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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
In countries such as the UK and Australia, Public-private partnerships (PPPs) have become the preferred tool for the public sector to procure infrastructure. With this development it has become necessary to assess PPPs regarding their success, and it seems that research has been insufficient to this point. This thesis will give an in-depth insight into the field of success measurement for PPPs. First, it explains the theory behind PPPs by explaining the theory. Then, in the next step, a framework for success measurement in PPPs will be derived based on this theory. It will serve as the basis for the Success Measurement System (SMS) that will be developed. In this regard, the thesis adds value to existing research by using a fully encompassing approach. The SMS will allow for a sound measurement of success for PPPs, which includes a measurement of success for different stakeholders, different phases and categories.
In the main part of this thesis, the system is applied on eight transport PPPs through case studies. The insights, from these case studies, will be used to answer the following questions: First, are PPPs in general successful and should governments continue their implementation? Second, in which areas do PPPs fail? This is especially relevant to improve outcomes of PPPs in the future and to enhance PPP policies. Third, how can PPPs be compared with each other? In this regard, the results of the case studies will serve as a benchmark for future PPPs.
In regard of the first and the second question, the research has shown that PPPs are in general successful but often fail to meet cost and time targets. In addition, sometimes problems were encountered during the procurement phase, contract management and risk allocation. These are the areas where the public and the private sector should focus to improve outcome of future PPPs. The results of the SMS assessment led to an average success rate which can be used as a benchmark to compare outcomes of other PPPs.
Despite its simplicity, the yield curve is one of the best predictors of future economic activity. Empirical studies suggest that the yield curve is capable of forecasting recessions in major economies. In this paper, the relationship between the yield curve and stock bear markets will be studied with the focus on predicting bear markets in the U.S. and Germany. Also this paper seeks to answer the question if a market-timing strategy, based on yield-curve information, can outperform the market.
The results of this study suggest that for the U.S. the spread between 10-year and 1-year interest rates outperforms other spreads in predicting bear markets. Furthermore, the yield spread can be used to profitably time the market and outperform a buy-and-hold strategy.
For the Germany yield curve, the study has found a statistical significant relationship between the yield curve and bear markets. However, depending on the observation period, the forecasting ability differs tremendously. For the entire period, the yield curve was not able to predict local bear markets reliably, nor was it possible to use the information contained in the yield curve to outperform the stock market.
The aim of this study is to analyze if Turkish firms apply a market timing strategy on their financing decisions and to analyze the persistence of the market timing decision on their capital structure. The sample data of this study contains the 85 initial public offers from 2010 to 2015 in Istanbul Stock Exchange(BIST). Regression analysis method is used for testing the relationship between market timing and equity issues, and short-run and long-run effect of market timing. The year before IPO and the three subsequent years after the IPO considered for analyzing the impact of market timing. The results of this study show that there is a positive relationship between market timing and equity issues. Firms that are decided to go public in “hot” market periods, issue more equites and reduce their leverage ratio sharply right after the IPO, and this relationship shows an impact on capital structure only in short run. This short-term impact of market timing starts vanishing after the second year of going public.