q-fin.MF papers | Gist.Science

This category explores the intersection of quantitative finance and machine learning, where advanced algorithms meet complex market data to uncover hidden patterns. Researchers in this space apply statistical modeling and artificial intelligence to predict asset prices, manage risk, and optimize trading strategies, pushing the boundaries of how financial systems are understood and navigated.

Every new preprint in this field is sourced directly from arXiv. At Gist.Science, we process these fresh submissions to provide both accessible plain-language explanations and detailed technical summaries, ensuring that groundbreaking insights are available to everyone, regardless of their background in mathematics or finance.

Below are the latest papers in Q-Fin — Mf, offering a curated look at the most recent developments shaping the future of algorithmic finance.

🤖 machine learning

How Much of a 10-K Matters? Aggregation-Dependent Value of Full-Text versus Risk-Factor Sentiment

This paper demonstrates that while full-text 10-K filings yield superior sentiment metrics for sector and portfolio-level predictions of returns and volatility, the narrower Item 1A risk-factor sections outperform at the individual firm level due to the interplay between document volume and available training signal, thereby establishing a supervised lexicon-learning approach as more effective than traditional dictionaries for regulatory disclosure analysis.

Sanggyu Sean Choi2026-07-17

💰 quantitative finance

On a Merton Problem with Irreversible Healthcare Investment

This paper proposes a tractable dynamic framework extending Merton's portfolio problem to include irreversible healthcare investment, formulating the joint optimization of consumption, portfolio choice, and investment timing as a stochastic control-stopping problem that is solved via a dual two-dimensional optimal stopping approach to derive regularity properties and characterize the optimal investment boundary.

Giorgio Ferrari, Shihao Zhu2026-07-15

💰 quantitative finance

A Cascade of Volterra-Operator BBP Transitions in a Correlated Wigner Matrix

This paper demonstrates that a Wigner-type random matrix with specific row-column correlations exhibits a cascade of distinct Baik--Ben Arous--Péché (BBP) transitions, where a countable family of outlier eigenvalues detaches from the semicircle bulk at critical coupling strengths determined by the singular values of a Volterra integral operator.

Masato Hisakado2026-07-14

💰 quantitative finance

Strategic OTC market making with reputation feedback

This paper introduces a stochastic-control model for electronic OTC market making that incorporates reputation feedback mechanisms, demonstrating how dealers must strategically balance immediate spread capture against long-term franchise value to navigate alternating phases of reputation building and monetization.

Alexander Barzykin2026-07-14

💰 quantitative finance

Signature SDEs from an affine and polynomial perspective

This paper demonstrates that signature stochastic differential equations can be characterized as affine and polynomial processes on the extended tensor algebra, enabling the derivation of explicit formulas for their Fourier-Laplace transforms and expected values via converging power series solutions to Riccati and linear ODEs, thereby providing a universal framework for path-dependent Itô-diffusions with analytically tractable laws.

Christa Cuchiero, Sara Svaluto-Ferro, Josef Teichmann2026-07-08

💰 quantitative finance

Entropic Dynamics of Jump-Diffusion Option Pricing

This paper derives the Merton jump-diffusion model and its associated option pricing framework from an entropic inference approach that utilizes information constraints on log-price dynamics and no-arbitrage conditions, thereby unifying continuous and jump processes while recovering the Black-Scholes limit when jumps are absent.

Mohammad Abedi2026-07-08

💰 quantitative finance

A Limit Order Market with Uncertain Informed Trading Participation

This paper analyzes a one-period limit order market with uncertain informed trading participation, characterizing equilibrium through a fixed point integral equation and demonstrating that price impact asymptotics depend jointly on the asset value distribution and the full distribution of informed trader counts rather than just their expected number.

Umut Çetin, Mingwei Lin2026-07-07

💰 quantitative finance

A Cap-Axis Integral Diagnostic of Factor Models

This paper introduces a cap-axis integral diagnostic that evaluates factor models by analyzing pricing errors along the market-capitalization rank axis, revealing distinct insights into model performance and zero-alpha violations that traditional metrics like the Sharpe ratio fail to capture.

Useong Shin2026-07-03

💰 quantitative finance

Exponential Hedging for the Ornstein-Uhlenbeck Process in the Presence of Linear Price Impact

This paper employs a purely probabilistic duality approach to derive the optimal portfolio strategy and value function for an exponential utility maximization problem involving an Ornstein-Uhlenbeck risky asset subject to linear temporary price impact.

Yan Dolinsky2026-07-02

💰 quantitative finance

When large trades are not news: Liquidity tail risk and price discovery

This paper demonstrates that modeling liquidity demand with heavy-tailed distributions fundamentally alters market equilibrium by creating ambiguity between informed and liquidity-driven trades, which flattens price impact, slows price discovery, and makes liquidity tail risk a critical state variable for market dynamics.

Umut Çetin, Mingwei Lin, Giulia Livieri2026-07-02