Economics & Finance · Interdisciplinary & Society
Computational Finance
The newest papers in Computational Finance that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
87 papers, from 7 September 2026 to 5 November 2026: 87 arXiv preprints.
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Newest papers, page 4
Information Games: Strategic Crowding and Firm Repositioning in Language-Model Space
Firms follow changing economic opportunities, but rivalry changes their response.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 Intraday Orderbook to Imbalance Price: Understanding Cross-Market Interaction
Power systems with increasing variable renewable generation face greater uncertainty in scheduling and balancing.Deep kernel hedging
We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods.Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios
In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture the underlying risk structures of financial…FinAutoRubric: Expert-Guided Automatic Rubric Generation for Evaluating Financial Research Agents
Evaluating finance research agents requires rubrics that reflect expert standards and fix the values correct as of an information cutoff.Introducing the CZAR Loss: A Tailored Objective Function for Financial Log-Return Predictions
In quantitative finance, standard regression losses are misaligned with the economics of return prediction.LiveOption: Evaluating LLM Agents in Structured Option Trading with Nonlinear Payoffs
Large language models (LLMs) and multi-agent systems (MAS) have shown promise in financial decision-making, yet existing evaluations focus on equity trading and primarily assess directional…Taming the Greeks: Option Portfolios with Inductive Biases
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures.Self-Evolving Multi-Agent Symbolic Discovery for Financial Fundamental Analysis
While symbolic regression (SR) has been successfully used in science to discover new equations, its use in financial valuation is hindered by several limitations.Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals
Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured form makes their forecasting value difficult to…Agentic Limit Order Books: Phase Transitions and Market Impact
We investigate the systemic macroscopic dynamics emerging from Limit Order Books (LOBs) populated exclusively by autonomous reinforcement-learning agentic traders.Taming the Option Factor Zoo: A High-Dimensional Analysis
Option-implied factors are largely, but not entirely, spanned by the equity factor zoo.Hierarchical Multi-Task Learning with Liquidity-Aware Signals for Stock Forecasting
Stock price forecasting is a long-standing challenge in computational finance, driven by the inherent randomness of markets and complex temporal patterns.Loss Choice or Model Choice? The Role of Forecast Level in Cryptocurrency Volatility Forecasting
Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions.Leaky-integrator reconstruction: taming error accumulation in recursive differenced time-series forecasting
Recursive differenced forecasting, the standard remedy for non-stationarity, predicts one-step changes and integrates them by cumulative summation.OrderFusion+: Probabilistic Buy--Sell Price Trajectory Forecasting in Intraday Electricity Markets
Intraday electricity markets enable participants to adjust energy positions close to delivery, with price forecasts necessary to support trading and the scheduling of flexible electricity resources…HARN: Hierarchical Associative Resonance Network for Event-Driven Multi-Timeframe Forecasting
Financial time series evolve across multiple temporal resolutions, challenging forecasting systems to incorporate newly available information without repeatedly recomputing unchanged representations.Universal Diffusion Models for Implied Volatility Surfaces: Learning Shared Dynamics Across Stocks
Modeling the dynamics of option implied volatility surface (IVS) is crucial for pricing, hedging, and risk-managing option portfolios.Efficient simulation schemes for pricing options under the Ornstein--Uhlenbeck driven stochastic volatility model
We develop an efficient Monte Carlo simulation scheme for pricing options under the Ornstein-Uhlenbeck driven stochastic volatility model via the operator splitting approach.