This week the pipeline scored 14 new papers. Here are the 10 strongest by our rigor-weighted score (how scoring works).
1. Nyström Attention Matches Full Attention for Cross-Sectional Stock Prediction
Holy Grail · Math 7.5/10 · Rigor 8.5/10 · Machine Learning, Factor Investing
MASTER’s inter-stock multi-head attention – the module responsible for modeling cross-sectional stock relationships – accounts for 42.5% of model parameters and 25% of predictive value. We systematically decompose this module and uncover a surprising structure: the learned attention is near-unifor…
2. Market-Informed Networks for Modeling and Forecast Evaluation of Financial Extremes
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Risk Management, Machine Learning
Modeling the joint distribution of extreme values in high-dimensional financial time series is challenging because extremes are sparse and locally extreme observations are not necessarily extreme relative to their full marginal distribution. To address this, we introduce a time-dependent network Hüs…
3. Deep Learning of Robust Market Making under Regime-Switching Order Flow
Holy Grail · Math 7.0/10 · Rigor 8.0/10 · Market Microstructure, Reinforcement Learning
Classical market-making strategies based on stochastic control, such as the Avellaneda-Stoikov and the Guéant-Lehalle-Fernandez-Tapia (GLFT) extension, provide closed-form quoting rules, but rest on assumptions that break down at realistic microstructure timescales. One of them is that order flow is…
4. The Double-Edged Sword of Short-Selling Bans
Holy Grail · Math 7.0/10 · Rigor 8.0/10 · Factor Investing
We develop a theoretical model that endogenizes the regulator’s decision to impose short-selling bans to prevent large stock price declines. Empirically, we test the model’s predictions using the cross-sectional variation in short-selling restrictions implemented across European countries in 2020. C…
5. Entropic Value-at-Risk parity for tempered stable returns
Holy Grail · Math 8.0/10 · Rigor 7.0/10 · Portfolio Optimization, Risk Management
We develop Entropic Value-at-Risk (EVaR) parity for tempered stable returns. EVaR-based inverse risk parity (IRP) and equal risk contribution (ERC) portfolios are constructed using multivariate normal tempered stable models and independent component analysis with tempered stable components. We deriv…
6. AlphaRJM: Reward-Jump Memory for Stochastic Return-Guided Alpha Discovery
Holy Grail · Math 8.0/10 · Rigor 7.0/10 · Reinforcement Learning
Formulaic alpha discovery is a pool-dependent symbolic search problem in which informative feedback is observed primarily when a complete expression is evaluated. This delayed feedback creates two coupled difficulties: the retained alpha pool does not preserve the full history of realized evaluation…
7. Variance-Optimal Hedging in the Rough Hawkes–Heston Model
Holy Grail · Math 9.0/10 · Rigor 6.0/10 · Volatility, Options & Derivatives
We study variance-optimal stock hedging and the convergence of approximate strategies in the rough Hawkes–Heston model. Starting from the model’s affine conditional transform and the affine Volterra jump framework, we obtain semi-explicit hedges for European calls and a representation of the minimu…
8. Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending
Holy Grail · Math 6.0/10 · Rigor 8.0/10 · Machine Learning
Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where applicants strategically alter self-reported inputs to secure favourable decisions, remains poorly understood. Most adversarial-robustness evidence comes…
9. AI for AI: Optimizing Additional Infrastructure Build-out to Power Artificial Intelligence Data Centers
Holy Grail · Math 8.5/10 · Rigor 6.0/10
The twenty-first century’s transformative technology, artificial intelligence, is increasingly constrained by the twentieth century’s transformative technology, the electricity grid. Rapid growth in electricity demand from data centers is leading to higher electricity prices, without a compensating…
10. The Delta of a Variance Swap
Holy Grail · Math 8.5/10 · Rigor 5.0/10 · Options & Derivatives, Volatility
We define the variance swap delta as the sensitivity of the price of variance to a change in underlying price. We use Carr-Madan spanning formulas to analyze this sensitivity when the implied volatility smile curve may depend on the underlying price. We show that the variance swap total delta is zer…
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