Portfolio Optimization
37 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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Most implemented papers
Recurrent Neural Networks for Stochastic Control Problems with Delay
frankhan91/RNN-ControlwithDelay
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Stochastic control problems with delay are challenging due to the path-dependent feature of the system and thus its intrinsic high dimensions.
Stock price prediction using Generative Adversarial Networks
ChickenBenny/Stock-prediction-with-GAN-and-WGAN
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Journal of Computer Science 2021
In this paper, it proposes a stock prediction model using Generative Adversarial Network (GAN) with Gated Recurrent Units (GRU) used as a generator that inputs historical stock price and generates future stock price and Convolutional Neural Network (CNN) as a discriminator to discriminate between the real stock price and generated stock price.
Deep Reinforcement Trading with Predictable Returns
Alessiobrini/Deep-Reinforcement-Trading-with-Predictable-Returns
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Classical portfolio optimization often requires forecasting asset returns and their corresponding variances in spite of the low signal-to-noise ratio provided in the financial markets.
Portfolio Allocation under Asymmetric Dependence in Asset Returns using Local Gaussian Correlations
It is well known that there are asymmetric dependence structures between financial returns.
A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints
PredOptwithSoftConstraint/PredOptwithSoftConstraint
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Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.
RPS: Portfolio Asset Selection using Graph based Representation Learning
Portfolio optimization is one of the essential fields of focus in finance.
Efficient and Scalable Parametric High-Order Portfolios Design via the Skew-t Distribution
Initially, profit and risk were measured by the first two moments of the portfolio's return, a. k. a.
Distributionally Robust End-to-End Portfolio Construction
Our proposed distributionally robust end-to-end portfolio selection system explicitly accounts for the impact of model risk.
Markov Decision Processes under Model Uncertainty
We introduce a general framework for Markov decision problems under model uncertainty in a discrete-time infinite horizon setting.
Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient
We introduce a new Langevin dynamics based algorithm, called e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear in real-world applications such as quantile estimation, vector quantization, CVaR minimization, and regularized optimization problems involving ReLU neural networks.
