMAR Toolbox: A MATLAB Toolbox for Student's t Mixture Autoregressive Models | 0.843 | 3 | 3 | 100% |
| 8 | Wong, C. and Li, W (2001) On logistic mixture autoregressive model | 0.644 | 2 | 2 | 100% |
| 9 | Wong, C. and Li, W (2000) On mixture autoregressive model | 0.644 | 2 | 2 | 100% |
| 10 | Wong, C. and Li, W (2001) On a mixture autoregressive conditional heteroskedastic model | 0.644 | 2 | 2 | 100% |
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