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Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2012.tde-28042012-114138
Document
Author
Full name
Akira Arice de Moura Galvão Uematsu
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2012
Supervisor
Committee
Iambartsev, Anatoli (President)
Belitsky, Vladimir
Soukhov, Iouri Mikhailovich
Title in Portuguese
Algoritmos de negociação com dados de alta frequência
Keywords in Portuguese
algoritmos de negociação.
bolsa de valores
mercado de alta frequência
processos de Markov
protocolo FIX
Abstract in Portuguese
Em nosso trabalho analisamos os dados provenientes da BM&F Bovespa, a bolsa de valores de São Paulo, no período de janeiro de 2011, referentes aos índices: BOVESPA (IND), o mini índice BOVESPA (WIN) e a taxa de câmbio (DOL). Estes dados são de alta frequência e representam vários aspectos da dinâmica das negociações. No conjunto de valores encontram-se horários e datas dos negócios, preços, volumes oferecidos e outras características da negociação. A primeira etapa da tese foi extrair as informações necessárias para análises a partir de um arquivo em protocolo FIX, foi desenvolvido um programa em R com essa finalidade. Em seguida, estudamos o carácter da dependência temporal nos dados, testando as propriedades de Markov de um comprimento de memória fixa e variável. Os resultados da aplicação mostram uma grande variabilidade no caráter de dependência, o que requer uma análise mais aprofundada. Acreditamos que esse trabalho seja de muita importância em futuros estudos acadêmicos. Em particular, a parte do carácter específico do protocolo FIX utilizado pela Bovespa. Este era um obstáculo em uma série de estudos acadêmicos, o que era, obviamente, indesejável, pois a Bovespa é um dos maiores mercados comerciais do mundo financeiro moderno.
Title in English
Algorithmic Trading with high frequency data
Keywords in English
FIX protocol
high frequency market
Markov process and Algorithmic trading.
Stock exchange
Abstract in English
In our work we analyzed data from BM&F Bovespa, the stock exchange in São Paulo. The dataset refers to the month January 2011 and is related to BOVESPA index (IND), mini BOVESPA index (WIN) and the exchange tax (DOL). These, are high frequency data representing various aspects of the dynamic of negotiations. The array of values includes the dates/times of trades, prices, volumes offered for trade and others trades characteristics. The first stage of the thesis was to extract information to the analysis from an archive in FIX protocol, it was developed a program in R with this aim. Afterwards, we studied the character of temporal dependence in the data, testing Markov properties of a fixed and variable memory length. The results of this application show a great variability in the character of dependence, which requires further analysis. We believe that our work is of great importance in future academic studies. In particular, the specific character of the FIX protocol used by Bovespa. This was an obstacle in a number of academic studies, which was, obviously, undesirable since Bovespa is one of the largest trading markets in the modern financial world.
 
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tese_06_PADRAO.pdf (2.52 Mbytes)
Publishing Date
2012-05-08
 
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