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Making good predictions is a critical feature of decision making in situations such as investing and predicting the spread of diseases. Past literature indicates that people use recent and longer-term trends while making predictions. Nonetheless, less is known about how these factors affect how well people make predictions and the timing of their predictions. Further, identifying factors underlying predictive judgments could be an important behavioral factor in manic-depression, anxiety, substance use, age effects, and understanding how income inequality affects decision making. To understand how people make predictive judgments, we conducted two experiments. In Experiment 1, we used an investment task where participants had to predict the future price of a stock based on an exponential trend of information. We found that participants generally had lower earnings with steeper exponential trends (e.g. slower starting) and delayed their decisions to sell bad stocks with steeper trends. We extended these results in Experiment 2 with an updated task with exponential and inverse exponential trends. Overall, our results suggested that people delayed longer to make their prediction with slower starting exponential trends compared to faster starting inverse exponential trends and delayed their predictions longer with more linear trends compared to more trend trends. When deciding how long to explore, participants incorporated both the average trend and recent trend, though they shifted their responses depending on the overall functional form. These choices were ultimately biased to be optimistic or pessimistic based on whether the trend started fast or slow, respectively. Additionally, we found that participants who self-reported taking more gambling risk and depressive symptoms had a greater tendency to stay with faster starting trends and to leave with slower starting trends, suggesting they were even more optimistic given initially fast starting trends. Results pointing to an optimism bias based on the trend in information available to the participant could suggest that an aspect of sunk-cost fallacy is due to errors in predicting the likelihood of future success based on past information. Our findings help understand the dynamics of how people make predictive judgments over time and could inform future research into the mechanisms people use for prospective decision making. Additionally, future research and potential interventions could account for biases in how people perceive past trends to minimize harmful effects of sunk-cost fallacy when making predictions. / Psychology

[pt] Esta dissertação tem como objetivo testar a possibilidade de obtenção de retornos anormais de capital entre jan/1997 e jul/2007 para o mercado acionário brasileiro no curtíssimo prazo. Investigou-se, para tanto, a hipótese de reversão à média. Estratégias contrárias com carteiras compradas em ações perdedoras e vendidas em ganhadoras foram montadas e testadas nos períodos subseqüentes. Evidências foram encontradas a favor da reversão e, consequentemente, a favor da possibilidade de retornos anormais. Depois de verificada a existência de tais retornos, o trabalho ainda corrigiu o risco sistemático da carteira, por meio do alfa de Jensen. Os retornos anormais, de uma forma geral, continuam a existir após incorporar-se o risco ao modelo. / [en] The goal of this study is to test the existence of abnormal stock returns in the Brazilian stock market in the very short run for the period of jan/1997 to jul/2007. The main hypothesis in focus is the mean reversion of returns. Contrarian strategies were used with portfolios built by winner and looser stocks to test the abnormal returns in subsequent periods. There is evidence in favor of the reversion and, consequently, in favor of the possibility of abnormal returns. After verified the existence of these returns, this study examines if they still remain after systematic risk correction (Alfa of Jensen). The abnormal returns still remain after taking into account the systematic risk.

[pt] Esta dissertação procura estudar os critérios de análise de investimentos baseados na metodologia do Valor Presente Líquido e de Opções Reais seguindo o processo estocástico de Reversão à Média fazendo uso de um caso prático na indústria de petróleo. O estudo de caso é a análise de viabilidade do desenvolvimento de um campo de petróleo onde as etapas de pesquisa e estudos já foram realizadas e que possue 3 alternativas de desenvolvimento à escolher. A partir deste estudo de caso será possível comparar através de uma ferramenta gerencial chamada de back-testing as análises de viabilidade realizadas. A dissertação tem como objetivo confirmar, com os resultados obtidos no back- testing, a geração de valor na utilização da teoria de opções reais que através da sua metodologia busca maximizar o valor do projeto pela inclusão de flexibilidades gerenciais neste caso uma opção de esperar até 2 anos. / [en] This dissertation compares the criteria of investments analysis based on the methodology of the Discounted Cash Flow and of Real Options Models following a Mean Reversion stochastic process making use of a real case in the oil industry. This case study is about the viability of the development of an oil field where all the stages of research have already been carried out, with 3 alternatives of development to choose. From the results of this case study it will be possible to compare with the aid of a managerial tool called back- testing the Discounted Cash Flow with the Real Option Method. The dissertation has the goal to confirm, with the backtesting results, the generation of value created by the use of real options theory which maximizes the value of the project with the addition of managerial flexibilities represented by an option to wait up to 2 years.

