This week the pipeline scored 44 new papers. Here are the 10 strongest by our rigor-weighted score (how scoring works).
1. Arithmetic Models for Commodity Futures, Vanilla, and Calendar Spread Options
Holy Grail · Math 8.0/10 · Rigor 9.0/10 · Volatility, Commodities & Energy
We develop an arithmetic multi-factor stochastic volatility model for commodity futures and options. The arithmetic specification yields a low-dimensional Markovian representation of the futures curve and semi-closed-form pricing formulas for vanilla and basket options, including calendar spread opt…
2. A game-theoretic analysis of the market microstructure in decentralized exchanges with concentrated liquidity
Holy Grail · Math 9.0/10 · Rigor 8.0/10 · Crypto & DeFi, Market Microstructure
We study strategic liquidity provision in decentralized exchanges with concentrated liquidity as a mean-field game. Liquidity providers choose the width of their price range and when to rebalance it, pay a transaction cost at each rebalancing, and share the fees collected at each tick in proportion…
3. Arbitrage-Free Implied Volatility Surface Reconstruction via Additive Martingales
Holy Grail · Math 8.0/10 · Rigor 8.0/10 · Options & Derivatives, Volatility
This work focuses on reconstructing a continuous implied volatility (IV) surface from a small number of option quotes, a fundamental task for option pricing and risk management. We propose Additive Martingale (AddMart), a few-shot IV surface reconstruction framework that satisfies static no-arbitrag…
4. Teacher Supervision, Fixed Representations and Calibration: Exact Risk Calculations for Candidate-Scoring Decision Models
Holy Grail · Math 8.5/10 · Rigor 7.5/10
Candidate-scoring decision models return a probability distribution over a presented set of answers. Public documentation of one such system, Jev, and of an open counterpart, JevAny, describes three training ingredients that determine what these probabilities estimate: soft targets from larger model…
5. SHADE: Shrinkage via Halted Alpha-stable Denoising for Heavy-Tailed Probabilistic Time Series Forecasting
Holy Grail · Math 8.5/10 · Rigor 7.5/10 · Machine Learning
Time-series observations are particularly susceptible to noise, and many real-world series have low signal-to-noise ratios (SNRs) together with heavy-tailed and time-varying disturbances. When Gaussian diffusion models are used for forecasting, reversing all the way to the zero-noise endpoint may yi…
6. Understanding the Inner Workings of a State-Space Foundation Model for Limit Order Books
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Market Microstructure
Autoregressive foundation models offer state-of-the-art capabilities to simulate the market by generating the message flow of limit order books (LOBs). Yet, without understanding their inner workings, research directions are hard to narrow and practical use in real-world trading environments remains…
7. Cross-product Modelling in Continuous Intraday Electricity Markets via Hawkes Processes
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Market Microstructure, Commodities & Energy
As renewable energy integration accelerates, intraday continuous (IDC) electricity markets have become essential for short-term balancing. However, the simultaneous trading of overlapping contracts with varying granularities creates complex, hidden liquidity dependencies that are critical to market…
8. Amortized Neural Filtering for Calibrated Posteriors in Statistical Arbitrage
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Statistical Arbitrage
Statistical arbitrage trades on an estimate of the state of a residual spread, and conventional practice discards the uncertainty of that estimate. We keep the uncertainty and use it in the trading decision. A Neural Filter Estimator (NFE) is trained on simulated paths of a mean-reverting process wh…
9. Dynamics of the Liquidity Profile in Concentrated Liquidity Provision: An SPIDE Approach
Holy Grail · Math 9.0/10 · Rigor 7.0/10 · Crypto & DeFi, Market Microstructure
We model the dynamics of the liquidity profile in Uniswap~V3 and other concentrated-liquidity automated market makers with a stochastic partial integro-differential equation (SPIDE). The profile, the aggregate of all provider positions across tick space, evolves under a degenerate Sturm–Liouville o…
10. Conditional Weight of Evidence for Gradient-Boosted Credit Models: Estimation, Additivity and Its Relation to Adverse Action Reasons
Holy Grail · Math 7.5/10 · Rigor 8.0/10
Traditional weight of evidence assigns a credit characteristic a value based on its association with default across a population. Credit analysis also requires an assessment of that characteristic in the context of an individual applicant’s record. We study conditional weight of evidence for this pu…
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