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 61–70 of 428 papers

TitleStatusHype
A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning—0
A mixture transition distribution approach to portfolio optimization—0
Multi-Hypothesis Prediction for Portfolio Optimization: A Structured Ensemble Learning Approach to Risk Diversification—0
Stochastic Optimal Control of Iron Condor Portfolios for Profitability and Risk Management—0
DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data—0
A Deep Reinforcement Learning Framework for Dynamic Portfolio Optimization: Evidence from China's Stock MarketCode0
Multimodal Deep Reinforcement Learning for Portfolio Optimization—0
Market-Neutral Strategies in Mid-Cap Portfolio Management: A Data-Driven Approach to Long-Short Equity—0
PolyModel for Hedge Funds' Portfolio Construction Using Machine Learning—0
Robust Portfolio Optimization using GOPALS: Geospatial Optimization and Portfolio Allocation using Landscape SegmentationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Different modelPortfolio1—Unverified