Search

This doctoral thesis comprises one essay on the risk management of momentum strategies and three essays on the implications of skewness preferences on financial markets. Chapter 1 provides an extensive summary and links all projects within the framework of behavioral finance. In Chapter 2 (co-authored with Maik Dierkes), we investigate momentum in stock returns and propose a novel approach to manage the downside risk of momentum strategies. Across markets, momentum is one of the most prominent anomalies and leads to high risk-adjusted returns. However, these returns come at the cost of substantial tail risk as there are short but persistent periods of highly negative returns. Momentum crashes occur in rebounding bear markets, when the momentum portfolio exhibits a negative beta and momentum volatility is high. Based on ex-ante estimates of these risk measures, we construct a crash indicator that effectively isolates momentum crashes. Subsequently, we propose an implementable trading strategy that combines both systematic and momentum-specific risk and more than doubles the Sharpe ratio of the original momentum strategy. Moreover, it outperforms existing risk management approaches over the 1928-2020 period, in sub-samples, and internationally. In Chapter 3 (co-authored with Maik Dierkes and Sebastian Schroen), we address the effects of time-varying skewness preference, referred to as lottery demand, on first-day returns and the long-term performance of initial public offerings (IPOs). Following the identification approach of Dierkes (2013), we measure lottery demand in terms of option-implied probability weighting functions and find a significantly positive impact on first-day returns, tantamount to higher IPO underpricing and more money left on the table. Furthermore, disentangling the effects of lottery demand and cross-sectional expected skewness reveals that IPO returns are particularly driven by the interaction of market-wide lottery demand and asset-specific lo, Diese Dissertation umfasst einen Aufsatz zum Risikomanagement von Momentum-Strategien und drei Aufsätze über die Auswirkungen von Schiefepräferenzen auf Finanzmärkte. Kapitel 1 enthält eine ausführliche Zusammenfassung und ordnet die Forschungsprojekte in den Rahmen der verhaltensorientierten Finanztheorie ein. In Kapitel 2 (gemeinsam mit Maik Dierkes verfasst) untersuchen wir das Momentum von Aktienrenditen und entwickeln einen neuartigen Ansatz zur Risikosteuerung von Momentum-Strategien. Die Momentum- Anomalie ist eine der bekanntesten Finanzmarkt-Anomalien und erzielt hohe risikobereinigte Renditen. Diese sind jedoch mit einem erheblichen Verlustrisiko verbunden, da sich wiederholt mehrmonatige Phasen stark negativer Renditen ereignen. Momentum-Crashes treten insbesondere in sich erholenden Bärenmärkten auf, wenn das Momentum-Portfolio zeitgleich ein negatives Beta und eine hohe Momentum-Volatilität aufweist. Auf Grundlage von ex-ante Schätzungen dieser Risikomaße konstruieren wir einen Crash-Indikator, welcher Momentum-Crashes erfolgreich isoliert. Infolgedessen stellen wir eine implementierbare Handelsstrategie vor, die systematisches und momentumspezifisches Risiko kombiniert und die Sharpe-Ratio der ursprünglichen Momentum-Strategie mehr als verdoppelt. Darüber hinaus übertrifft sie bestehende Risikomanagement- Strategien im Zeitraum von 1928-2020 sowie in Subperioden und im internationalen Kontext. In Kapitel 3 (gemeinsam mit Maik Dierkes und Sebastian Schrön verfasst) untersuchen wir die Auswirkungen von zeitlich variierenden Schiefepräferenzen, im Folgenden als Lotterienachfrage bezeichnet, auf kurz- und langfristige Renditen nach Börsengängen (IPOs). Aufbauend auf der Identifikationsstrategie von Dierkes (2013) messen wir die Lotterienachfrage anhand optionsimplizierter Wahrscheinlichkeitsgewichtungsfunktionen und stellen einen signifikant positiven Einfluss auf die Renditen am ersten Handelstag fest. Dieses Resultat ist gleichbedeutend mit einer stärker

Households in developing countries are exposed to various shocks and risks, which leaves them vulnerable as they typically have limited resources to cope with them. Even though a large body of development literature has focused on the role of risk in rural livelihoods, the focus is often on single sources of risk and taking a unidimensional view on risk preference. This paper explores the diversity in risk perception and risk preferences of Ethiopian households by combining incentivized field experiments with detailed primary household survey data. We disentangle the relationship between risk perception and risk preferences using an innovative combination of time framing and instrumental variable estimation approaches. We find that our respondents are exposed to multiple past shocks and perceive multiple sources of future threats across different agricultural risk domains. Our respondents can be characterized as relatively risk-averse and loss-averse, and they also overweight unlikely extreme outcomes. We find a statistically significant association between the prospect theory risk preferences parameters—risk aversion, loss aversion, and probability weighting—and overall risk perception, domain-specific risk perceptions (except for the personal domain) and the impact dimension of future risk. Our findings make an important contribution to our understanding of farm households’ risk behavior, and can guide prioritizing development efforts to stimulate better informed and well-targeted risk management policy interventions.

