Economics & Finance · Interdisciplinary & Society
Statistical Finance
The newest papers in Statistical Finance that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
72 papers, from 6 September 2026 to 5 November 2026: 72 arXiv preprints.
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Newest papers, page 3
From Economic Explanation to Performance Improvement in Machine-Learning Portfolios
To extend conventional model-level feature importance to economically meaningful portfolio outcomes and decisions, we propose a local first-order attribution-propagation framework that maps…FOMO: FLEX Options and Market Outcomes
FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing.$L_0$ Feature Selection via Monte Carlo Tree Search in High-Dimensional Financial Regression
Feature selection is a central problem in high-dimensional financial regression, where large numbers of engineered variables and strong correlations among predictors reduce model stability and…Residual Learning in Empirical Asset Pricing
Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones.DSTNet: Dynamic Spectral Trajectory Network for Causal Multi-Horizon Financial Forecasting
Wavelet-based financial forecasters typically use the transform only to denoise, or reduce it to a single spectral snapshot at the forecast origin, and the convolution that produces the coefficients…From a Hierarchy of Stochastic Differential Equations to a Hierarchy of Generalized Beta Distributions
We introduce a mean-reverting stochastic differential equation with a three-component stochastic term and show that it generates a hierarchy of steady-state (stationary) distributions.Latent Continuum of Regimes in Limit Order Book Dynamics
Market-regime models typically assume a finite set of discrete latent states.STOCK-JEPA: Prior-Anchored Latent Revision Representation Learning in Equity Markets
Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio.A Generalized Langevin Model of Latent Liquidity and Concave Price Impact
We model market impact as the response to submitted order flow net of counterflow from latent traders, activated when price displacements from the level that would prevail without the order exceed…From Word Counts to Context: Topic Models for Asset Pricing
News may reveal systematic risk, but whether its context enhances the construction of systematic risk factors is still unclear.From Cointegration to Out-of-Sample Failure: A Pairs-Trading Case Study on PEP-KO
This paper examines whether a cointegration-based pairs trading strategy between PepsiCo and The Coca-Cola Company is statistically robust and economically exploitable.EverMine: Dissecting the Self-Evolution of Research Capabilities in Long-Horizon Alpha Research
Self-evolving agents aim to turn research feedback into reusable skills, tools, and research rules.Packets, Transactions and Queues: Design Principles for HFT Systems from a Measurement Study of CME Market Data
HFT systems are conventionally built as a single-threaded event loop, on the rule that every thread hop adds latency.Model-agnostic noise reduction for high-dimensional time series data
We develop a model-agnostic framework for noise reduction in high-dimensional time series that explicitly targets optimal recovery of a low-dimensional latent dynamic component contaminated by…FedIncome: Federated Learning for Income Estimation in Digital Lending Under Data Sovereignty Constraints
Verified income is often unavailable in digital loan applications, forcing lenders to rely on reported income and potentially leading to over-lending, overly conservative offers, or rejection of…Modeling interest rate swap volatility with GARCH processes
We examine the conditional volatility dynamics of the USD 1Yx10Y forward swap rate using GARCH(1,1), GJR-GARCH(1,1), and a two-regime Markov-switching GARCH (MSGARCH) model.Target alignment, dilution and forecast selection when cross-sectional forecasts share a common target
Forecasters often score the same units per date against one standardized realized outcome.Propose, Don't Judge: An Anytime-Valid Referee for LLM Agents That Mine Investment Factors
Language-model agents now run the whole of quantitative factor research: they propose investment factors, backtest them, select the survivors and retire them.Stealing profits: Spread-based temporal hierarchy forecasting for day-ahead electricity markets
Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more relevant than predicting individual hourly prices.Adapting Pairs Trading to Gambling Markets A Case Study of the U.S. Presidential Election
Pairs trading exploits mean reversion in the relationship between related assets.