Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Non-parametric kernel estimation for symmetric Hawkes processes.
  Application to high frequency financial data   We define a numerical method that provides a non-parametric estimation of the
kernel shape in symmetric multivariate Hawkes processes. This method relies on
second order statistical properties of Hawkes processes that relate the
covariance matrix of the process to the kernel matrix. The square root of the
correlation function is computed using a minimal phase recovering method. We
illustrate our method on some examples and provide an empirical study of the
estimation errors. Within this framework, we analyze high frequency financial
price data modeled as 1D or 2D Hawkes processes. We find slowly decaying
(power-law) kernel shapes suggesting a long memory nature of self-excitation
phenomena at the microstructure level of price dynamics.

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The categories of this paper are: comp-gas
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The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
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The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
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The categories of this paper are: hep-lat
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-th
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The categories of this paper are: astro-ph