April 2025
Intermediate to advanced
504 pages
15h
Portuguese (Portugal, Brazil)
Content preview from Análise prática de séries temporais
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Capítulo 14. Aplicações financeiras
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Os mercados financeiros são o avô de todos os dados de séries cronológicas. Se pagares por dados de negociação próprios numa bolsa de alta tecnologia, podes receber fluxos de dados do tamanho de terabytes que podem levar dias a processar, mesmo com computação de alto desempenho e processamento embaraçosamente paralelo.
Os operadores de alta frequência estão entre os membros mais recentes e mais infames da comunidade financeira e negoceiam com base em informações e conhecimentos resultantes da análise de séries cronológicas ao nível dos microssegundos. Por outro lado, as empresas de negociação tradicionais - que analisam séries temporais a mais longo prazo, ao longo de horas, dias ou mesmo meses - continuam a ter sucesso nos mercados, mostrando que a análise de séries temporais de dados financeiros pode ser efectuada de inúmeras formas bem sucedidas e em escalas temporais que abrangem muitas ordens de grandeza, desde milissegundos a meses.
Nota
Otermo embaraçosamente paralelo descreve tarefas de processamento de dados em que os resultados do processamento de um segmento de dados não dependem de forma alguma dos valores de outro segmento de dados. Nestes casos, é extremamente fácil converter tarefas de análise de dados para serem executadas em paralelo, em vez de em sequência, para tirar partido das opções de computação multicore ...
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