Modelos estocásticos com heterocedasticidade: Uma abordagem Bayesiana para os retornos do Ibovespa

Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student's t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters' space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student's t distribution adjusted better to the data.

Distribuição estatística de um indexo econômico em mercado emergente - Bolsa de valores de São Paulo (IBOVESPA)

Pós-graduação em Física - IGCE

Estratégia de Investimento baseada em padrões descobertos por mineração de dados em séries históricas de preços diários do Indice IBOVESPA e das ações da PETROBRAS-PN (PETR4.SA)

With the increase of stakeholders and consequently increase of amount of nancial transaction the study of news investment strategies in the stock market with data mining techniques has been the target of important researches. It allows that great historical data base to be processed and analysed looking for pattern that can be used to take a decision in investments. With the idea of getting pro t more than the real indexs' gain, we propose a strategy method of transactions using rules built by algorithm classi cation. For that, diary historical data of Ibovespa index and Petrobras stocks are organized and processed to nding the most important attribute that act decisively when taking a investment decision.To test the accuracy of proposed rules, a non real portfolio management is created, showing the decisions' performance over the real index and stocks' performance. Following the proposed rules, the results show that the strategy of investment give me back a high return that Stock market's return. The exclusive characteristics of algorithms maximize the gain inside the analysed time allowing to determine the techniques' return and the number of the days necessary to double the initial investment. The best classi er applied on the time series and its use on the propose investments strategy will demand 104 days to double the initial capital

Underlying dynamics of typical fluctuations of an emerging market price index: the Heston model from minutes to months

We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics. (c) 2005 Elsevier B.V. All rights reserved.

Generalizações do movimento browniano e suas aplicações à física e a finanças

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Esforço de modernidade do mercado de capitais no Brasil: o novo mercado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimativa do custo médio ponderado de capital em produtos agrícolas

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Mercado de ações brasileiro: uma investigação empírica sobre suas relações de longo prazo e de precedência temporal pré-crise de 2008

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Suposição de normalidade e gestão de risco: uma aplicação do var paramétrico via teste de aderência

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo e análise estatística no mercado de ações brasileiro

The objective of this paper is to verify and analyze the existence in Brazil of stylized facts observed in financial time series: volatility clustering, probability distributions with fat tails, the presence of long run memory in absolute return time series, absence of linear return autocorrelation, gain/loss asymmetry, aggregative gaussianity, slow absolute return autocorrelation decay, trading volume/volatility correlation and leverage effect. We analyzed intraday prices for 10 stocks traded at the BM&FBovespa, responsible for 52.1% of the Ibovespa portfolio on Sept. 01, 2009. The data analysis confirms the stylized facts, whose behavior is consistent with what is observed in international markets.