Graziella Felizia Widmer, ESG-Faktoren im Asset-Management von Schweizer Banken, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
 
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Sasha Lu, Investor Behaviour in Socially Responsible Investments - A Survey of Swiss Retail Investors in Microfinance, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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 Chiphong Vu, Empirical Evidence on the Persistence of Profits in Valuation Models, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
Empirical observations and microeconomic theory suggest that economic profit margins tend to mean-revert under competitive forces. The present empirical study examines this phenomenon based on a global sample of more than 10,000 listed firms between 1966 and 2016. We provide further support that a firm’s economic profit converges toward a long-term profitability level by fitting the data in an autoregressive (AR1) exponential decay model. The quantification of how fast and to which extent the profit margin develops allows for valuation practitioners to model the profits in a terminal value that incorporates a firm’s expected profit cycle more realistically and explicitly. |
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Luca Hany, Do Activist Investors Add Value?, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
Although the roots of activism – commonly defined as an intervention of a shareholder to unlock value in some form – go back to the beginning of the 20iest century, the topic attracted considerable attention in the past two decades, with more than 60% of all activist campaigns taking place after 2007. As these campaigns are often accompanied by martial communication by the activists, media often portray this investor type as reckless and greedy. Hence, the public perception is that the interventions are detrimental to the target company’s value. This thesis aims to answer the question whether activists truly achieve their goal in unlocking value when executing an intervention at their respective target or not. Existing academic literature has come to the conclusion that this is the case (e.g Brav et al (2008), Clifford (2008), Goodwin (2015)).
As in the past, researchers have primarily focused on analyzing the value generation for (1) the shareholder (expressed by excess returns) or (2) for the targeted company (expressed by an improvement of the operations) or (3) the debt providers (expressed by lower credit risk); I introduce a novel empirical model which accounts for all three components of value at once.
My sample is based on SharkWatch50, a database which comprises all campaigns initiated by the top 50 activist hedge funds according to SharkRepellent. Given the importance of the filing system as a source of information, I removed all targets which weren’t having a primary listing in the US. As the operational performance was also in the spotlight of this empirical analysis, no targets operating in the financial industry were represented due to the different composition of the accounting measures compared to the other industries. Additionally, I removed all targets with a market capitalization below USD 20m at the time of the campaign announcement. The final, adjusted sample consists of 720 campaigns, resulting in 512 unique targets with a primary listing in the US. Compared to existing research, this sample is featuring the most actual time span (from January 1st, 2007 to July 26th, 2017) and hence mitigates the prevailing criticism in academia of the use of outdated samples.
In order to find an econometric solution to the question of this thesis, I use linear regressions. In the empirical model, I introduce three dependent variables accounting for excess returns, 24 for operating performance and six for the capital structure. Then, six different independent variables are presented: Size measured by market capitalization (at the campaign announcement date), campaign duration (i.e. time span between announcement and end of campaign), number of campaigns in industry of activist target, activist campaign objective: Activist seeking board control rather than board representation only, 13D filing submission rate of the activist when initiating a campaign, submission rate of publicly disclosed letters to management.
My findings - which are statistically significant - indicate that an activist generates (1) value for the shareholder through excess returns in the following cases: (i) target’s market capitalization is small, (ii) the campaign duration is short, (iii) the activist density in the general industry is high, (iv) the activist is seeking solely board representation as opposed to board control, (v) a 13D filing was submitted and (vi) a publicly disclosed letter to the target’s management was sent. In contrast, no final conclusion can be drawn on how their campaigns improve operational performance and hence (2) value for the target as none of the effects is significant: credit risk, measured by the evolution of the capital structure and hence representing (3) the value for a debt provider, is minimized if the target has (i) a low market capitalization, (ii) a long campaign duration, (iii) the activist is obtaining board control as opposed to board representation only and (iv) submits a 13D form with all effects being significant.
While this thesis helps gaining a deeper understanding of the value generation process, two fundamental limitations exist: First, the results of the empirical model show that value creation takes place when the campaign has certain characteristics. Nevertheless it fails at quantifying the extent the activist was solely responsible for this effect as opposed to value generation that happened independently of the campaign. Second: The model only quantifies excess value generation for the shareholder (expressed by excess returns). For the two other components of value, the model does only deliver an answer to the question if value was generated but not if they were generated in excess compared to their respective peers which weren’t targeted by activists.
