Portfolio Optimization
38 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.
Benchmarks
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Latest papers
Qlib: An AI-oriented Quantitative Investment Platform
microsoft/qlib
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Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments.
Bayesian Optimization of Risk Measures
saitcakmak/BoRisk
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NeurIPS 2020
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 $W$.
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
guaguakai/surrogate-optimization-learning
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NeurIPS 2020
Solving optimization problems with unknown parameters often requires learning a predictive model to predict the values of the unknown parameters and then solving the problem using these values.
Constrained regret minimization for multi-criterion multi-armed bandits
We consider a stochastic multi-armed bandit setting and study the problem of constrained regret minimization over a given time horizon.
A Novel Meta-Heuristic Optimization Algorithm Inspired by the Spread of Viruses
In this paper, a novel nature-inspired meta-heuristic optimization algorithm called virus spread optimization (VSO) is proposed.
Deep Stock Predictions
Forecasting stock prices can be interpreted as a time series prediction problem, for which Long Short Term Memory (LSTM) neural networks are often used due to their architecture specifically built to solve such problems.
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
qcappart/hybrid-cp-rl-solver
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In this work, we propose a general and hybrid approach, based on DRL and CP, for solving combinatorial optimization problems.
Deep Learning for Portfolio Optimization
shilewenuw/deep-learning-portfolio-optimization
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We adopt deep learning models to directly optimise the portfolio Sharpe ratio.
Solving Portfolio Optimization Problems Using MOEA/D and Levy Flight
Portfolio optimization is a financial task which requires the allocation of capital on a set of financial assets to achieve a better trade-off between return and risk.
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?
