Tamás Kiss
Tamás Kiss Position: Senior Lecturer School/office: Örebro University School of BusinessEmail: dGFtYXMua2lzcztvcnUuc2U=
Phone: +46 19 302306
Room: N4018
About Tamás Kiss
Tamás Kiss is an economist with a specialization in time series econometrics and financial economics. He defended his thesis at the University of Gothenburg in 2019. Since then he has been a postdoctoral researcher at the School of Business at Örebro University.
His research is about application of time series econometrics methods to various applications within finance and empirical macroeconomics, with a focus on making predictions. His research stretches from return predictability in equity markets to analysing empirical features of financial and macroeconomic predictions.
Research interests
- Time series econometrics
- Financial economics
- Empirical macroeconomics
Selected publications
Hjalmarsson, E., Kiss, T. (2022), “Long-Run Predictability Tests are Even Worse than You Thought.”, forthcoming in Journal of Applied Econometrics
Kiss, T., Mazur, S., Nguyen, H., Österholm, P. (2022), ”Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Innovations” forthcoming in Journal of Forecasting
Kiss, T., Nguyen, H., Österholm, P. (2022), “Modelling Okun’s Law – Does non-Gaussianity Matter?” forthcoming in Empirical Economics
Javed, F., Kiss, T., Österholm, P. (2022), “Performance Analysis of Nowcasting of GDP Growth when Allowing for Conditional Heteroscedasticity and Non-Gaussianity.”, Applied Economics 54(58), 6669-6686.
Kiss, T., Mazur, S., Nguyen, H. (2022), “Predicting Returns and Dividend Growth - The Role of non-Gaussian Innovations.”, Finance Research Letters 46, 102315
Kiss, T., Nguyen, H., Österholm, P. (2022), “The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area.” Finance Research Letters 46, 102365
Hjalmarsson, E., Kiss, T. (2021), “Dividend Growth Does Not Help Predict Returns Compared to Likelihood-Based Tests: An Anatomy of the Dog.”, Critical Finance Review 10(3), 445-464
Kiss, T., Österholm, P. (2020), “Corona, Crisis and Conditional Heteroscedasticity.”, Applied Economics Letters 28(9), 755-759.
Kiss, T., Österholm, P. (2020), “Fat Tails in Leading Indicators.”, Economics Letters 193, 109317
Research groups
Publications
Articles in journals
- Farago, A. , Hjalmarsson, E. & Kiss, T. (2025). Understanding Wealth-Tax Rates: An Investor-Utility Mapping to Capital-Gains Taxes. European Financial Management. [BibTeX]
- Kiss, T. , Kladivko, K. , Silfverberg, O. & Österholm, P. (2023). Market participants or the random walk-who forecasts better? Evidence from micro-level survey data. Finance Research Letters, 54. [BibTeX]
- Kiss, T. , Mazur, S. , Nguyen, H. & Österholm, P. (2023). Modeling the relation between the US real economy and the corporate bond-yield spread in Bayesian VARs with non-Gaussian innovations. Journal of Forecasting, 42 (2), 347-368. [BibTeX]
- Kiss, T. , Nguyen, H. & Österholm, P. (2023). Modelling Okun's law: Does non-Gaussianity matter?. Empirical Economics, 64 (5), 2183-2213. [BibTeX]
- Karlsson, S. , Kiss, T. , Nguyen, H. & Österholm, P. (2023). Svensk ekonomi är inte normal (och oberoende) – fakta om makroekonomiska variablers tidsserieegenskaper. Ekonomisk Debatt, 51 (1), 42-54. [BibTeX]
- Hjalmarsson, E. & Kiss, T. (2022). Long-run predictability tests are even worse than you thought. Journal of applied econometrics (Chichester, England), 37 (7), 1334-1355. [BibTeX]
- Javed, F. , Kiss, T. & Österholm, P. (2022). Performance analysis of nowcasting of GDP growth when allowing for conditional heteroscedasticity and non-Gaussianity. Applied Economics, 54 (58), 6669-6686. [BibTeX]
- Kiss, T. , Mazur, S. & Nguyen, H. (2022). Predicting returns and dividend growth - The role of non-Gaussian innovations. Finance Research Letters, 46 (Part A). [BibTeX]
- Kiss, T. , Nguyen, H. & Österholm, P. (2022). The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area. Finance Research Letters, 46 (Part A). [BibTeX]
- Kiss, T. & Österholm, P. (2021). Corona, Crisis and Conditional Heteroscedasticity. Applied Economics Letters, 28 (9), 755-759. [BibTeX]
- Hjalmarsson, E. & Kiss, T. (2021). Dividend Growth Does Not Help Predict Returns Compared To Likelihood-Based Tests: An Anatomy of the Dog. Critical Finance Review, 10 (3), 445-464. [BibTeX]
- Kiss, T. , Nguyen, H. & Österholm, P. (2021). Modelling Returns in US Housing Prices-You're the One for Me, Fat Tails. Journal of Risk and Financial Management, 14 (11). [BibTeX]
- Kiss, T. & Österholm, P. (2020). Fat tails in leading indicators. Economics Letters, 193. [BibTeX]
Conference papers
- Kiss, T. , Mazur, S. , Nguyen, H. & Österholm, P. (2021). Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances. Paper presented at 11th European Seminar on Bayesian Econometrics, Madrid, Spain, September 2-3, 2021. [BibTeX]
Doctoral theses, monographs
- Kiss, T. (2019). Predictability in Equity Markets: Estimation and Inference. (Doctoral dissertation). University of Gothenburg. [BibTeX]
Manuscripts
- Kiss, T. Predictive Regressions in Predictive Systems. [BibTeX]
- Hjalmarsson, E. & Kiss, T. Testing Return Predictability with the Dividend-Growth Equation : An Anatomy of the Dog. [BibTeX]
- Kiss, T. Vanishing Predictability and Non-Stationary Regressors. [BibTeX]
Reports
- Kiss, T. , Mazur, S. , Nguyen, H. & Österholm, P. (2024). VAR Models with Fat Tails and Dynamic Asymmetry. Örebro: Örebro University School of Business (Working Papers, School of Business 8). [BibTeX]
- Kiss, T. , Mazur, S. , Nguyen, H. & Österholm, P. (2021). Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances. Örebro: Örebro University, School of Business (Working Papers, School of Business 9/2021). [BibTeX]