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The digital currency Bitcoin offers investors high returns
and a low correlation with other asset classes. However, Bit-
coin's unusually high volatility raises doubt about its eligibility
for investors.
The objective of this thesis is to ascertain, if the market risk
of Bitcoin can be adequately forecasted with the prevalent risk
measures Value-at-Risk and Expected Shortfall. To this end, an
empirical analysis is performed, which applies commonly used
techniques of risk modeling on seven years of Bitcoin return
data. Forecasts for VaR and ES are backtested and the results
compared with those of other asset classes.
The empirical results show, that although Bitcoin's fore-
casts perform significantly worse than those of other asset classes,
risk models with conditional volatility are able to estimate re-
liable VaR and ES for Bitcoin. Other findings incluce the inef-
fectiveness of historical simulation models and the importance
of the assumed distribution of returns.
This paper prices risk factors in the Capital Asset Pricing Model (CAPM) to
explain portfolio returns of the German stock market. Using a two-part
regression procedure, we show that beta exhibits slight significance in
capturing the variations of asset returns. When higher co-moments and Fama
French factors are added to the model, we find a moderate improvement in the
significance levels of all risk factors and in the overall explanatory power of
the model. Moreover, following the conditional beta method employed in
Pettengill et al. (1995), we show that risk factors perform fairly well in crosssection
settings, especially in the down-market condition. Our chosen long
time horizon shows that the composite model with all factors included
performs better in post-recession periods.
This thesis undertakes an investigation on the potential impact of FDI on Balkan countries economic growth after the 90‘. The main purpose is to analyze whether inward FDI had been a determinant of growth for this region leading to the FDI-led growth hypothesis. The empirical procedure relies on a multivariate VAR approach and Granger causality test to check for a possible causal relationship. The main finding suggests evidence of a weak causality running from economic growth to FDI. Furthermore, possible reasons are analyzed why the FDI-led growth hypothesis was not possible to be supported. Lastly, potential policy recommendations are proposed in order to assist the countries in tackling various challenges and benefiting more from FDI inflows in the future.
The area of scientific research around the relationship between stocks and macroeconomic activity has been of great interest for scholars, especially after the introduction of the Arbitrage Pricing Theory. Such macro variables as industrial production and long-term interest rates, are expected to influence the stock price through the firms’ expected cash flows and the discount rate (Rapach, et al., 2005: 137).
Following this body of research, this master thesis examines the relationship between stock returns and six macro variables in the German stock market. The applied methodology ranges from standard OLS regressions with different leads of macro variables to more advanced time-series techniques.
Overall, the explanatory power of OLS regressions is quite low meaning that only a small fraction of stock returns is explained by the selected macro factors, even if some of them are statistically significant. The findings from Granger causality and Johansen cointegration tests are more conclusive but should be taken with caution