該篇文章中提出一個新的交易方式：條件機率交易模型conditional probability trading model。 這個模型應用了三個主要的基本假設： （1）總體經濟因子和股價指數間有相關性。因此可以透過總經指標來衡量股市應有的合理價位。 （2）股價具有回歸均數的特質。亦即股價一旦過度偏離基本價值，理論上會傾向回復到基本價值之上。 （3）股價指數相對於基本價值線的距離，將會影響偏態係數的大小。 根據以上三個性質，試圖建構出一個能夠捕捉股價指數變動的模型，並用以進行交易模擬，觀察其是否能獲取正報酬。 / The trading strategy, conditional probability trading model(CPTM), is presented in this article. We’ve tried to develop a new trading strategy which is built up by the combination of the properties which includes 1)the relationship between macroeconomic factors and stock market. 2) mean reversion and 3) conditional skewness. The conclusion implies that we may successfully find out a method to combine fundamental and technical analysis, if this method is proved effective. The former hypothesis is assumed that the different level of stock market index may stand for a specific condition of macroeconomic environment. Meanwhile, a better fundamental economic condition could reasonably create a higher stock market index, vice versa. By observing the fundamental value, we can figure out the market ,currently, is over-priced or under-priced. Next, we construct a trading model which is graphed like Bollinger bands. According to specific rules, it provides buying or selling signals. In some special situations, it can also forecast the turning points of the stock market precisely. 3) Skewness also plays a very important role in CPTM, because one of the hypothesis assumes that overpriced /underpriced stock market probably accompanies with left-skewed / right-skewed distribution of daily stock return. The hypothesis of dynamically adjusted skewness implies the concept that over-priced/under-priced stock market has higher propensity to decline/rise. To judge the trading timing is the core value in this model.

NJ, Rutgers State Univ. of New Jersey, Diss.--Newark, 2005. / Kopie, ersch. im Verl. UMI, Ann Arbor, Mich. - Enth. 2 Beitr.

Submitted by Cristina Tessari (tinatessari@gmail.com) on 2016-06-09T13:51:42Z No. of bitstreams: 1 DissertationEPGE_CristinaTessari2016.pdf: 1264081 bytes, checksum: 14e65157457bfe8deea5353bb192a0af (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-06-29T14:03:25Z (GMT) No. of bitstreams: 1 DissertationEPGE_CristinaTessari2016.pdf: 1264081 bytes, checksum: 14e65157457bfe8deea5353bb192a0af (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-06-29T14:06:59Z (GMT) No. of bitstreams: 1 DissertationEPGE_CristinaTessari2016.pdf: 1264081 bytes, checksum: 14e65157457bfe8deea5353bb192a0af (MD5) / Made available in DSpace on 2016-06-29T14:07:23Z (GMT). No. of bitstreams: 1 DissertationEPGE_CristinaTessari2016.pdf: 1264081 bytes, checksum: 14e65157457bfe8deea5353bb192a0af (MD5) Previous issue date: 2016-03-22 / We use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month. / In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.

