This week the pipeline scored 49 new papers. Here are the 10 strongest by our rigor-weighted score (how scoring works).
1. The Logic of Factor Portfolios: Boolean Rules, Interactions, and Trading Costs
Holy Grail · Math 8.0/10 · Rigor 9.0/10 · Factor Investing, Volatility
Investors turn signals into holdings through decision rules: buy the top decile, hold stocks with high momentum and low volatility, exclude stocks that fail a screen. Many such rules are Boolean functions of threshold statements about signal ranks, and writing them this way shows both what a rule ho…
2. Polynomial-Preserving Processes and Volatility Modelling in Discrete Time
Holy Grail · Math 9.0/10 · Rigor 8.0/10 · Volatility, Options & Derivatives
This paper develops a discrete-time framework for volatility modelling and derivative pricing based on polynomial preservation. The framework provides exact moments of arbitrary order and serial cross-moments of variance and return processes over any finite horizon through finite-dimensional matrix…
3. Trained, Frozen, or Absent: Identifying What a Quantum Layer Contributes to Cross-Sectional Equity Ranking
Holy Grail · Math 6.5/10 · Rigor 9.5/10 · Factor Investing
Hybrid quantumclassical models are increasingly proposed for nancial prediction, but reported gains are rarely separated from the classical components around them. We study a hybrid quantum temporal convolutional network for daily cross-sectional ranking of 2000 Tokyo Stock Exchange equities under a…
4. Conformal Risk Certificates for Portfolio Optimization Under Uncertainty: A Gated Reinforcement-Learning Approach
Holy Grail · Math 8.0/10 · Rigor 8.5/10 · Reinforcement Learning, Portfolio Optimization
Reinforcement-learning portfolio policies can optimize allocations from prices, covariances, and prior positions, yet they lack a calibrated, replayable mechanism for certifying that a proposed allocation respects a bounded risk envelope before execution. Regulators increasingly expect automated por…
5. TAPES: Terminal Adjoint-Propagated Error Scheduling for Financial Diffusion Samplers
Holy Grail · Math 8.5/10 · Rigor 8.0/10 · Risk Management
Financial diffusion samplers are often reused with a small number of function evaluations (NFE) inside scenario and risk pipelines, where numerical time-grid error can distort terminal quantities such as covariances, tails, and drawdown proxies. We study offline grid construction for a frozen probab…
6. Does a Trading Policy Need to Know What It Trades? Microstructure Invariance and Zero-Shot Transfer of Execution Policies
Holy Grail · Math 6.5/10 · Rigor 9.0/10 · Market Microstructure, Reinforcement Learning
Execution algorithms are calibrated asset by asset, because the queues, trade rates and bid-ask spreads they face differ by orders of magnitude across assets. For reinforcement learning this is zero-shot generalisation across contexts of very different scales, and microstructure invariance proposes…
7. Diversified-Risk-Perception Risk Measures and Portfolio Selection
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Risk Management, Portfolio Optimization
Traditional risk measures generally rely on a single probability model, potentially overlooking information from alternative models and leading to biased risk assessments. This limitation cannot be addressed by asset diversification alone in risk management. In this paper, we propose a Diversified-R…
8. Dynamic Scenario-Based Portfolio Optimization for Multi-Asset ETFs
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Volatility, Risk Management
Portfolio outcomes may depend as much on trading restrictions as on how returns are modeled. We compared historical moving-window returns with conditional scenarios from ARMA–GARCH models and a Student-$t$ copula for 30 U.S.-listed exchange-traded funds. Matched mean–variance and conditional value…
9. Deceleration without identification: testing a power-law trend in Bitcoin prices under persistent noise
Holy Grail · Math 7.5/10 · Rigor 8.0/10 · Crypto & DeFi
Plotted against time since its first block on logarithmic axes, the price of Bitcoin lies close to a straight line, and a power law in time has been proposed as its long-run trend. A good fit is weak evidence: when deviations from a trend are as persistent as a random walk, regressions on time find…
10. Joint modelling of financial cost and carbon footprint in motor insurance claims: a BINAR(1) decision framework for circular auto parts adoption
Holy Grail · Math 8.5/10 · Rigor 7.0/10 · Insurance & Actuarial
Motor insurance claims management increasingly faces a dual objective: controlling claim costs while reducing greenhouse-gas emissions associated with vehicle repair decisions. This paper proposes a bivariate, discrete-time modelling framework that links the dynamics of financial claims and repair-r…
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