Increasing agricultural production, while decreasing its impact on the environment is a global challenge. Sustainable innovations, such as microbial applications, can play an important role in this light. However, risk averse farmers are often reluctant to adopt such innovations. In this study, we investigate (i) the relationship between risk attitude and farmers' intention to adopt microbial applications and (ii) the effectiveness of an informational video to stimulate the adoption. In July 2020, 98 Dutch arable farmers have participated in an online survey with an experiment. In the experiment, half of the farmers have watched an informational video on microbial applications, while the other half was a clean control without receiving information. Then, all farmers are assigned a monetarily incentivised standard Multiple Price List (MPL) and a payoff-varying MPL lottery game to assess the relationship between innovation adoption and risk attitudes. We find evidence that the video has a significant effect on farmers' intention to adopt microbial applications. Further, our results suggest that the intention to use microbial applications can be influenced by farmers' risk attitude.

This thesis focuses on how individuals and groups perceive and behave in the face of risky and ambiguous outcomes. There has been much research on how individuals behave in these situations, but much less investigation into when and why they behave in this way. These questions are addressed from a behavioural, neuro-biological and environmental perspective and answered using individual and group lab-based experiments. The results of these experiments indicate that the amount of information presented, prevailing sentiment and biological factors all influence how we make decisions and the extent to which these decisions are "logical".

How do individuals and societies make such decisions about health in practice, and does economic research provide the right tools to inform and study such decision-making? In his dissertation, Stefan Lipman tries to answer these questions. In economics, decisions about health are typically studied assuming they are made rationally. However, over the past decades the traditional economic view of rationality has been suggested to be highly unrealistic. As most work challenging this view is based on financial decision-making, in the first part of his dissertation, Lipman extends

Decisions from description typically concern risk in the literature on decision making. It is identified as a case where outcome probabilities are objectively known. Decisions from experience, on the other hand, represent a case of ambiguity. Here, the outcome probabilities are not known objectively but they are subjectively inferred based on observations. As in many real life situations, probabilistic inference and information search are integral parts of decisions from experience. This dissertation explores behavioral differences between decisions from experience and from description by focusing on the role of (1) probability weighting, and (2) subjective beliefs. _Chapter 2_ investigates the impact of experience on probability weighting. _Chapter 3_ points out the role of prior beliefs in accounting for decisions from experience. _Chapter 4_ introduces a non-Bayesian model of updating which accommodates common biases in probabilistic inference. _Chapter 5_ reports results of a laboratory experiment testing Prelec’s (1998) theory of probability weighting

This thesis presents evidence suggesting that the same types of biases in individual decision making under uncertainty pertain in interpersonal contexts. The chapters above demonstrate in specific contexts how specific interpersonal factors attenuate, amplify, or replicate these biases. One of the most natural interpersonal contexts is group decision making. The group effects on decisions consist of aggregation and communication, and disentangling these could help us improve our understanding of the group decision making process and make better predictions. Because the two measures of rationality applied in Chapter 2, namely stochastic dominance and EU-compliance, are both dichotomous, we use the simulated decisions from pure voting as benchmarks to isolate the communication effects. Chapter 3 describes how simple pieces of information were provided to individuals, with the aim of helping them evaluate the quality of the estimates they received in interpersonal communication. Chapter 4 extends Yaari's definition of comparative risk aversion to enable comparisons between people holding different beliefs. The last chapter presents evidence that the mere presentation with cash could make a substantial psychological impact on people's risk attitudes by changing their likelihood insensitivity in probability weighting. The cash effects that lower valuations could potentially come from a buyer's evolutionary instinct in bargaining triggered by cash. Testing the existence of such instincts and, if they exist, finding what triggers them could be complementary to the current study.

Political psychologists have been quick to use prospect theory in their work, realizing its potential for explaining decisions under risk. Applying prospect theory to political decision-making is not without problems, though, and here we address two of these: (1) Does prospect theory actually apply to political decision-makers, or are politicians unlike the rest of us? (2) Which dimension do politicians use as their reference point when there are multiple dimensions (e.g., votes and policy)? We address both problems in an experiment with a unique sample of Dutch members of parliament as participants. We use well-known (incentivized) decision situations and newly developed hypothetical political decision-making scenarios. Our results indicate that politicians' deviate from expected utility theory in the direction predicted by prospect theory but that these deviations are somewhat smaller than those of other people. Votes appear to be a more important determinant of politicians' reference point than is policy.