Submitted by Jerckns Cruz (jerckns@hotmail.com) on 2009-12-11T03:37:02Z No. of bitstreams: 1 tese_Jerckns Cruz.pdf: 208471 bytes, checksum: 6be3209c95745116ae6d8db9f6c2ea1b (MD5) / Approved for entry into archive by Gisele Gammaro(gisele.gammaro@fgv.br) on 2009-12-14T15:03:00Z (GMT) No. of bitstreams: 1 tese_Jerckns Cruz.pdf: 208471 bytes, checksum: 6be3209c95745116ae6d8db9f6c2ea1b (MD5) / Made available in DSpace on 2009-12-14T15:03:09Z (GMT). No. of bitstreams: 1 tese_Jerckns Cruz.pdf: 208471 bytes, checksum: 6be3209c95745116ae6d8db9f6c2ea1b (MD5) / The theory of Behavioral Finance emerges as a new approach to the financial market, arguing that some events are better explained if the restrictions of investor’s rationality are relaxed. Concepts of psychology and limits to arbitrage are used to model market inefficiencies, bringing up the idea that market can be systematically beaten. This paper proposes a new model, of simple implementation, to explore the abnormal returns from the momentum and mean reversion strategies simultaneously. The idea of a long term momentum effect stronger than the short term effect is introduced, but the empirical results show that the Brazilian market dynamics reject this concept. The model fails to achieve riskless positive returns. / A teoria de Finanças Comportamentais surge como uma nova abordagem ao mercado financeiro, argumentando que alguns eventos podem ser mais bem explicados se as restrições da racionalidade do investidor são relaxadas. Conceitos de psicologia e limites à arbitragem são usados para modelar as ineficiências, criando a idéia de ser possível ganhar sistematicamente do mercado. Este trabalho propõe um novo modelo, simplista na sua implementação, para aproveitar os retornos anormais advindos de estratégias de momentum e reversão à média simultaneamente. A idéia de um efeito momentum de longo prazo mais forte que o de curto prazo é introduzida, mas os resultados empíricos mostram que a dinâmica do mercado brasileiro rejeita este conceito. O modelo falha em conseguir retornos positivos e livres de risco.

In this thesis, we consider the pricing problem of an American put option. We introduce a new market model for the evolution of the underlying asset price. Our model adds a new parameter to the well known Heston model. Hence we name our model the extended Heston model. To solve the American put pricing problem we adapt the idea developed by Fouque et al. (2000) to derive the asymptotic formula. We then connect the idea developed by Medvedev and Scaillet (2010) to provide an asymptotic solution for the leading order term P0. We do numerical analysis to gain insight into the accuracy and validity of our asymptotic approximation formula.

The first chapter investigates how corporate governance influences firms’ capital structure behavior. Based on the premise that costs associated with deviations from the target capital structure are positively correlated to the extent of deviation, we hypothesize that the initial deviation from the target will be shorter for a firm with good corporate governance than for a firm with poor corporate governance. We also hypothesize that the former group will employ a higher speed of adjustment towards target than the latter group due primarily to the following reasons. First, a firm with well-placed governance system will adjust at a faster rate because longer it stays deviated, the higher the loss of value it faces. Second, firms with better governance structures enjoy lower adjustment costs. We develop three sets of measures for the quality of corporate governance and analyze how they influence a firm’s rebalancing behavior in presence of relevant control variables. Our results are consistent with the hypotheses. The second chapter explores investors’ reactions to new information on REITs and non-REITs option markets. The real estate market can be fairly volatile; what remains unclear is whether price changes are excessively volatile relative to fundamentals. This study attempts to examine the latter by using the methodology based on Stein (1989), which utilizes option data. The advantage of using option data rather than stock data to assess the reactions to information is that option valuation is not affected by changes in risk premium. Under volatility mean reversion, the changes in implied volatilities of long-term options should be less than those of short-term options. If not, an excessive reaction is suggested. Specifically, the study compares the changes in implied volatilities of options on REITs and non-REITs. Because real estate transactions typically involve a great degree of leverage, reactions can be greater for REITs than for non-REITs; on the other hand, there are several reasons that REITs are subject to potentially a lower degree of excessive reactions. Empirical results indicate that the reactions to information are stronger in non-REITs than in REITs. Moreover, we find that down markets are associated with stronger reactions, which we argue might be due to a leverage effect.