SOTAVerified

Portfolio Optimization

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.

Papers

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Showing 176–200 of 428 papers

TitleStatusHype
From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing—0
Functional Constrained Optimization for Risk Aversion and Sparsity Control—0
Functional portfolio optimization in stochastic portfolio theory—0
Fusion of Sentiment and Asset Price Predictions for Portfolio Optimization—0
Fuzzy Expert System for Stock Portfolio Selection: An Application to Bombay Stock Exchange—0
Discrete-time risk sensitive portfolio optimization with proportional transaction costs—0
Generative Machine Learning for Multivariate Equity Returns—0
Combining Reinforcement Learning and Barrier Functions for Adaptive Risk Management in Portfolio Optimization—0
Green portfolio optimization: A scenario analysis and stress testing based novel approach for sustainable investing in the paradigm Indian markets—0
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making—0
Hedge Error Analysis In Black Scholes Option Pricing Model: An Asymptotic Approach Towards Finite Difference—0
Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework—0
Hierarchical Minimum Variance Portfolios: A Theoretical and Algorithmic Approach—0
Portfolio Optimization based on Neural Networks Sensitivities from Assets Dynamics respect Common Drivers—0
High-dimensional Portfolio Optimization using Joint Shrinkage—0
A Survey of Risk-Aware Multi-Armed Bandits—0
Hopfield Networks for Asset Allocation—0
Pontryagin-Guided Deep Learning for Large-Scale Constrained Dynamic Portfolio Choice—0
Improved Regret Bounds for Tracking Experts with Memory—0
Application of Black-Litterman Bayesian in Statistical Arbitrage—0
Inferring Option Movements Through Residual Transactions: A Quantitative Model—0
Dynamic Black-Litterman—0
Integrating multiple sources of ordinal information in portfolio optimization—0
Integrating prediction in mean-variance portfolio optimization—0
Discrete-time portfolio optimization under maximum drawdown constraint with partial information and deep learning resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Different modelPortfolio1—Unverified