Political psychologists have been quick to use prospect theory in their work, realizing its potential for explaining decisions under risk. Applying prospect theory to political decision-making is not without problems, though, and here we address two of these: (1) Does prospect theory actually apply to political decision-makers, or are politicians unlike the rest of us? (2) Which dimension do politicians use as their reference point when there are multiple dimensions (e.g., votes and policy)? We address both problems in an experiment with a unique sample of Dutch members of parliament as participants. We use well-known (incentivized) decision situations and newly developed hypothetical political decision-making scenarios. Our results indicate that politicians' deviate from expected utility theory in the direction predicted by prospect theory but that these deviations are somewhat smaller than those of other people. Votes appear to be a more important determinant of politicians' reference point than is policy.

Scheduling preferences, derived under the assumption of expected utility maximization, can be used for measuring the value of travel time variability. As an alternative to the expected utility maximization, the rank dependent utility is chosen in this paper. Considering a flexible probability weighting for ranked outcomes, two frequently applied scheduling models are derived and estimated on a data set with specific travel time distributions. Optimistic respondents are observed. Allowing for heterogeneity of scheduling preferences improves the model performance significantly. We also found evidence for valuing excessive travel time, which is not included in the traditional scheduling model specifications., QC 20140613

For each stock in the U.S. universe in turn, we take the stock’s distribution of past returns, and compute the value that would be assigned to this distribution by (cumulative) prospect theory. We find that this “prospect theory value” predicts subsequent returns in the cross-section, with a negative sign. This is particularly true for stocks traded primarily by individual investors and for stocks that are hard to arbitrage. We repeat our tests in 46 international markets, and find a similar pattern in a majority of those markets. Our conjecture is that some investors are influenced in their trading by the quick initial impression of a stock that they form after glancing at a chart of the stock’s historical price movements - a so-called “system 1” impression that we quantify as the stock’s prospect theory value. Stocks with high prospect theory values make a positive impression on these investors, who tilt toward them, causing them to be overpriced and to earn low subsequent returns.

For mergers and acquisitions with a small failure probability, the average decline in target stock price if the deal fails is much larger than any increase that accompanies deal success. Probability weighting implies that the deal failure probability of such target stocks will be overweighted, leading them to be undervalued. I test whether investors are averse to holding such stocks and find strong supporting evidence. Target stocks with lower ex-ante failure probability yield positive abnormal returns, but other targets do not generate significant abnormal returns. A trading strategy that buys target stocks with low ex-ante failure probability and sells short target stocks with high ex-ante failure probability delivers around 1% abnormal return per month. These abnormal returns are not subsumed by a preference for positive skewness under traditional (expected) utility models; in fact, target stocks with lower ex-ante failure probability have lower betas, lower volatilities, and lower downside risk. I also find that profits from the strategy are significantly higher when arbitrage is more difficult.

For each stock in the U.S. universe in turn, we take the stock’s distribution of past returns, and compute the value that would be assigned to this distribution by (cumulative) prospect theory. We find that this “prospect theory value” predicts subsequent returns in the cross-section, with a negative sign. This is particularly true for stocks traded primarily by individual investors and for stocks that are hard to arbitrage. We repeat our tests in 46 international markets, and find a similar pattern in a majority of those markets. Our conjecture is that some investors are influenced in their trading by the quick initial impression of a stock that they form after glancing at a chart of the stock’s historical price movements - a so-called “system 1” impression that we quantify as the stock’s prospect theory value. Stocks with high prospect theory values make a positive impression on these investors, who tilt toward them, causing them to be overpriced and to earn low subsequent returns.

For mergers and acquisitions with a small failure probability, the average decline in target stock price if the deal fails is much larger than any increase that accompanies deal success. Probability weighting implies that the deal failure probability of such target stocks will be overweighted, leading them to be undervalued. I test whether investors are averse to holding such stocks and find strong supporting evidence. Target stocks with lower ex-ante failure probability yield positive abnormal returns, but other targets do not generate significant abnormal returns. A trading strategy that buys target stocks with low ex-ante failure probability and sells short target stocks with high ex-ante failure probability delivers around 1% abnormal return per month. These abnormal returns are not subsumed by a preference for positive skewness under traditional (expected) utility models; in fact, target stocks with lower ex-ante failure probability have lower betas, lower volatilities, and lower downside risk. I also find that profits from the strategy are significantly higher when arbitrage is more difficult.

