Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement
  Learning for Stock Portfolio Allocation   Portfolio allocation is crucial for investment companies. However, getting
the best strategy in a complex and dynamic stock market is challenging. In this
paper, we propose a novel Adaptive Deep Deterministic Reinforcement Learning
scheme (Adaptive DDPG) for the portfolio allocation task, which incorporates
optimistic or pessimistic deep reinforcement learning that is reflected in the
influence from prediction errors. Dow Jones 30 component stocks are selected as
our trading stocks and their daily prices are used as the training and testing
data. We train the Adaptive DDPG agent and obtain a trading strategy. The
Adaptive DDPG's performance is compared with the vanilla DDPG, Dow Jones
Industrial Average index and the traditional min-variance and mean-variance
portfolio allocation strategies. Adaptive DDPG outperforms the baselines in
terms of the investment return and the Sharpe ratio.

23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an