Economics & Finance · Interdisciplinary & Society
Portfolio Management
The newest papers in Portfolio Management that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
66 papers, from 7 September 2026 to 4 November 2026: 66 arXiv preprints.
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Newest papers
Constrained defined-contribution pension management: A reparameterized neural network approach
This paper studies constrained defined contribution (DC) pension management under a two-factor financial market model.Safe Portfolio Learning from Untrusted Predictions: Signed Trust, Abstention, and Cross-Universe Polarity Failure
Portfolio use of machine predictions must often proceed while the predictions' economic direction, reliability, and timing remain untrusted, and while feedback from overlapping multi-period…Mitigating Return Drag and Regime Whipsaws in Sector Rotation: An Asymmetric Downside-Aware Nested Clustered Optimization Framework
Hierarchical clustering and Nested Clustered Optimization (NCO) mitigate the mathematical ill-conditioning of classical Markowitz covariance matrices.Interpretable Allocation and Model-Predictive Rebalancing of Equity Portfolios, Tested on Real and Synthetic Markets
A live equity portfolio poses three problems: which stocks to hold, when to trade, and whether the strategy holds up beyond the observed market.Specification LASSO and a Flexible Characteristics-Based Asset Pricing Model
This paper studies a partially linear semiparametric additive model that allows for interactions among variables in high-dimensional settings.Penalize the Common Trade: A Collision-Aware Layer for Learned Portfolios
Different learning systems can make nearly the same trade when they share data, objectives, or representations.Non-asymptotic analysis of SGLD with discontinuous stochastic gradients: a new route to portfolio CVaR minimization
Conditional-Value-at-Risk (CVaR) optimization is a fundamental tool in portfolio selection, yet its nonsmooth loss structure poses a challenge for the existing theory of stochastic gradient methods…Optimal portfolio and consumption under no-shorting constraints: The exploratory formulation and reinforcement learning
We develop a reinforcement-learning framework for the continuous-time optimal portfolio-consumption via utility maximization under no-shorting portfolio constraints.Sparse Autoencoders as Implicit Diversification Regularisers for Cross-Sectional Cryptocurrency Returns
Factor models are central to asset pricing and portfolio construction, but neural factors are often difficult to interpret, and their effect on portfolio risk is unclear.The Generalised Kessler Syndrome and the Persian Gulf
The term Kessler syndrome was coined for a runaway orbital cascade creating a high-density debris field.Simple Portfolios that Deliver Consistent Decent Returns
Portfolio construction has been studied extensively in both academia and industry.Decorrelating the Advice Layer: A Calibrated Fragility Metric and Tested Mitigations for Synchronized Liquidation in Agentic Wealth Management
Conversational AI agents are turning wealth management into a continuous loop of market analysis, allocation, risk checks and execution, run for millions of clients on a handful of foundation models.Certifying Reward Alignment in Portfolio Reinforcement Learning
Financial reinforcement learning often translates an investment objective into an additive risk-adjusted reward.Optimal portfolio choice under green transition timing risk
We study an investor's optimal portfolio choice problem when they account for the impact of a possible future green transition, whose timing is uncertain.Financial Context-Rich Strategy for Actor-Critic based Agents: A Deep Reinforcement Learning Approach for Stock Trading
In modern financial markets, more than 3/4th of the large volume trade is executed by algorithmic trading based on advanced trading strategies to attain higher precision and speed than traditional…Optimal collective investment under regulatory uncertainty
We study optimal collective investment subject to a Value-at-Risk (VaR)-type constraint that accounts for uncertainty about future regulatory requirements.Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core
LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards.When News Gets Old: Portfolio Allocation with Reinforcement Learning and Large Language Models
Financial news can influence investment decisions long after publication.Directionally Correct Views in Portfolio Optimization
Portfolio optimization techniques often use historical data to estimate parameters for Markowitz-type or ML models.Market Regime-Based Multi-Asset Portfolio Optimization Using Nested Clustered Optimization for Tactical Asset Allocation
We propose a regime-aware tactical asset allocation (TAA) framework integrating market regime detection with Nested Clustered Optimization (NCO) for multi-asset portfolio construction.