Academy of Finland post-doc 2013 - 2016
New Nonlinear Models for Macroeconomic and Financial Time Series
Academy of Finland, funding decisions spring 2013 (237 400 €)
Project description
During the last few decades, an increasing interest in economic research has been devoted to different nonlinear econometric time series models. The aim of this research is to explore new nonlinear methods. The planned advances in the methods offer great potential for interesting applications and completely new ways of the econometric analysis of financial and macroeconomic time series. The expected empirical results should shed light on the behavior of macroeconomy and financial market as well as their important linkages being thus valuable also for decision makers and practitioners including central banks, government agencies and investment authorities.
Publications
Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models (with Markku Lanne) Forthcoming in Oxford Bulletin of Economics and Statistics (2015) Working paper version: CREATES Research Paper 2014 - 17
Forecasting with a noncausal VAR model (with Pentti Saikkonen) Computational Statistics & Data Analysis, 76, 536 - 555 (2014)
A Bivariate Autoregressive Probit Model: Business Cycle Linkages and Transmission of Recession Probabilities Macroeconomic Dynamics, 18, 838 – 862 (2014)
Predicting bear and bull stock markets with dynamic binary time series models Journal of Banking & Finance, 37, 3351 - 3363 (2013)
Domestic publications
Suomen kansantalouden suhdanneindeksi 2009 - 2014 (with Markku Lanne). Finnish Economic Journal (Kansantaloudellinen aikakauskirja) 1, 6 - 15 (2015)
Working papers
Noncausality and the Commodity Currency Hypothesis (with Matthijs Lof) SSRN working paper (2015).
Nonlinear dynamic interrelationships between real activity and stock returns (with Markku Lanne) CREATES Research Paper 2015 - 36 (2015).
International Sign Predictability of Stock Returns: The Role of the United States (with Harri Pönkä) CREATES Research Paper 2015 - 20 (2015).
Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models (with Markku Lanne) CREATES Research Paper 2014 - 17.
A Multinomial Logit-based Statistical Test of Association Football Betting Market Efficiency HECER Discussion Paper No. 380 (2014).
A Qualitative Response VAR Model: An Application to Joint Dynamics of U.S. Interest Rates and Business Cycle HECER Discussion Paper No. 369 (2013).
Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation? (with Markku Lanne and Jani Luoto) CREATES Research Paper 2014 - 26 (2014).
The Risk of Financial Crises: Is It in Real or Financial Factors? (with Karolin Kirschenmann and Tuomas Malinen) ECINEQ Working Paper 2014 – 336 (2014).
Conference and seminar presentations
Noncausality and the Commodity Currency Hypothesis
Energy Finance Conference 2015, Cass Business School London, London, September 2015.
Nonlinear Dynamic Interrelationships between Real Activity and Stock Returns
ACE workshop 2015, Turku, November 2015
23rd Symposium of the Society for Nonlinear Dynamics and Econometrics, Oslo, March 2015
International Sign Predictability of Stock Returns: The Role of the United States
Nottingham University Business School, Nottingham, April 2015
Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?
Royal Economic Society Meeting 2015, Manchester, March 2015.
Generalized forecast error variance decomposition for linear and nonlinear multivariate models"
8th International Conference on Computational and Financial Econometrics, Pisa, December 2014.
A Qualitative Response VAR Model: An Application to Joint Dynamics of U.S. Interest Rates and Business Cycle
34th International Symposium on Forecasting, Rotterdam, June-July 2014
7th International Conference on Computational and Financial Econometrics, London, December 2013
Suomen kansantalouden suhdanneindeksi 2009 - 2014
Ministry of Finance, May 2015
Project completed in 2015 due to my move to the University of Turku, Department of Mathematics and Statistics