Haku
Viitteet 1-4 / 4
Forecasting stock market returns by summing the frequency-decomposed parts
(15.01.2018)
Journal of Empirical Finance January 2018
Journal of Empirical Finance January 2018
We generalize the Ferreira and Santa-Clara (2011) sum-of-the-parts method for forecasting stock market returns. Rather than summing the parts of stock returns, we suggest summing some of the frequency-decomposed parts. The ...
Predicting Banking Crises with Artificial Neural Networks: The Role of Nonlinearity and Heterogeneity
(28.12.2017)
Scandinavian Journal of Economics 1; January 2018
Scandinavian Journal of Economics 1; January 2018
Studies of the early warning systems (EWSs) for banking crises usually rely on linear classifiers, estimated with international datasets. I construct an EWS based on an artificial neural network (ANN) model, and I also ...
Real-time uncertainty in budget planning : evidence from euro area countries
(15.10.2018)
Journal of Economic Policy Reform 4
Journal of Economic Policy Reform 4
Using rich panel data including potential output for euro area countries, we analyse budget balance forecasts and their errors. We find that budget balance forecasts are systematically biased and subject to mean reversion ...
Can bubble theory foresee banking crises?
(21.02.2018)
Journal of Financial Stability June 2018
Journal of Financial Stability June 2018
We consider the effectiveness of unit root exuberance tests in predicting banking crises. Using a sample of 15 EU countries over the past three decades, our crisis dating follows the scheme of the European Systemic Risk ...