Asymmetric preferences in investment decisions in the Brazilian financial market

The main objective of this article is to test the hypothesis that utility preferences that incorporate asymmetric reactions between gains and losses generate better results than the classic Von Neumann-Morgenstern utility functions in the Brazilian market. The asymmetric behavior can be computed through the introduction of a disappointment (or loss) aversion coefficient in the classical expected utility function, which increases the impact of losses against gains. The results generated by both traditional and loss aversion utility functions are compared with real data from the Brazilian market regarding stock market participation in the investment portfolio of pension funds and individual investors.

Stima dei parametri di modelli idrologici mediante ottimizzazione dell’utilità

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste.

Social Welfare and Behavioral Public Policies

In this work I discuss several key aspects of welfare economics and policy analysis and I propose two original contributions to the growing field of behavioral public policymaking. After providing a historical perspective of welfare economics and an overview of policy analysis processes in the introductory chapter, in chapter 2 I discuss a debated issue of policymaking, the choice of the social welfare function. I contribute to this debate by proposing an original methodological contribution based on the analysis of the quantitative relationship among different social welfare functional forms commonly used by policy analysts. In chapter 3 I then discuss a behavioral policy to contrast indirect tax evasion based on the use of lotteries. I show that the predictions of my model based on non-expected utility are consistent with observed, and so far unexplained, empirical evidence of the policy success. Finally, in chapter 4 I investigate by mean of a laboratory experiment the effects of social influence on the individual likelihood to engage in altruistic punishment. I show that bystanders’ decision to engage in punishment is influenced by the punishment behavior of their peers and I suggest ways to enact behavioral policies that exploit this finding.

Tribalism as a Minimax-Regret Strategy: Evidence from Voting in the 2007 Kenyan Elections

Although many studies find that voting in Africa approximates an ethnic census in that voting is primarily along ethnic lines, hardly any of the studies have sought to explain ethnic voting following a rational choice framework. Using data of voter opinions from a survey conducted two weeks before the December 2007 Kenyan elections, we find that the expected benefits associated with a win by each of the presidential candidates varied significantly across voters from different ethnic groups. We hypothesize that decision to participate in the elections was influenced by the expected benefits as per the minimax-regret voting model. We test the predictions of this model using data of voter turnout in the December 2007 elections and find that turnout across ethnic groups varied systematically with expected benefits. The results suggest that individuals participated in the elections primarily to avoid the maximum regret should a candidate from another ethnic group win. The results therefore offer credence to the minimax regret model as proposed by Ferejohn and Fiorina (1974) and refute the Downsian expected utility model.

Análisis empírico del tráfico en las autopistas de peaje radiales 3 y 5 de Madrid

