dc.contributor.author | Lux, Yannik | |
dc.date.accessioned | 2019-10-30T09:28:51Z | |
dc.date.available | 2019-10-30T09:28:51Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://hdl.handle.net/11250/2625331 | |
dc.description | Master of Science in Business - QTEM Masters Network - Handelshøyskolen BI, 2019 | nb_NO |
dc.description.abstract | In my thesis, I introduce a state-space representation of the present-value model to
analyze predictability in the aggregated German stock market. The proposed model
uses the information contained in annualized price-dividend ratios and realized dividend
growth rates and defines relations to the latent state variables in the form of
expected returns and expected dividend growth rates. I apply the Kalman Filter to
generate estimates of the model parameters using a conditional Maximum Likelihood
Estimation. The corresponding optimization problem is solved via an adjusted
version of the Simulated Annealing algorithm. The final model produces good estimates
for dividend-growth rates, while it lacks quality in terms of the estimation of
stock returns. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Handelshøyskolen BI | nb_NO |
dc.subject | QTEM | nb_NO |
dc.subject | quantitative techniques | nb_NO |
dc.subject | economics | nb_NO |
dc.subject | management | nb_NO |
dc.subject | masters network | nb_NO |
dc.title | Predictability of Stock Returns: An application of presentvalue state-space models to the German Stock Market | nb_NO |
dc.type | Master thesis | nb_NO |