For each stock in the U.S. universe in turn, we take the stock’s distribution of past returns, and compute the value that would be assigned to this distribution by (cumulative) prospect theory. We find that this “prospect theory value” predicts subsequent returns in the cross-section, with a negative sign. This is particularly true for stocks traded primarily by individual investors and for stocks that are hard to arbitrage. We repeat our tests in 46 international markets, and find a similar pattern in a majority of those markets. Our conjecture is that some investors are influenced in their trading by the quick initial impression of a stock that they form after glancing at a chart of the stock’s historical price movements - a so-called “system 1” impression that we quantify as the stock’s prospect theory value. Stocks with high prospect theory values make a positive impression on these investors, who tilt toward them, causing them to be overpriced and to earn low subsequent returns.

In this paper, we delve into the evolutionary foundation of both probability weighting and hyperbolic discounting. It is argued that it is evolution which selects between various kinds of people those who have the optimal preference profile. As such, utility functions and behavioural biases can be explained from an evolutionary perspective. It is also argued that there may be an intimate connection between hyperbolic discounting and probability weighting. This follows from the similarities between these two deviations from what normative economic theory would consider 'rational'. Following the suggestion of this intimate connection, we analyse a model which is capable of explaining why probability weighting may have been advantageous for our ancestors and we look whether we can reinterpret this model to also include hyperbolic discounting. This turns out to be difficult, however, as an analysis of the properties of the model makes clear.

In this paper, we delve into the evolutionary foundation of both probability weighting and hyperbolic discounting. It is argued that it is evolution which selects between various kinds of people those who have the optimal preference profile. As such, utility functions and behavioural biases can be explained from an evolutionary perspective. It is also argued that there may be an intimate connection between hyperbolic discounting and probability weighting. This follows from the similarities between these two deviations from what normative economic theory would consider 'rational'. Following the suggestion of this intimate connection, we analyse a model which is capable of explaining why probability weighting may have been advantageous for our ancestors and we look whether we can reinterpret this model to also include hyperbolic discounting. This turns out to be difficult, however, as an analysis of the properties of the model makes clear.

The economic concept of the second-best involves the idea that multiple simultaneous deviations from a hypothetical first-best optimum may be optimal once the first-best itself can no longer be achieved, since one distortion may partially compensate for another. Within an evolutionary framework, we translate this concept to behavior under uncertainty. We argue that the two main components of prospect theory, the value function and the probability weighting function, are complements in the second-best sense. Previous work has shown that an adaptive S-shaped value function may be evolutionary optimal if decision-making is subject to cognitive or perceptive constraints. We show that distortions in the way probabilities are perceived can further enhance fitness. The second-best optimum involves overweighting of small and underweighting of large probabilities. Behavior as described by prospect theory might therefore be evolution's second-best solution to the fitness maximization problem. Our model makes empirically testable predictions about the relation between individuals' value and probability weighting functions.

I explore the implications of reference-dependent preferences in sealed-bid auctions. In the first part, I develop a Prospect theory based model to explain bidding in first-price auctions. I show that bidding in induced-value first-price sealed-bid auctions can be rationalized as a combination of reactions to underlying ambiguity and anticipated loss aversion. Using data from experimental auctions, I provide evidence that in induced-value auctions with human bidders, this approach works well. In auctions with prior experience and /or against risk-neutral Nash rivals where ambiguity effects could be altogether irrelevant, anticipated loss aversion by itself can explain aggressive bidding. This is a novel result in the literature. Using data from experiments, I find that ambiguity effects become negligible in auctions with experienced human bidders against (i) experienced human rivals and (ii) Nash computer rivals, when loss aversion is taken in consideration. The estimates for loss aversion are similar in auctions with human bidders (with or without experience). Next, I extend my approach of anticipated loss aversion to address bidding outcomes in first- and second-price sealed-bid auctions. As shown in first part, the model predicts overbidding in first-price induced-value auctions consistent with evidence from most laboratory experiments. However, substantially different bidding behavior could result in commodity auctions where money and auction item are consumed along different dimensions of the consumption space. Differences also result in second-price auctions. The study thereby indicates that transferring qualitative behavioral findings from induced-value laboratory experiments to the field may be problematic if subjects are loss averse and anticipate such losses at the time of bidding. Finally, I explore the effect of resale or procurement opportunities, to which bidders have heterogeneous market access, on bidding in first- price sealed-bid auctions. My model