El propósito de la presente investigación es determinar si, a través del estudio y análisis de los estudios de tráfico en autopistas de peaje, se pueden determinar las razones de los incumplimientos en las previsiones de estos estudios. La metodología se basa en un análisis empírico ex- post facto de los estudios de tráfico contenidos en los anteproyectos de las autopistas Radial 3 y Radial 5 y los datos realmente verificados. Tras una introducción para presentar las principales características de las autopistas de peaje, se realiza una revisión de la bibliografía sobre el cumplimiento de las previsiones de tráfico. Lo anterior permite establecer una serie de aspectos que pueden contribuir a estos incumplimientos, así como una serie de medidas encontradas para mejorar las futuras previsiones. Ya en el núcleo fundamental de la investigación, esta se centra en el análisis del cumplimiento de las previsiones de tráfico contenidas en los anteproyectos de la Radial 3 y Radial 5. Se realiza un análisis crítico de la metodología adoptada, así como de las variables e hipótesis realizadas. Tras este primer análisis, se profundiza en la fase de asignación de los estudios. Siempre con base a los tráficos reales y para el año 2006, se cuantifica el efecto en los incumplimientos, por un lado de las variables utilizadas, y por otro, del propio método ó curva de asignación. Finalmente, y con base en los hallazgos anteriores, se determinan una serie de limitaciones en el método de asignación de tráficos entre recorridos alternativos para el caso de entornos urbanos usado. El planteamiento con base a las teorías del agente racional y maximización de la utilidad esperada es criticado desde la perspectiva de la teoría de decisión bajo condiciones de riesgo planteada por Kahneman y Tversky. Para superar las limitaciones anteriores, se propone una nueva curva de asignación semi empírica que relaciona la proporción del tráfico que circula por la autopista de peaje con la velocidad media en la autovía libre alternativa. ABSTRACT The aim of this research is to confirm whether the forensic analysis of the traffic forecast studies for tolled highways may bring to light the reasons behind the lack of accuracy. The methodology used on this research is empirical and is based on the ex –post facto analysis of the real traffic numbers compared to the forecasted for the tolled highways Radial 3 and Radial 5. Firstly the main features of tolled highways are presented as an introductory chapter. Secondly a broad bibliographic search is presented, this is done from a global perspective and from the Spanish perspective too. From this review, a list of the main causes behind the systematic inaccuracy together with measures to improve future traffic forecast exercises are shown. In what we could consider as the core of the research, it focuses on the ratios of actual / forecast traffic for the tolled highways Radial 3 y Radial 5 in Madrid outskirts. From a critical perspective, the methodology and inputs used in the traffic studies are analysed. In a further step, the trip assignment stage is scrutinised to quantify the influence of the inputs and the assignment model itself in the accuracy of the traffic studies. This exercise is bases on the year 2006. Finally, the assignment model used is criticised for its application in tolled urban highways. The assumptions behind the model, rational agent and expected utility maximization theories, are questioned under the theories presented by Kahneman and Tversky (Prospect Theory). To overcome these assignment model limitations, the author presents a semi empiric new diversion curve. This curve links the traffic proportion using the tolled highway and the average speed in the toll free alternative highway.

Assessment of irrigators’ preferences for different water supply risk management tools: option contract and insurance.

Irrigators face the risk of not having enough water to meet their crops’ demand. There are different mechanisms to cope with this risk, including water markets (option contracts) or insurance. A farmer will purchase them when the expected utility change derived from the tool is positive. This paper presents a theoretical assessment of the farmer’s expected utility under two different option contracts, a drought insurance and a combination of an option contract and the insurance. We analyze the conditions that determine farmer’s reference for one instrument or the other and perform a numerical application that is relevant for a Spanish region.

A group decision-making methodology with incomplete individual beliefs applied to e-Democracy

We consider the situation where there are several alternatives for investing a quantity of money to achieve a set of objectives. The choice of which alternative to apply depends on how citizens and political representatives perceive that such objectives should be achieved. All citizens with the right to vote can express their preferences in the decision-making process. These preferences may be incomplete. Political representatives represent the citizens who have not taken part in the decision-making process. The weight corresponding to political representatives depends on the number of citizens that have intervened in the decision-making process. The methodology we propose needs the participants to specify for each alternative how they rate the different attributes and the relative importance of attributes. On the basis of this information an expected utility interval is output for each alternative. To do this, an evidential reasoning approach is applied. This approach improves the insightfulness and rationality of the decision-making process using a belief decision matrix for problem modeling and the Dempster?Shafer theory of evidence for attribute aggregation. Finally, we propose using the distances of each expected utility interval from the maximum and the minimum utilities to rank the alternative set. The basic idea is that an alternative is ranked first if its distance to the maximum utility is the smallest, and its distance to the minimum utility is the greatest. If only one of these conditions is satisfied, a distance ratio is then used.

Strategic Voting in Proportional Systems: The Case of Finland. IHS Political Science Series No. 138, September 2014

Voters try to avoid wasting their votes even in PR systems. In this paper we make a case that this type of strategic voting can be observed and predicted even in PR systems. Contrary to the literature we do not see weak institutional incentive structures as indicative of a hopeless endeavor for studying strategic voting. The crucial question for strategic voting is how institutional incentives constrain an individual’s decision-making process. Based on expected utility maximization we put forward a micro-logic of an individual’s expectation formation process driven by institutional and dispositional incentives. All well-known institutional incentives to vote strategically that get channelled through the district magnitude are moderated by dispositional factors in order to become relevant for voting decisions. Employing data from Finland – because of its electoral system a particularly hard testing ground - we find considerable evidence for observable implications of our theory.

