Cristina Amado is currently an Assistant Professor in the Department of Economics at the University of Minho, Portugal, and an integrated member at NIPE (Centre for Research in Economics and Management). 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 under the supervision of Professor Timo Teräsvirta. Her main research interests lie within the fields of time-series analysis, nonlinear modelling and financial econometrics.
Time-series analysis
nonlinear modelling and financial econometrics.
Selected publications
Martins, S. C.-, & Amado, C. (2025). Modelling Dynamic Interdependence in Nonstationary Variances with an Application to Carbon Markets. Journal of Economic Dynamics and Control, 173(105062). DOI
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. DOI
Amado, C., & Teräsvirta, T. (2013). Modelling volatility by variance decomposition. Journal of Econometrics, 175(2), 142–153. DOI
Other publications
Amado, C. Outlier Robust Specification of Multiplicative Time-Varying Volatility Models. Computational Economics. DOI
Martins, S. C.-, & Amado, C. (2025). Modelling Dynamic Interdependence in Nonstationary Variances with an Application to Carbon Markets. Journal of Economic Dynamics and Control, 173(105062). DOI
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. 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., Silvennoinen, A., & Teräsvirta, T. (2017). Modelling and Forecasting WIG20 Daily Returns. Central European Journal of Economic Modelling and Econometrics, 9, 173–200. DOI
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. 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. DOI
Amado, C., & Teräsvirta, T. (2014). Modelling changes in the unconditional variance of long stock return series. Journal of Empirical Finance, 25, 15–35. DOI
Amado, C., & Teräsvirta, T. (2013). Modelling volatility by variance decomposition. Journal of Econometrics, 175(2), 142–153. DOI
Mathmatical Economics
Doctorate
Research Methodology and Proposal in Economics
Master
Topics in Econometrics
Master
