Contributions in Merlin

The blockchain technology came to light some years ago with the growing popularity of Bitcoin. Despite being seen by many as a worthless cryptocurrency, the underpinning technology is truly revolutionary. Indeed, this technology, the blockchain, is likely to be at the origin of a total reorganization of the economy as we know it. The blockchain technology makes it possible to remove a central authority which has recording and checking all the transactions as functions. By the way the network is designed, it is impossible to alter the data stored as all participants agree on what is the correct version of data. Since no middle-man is involved in the process of transactions, this removes the possibility of human corruptibility. Additionally, this middle-man free system enables the network to process transactions on a real-time basis and at a reduced cost. The removal of one of the key functions of the financial services as intermediaries raises the question as to whether the intermediaries were doomed to disappear. The question can be answered in the negative for various reason. First, intermediaries will still be needed in specific situations such as disputes between parties. Their role as arbitrator will be of utmost importance. Then comes the legal responsibility question for illicit actions that would hinder the transactions made on the blockchain. The question as to who will be legally responsible should be addressed by the regulators, but we can assume that the responsibility should be given to the financial institution providing the blockchain-based platform. This thesis limits itself to this assumption and thus further research in this direction would be required. Hence, we understand that the roles of financial institutions as intermediaries are likely to change. What is certain is that banks and other financial services need to be at the forefront of the development of this technology. Indeed, this is crucial as they are likely to be most threatened. Financial institutions have a strong interest in developing blockchain-based platforms that would enable them to make cross-border intrabank payments or interbank transactions. Indeed, there is a huge potential for banks in the field of cost cutting. Additionally, a distributed ledger also offers simplification in auditing as all transactions recorded can be easily traced back. Among the opportunities offered by the technology, there is also the potential for the creation of new products and services. Moreover, the blockchain technology does not stop at value transfers. It is possible to store and transfer assets or property titles and use smart contracts. Smart contracts can be designed so that outcomes are automatized given specific conditions are met. This kind of contract is very promising as it can be applied to other industries than financial services. However, despite all the advantages mentioned above, there are some open questions that still need to be addressed. Among the main challenges, we find regulatory concerns and security. Indeed, there is still a need to determine what is compliant with the Know Your Customer regulations and what is not. On the security level, a hacker being able to access the private key of an individual could make transactions on his behalf. Hence, finding a way to store safely the private key is crucial. Then, the technology being still not mature enough to be implemented, the companies need to keep researching and experimenting. But here comes a key element. What is of utmost importance is to work with other firms, even competitors, to create common platforms. The business models that we know will need to be adapted to take into consideration decentralization of data. The network built by the participants, i.e. the firms, is a prerequisite for creating strong platforms that will meet the needs of each player. Coordination between the firms is central to be able to set up a strong platform and define what standards and obligations should be applied within the network.

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Experimental evidence shows that risk tolerance for future prospects is higher than for immediate ones, which can have profound implications for many aspects of life. The Missing-Link Model by Epper and Fehr-Duda (2015) explains higher risk tolerance for future prospects by the risk inherent in the future in conjunction with people’s proneness to Allais-type common-ratio violations. The latter is a characteristic of probability weighting and constitutes preference reversals for a pair of prospects as a consequence of scaling down the probabilities p of the best outcomes. Future risk, which reduces the probability of prospect survival, shifts the probability weighting function upwards and thereby increases risk tolerance. Moreover, the reduced curvature of the weighting function implies a decreasing proneness to common-ratio violations. The purpose of this thesis is to examine several predictions of the Missing-Link Model by means of a laboratory experiment with monetary incentives. The task of the subjects was to determine the sure amount payable at time t that was considered as being equivalent to the risky prospect paid out at t. Although the study does not provide evidence of increased risk tolerance for future prospects, the results support several other predictions of the model. There is evidence of increased risk tolerance for future prospects with p = 90% and p = 10% when the future is perceived as more uncertain. This impression was conveyed by a priming manipulation. The manipulation check suggests that future risk may stem from mistrust of other people which makes people feel that future prospects are less likely to survive. Further results indicate that the valuation of delayed prospects with p = 50% is higher when the final outcome is revealed at the payment date rather than immediately. Moreover, there is evidence that risk tolerance for future prospects with p = 90% increases with the degree of departure from linear probability weighting. The results for the sample of prospects with all levels of p indicate that risk tolerance increases with future risk and the departure from linear probability weighting. Therefore, the Missing-Link Model can make important contributions to theories of decision making.

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The goal of this thesis is to explore and test new methods to learn, describe and predict economic cycles. In particular, a comparison of inference algo-rithms for hidden Markov models (HMM) and hidden semi-Markov models (HSMM) is conducted. Both proposed approachesthe popular Expectation-maximization (EM) algorithm and a Markov chain Monte Carlo (MCMC) samplerhave advantages depending on the size and noise of the underlying data as well as whether interval estimation or the addition of data-specific knowledge is desired. Furthermore, HMMs and HSMMs are used to describe financial markets. While the hidden Markov model performs well as a trading tool, it is less suitable to model economic cycles, since its implicit geometric state duration distribution flips states unrealistically often. In contrast, the hidden semi-Markov regime switching model appears to be very promising, demonstrating high potential as a strategic asset allocation (SAA) overlay from a finance perspective and as a model for economic cycle predictions from an economics perspective. Keywords: Hidden Markov Models, Hidden Semi-Markov Models, Statistics, Machine Learning, Algorithms, EM-Algorithm, MCMC, Economic Cycles, Financial Markets, ETH Zurich, University of Zurich