Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comment partitionner automatiquement des marches al\'eatoires ? Avec
  application \`a la finance quantitative   We present in this paper a novel non-parametric approach useful for
clustering Markov processes. We introduce a pre-processing step consisting in
mapping multivariate independent and identically distributed samples from
random variables to a generic non-parametric representation which factorizes
dependency and marginal distribution apart without losing any. An associated
metric is defined where the balance between random variables dependency and
distribution information is controlled by a single parameter. This mixing
parameter can be learned or played with by a practitioner, such use is
illustrated on the case of clustering financial time series. Experiments,
implementation and results obtained on public financial time series are online
on a web portal \url{http://www.datagrapple.com}.

22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas