Portfolio Optimization
39 papers with code • 0 benchmarks • 0 datasets
Portfolio management is the task of obtaining higher excess returns through the flexible allocation of asset weights. In reality, common examples are stock selection and the Enhanced Index Fund (EIF). The general solution of portfolio management is to score the potential of assets, buy assets with upside potential and increase their weighting, and sell assets that are likely to fall or are relatively weak. A large number of strategies have been proposed for portfolio management.
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Latest papers
Deep Deterministic Portfolio Optimization
CFMTech/Deep-RL-for-Portfolio-Optimization
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Can deep reinforcement learning algorithms be exploited as solvers for optimal trading strategies?
Online Mixed-Integer Optimization in Milliseconds
bstellato/mlopt
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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.
Continuous-Time Mean-Variance Portfolio Selection: A Reinforcement Learning Framework
We approach the continuous-time mean-variance (MV) portfolio selection with reinforcement learning (RL).
Artificial Counselor System for Stock Investment
This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment.
Stock Price Correlation Coefficient Prediction with ARIMA-LSTM Hybrid Model
Predicting the price correlation of two assets for future time periods is important in portfolio optimization.
Reweighted Price Relative Tracking System for Automatic Portfolio Optimization
In the portfolio optimizing stage, a novel tracking system with a generalized increasing factor is proposed to maximize the future wealth of next period.
Computation of optimal transport and related hedging problems via penalization and neural networks
stephaneckstein/transport-and-related
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This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks.
Smart "Predict, then Optimize"
Our SPO+ loss function can tractably handle any polyhedral, convex, or even mixed-integer optimization problem with a linear objective.
A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
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.
