Autor(es)

Leles, Michel C. R. ; Cardoso, Adriano S. V. ; Moreira, Mariana G. ; Sbruzzi, Elton F. ; Nascimento, Cairo L., Jr. ; Guimaraesf, Homero N. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 12TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON2018); v. N/A, p. 5-pg., 2018-01-01.

Resumo

A comparison between Moving Averages (MA) and two versions of Singular Spectrum Analysis (SSA) methodology - the Caterpillar and the Toeplitz - is presented. Caterpillar had already been studied in this manner but the same is not true for the Toeplitz SSA. Toeplitz SSA assumes the stationarity of the time-series, which means that the process needs to be mean-reverting. However, such assumption is not a necessary condition for the Caterpillar SSA. In this paper both approaches are applied to a trend estimation problem in order to be used as an indicator in trend-following technical rules design. Similarities and differences between these techniques are addressed. The obtained results suggest that, although SSA approaches provides more flexibility to achieve a desired trend resolution compared to the traditional MA, the Toeplitz SSA exhibit some issues that might put it off its use in this particular application. (AU)

• Processo FAPESP: 17/20248-8 - Aplicação de técnicas de inteligência computacional e de análise de Big Data em um experimento com sistemas multi-agentes na área de finanças
• Beneficiário: Michel Carlo Rodrigues Leles
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 16/04992-6 - Aplicação de técnicas de inteligência computacional e de análise de Big Data em um experimento com sistemas multi-agentes na área de finanças
• Beneficiário: Cairo Lúcio Nascimento Júnior
• Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Regular