Two envelope problems and the roles of ignorance

Four variations on Two Envelope Paradox are stated and compared. The variations are employed to provide a diagnosis and an explanation of what has gone awry in the paradoxical modeling of the decision problem that the paradox poses. The canonical formulation of the paradox underdescribes the ways in which one envelope can have twice the amount that is in the other. Some ways one envelope can have twice the amount that is in the other make it rational to prefer the envelope that was originally rejected. Some do not, and it is a mistake to treat them alike. The nature of the mistake is diagnosed by the different roles that rigid designators and definite descriptions play in unproblematic and in untoward formulations of decision tables that are employed in setting out the decision problem that gives rise to the paradox. The decision maker’s knowledge or ignorance of how one envelope came to have twice the amount that is in the other determines which of the different ways of modeling his decision problem is correct. Under this diagnosis, the paradoxical modeling of the Two Envelope problem is incoherent.

Equity weights in the allocation of health care: the rank-dependent QALY model

This paper introduces the rank-dependent quality-adjusted life-years (QALY) model, a new method to aggregate QALYs in economic evaluations of health care. The rank-dependent QALY model permits the formalization of influential concepts of equity in the allocation of health care, such as the fair innings approach, and it includes as special cases many of the social welfare functions that have been proposed in the literature. An important advantage of the rank-dependent QALY model is that it offers a straightforward procedure to estimate equity weights for QALYs. We characterize the rank-dependent QALY model and argue that its central condition has normative appeal. (C) 2003 Elsevier B.V. All rights reserved.

Increasing uncertainty: A definition

We present a definition of increasing uncertainty, in which an elementary increase in the uncertainty of any act corresponds to the addition of an 'elementary bet' that increases consumption by a fixed amount in (relatively) 'good' states and decreases consumption by a fixed (and possibly different) amount in (relatively) 'bad' states. This definition naturally gives rise to a dual definition of comparative aversion to uncertainty. We characterize this definition for a popular class of generalized models of choice under uncertainty.

Supermodularity and risk aversion

In this paper, we consider the relationship between supermodularity and risk aversion. We show that supermodularity of the certainty equivalent implies that the certainty equivalent of any random variable is less than its mean. We also derive conditions under which supermodularity of the certainty equivalent is equivalent to aversion to mean-preserving spreads in the sense of Rothschild and Stiglitz. (c) 2006 Elsevier B.V. All rights reserved.

Beszámoló a spudm 25 konferenciáról

1969 óta kétévente rendezik meg a Subjective Probability, Utility, and Decision Making (SPUDM) elnevezésű konferenciát, amelynek 2015-ben a Döntéselmélet Tanszék szervezésében a Budapesti Corvinus Egyetem adott otthont. A konferencia tudományos tanácsának tagjai Adreas Glöckner, Ana Franco-Watkins, Ido Erev, Aczél Balázs és Szántó Richárd voltak, utóbbi egyben a konferencia szervezőbizottságának elnöki tisztét is betöltötte. A konferencia a European Association for Decision Making közgyűlésének is helyszíne egyben, a résztvevők itt határozzák meg a szervezet rövid távú céljait, döntenek a költségvetés felhasználásáról, és itt jelentik be a megválasztott, soron következő elnököt is, aki ebben az évben a Göttingeni Egyetem professzora, Andreas Glöckner lett. A rendezvényen mintegy 340-en vettek részt, főként Európából, de érkeztek kutatók Amerikából, Ázsiából és Ausztráliából is. A konferencia keretében megrendezett 40 szekcióban és 8 önálló szimpóziumon az ítéletalkotással és a döntéshozatallal (judgment and decision making) kapcsolatos szinte minden kutatási terület megjelent.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

Risk Preferences and the Role of Emotions

There is a large volume of research showing that emotions have relevant effects on decision-making. We contribute to this literature by experimentally investigating the impact of four specific emotional states - joviality, sadness, fear, and anger - on risk attitudes. In order to do so, we fit two models of behavior under risk: the Expected Utility model (EU) and the Rank Dependent Expected Utility model (RDEU), assuming several functional forms of the weighting function. Our results indicate that all emotional states mitigate risk aversion. Furthermore, we show that there are some differences across gender and participants' experience in laboratory experiments.