Cristina Amado
PhD Economic Statistics (Stockholm School of Economics)
Cristina Amado is currently an Assistant Professor in the Department of Economics at the University of Minho, Portugal, and an international research fellow at CREATES, Aarhus University. She holds a PhD in Economic Statistics from the Stockholm School of Economics with a thesis entitled "Four essays on the econometric modelling of volatility and durations" since 2009. She is also a research member at the Economic Policies Research Centre (NIPE). Her main research interests lie within the fields of time-series analysis, nonlinear modelling and mathematical statistics.
Selected publications
Campos-Martins, S., & Amado, C. (2022). Financial market linkages and the sovereign debt crisis. Journal of International Money and Finance, 123. DOI
Amado, C., & Teräsvirta, T. (2017). Specification and Testing of Multiplicative Time-Varying GARCH Models with Applications. Econometric Reviews, 36(4), 421–446. DOI
Amado, C., & Teräsvirta, T. (2014). Conditional correlation models of autoregressive conditional heteroscedasticity with nonstationary GARCH equations. Journal of Business and Economic Statistics, 32(1), 69–87. RepositoriUM DOI
Amado, C., & Teräsvirta, T. (2014). Modelling changes in the unconditional variance of long stock return series. Journal of Empirical Finance, 25, 15–35. RepositoriUM DOI
Amado, C., & Teräsvirta, T. (2013). Modelling volatility by variance decomposition. Journal of Econometrics, 175(2), 142–153. RepositoriUM DOI
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Publications
Campos-Martins, S., & Amado, C. (2022). Financial market linkages and the sovereign debt crisis. Journal of International Money and Finance, 123. DOI
Amado, C., Silvennoinen, A., & Teräsvirta, T. (2019). Models with Multiplicative Decomposition of Conditional Variances and Correlations. In J. Chevallier, S. Goutte, D. Guerreiro, S. Saglio, & B. Sanhaji (Eds.), Financial Mathematics, Volatility and Covariance Modelling (1st ed., Vol. 2). Routledge.
Amado, C., & Teräsvirta, T. (2017). Specification and Testing of Multiplicative Time-Varying GARCH Models with Applications. Econometric Reviews, 36(4), 421–446. DOI
Amado, C., Silvennoinen, A., & Teräsvirta, T. (2017). Modelling and Forecasting WIG20 Daily Returns. Central European Journal of Economic Modelling and Econometrics, 9, 173–200. RepositoriUM
Amado, C., & Laakkonen, H. (2014). Modelling Time-Varying Volatility in Financial Returns: Evidence from the Bond Markets. In N. Haldrup, M. Meitz, & P. Saikkonen (Eds.), Essays in Nonlinear Time Series Econometrics (pp. 139–160). Oxford University Press.
Amado, C., & Teräsvirta, T. (2014). Conditional correlation models of autoregressive conditional heteroscedasticity with nonstationary GARCH equations. Journal of Business and Economic Statistics, 32(1), 69–87. RepositoriUM DOI
Amado, C., & Teräsvirta, T. (2014). Modelling changes in the unconditional variance of long stock return series. Journal of Empirical Finance, 25, 15–35. RepositoriUM DOI
Amado, C., & Teräsvirta, T. (2013). Modelling volatility by variance decomposition. Journal of Econometrics, 175(2), 142–153. RepositoriUM DOI
Teaching
Data Analysis and Transferable Skills (Master)