This paper introduces a parameter-free method for measuring the weighting functions of prospect theory and rank-dependent utility. These weighting functions capture risk attitudes, subjective beliefs, and ambiguity attitudes. Our method, called the midweight method, is based on a convenient way to obtain midpoints in the weighting function scale. It can be used both for risk (known probabilities) and for uncertainty (unknown probabilities). The resulting integrated treatment of risk and uncertainty is particularly useful for measuring the differences between them: ambiguity. Compared to existing methods to measure ambiguity attitudes, our method is more efficient and it can accommodate violations of expected utility under risk. An experiment demonstrates the feasibility and tractability of our method, yielding plausible results such as ambiguity aversion for moderate and high likelihoods but ambiguity seeking for low likelihoods, as predicted by Ellsberg.

Gul's theory of disappointment aversion (DA) has several attractive features, being intuitive, analytically tractable, and parsimonious. In spite of this, the DA model has received little attention in practical applications, which may be partly due to the absence of a procedure to elicit the model. We show how the tradeoff method, developed by Wakker and Deneffe can be used to elicit DA. Our elicitation method is parameter-free: it requires no assumption about utility and/or disappointment aversion. Quantitative tests of DA in three outcome domains, monetary gains, monetary losses, and life-years, suggest that the DA model is too parsimonious. Of the other models of disappointment aversion that have been proposed in the literature, our data are most consistent with the model of Loomes and Sugden.

Stewart, Reimers and Harris (2015, SRH hereafter) demonstrated that shapes of utility and probability weighting functions could be manipulated by adjusting the distributions of outcomes and probabilities on offer, as predicted by the theory of Decision by Sampling. So marked were these effects that, at face value, they profoundly challenge standard interpretations of preference theoretic models where such functions are supposed to reflect stable properties of individual risk preferences. Motivated by this challenge, we report an extensive replication exercise based on a series of experiments conducted as a quasi-adversarial collaboration across different labs and involving researchers from both economics and psychology. We replicate the SRH effect across multiple experiments involving changes in many design features; importantly, however, we find that the effect is also present in designs modified so that Decision by Sampling predicts no effect. While those results depend on model-based inferences, an alternative analysis using a model free comparison approach finds no evidence of patterns akin to the SRH effect. On the basis of simulation exercises, we demonstrate that the SRH effect may be a consequence of misspecification biases arising in parameter recovery exercises that fit imperfectly specified choice models to experimental data. Overall, our analysis casts the SRH effect in an entirely new light.

Stewart, Reimers and Harris (2015, SRH hereafter) demonstrated that shapes of utility and probability weighting functions could be manipulated by adjusting the distributions of outcomes and probabilities on offer, as predicted by the theory of Decision by Sampling. So marked were these effects that, at face value, they profoundly challenge standard interpretations of preference theoretic models where such functions are supposed to reflect stable properties of individual risk preferences. Motivated by this challenge, we report an extensive replication exercise based on a series of experiments conducted as a quasi-adversarial collaboration across different labs and involving researchers from both economics and psychology. We replicate the SRH effect across multiple experiments involving changes in many design features; importantly, however, we find that the effect is also present in designs modified so that Decision by Sampling predicts no effect. While those results depend on model-based inferences, an alternative analysis using a model free comparison approach finds no evidence of patterns akin to the SRH effect. On the basis of simulation exercises, we demonstrate that the SRH effect may be a consequence of misspecification biases arising in parameter recovery exercises that fit imperfectly specified choice models to experimental data. Overall, our analysis casts the SRH effect in an entirely new light.

This paper provides experimental evidence of the role of higher order risk attitudes—especially prudence—in prevention behavior. Prudence, under an expected utility framework, increases (decreases) self-protection effort compared to the risk neutral level when the risk of losing part of an income exists in a future (the same) period. Motivated by these predictions that give the exact test on prudence, an experiment was designed where subjects go through higher order risk attitude elicitation and make a self-protection decision. In contrast to expected utility theory, the observed efforts are less than the risk neutral level, regardless of the timing of loss. This violation of expected utility predictions could be explained by probability weighting.

This paper provides experimental evidence of the role of higher order risk attitudes—especially prudence—in prevention behavior. Prudence, under an expected utility framework, increases (decreases) self-protection effort compared to the risk neutral level when the risk of losing part of an income exists in a future (the same) period. Motivated by these predictions that give the exact test on prudence, an experiment was designed where subjects go through higher order risk attitude elicitation and make a self-protection decision. In contrast to expected utility theory, the observed efforts are less than the risk neutral level, regardless of the timing of loss. This violation of expected utility predictions could be explained by probability weighting.