Long memory in high frequency time series using wavelets and conditional volatility models (2022)
- Authors:
- USP affiliated authors: CHIANN, CHANG - IME ; PINTO, MATEUS GONZALEZ DE FREITAS - IME
- Unidade: IME
- Subjects: ANÁLISE DE SÉRIES TEMPORAIS; ANÁLISE DE ONDALETAS
- Keywords: Volatility; High-Frequency Data
- Language: Inglês
- Abstract: The presence of spikes or cusps in high-frequency return series might generate problems in terms of inference and estimation of the parameters in volatility models. For example, the presence of jumps in a time series can influence the sample autocorrelations, which can cause misidentification or generate spurious ARCH effects. On the other hand, these jumps might also hide the proper heteroskedastic behavior of the dependence structure of a series, leading to identification issues and a poorer fit of a model. We propose a method to separate jumps with wavelet shrinkage in high-frequency financial series, fitting a suitable model that accounts for its stylized facts. We also perform simulation studies to assess the effectiveness of the proposed method, whereas also to exemplify the effect of the jumps in time series. Finally, we use the methodology to model real high-frequency time series of stocks traded in the Brazilian Exchange and OTC and a series of cryptocurrencies.
- Imprenta:
- Source:
- Título do periódico: Livro de Resumos
- Conference titles: Simpósio Nacional de Probabilidade e Estatística - SINAPE
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ABNT
PINTO, Mateus Gonzalez de Freitas e MARQUES, Guilherme de Oliveira Lima Cagliari e CHIANN, Chang. Long memory in high frequency time series using wavelets and conditional volatility models. 2022, Anais.. São Paulo: ABE, 2022. Disponível em: https://app.eventize.com.br/upload/004449/files/Sinape2022_FINAL.pdf. Acesso em: 13 set. 2024. -
APA
Pinto, M. G. de F., Marques, G. de O. L. C., & Chiann, C. (2022). Long memory in high frequency time series using wavelets and conditional volatility models. In Livro de Resumos. São Paulo: ABE. Recuperado de https://app.eventize.com.br/upload/004449/files/Sinape2022_FINAL.pdf -
NLM
Pinto MG de F, Marques G de OLC, Chiann C. Long memory in high frequency time series using wavelets and conditional volatility models [Internet]. Livro de Resumos. 2022 ;[citado 2024 set. 13 ] Available from: https://app.eventize.com.br/upload/004449/files/Sinape2022_FINAL.pdf -
Vancouver
Pinto MG de F, Marques G de OLC, Chiann C. Long memory in high frequency time series using wavelets and conditional volatility models [Internet]. Livro de Resumos. 2022 ;[citado 2024 set. 13 ] Available from: https://app.eventize.com.br/upload/004449/files/Sinape2022_FINAL.pdf - Jump detection in high-frequency financial data using wavelets
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