On the closed-form approximation of short-time random strike options

In this paper we propose a general technique to develop first and second order closed-form approximation formulas for short-time options withrandom strikes. Our method is based on Malliavin calculus techniques andallows us to obtain simple closed-form approximation formulas dependingon the derivative operator. The numerical analysis shows that these formulas are extremely accurate and improve some previous approaches ontwo-assets and three-assets spread options as Kirk's formula or the decomposition mehod presented in Alòs, Eydeland and Laurence (2011).

Constant coefficient tests for random coefficient regression

Random coefficient regression models have been applied in differentfields and they constitute a unifying setup for many statisticalproblems. The nonparametric study of this model started with Beranand Hall (1992) and it has become a fruitful framework. In thispaper we propose and study statistics for testing a basic hypothesisconcerning this model: the constancy of coefficients. The asymptoticbehavior of the statistics is investigated and bootstrapapproximations are used in order to determine the critical values ofthe test statistics. A simulation study illustrates the performanceof the proposals.

General preferences for consumption goods in the random matching model of commodity money

This paper generalizes the original random matching model of money byKiyotaki and Wright (1989) (KW) in two aspects: first, the economy ischaracterized by an arbitrary distribution of agents who specialize in producing aparticular consumption good; and second, these agents have preferences suchthat they want to consume any good with some probability. The resultsdepend crucially on the size of the fraction of producers of each goodand the probability with which different agents want to consume eachgood. KW and other related models are shown to be parameterizations ofthis more general one.

Is confidence in decisions related to feedback? Evidence-and lack of evidence-from random samples of real-world managerial behavior?

Confidence in decision making is an important dimension of managerialbehavior. However, what is the relation between confidence, on the onehand, and the fact of receiving or expecting to receive feedback ondecisions taken, on the other hand? To explore this and related issuesin the context of everyday decision making, use was made of the ESM(Experience Sampling Method) to sample decisions taken by undergraduatesand business executives. For several days, participants received 4 or 5SMS messages daily (on their mobile telephones) at random moments at whichpoint they completed brief questionnaires about their current decisionmaking activities. Issues considered here include differences between thetypes of decisions faced by the two groups, their structure, feedback(received and expected), and confidence in decisions taken as well as inthe validity of feedback. No relation was found between confidence indecisions and whether participants received or expected to receivefeedback on those decisions. In addition, although participants areclearly aware that feedback can provide both confirming and disconfirming evidence, their ability to specify appropriatefeedback is imperfect. Finally, difficulties experienced inusing the ESM are discussed as are possibilities for further researchusing this methodology.

On the performance of small-area estimators: Fixed vs. random area parameters

Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.

Psychological pressure in competitive environments: Evidence from a randomized natural experiment

Much like cognitive abilities, emotional skills can have major effects on performance and economic outcomes. This paper studies the behavior of professionalsubjects involved in a dynamic competition in their own natural environment. Thesetting is a penalty shoot-out in soccer where two teams compete in a tournamentframework taking turns in a sequence of five penalty kicks each. As the kicking order is determined by the random outcome of a coin flip, the treatment and control groups are determined via explicit randomization. Therefore, absent any psychological effects, both teams should have the same probability of winning regardless of the kicking order. Yet, we find a systematic first-kicker advantage. Using data on 2,731 penalty kicks from 262 shoot-outs for a three decade period, we find that teams kicking first win the penalty shoot-out 60.5% of the time. A dynamic panel data analysis shows that the psychological mechanism underlying this result arises from the asymmetry in the partial score. As most kicks are scored, kicking first typically means having the opportunity to lead in the partial score, whereas kicking second typically means lagging in the score and having the opportunity to, at most, get even. Having a worse prospect than the opponent hinders subjects' performance.Further, we also find that professionals are self-aware of their own psychological effects. When a recent change in regulations gives winners of the coin toss the chance to choose the kicking order, they rationally react to it by systematically choosing to kick first. A survey of professional players reveals that when asked to explain why they prefer to kick first, they precisely identify the psychological mechanism for which we find empirical support in the data: they want to lead in the score inorder to put pressure on the opponent.

Fixed and random effects in Classical and Bayesian regression

This paper proposes a common and tractable framework for analyzingdifferent definitions of fixed and random effects in a contant-slopevariable-intercept model. It is shown that, regardless of whethereffects (i) are treated as parameters or as an error term, (ii) areestimated in different stages of a hierarchical model, or whether (iii)correlation between effects and regressors is allowed, when the sameinformation on effects is introduced into all estimation methods, theresulting slope estimator is also the same across methods. If differentmethods produce different results, it is ultimately because differentinformation is being used for each methods.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

Comparing Random-based and k-Anonymity-Based Algorithms for Graph Anonymization

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.

Adéquation et choix de modele de marche aléatoire des trajectoires des navires de peches

L'étude du mouvement des organismes est essentiel pour la compréhension du fonctionnement des écosystèmes. Dans le cas des écosystèmes marins exploités, cela amène à s'intéresser aux stratégies spatiales des pêcheurs. L'une des approches les plus utilisées pour la modélisation du mouvement des prédateurs supé- rieurs est la marche aléatoire de Lévy. Une marche aléatoire est un modèle mathématique composé par des déplacements aléatoires. Dans le cas de Lévy, les longueurs des déplacements suivent une loi stable de Lévy. Dans ce cas également, les longueurs, lorsqu'elles tendent vers l'in ni (in praxy lorsqu'elles sont grandes, grandes par rapport à la médiane ou au troisième quartile par exemple), suivent une loi puissance caractéristique du type de marche aléatoire de Lévy (Cauchy, Brownien ou strictement Lévy). Dans la pratique, outre que cette propriété est utilisée de façon réciproque sans fondement théorique, les queues de distribution, notion par ailleurs imprécise, sont modélisée par des lois puissances sans que soient discutées la sensibilité des résultats à la dé nition de la queue de distribution, et la pertinence des tests d'ajustement et des critères de choix de modèle. Dans ce travail portant sur les déplacements observés de trois bateaux de pêche à l'anchois du Pérou, plusieurs modèles de queues de distribution (log-normal, exponentiel, exponentiel tronqué, puissance et puissance tronqué) ont été comparés ainsi que deux dé nitions possible de queues de distribution (de la médiane à l'in ni ou du troisième quartile à l'in ni). Au plan des critères et tests statistiques utilisés, les lois tronquées (exponentielle et puissance) sont apparues les meilleures. Elles intègrent en outre le fait que, dans la pratique, les bateaux ne dépassent pas une certaine limite de longueur de déplacement. Le choix de modèle est apparu sensible au choix du début de la queue de distribution : pour un même bateau, le choix d'un modèle tronqué ou l'autre dépend de l'intervalle des valeurs de la variable sur lequel le modèle est ajusté. Pour nir, nous discutons les implications en écologie des résultats de ce travail.