https://www.ml-quant.com/topics/portfolio-allocation/Portfolio construction, allocation, rebalancing and risk budgeting, from Markowitz to deep RL. en https://www.ml-quant.com/papers/arxiv/2609.27113/https://www.ml-quant.com/papers/arxiv/2609.27113/Fri, 25 Sep 2026 07:00:00 +0000Formulates a stochastic control problem for actively allocating between equal-weighted and market portfolios based on a diversity-dispersion model, outperforming passive strategies during market bubbles. https://www.ml-quant.com/papers/arxiv/2609.21427/https://www.ml-quant.com/papers/arxiv/2609.21427/Fri, 25 Sep 2026 07:00:00 +0000Proposes a KKT-based decision-focused learning method that trains mean-variance portfolio models by directly minimizing downstream portfolio loss while preserving all constraints. https://www.ml-quant.com/papers/arxiv/2609.25704/https://www.ml-quant.com/papers/arxiv/2609.25704/Fri, 25 Sep 2026 07:00:00 +0000Shows that mean-variance portfolio selection and the constrained LASSO trace identical piecewise-linear solution paths, mapping their parametrizations exactly. https://www.ml-quant.com/papers/arxiv/2609.26349/https://www.ml-quant.com/papers/arxiv/2609.26349/Fri, 25 Sep 2026 07:00:00 +0000Characterizes optimal consumption and investment strategies in markets with stochastic volatility clocks using infinite-horizon backward SDEs, extending to rough and hyper-rough regimes. https://www.ml-quant.com/papers/ssrn/7508299/https://www.ml-quant.com/papers/ssrn/7508299/Fri, 25 Sep 2026 07:00:00 +0000Using factor selection, the study finds mean active alpha of plus 9 basis points monthly for mutual funds, reversing the no-alpha conclusion when benchmarks are tailored to each fund. https://www.ml-quant.com/papers/ssrn/7486600/https://www.ml-quant.com/papers/ssrn/7486600/Fri, 25 Sep 2026 07:00:00 +0000The research proposes a data-driven portfolio method that blends tail-risk models and projects onto valid mixtures, providing bounds on Expected Shortfall regret without Wasserstein assumptions. https://www.ml-quant.com/papers/repec/cxv-wpaper-2602/https://www.ml-quant.com/papers/repec/cxv-wpaper-2602/Fri, 25 Sep 2026 07:00:00 +0000Corporate leverage affects how monetary tightening transmits to the real economy: equity holders lose wealth while safe-asset holders are cushioned, raising the sacrifice ratio. https://www.ml-quant.com/papers/arxiv/2509.09585/https://www.ml-quant.com/papers/arxiv/2509.09585/Thu, 16 Apr 2026 07:00:00 +0000Causal PDE-Control Models (CPCMs) offer a strong and clear framework for portfolio allocation that combines causal factors and complex filtering, outperforming standard econometric and machine-learning techniques. https://www.ml-quant.com/papers/arxiv/2604.08252/https://www.ml-quant.com/papers/arxiv/2604.08252/Thu, 16 Apr 2026 07:00:00 +0000Remote work after the pandemic is causing people to move within cities for better quality of life, rather than relocating to rural areas. https://www.ml-quant.com/papers/arxiv/2601.05975/https://www.ml-quant.com/papers/arxiv/2601.05975/Fri, 16 Jan 2026 07:00:00 +0000Deep Learning for Portfolio Management: DeePM uses deep learning to improve macro portfolio management, delivering better risk-adjusted returns than traditional methods across various economic conditions. https://www.ml-quant.com/papers/ssrn/4480682/https://www.ml-quant.com/papers/ssrn/4480682/Sun, 28 Dec 2025 07:00:00 +0000A portfolio approach to drug development may improve investment returns and speed up vaccine creation. https://www.ml-quant.com/papers/ssrn/4478272/https://www.ml-quant.com/papers/ssrn/4478272/Sun, 28 Dec 2025 07:00:00 +0000Israeli mutual funds hold excessive cash, indicating a need for better liquidity management to reduce redemption risks. https://www.ml-quant.com/papers/ssrn/4475732/https://www.ml-quant.com/papers/ssrn/4475732/Sun, 28 Dec 2025 07:00:00 +0000Global investments in environmental and climate projects are diversifying as investors integrate more green initiatives into their portfolios. https://www.ml-quant.com/papers/ssrn/4470609/https://www.ml-quant.com/papers/ssrn/4470609/Sun, 28 Dec 2025 07:00:00 +0000It tackles a sparse risk parity portfolio problem for index tracking while managing asset risks, with successful results on the SP 500. https://www.ml-quant.com/papers/ssrn/4463810/https://www.ml-quant.com/papers/ssrn/4463810/Sun, 28 Dec 2025 07:00:00 +0000It develops real-time Tail Risk-Managed portfolios that minimize tail risks and enhance risk-return profiles compared to standard strategies. https://www.ml-quant.com/papers/arxiv/2512.16452/https://www.ml-quant.com/papers/arxiv/2512.16452/Fri, 19 Dec 2025 07:00:00 +0000The Smart Data Portfolio framework defines data governance in AI as