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Thematic Sessions ST3: High Dimensional Time Series SICREDI Session Chair: Flavio Ziegelmann Thursday, September 5th 10:30 Generalized Conjugate Processes: Lévy Diffusions and Financial Applications Eduardo Horta IME/UFRGS We consider sequences of Lévy Diffusions driven by a latent, discrete time state (possibly infinite dimensional). The proposed model is a generalization of Horta and Ziegelmann (Stochastic Processes and Applications, 2018). We show that the usual approach of estimating the covariance operator of the diffusion entails difficulties in this framework, and propose an alternative based on the functional Fourier transform. Asymptotic results are derived, and the theory is illustrated by an application to financial data. Keywords: Functional Time Series; High Frequency Financial Data; Conjugate Processes; Random measure 22
ST3: High Dimensional Time Series SICREDI Session Chair: Flavio Ziegelmann Thematic Sessions Thursday, September 5th 10:30 Testing for high-dimensional white noise using maximum cross-correlations Jinyuan Chang Southwestern University of Finance and Economics We propose a new omnibus test for vector white noise using the maximum absolute autocorrelations and cross-correlations of the component series. Based on an approximation by the L ∞ -norm of a normal random vector, the critical value of the test can be evaluated by bootstrapping from a multivariate normal distribution. In contrast to the conventional white noise test, the new method is proved to be valid for testing departure from white noise that is not independent and identically distributed.We illustrate the accuracy and the power of the proposed test by simulation, which also shows that the new test outperforms several commonly used methods, including the Lagrange multiplier test and the multivariate Box-Pierce portmanteau tests, especially when the dimension of the time series is high in relation to the sample size. The numerical results also indicate that the performance of the new test can be further enhanced when it is applied to pre-transformed data obtained via the time series principal component analysis proposed by Chang, Guo and Yao (2018, Annals of Statistics). The proposed procedures have been implemented in an R package. 23
Page 1 and 2: BOOK OF ABSTRACTS
Page 3 and 4: Contents About the 18th ESTE 4 Time
Page 5 and 6: Timetable The 18th ESTE will be occ
Page 7 and 8: Minicourse Wednesday to Friday, Sep
Page 9 and 10: Plenary Talks CF2 Wednesday, Septem
Page 11 and 12: Plenary Talks CF4 Thursday, Septemb
Page 13 and 14: Plenary Talks CF6 Thursday, Septemb
Page 15 and 16: Plenary Talks CF8 Friday, September
Page 17 and 18: Thematic Sessions ST1: Data Science
Page 19 and 20: ST2: Nonlinear Time Series Chair: A
Page 21: ST2: Nonlinear Time Series Chair: A
Page 25 and 26: Thematic Sessions ST4: Econometrics
Page 27 and 28: Thematic Sessions ST4: Econometrics
Page 29 and 30: Oral Communications CO1 Tuesday, Se
Page 35 and 36: Oral Communications CO3 Wednesday,
Page 43 and 44: Oral Communications CO5 Thursday, S
Page 51 and 52: Poster Communications SP1 Wednesday
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Poster Communications SP1 Wednesday
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Poster Communications SP2 Thursday,
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Useful Information Talks will be he
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