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# Qlib: An AI-oriented Quantitative Investment Platform

22 Sep 2020microsoft/qlib

Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments.

3,703

# A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

30 Jun 2017ZhengyaoJiang/PGPortfolio

They are, along with a number of recently reviewed or published portfolio-selection strategies, examined in three back-test experiments with a trading period of 30 minutes in a cryptocurrency market.

1,227

# Stock Price Correlation Coefficient Prediction with ARIMA-LSTM Hybrid Model

5 Aug 2018imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid

Predicting the price correlation of two assets for future time periods is important in portfolio optimization.

212

# Model-based Deep Reinforcement Learning for Dynamic Portfolio Optimization

25 Jan 2019ibm-research-tokyo/dybm

Dynamic portfolio optimization is the process of sequentially allocating wealth to a collection of assets in some consecutive trading periods, based on investors' return-risk profile.

109

# Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

2 Jun 2020qcappart/hybrid-cp-rl-solver

In this work, we propose a general and hybrid approach, based on DRL and CP, for solving combinatorial optimization problems.

40

# Online Mixed-Integer Optimization in Milliseconds

4 Jul 2019bstellato/mlopt

Compared to state-of-the-art MIO routines, the online running time of our method is very predictable and can be lower than a single matrix factorization time.

26

# Deep Deterministic Portfolio Optimization

13 Mar 2020CFMTech/Deep-RL-for-Portfolio-Optimization

Can deep reinforcement learning algorithms be exploited as solvers for optimal trading strategies?

21

# Bayesian Optimization of Risk Measures

We consider Bayesian optimization of objective functions of the form $\rho[ F(x, W) ]$, where $F$ is a black-box expensive-to-evaluate function and $\rho$ denotes either the VaR or CVaR risk measure, computed with respect to the randomness induced by the environmental random variable $W$.

5

# Computation of optimal transport and related hedging problems via penalization and neural networks

23 Feb 2018stephaneckstein/transport-and-related

This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks.

5