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Roman Seiler, The relation between implied volatility and market returns: Is it possible to predict market movements with option price information?, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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Vincent Rime, Investment Cash Flows Sensitivity - Evidence from a cross-country analysis and the determinants of the ICFS, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Rafael Gerpe Lorenzo, Portfolio Analysis of Cryptocurrencies: Diversification Benefits and Return Factors, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
Monetary policy is of central interest to economists, and in-depth analyses of investments are a main interest of finance research. Cryptocurrencies essentially affect both research fields and divide the opinions of researchers about the fundamental assessment of alternative assets. Besides addressing different fields of economics, the assessment of cryptocurrencies additionally requests traditional economic researchers to deal with the latest information technology. It even forces researchers, who are perhaps inexperienced in the field of informatics, to get involved in information science at least at a basic level to understand the main mechanisms of the research object. This interdisciplinary assignment causes a major challenge to carry out a sound evaluation of the risk and return characteristics of cryptocurrencies, and few academics committed their research to this area. However, an academic assessment of cryptocurrencies in a portfolio context is needed to investigate the inherent risks of the cryptocurrency market as well as to point out potential return benefits from the inclusion of cryptocurrencies in a traditional portfolio. Since cryptocurrencies represent primarily digital goods, an open question remains, if cryptocurrency properties can be found in financial or alternative assets at all. This thesis attempts to examine the risk-return characteristics of cryptocurrencies with several methods including a traditional finance approach and merely statistical analyses of cryptocurrency returns. Latter are conducted only for cryptocurrencies, as well as together with the returns of financial and alternative assets. This procedure ensures a balanced assessment of cryptocurrency properties in a portfolio context and helps to answer the question, if cryptocurrencies should be considered in the investment process from an academic point of view.
The objective of this thesis is to investigate the risk-return characteristics of cryptocurrencies and asses them in a broader portfolio view. For this reason, the cryptocurrency market development is investigated over time, and the inherent risk-return characteristics are examined. Furthermore, it is tested how cryptocurrency returns are evaluated within several traditional finance optimization frameworks. Also, this thesis emphasizes on sensitivity parameters that most optimizations are subject to and that eventually influence optimal portfolio outcomes of traditional investors. To assess cryptocurrencies in a portfolio context, the focus is set on the investigation of cryptocurrency return correlations, both among each other and in relation to other asset returns. Finally, the whole approach attempts to find indications of relevant cryptocurrency return factors and to suggest long-term drivers of the cryptocurrency market. Beside all these objectives, the scope of the thesis can also serve as a starting point for future academic research in this field and contribute to the general understanding of the cryptocurrency markets. In particular, it is not excluded that interested readers may find an alternative perspective of the risk assessment of their overall portfolio. |
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Clirim Mehmedi, Der Schweizer Arbeitsmarkt in der Grossen Depression, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Fabian Gschwend, Swiss stock return patterns around Federal Open Market Committee meetings, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
The goal of my thesis was to examine if there are excess stock return patterns around Federal Open Market Committee (FOMC) meetings similar to the biweekly patterns found by Cieslak et al (2016). The thesis extends in the way that possible explanatory variables are tested and evaluated. Industry indices will be examined and their behavior in the biweekly cycle intuitionally explained. The collected data and properties will then be used to create trading strategies that maximize returns and their performance metrics will be assessed. |
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Valdrin Edipi, Die Entwicklung des Mittelstands zu Beginn des 20. Jahrhunderts, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Thomas Schaad, The effects of temporary write-down CoCos on equity prices and CDS spreads, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Rajeevan Thiyagarajah, Credit Scoring 2.0 - Am Beispiel der Mobiltelefondatenauswertung, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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Remo Berger, Business Applications of Monte Carlo Simulation, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Emanuel Gabriel, Limit Order Books and Estimation of Market Impact Costs, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Loreno Schaufelberger, A statistical approximation of a high-dimensional climate model in an Integrated Assessment Model, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Erich Meier, Blockchein Technology and Cryptocurrencies, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Master Thesis)
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Nikolija Grahovac, Value-at-Risk-basierte Portfolioselektion, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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Giselbrecht Sibyl, Mean-Variance Portfolio-Selection under Additional Linear Constraints and Tobin Separation Theorem, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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Melanie Kuhn, Risk-Contribution Ansätze zur Portfolioselektion, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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Markendorf Enrico, Portfolio-Selektion durch Maximierung des Performancemasses Omega, University of Zurich, Faculty of Business, Economics and Informatics, 2018. (Bachelor Thesis)
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