a trade-off between information risk and fairness, creating a Governance-Efficient Frontier for optimal data allocation in AI services. https://www.ml-quant.com/papers/arxiv/2512.09224/https://www.ml-quant.com/papers/arxiv/2512.09224/Sun, 14 Dec 2025 07:00:00 +0000This study uses Reinforcement Learning to solve the Mean-Variance Portfolio Optimization problem, creating a profitable investment strategy that adapts to changing preferences over time. https://www.ml-quant.com/papers/ssrn/4960502/https://www.ml-quant.com/papers/ssrn/4960502/Mon, 01 Dec 2025 07:00:00 +0000This research highlights the rise of collective investment trusts in 401k plans due to their lower costs and tailored options for investors. https://www.ml-quant.com/papers/ssrn/4961553/https://www.ml-quant.com/papers/ssrn/4961553/Mon, 01 Dec 2025 07:00:00 +0000The study looks at how mutual fund performance is influenced by internal biases when large amounts of capital are invested. https://www.ml-quant.com/papers/arxiv/2511.21221/https://www.ml-quant.com/papers/arxiv/2511.21221/Mon, 01 Dec 2025 07:00:00 +0000A portfolio strategy leveraging transfer learning improves investment results by filtering useful information from noise, leading to better performance as indicated by a higher Sharpe ratio. https://www.ml-quant.com/papers/arxiv/2511.21850/https://www.ml-quant.com/papers/arxiv/2511.21850/Mon, 01 Dec 2025 07:00:00 +0000A unique portfolio optimization method that incorporates ESG scores into the Black-Litterman framework shows significant returns with daily updates. https://www.ml-quant.com/papers/arxiv/2211.09968/https://www.ml-quant.com/papers/arxiv/2211.09968/Wed, 12 Nov 2025 07:00:00 +0000In Poland, cheap online portfolio challenges and one‑on‑one mentoring sharply increased women’s tech employment, and data-driven targeting improved admissions. https://www.ml-quant.com/papers/arxiv/2510.25740/https://www.ml-quant.com/papers/arxiv/2510.25740/Tue, 04 Nov 2025 07:00:00 +0000- Excess Growth - Excess Rate - Growth Excess - Surplus Growth - Overgrowth - Growth Surplus Recommended: Excess Growth (keeps meaning but is more concise).: The paper proves that a central portfolio metric—the excess growth rate—can be exactly described using basic information‑theory ideas and a few natural axioms. In short, it shows that the extra growth a portfolio achieves is essentially an information quantity, so portfolio performance can be understood like information gain. https://www.ml-quant.com/papers/arxiv/2510.19619/https://www.ml-quant.com/papers/arxiv/2510.19619/Mon, 27 Oct 2025 07:00:00 +0000Finds Indian mutual funds often change investment styles, which can materially alter their risk‑adjusted returns. https://www.ml-quant.com/papers/arxiv/2510.19271/https://www.ml-quant.com/papers/arxiv/2510.19271/Mon, 27 Oct 2025 07:00:00 +0000Finds that investors targeting specific outcome quantiles change volatility exposure (cutting risk to protect downside or seeking dispersion for upside) and introduces a distributional actor‑critic to learn such strategies. https://www.ml-quant.com/papers/arxiv/2510.18236/https://www.ml-quant.com/papers/arxiv/2510.18236/Mon, 27 Oct 2025 07:00:00 +0000Groups people with similar risk attitudes, reducing the n‑agent risk‑sharing problem to a two‑agent (risk‑averse vs risk‑seeking) model with clear existence conditions. https://www.ml-quant.com/papers/repec/eee-ememar-v-51-y-2022-i-pb-s1566014122000085/https://www.ml-quant.com/papers/repec/eee-ememar-v-51-y-2022-i-pb-s1566014122000085/Fri, 24 Oct 2025 07:00:00 +0000The research investigates the use of machine learning to predict stock returns in Brazil, showing that an Equal Risk Contribution approach greatly enhances risk-adjusted returns. https://www.ml-quant.com/papers/arxiv/2510.02986/https://www.ml-quant.com/papers/arxiv/2510.02986/Thu, 09 Oct 2025 07:00:00 +0000FR-LUX is a new reinforcement learning framework that learns trading policies and remains stable across different market conditions, offering high average Sharpe ratio and excellent risk-return efficiency. https://www.ml-quant.com/papers/arxiv/2510.05377/https://www.ml-quant.com/papers/arxiv/2510.05377/Thu, 09 Oct 2025 07:00:00 +0000The study shows that using negative edges in weighted signed network representations of financial markets can help reduce portfolio risk, performing on par with traditional models. https://www.ml-quant.com/papers/arxiv/2510.06986/https://www.ml-quant.com/papers/arxiv/2510.06986/Thu, 09 Oct 2025 07:00:00 +0000The research introduces an inverse portfolio optimization framework that can deduce latent investor preferences from observed portfolio allocations, offering a robust tool for preference inference and portfolio design.