Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Equity2Vec: End-to-end Deep Learning Framework for Cross-sectional Asset
  Pricing   Pricing assets has attracted significant attention from the financial
technology community. We observe that the existing solutions overlook the
cross-sectional effects and not fully leveraged the heterogeneous data sets,
leading to sub-optimal performance.
  To this end, we propose an end-to-end deep learning framework to price the
assets. Our framework possesses two main properties: 1) We propose Equity2Vec,
a graph-based component that effectively captures both long-term and evolving
cross-sectional interactions. 2) The framework simultaneously leverages all the
available heterogeneous alpha sources including technical indicators, financial
news signals, and cross-sectional signals. Experimental results on datasets
from the real-world stock market show that our approach outperforms the
existing state-of-the-art approaches. Furthermore, market trading simulations
demonstrate that our framework monetizes the signals effectively.

18
The categories of this paper are: econ
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol