This study is set out to explore how cognitive biases, gambler’s fallacy and hot hand effect, exert an effect on individual crop insurance purchase decision. A laboratory experiment comprised of two separate games was used to establish an insurance purchase environment to induce individual’s behavior. The gambler’s fallacy and hot hand effect failed to be found in the experiment. But the subjects’ perceived probability of loss plays a significant role in determine their purchase decisions—the higher probability they predicted, the more likely to buy insurance they were. It is also fascinating to find that the longer the exposure to random risks the subjects had, the more willing to engage in insurance protection they were.

This thesis examines the response of a representative agent investor to sequences (streaks) of quarterly earnings surprises over a period of twelve quarters using the United States S&P500 constituent companies sample frame in the years 1991 to 2006. This examination follows the predictive performance of the representative agent model of Rabin (2002b) [Inference by believers in the law of small numbers. The Quarterly Journal of Economics. 117(3).p.775 816] and Barberis, Shleifer, and Vishny (1998) [A model of investor sentiment. Journal of Financial Economics. 49. p.307 343] for an investor who might be under the influence of the law of small numbers, or another closely related cognitive bias known as the gambler s fallacy. Chapters 4 and 5 present two related empirical studies on this broad theme. In chapter 4, for successive sequences of annualised quarterly earnings changes over a twelve-quarter horizon of quarterly earnings increases or falls, I ask whether the models can capture the likelihood of reversion. Secondly, I ask, what is the representative investor s response to observed sequences of quarterly earnings changes for my S&P500 constituent sample companies? I find a far greater frequency of extreme persistent quarterly earnings rises (of nine quarters and more) than falls and hence a more muted reaction to their occurrence from the market. Extreme cases of persistent quarterly earnings falls are far less common than extreme rises and are more salient in their impact on stock prices. I find evidence suggesting that information discreteness; that is the frequency with which small information about stock value filters into the market is one of the factors that foment earnings momentum in stocks. However, information discreteness does not subsume the impact of sequences of annualised quarterly earnings changes, or earnings streakiness as a strong candidate that drives earnings momentum in stock returns in my S&P500 constituent stock sample. Therefore, earnings streakiness and informational discreteness appear to have separate and additive effects in driving momentum in stock price. In chapter 5, the case for the informativeness of the streaks of earnings surprises is further strengthened. This is done by examining the explanatory power of streaks of earnings surprises in a shorter horizon of three days around the period when the effect of the nature of earnings news is most intense in the stock market. Even in shorter windows, investors in S&P500 companies seem to be influenced by the lengthening of negative and positive streaks of earnings surprises over the twelve quarters of quarterly earnings announcement I study here. This further supports my thesis that investors underreact to sequences of changes in their expectations about stock returns. This impact is further strengthened by high information uncertainties in streaks of positive earnings surprise. However, earnings streakiness is one discrete and separable element in the resolution of uncertainty around equity value for S&P 500 constituent companies. Most of the proxies for earnings surprise show this behaviour especially when market capitalisation, age and cash flow act as proxies of information uncertainty. The influence of the gambler s fallacy on the representative investor in the presence of information uncertainty becomes more pronounced when I examine increasing lengths of streaks of earnings surprises. The presence of post earnings announcement drift in my large capitalised S&P500 constituents sample firms confirms earnings momentum to be a pervasive phenomenon which cuts across different tiers of the stock markets including highly liquid stocks, followed by many analysts, which most large funds would hold.

O elemento central deste estudo é o problema de predição em seqüências de variáveis aleatórias binárias (0-1). Modelos são estudados para esse tipo de situação e então relacionados com a Falácia do Apostador - um famoso caso de estudo da Psicologia (também conhecida como Lei da Maturidade). Estudos estatísticos anteriores propõem tal modelagem sob a perspectiva bayesiana. Neles, tem-se a suposição de permutabilidade infinita e, como conseqüência, a maturidade é um comportamento inadmissível. Neste estudo, um novo modelo é apresentado, no qual a crença do apostador não é necessariamente uma falácia. Este é o modelo preditivista usual de população finita e, portanto, somente quantidades com significado operacional (parâmetros operacionais) são envolvidas. Uma classe de prioris para o parâmetro operacional que resulta em modelos não estendíveis é apresentada. Trata-se de uma classe de distribuições que definimos como mais estreitas que a Binomial. Maturidade é uma conseqüência da crença em prioris dessa classe. Apresenta-se ainda uma subclasse referente às distribuições mais estreitas de segunda ordem que a Binomial. Para prioris dessa subclasse tem-se taxa de falha preditiva crescente, que pode ser interpretado como o resultado mais extremo de maturidade. Os resultados deste estudo podem contribuir para o julgamento de quão razoável é a suposição de permutabilidade infinita em relação ao típico comportamento humano. Outra principal contribuição está associada ao estudo de condições de estendibilidade em processos binários. / We study the problem of prediction in sequences of binary random variables. Models are studied for this kind of situation and then considered vis-à-vis the Gambler\'s Fallacy - a famous case study in Psychology (also known as Law of Maturity). Previous statistical studies proposed such modeling under the bayesian perspective. In them there is the assumption of exchangeability and, as a result, maturity is a inadmissible behavior. In this study, a new model in which the Gambler\'s belief need not be a fallacy is presented. This one is the usual finite population model and, therefore, only operationally meaningful quantities (operational parameters) are involved. A class of prior distributions for the operational parameter which yield non-extendable models is presented. It is a class of distributions which we defined as tighter than the Binomial. Maturity is a consequence of the belief in the prior distributions of this class. Furthermore, a subclass which refers to the distributions that are second-order tighter than the Binomial is presented. For prior distributions of this subclass the predictive failure rate is increasing, which can be interpreted as the most extreme case of maturity. The results of this study may contribute on the judgment of how reasonable the assumption of infinite exchangeability is relative to typical human perception. Another major contribution is related to the study on extendibility conditions in binary processes.

O elemento central deste estudo é o problema de predição em seqüências de variáveis aleatórias binárias (0-1). Modelos são estudados para esse tipo de situação e então relacionados com a Falácia do Apostador - um famoso caso de estudo da Psicologia (também conhecida como Lei da Maturidade). Estudos estatísticos anteriores propõem tal modelagem sob a perspectiva bayesiana. Neles, tem-se a suposição de permutabilidade infinita e, como conseqüência, a maturidade é um comportamento inadmissível. Neste estudo, um novo modelo é apresentado, no qual a crença do apostador não é necessariamente uma falácia. Este é o modelo preditivista usual de população finita e, portanto, somente quantidades com significado operacional (parâmetros operacionais) são envolvidas. Uma classe de prioris para o parâmetro operacional que resulta em modelos não estendíveis é apresentada. Trata-se de uma classe de distribuições que definimos como mais estreitas que a Binomial. Maturidade é uma conseqüência da crença em prioris dessa classe. Apresenta-se ainda uma subclasse referente às distribuições mais estreitas de segunda ordem que a Binomial. Para prioris dessa subclasse tem-se taxa de falha preditiva crescente, que pode ser interpretado como o resultado mais extremo de maturidade. Os resultados deste estudo podem contribuir para o julgamento de quão razoável é a suposição de permutabilidade infinita em relação ao típico comportamento humano. Outra principal contribuição está associada ao estudo de condições de estendibilidade em processos binários. / We study the problem of prediction in sequences of binary random variables. Models are studied for this kind of situation and then considered vis-à-vis the Gambler\'s Fallacy - a famous case study in Psychology (also known as Law of Maturity). Previous statistical studies proposed such modeling under the bayesian perspective. In them there is the assumption of exchangeability and, as a result, maturity is a inadmissible behavior. In this study, a new model in which the Gambler\'s belief need not be a fallacy is presented. This one is the usual finite population model and, therefore, only operationally meaningful quantities (operational parameters) are involved. A class of prior distributions for the operational parameter which yield non-extendable models is presented. It is a class of distributions which we defined as tighter than the Binomial. Maturity is a consequence of the belief in the prior distributions of this class. Furthermore, a subclass which refers to the distributions that are second-order tighter than the Binomial is presented. For prior distributions of this subclass the predictive failure rate is increasing, which can be interpreted as the most extreme case of maturity. The results of this study may contribute on the judgment of how reasonable the assumption of infinite exchangeability is relative to typical human perception. Another major contribution is related to the study on extendibility conditions in binary processes.

