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Studies on the empirical validation of beta-return relationship postulated in the CAPM has a relatively long history. The first study was conducted by John Lintner in 1965, shortly after the introduction of the model. In one of the recent studies, Malcolm Baker (forthcoming) examines two portfolios, one consisting of the 30% of U.S. stocks with the lowest beta, another of the 30% with the highest beta. By the end of the period, the low-beta portfolio significantly outperforms the high-beta portfolio (Economist, 2016).
Following two recognized testing methods developed by Lintner (1965) and Fama/MacBeth (1973), this bachelor thesis examines the nature of the relationship between beta and return for the German stock market. The sample periods observed in this study range from January 1973 to May 2016 depending on the testing method. The obtained results are then compared with the outcome of the previous studies for the European stock market. The analysis reveals that the relationship between beta and return is insignificant in most of the models. These results are consistent with the European stock market, if the unconditional cross-sectional analysis is considered.
In the last recent years, Bitcoin along with many other cryptocurrencies has grown and developed into multibillion dollar industry. Cryptocurrencies are perceived or even misunderstood by many people and experts as purely speculative assets, which have unpredictable values and extreme volatility. The public opinion is separated into two sides: the first side considers cryptocurrency, respectively, Bitcoin as one of the biggest financial bubble and the second side thinks of cryptocurrency as the future which has great potential to revolutionize the financial industry. In fact, the revolution initiated by digital currency does not lie in the transaction value or short-term earning opportunities for cryptocurrency investors, but rather in the underlying technology behind it called „Blockchain”. Since the very beginning of currency and private infor-mation, the existence of thieves and fraudster has always been problematic. Due to the complexity of fraud and the serious risks that fraud presents to business, fraud detection and fraud prevention is often conceived as cat-and-mouse game between companies and fraudsters. Admittedly, there is no completely fool-proofed system or technology, on the other hand fraudsters nowadays constantly change and develop their technique in order to bypass even the most complex security system. Block-chain is a shared distributed ledger that is immutable and resistant to tampering. Only verified contributors by blockchain are allowed to store, view and share digital infor-mation in a security-enhanced environment. The three following features of block-chain: distribution, immutability, permission which help to maintain trust, accountabil-ity and transparency in business relationships. This cutting-edged technology called blockchain has the capabilities and potentials to provide companies and organiza-tions the ultimate fraud prevention solution which they have been waiting for in a long time.
“The technology likely to have the greatest impact on the next few decades has ar-rived. And it is not social media, it’s not big data, it’s not robotic, it’s not even AI. You will be surprised to learn that it is the underlying technology of digital currencies like Bitcoin. It is called the blockchain – Blockchain.”.
Don Tapscott (Tapscott, 2016)
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.