Study on Singular Spectrum Analysis as a New Technical Oscillator for Trading Rules Design

Autor(es)

Rodrigues Leles, Michel Carlo ^[1] ; Mozelli, Leonardo Amaral ^[2] ; Nascimento Junior, Cairo Lucio ^[3] ; Sbruzzi, Elton Felipe ^[4] ; Guimaraes, Homero Nogueira ^[2]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Joao del Rei, CELTA Ctr Studies Elect Engn & Automat, BR-36420000 Ouro Branco, MG - Brazil

^[2] Univ Fed Minas Gerais, Dept Elect Engn, BR-31270901 Belo Horizonte, MG - Brazil

^[3] Inst Tecnol Aeronaut, Div Elect Engn, BR-12228900 Sao Jose Dos Campos, SP - Brazil

^[4] Fluminense Fed Univ, Sch Ind & Met Engn, BR-27255125 Volta Redonda, RJ - Brazil

• Tipo de documento: Artigo Científico
• Fonte: FLUCTUATION AND NOISE LETTERS; v. 17, n. 4 DEC 2018.
• Citações Web of Science: 0

Resumo

The connection between Singular Spectrum Analysis (SSA) decomposition and short-term market movements is investigated. Since SSA is a non-parametric approach, suitable to decompose general time-series into meaningful components, such as trends, oscillations and noise, it is proposed as a new oscillator-type Technical Indicator, replacing popular ones. New Technical Trading Rules (TTRs) are designed and applied to some major global stock indexes to illustrate the benefits in terms of revealing market movements. The performance is evaluated according to different risk-adjustment metrics and the empirical results reveal that the SSA-TTRs may outperform some popular technical oscillators and also the Buy \& Hold strategy. (AU)

• 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
• 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