Cette présentation examinera le degré de certitude qui peut être atteint dans le domaine scientifique. Le paradigme scientifique est composé de deux extrêmes; causalité et déterminisme d'un côté et probabilité et indéterminisme de l'autre. En faisant appel aux notions de Hume de la ressemblance et la contiguïté, on peut rejeter la causalité ou le hasard objectif comme étant sans fondement et non empirique. Le problème de l'induction et le sophisme du parieur proviennent d’une même source cognitif / heuristique. Hume décrit ces tendances mentales dans ses essais « Of Probability » et « Of the Idea of Necessary Connexion ». Une discussion sur la conception de la probabilité de Hume ainsi que d'autres interprétations de probabilité sera nécessaire. Même si la science glorifie et idéalise la causalité, la probabilité peut être comprise comme étant tout aussi cohérente. Une attitude probabiliste, même si elle est également non empirique, pourrait être plus avantageuse que le vieux paradigme de la causalité. / This presentation examines the degree of certainty which can be attained in science. The scientific paradigm is composed of two extremes; causality and determinism on one end and probability and indeterminism on the other. By appealing to Hume’s notions of resemblance and contiguity, we can dismiss any claim of objective causality or chance as being ungrounded for lack of an empirical basis. The problem of induction as well as the gambler’s fallacy stem from the same cognitive/heuristic source. Hume describes these mental tendencies in his essays ‘Of Probability’ and ‘Of the Idea of Necessary Connexion’. This will necessitate a discussion of Hume’s notion of probability, as well as other interpretations of probability. While science has glorified and romanticized causality, probability can be understood as being just as consistent. While a probabilistic stance is as non-empirical as a causal stance, it will be remarked that we may benefit from a paradigmatic switch to probabilism.

No description available.

Cette présentation examinera le degré de certitude qui peut être atteint dans le domaine scientifique. Le paradigme scientifique est composé de deux extrêmes; causalité et déterminisme d'un côté et probabilité et indéterminisme de l'autre. En faisant appel aux notions de Hume de la ressemblance et la contiguïté, on peut rejeter la causalité ou le hasard objectif comme étant sans fondement et non empirique. Le problème de l'induction et le sophisme du parieur proviennent d’une même source cognitif / heuristique. Hume décrit ces tendances mentales dans ses essais « Of Probability » et « Of the Idea of Necessary Connexion ». Une discussion sur la conception de la probabilité de Hume ainsi que d'autres interprétations de probabilité sera nécessaire. Même si la science glorifie et idéalise la causalité, la probabilité peut être comprise comme étant tout aussi cohérente. Une attitude probabiliste, même si elle est également non empirique, pourrait être plus avantageuse que le vieux paradigme de la causalité. / This presentation examines the degree of certainty which can be attained in science. The scientific paradigm is composed of two extremes; causality and determinism on one end and probability and indeterminism on the other. By appealing to Hume’s notions of resemblance and contiguity, we can dismiss any claim of objective causality or chance as being ungrounded for lack of an empirical basis. The problem of induction as well as the gambler’s fallacy stem from the same cognitive/heuristic source. Hume describes these mental tendencies in his essays ‘Of Probability’ and ‘Of the Idea of Necessary Connexion’. This will necessitate a discussion of Hume’s notion of probability, as well as other interpretations of probability. While science has glorified and romanticized causality, probability can be understood as being just as consistent. While a probabilistic stance is as non-empirical as a causal stance, it will be remarked that we may benefit from a paradigmatic switch to probabilism.