Contributions published at Financial Economics (Thorsten Hens)

This study documents experimental evidence that naïve beliefs about the behavior of others contribute to excessive trading. The mechanism is based on the idea that when people process new information they naïvely neglect other market participants’ reaction to the information and consequently trade too much. In a series of laboratory experiments, I find that people actively trade on information that they should expect to be already incorporated into the price by other players. In line with naïve news trading, people underestimate the response of others to new information and consequently trade too much compared to the rational benchmark. A simple model with naïve investors who partially neglect that other investors respond to new information provides a good fit of the observed trading behavior.

Bitcoin und die zugrunde liegende Technologie der Blockchain sind längst keine Randphänomene mehr. Zwar ist Bitcoin in vielerlei Hinsicht neuartig. Das steht aber einer Einordnung als «Geld im weiteren Sinn» bzw. als «Kryptowährung» nicht im Weg. Bitcoin ient zurzeit primär als Spekulationsobjekt, aber auch zur Wertaufbewahrung und als Zahlungsmittel. Während das Bitcoin-System nur die Übertragung von Bitcoins erlaubt, ist die Blockchain von Ethereum, der zweitgrössten Kryptowährung, frei programmierbar and erlaubt die Emission beliebiger «Tokens». Diese können Währungen, Anleihen, Aktien oder beliebige andere Vermögenswerte mit oder ohne vom Emittenten garantierten Wert darstellen. Kryptowährungen haben das Potenzial, einen Digitalisierungsschub im Finanzbereich auszulösen. Um dieses Potenzial zu realisieren, bedarf es aber noch der Klärung verschiedener Rechtsfragen und der Beseitigung rechtlicher Hürden.

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This thesis assesses the efficacy of strategies attempting to harvest equity premia related to value, size, momentum, quality and low beta factors in US equities and investigates potential improvements in strategy design that lead to increased real-world performance. In detail, this study empirically tests factor investing strategies and their predictability using data for all listed US stocks from 1990 to 2016. The size factor is constructed following the methodology explored in Fama and French (1992), value follows Asness and Frazzini (2013), momentum is implemented according to Carhart (1997), quality is based on Novy-Marx (2013a) and low beta follows Frazzini and Pedersen (2014). Stock selection is constricted to non-penny stocks and the most illiquid 10% of stocks are ignored at every rebalancing date. Additionally to the sort based long-short strategy implementation, ong-versus-index and short-versus-index implementations are investigated in order to attribute the excess return of the factor to the long and short legs. Under practical considerations, the long-versus-index approach is preferable, as short positions in the market are easy to implement via index products and futures. In an extension of the framework presented in Frazzini and Pedersen (2014), the benefits of hedging factor strategies using index products is also explored. Any design changes that lead to performance increases of individual premia are tested against an equal-weighted 1/N benchmark of the factors. If the improvement is unrelated to the other factors, the combination of the altered factors should outperform the original benchmark. My results show that the beta neutral combination of factors outperforms the dollar neutral combination. Adding to this, premia can, on average, be harvested without having to short individual securities. The exceptions are the momentum and quality factors, where the short leg adds significant outperformance. Combining long-short momentum and quality strategies with long-versus-index implementations of the other premia produces a market neutral strategy that returns an annual CAPM alpha of 11.4% at a Sharpe ratio of 1.40 on paper. This strategy outperforms the individual factors and the market in terms of risk-adjusted returns.

Die Verteilung von digitalen Werten über miteinander verknüpfte Rechner scheint Transaktionen im Bereich der Effizienz im IT-, Fintech-Sektor, aber auch im Schweizer Regierungs- und Rechtswesen zu fördern, wenn nicht zu verbessern. Derweil versuchen Experten die vielverheissende und doch komplexe Blockchain-Technologie bestmöglich zu regulieren.

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Bewerten im eigentlichen Sinne ist Aufgabe der Immobilienkäufer und -verkäufer. Die Immobilienbewerter bilden lediglich deren Verhalten am Markt ab, was mit Unsicherheiten verbunden ist. Jeder Versuch, diese Unschärfe wegzudefinieren, ist zum Scheitern verurteilt und führt zu Fehlentscheidungen, Marktineffizienzen und Systemrisiken.

