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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 121–130 of 428 papers

TitleStatusHype
Quantum computing approach to realistic ESG-friendly stock portfolios—0
Using Machine Learning to Forecast Market Direction with Efficient Frontier Coefficients—0
Portfolio management using graph centralities: Review and comparison—0
Deep Reinforcement Learning and Mean-Variance Strategies for Responsible Portfolio Optimization—0
From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing—0
Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization—0
Finding Near-Optimal Portfolios With Quality-Diversity—0
Combining Transformer based Deep Reinforcement Learning with Black-Litterman Model for Portfolio Optimization—0
Portfolio Optimization under Transaction Costs with Recursive Preferences—0
Beyond Expectations: Learning with Stochastic Dominance Made Practical—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Different modelPortfolio1—Unverified