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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The digital evolution is enabling the creation of sophisticated software solutions that make money management more accessible, affordable and eponymous. Full automation is attractive to investors at an early stage of wealth accumulation, but hybrid models are of interest to investors who control larger amounts of wealth, particularly those who have enough wealth to be able to efficiently diversify their holdings. Investors can now outperform their benchmarks more easily using the latest tech tools. The WEALTHTECH Book is the only comprehensive guide of its kind to the disruption, innovation and opportunity in technology in the investment management sector. It is an invaluable source of information for entrepreneurs, innovators, investors, insurers, analysts and consultants working in or interested in investing in this space. - Explains how the wealth management sector is being affected by competition from low-cost robo-advisors - Explores technology and start-up company disruption and how to delight customers while managing their assets - Explains how to achieve better returns using the latest fintech innovation - Includes inspirational success stories and new business models - Details overall market dynamics The WealthTech Book is essential reading for investment and fund managers, asset allocators, family offices, hedge, venture capital and private equity funds and entrepreneurs and start-ups.

Behavioral Finance for Private Banking provides a complete framework for wealth management tailored to the unique needs of each client. Merging behavioral finance with private banking, this framework helps you gain a greater understanding of your client’s wants, needs, and perspectives to streamline the decision making process. Beginning with the theoretical foundations of investment decision making and behavioral biases, the discussion delves into cultural differences in global business and asset allocation over the life cycle of the investment to help you construct a wealth management strategy catered to each individual’s needs. This new second edition has been updated to include coverage of fintech and neurofinance, an extension of behavioral finance that is beginning to gain traction in the private banking space.

Currency carry trade returns are on average large and non-normally distributed. While the literature has found different explanations for the existence of carry trade returns, the higher order moments of their return distribution still pose a puzzle. We propose a new model to explain these non-normal properties of currency carry trade returns, by assuming that agents are loss averse and overweight states with low probabilities. This combination of loss aversion and probability weighting is called crash-o-phobia. Using non-linear least squares and risk-neutral state prices implied by currency options, we estimate this crash-o-phobia model to price developed and emerging market currencies. The parameter estimates reveal crash-o-phobic beliefs and preferences with significant differences across currencies. Compared to a model with rational beliefs and CRRA utility, our crash-o-phobia model performs significantly better at explaining the whole distribution of currency carry trade returns.

Purpose An outcome bias occurs when performance is evaluated based upon the outcome of the decision rather than upon the quality of the decision itself. The purpose of this paper is to test experimentally whether advisors eliminating the uncertainty in the quality of decisions as a potential driver of the outcome bias can eliminate this bias in judgements. Additionally, the paper analyses whether such advisors can attenuate the emotional experience after decisions’ outcomes by supporting the cognitive understanding of these outcomes. Design/methodology/approach The paper employs a between-subject experimental setting where decision makers are asked to make investment decisions. The two variables manipulated were advice (receiving advice vs deciding without an advice) and state (loss vs neutral vs gain state). Participants were randomly assigned to each group. One group completed all tasks while receiving advice before making a final decision. Another group completed all tasks without any advice. After completing each investment task, participants were randomly assigned to one of three possible states that determine their payoff. Findings The results reveal that advisors eliminating the uncertainty in the quality of decision can eliminate the outcome bias in the judgements of decision quality, especially after bad outcomes. Nevertheless, after controlling for the perceived quality of the decisions, advised individuals show a greater emotional sensitivity to bad outcomes than non-advised decision makers. These observations suggest that advisors eliminating the uncertainty in the decision quality can improve the understanding that good decisions can lead to bad outcomes just by chance, but they are not able to prevent affective reactions after bad outcomes; on the contrary, they may even reinforce them. Research limitations/implications The observation that, after bad outcomes, advised decision makers are less willing to decide the same way than non-advised decision makers is consistent with empirical findings on the risk-taking behaviour of self-directed and mutual fund investors. Self-directed investors are less likely to revise their decision and sell an investment at a loss than mutual fund investors (Chang et al., 2016). While investors might sell funds because they are unable to observe the decision process of the manager and use the outcome to judge the manager’s skills, this study shows that such learning from decision outcomes is not necessary for observing the risk-taking behaviour of the investors. Even if the decision process of the advisor is observable (as in this study), the decision makers’ willingness to decide the same way is influenced by the losses – an effect that goes beyond the assessed quality of advice as the results of this study show. Practical implications The results of this study have important implications for advisors aiming to maintain a positive relationship with their clients. Convincing clients that an advice is optimal supports their understanding that a good advice can have bad outcomes. However, this understanding may not prevent affective reactions after bad outcomes. On the contrary, the affective response after bad outcomes is even stronger with the advice than without it. Hence, advisors should address not only issues related to the quality of the provided advice, but also emotional aspects, which could be related to what clients expect from following the advice. Originality/value This study is one of the few that account for the possibility that the outcome bias may arise because there is uncertainty regarding the optimal choice. In particular, this paper uses a much more powerful criterion to define an optimal choice than the expected value criterion used in previous studies. The criterion represents a minimal requirement for rational behaviour in expected utility theory and many non-expected utility theories.