Quant Letter: June 2025, Week-1

Weekly (94th Edition)

SSRN

Recently Published

Quantitative

Anomaly Persistence: The article introduces a method for testing asset pricing anomalies, showing that multiple paths on the same dataset lead to high outcome correlations, significantly affecting inference. (2025-05-31, shares: 3.0)

Reinforcement Learning for Life Insurance Hedging: A new framework using deep reinforcement learning is suggested to improve the hedging of specific risk factors in financial instruments, using Shapley value decompositions to assign profit and loss to different risk categories. (2025-06-02, shares: 5.0)

Financial Language Models Ontological Reasoning: Large Language Models (LLMs) show limitations and low accuracy in specialized domains due to the absence of domain-specific knowledge in the data used for pretraining, requiring the use of finetuning techniques. (2025-05-29, shares: 3.0)

Shifted Wishart Processes Portfolio Optimization: The Markov-Modulated Shifted Wishart (MMSW) process is utilized to capture covariance dynamics in a portfolio optimization problem, providing a flexible strategy that adapts to sudden market stress and maintains diversification benefits. (2025-06-01, shares: 2.0)

Portfolio Optimization with RL: The authors suggest a new approach to portfolio optimization that incorporates turnover cost and diversification into a convex optimization framework, using reinforcement learning-based control. (2025-05-30, shares: 2.0)

Neural Networks Logarithm Entropy: The article introduces the LogDet estimator, a new matrix-based entropy estimator designed for handling high-dimensional samples in modern machine learning. (2025-05-29, shares: 2.0)

AI Asset Pricing Impacts: The article presents a model that examines the impact of AI on the economy, portfolio choices, and asset prices, suggesting that AI increases output growth and volatility and influences investor behavior. (2025-05-31, shares: 2.0)

Imbalanced Node Classification Exploration: The authors introduce a new method, Topological Node Exploration and Suppression, to tackle the problem of imbalanced class distribution in graph data for semi-supervised learning in Graph Machine Learning. (2025-06-02, shares: 2.0)

Financial

High-D Learning in Finance: The article investigates the role of machine learning in financial forecasting, focusing on the impact of standardization in Random Fourier Features and the challenges of learning in low signal-to-noise environments. (2025-06-04, shares: 8.0)

Volatility Spillovers Model: The study analyzes four GARCH methods in modeling the relationship between petroleum prices and stock indices in Canada, Saudi Arabia, the US, and China, highlighting varied volatility interdependencies. (2025-05-29, shares: 4.0)

FOMO CAPM: The paper presents a Fear of Missing Out (FOMO) Capital Asset Pricing Model, suggesting that investors gain satisfaction from avoiding underperformance compared to their peers. (2025-05-31, shares: 2.0)

Equity Market Response to Shocks: The note reexamines the impact of monetary policy on equity prices, considering changes in interest rates, term premia, and dividend risk compensation. (2025-05-30, shares: 2.0)

Time Preference and Premium: The research studies the time variations of forward premiums in the currency market, pinpointing variables that can predict these changes, especially in less-developed countries. (2025-06-02, shares: 3.0)

Predicting S&P 500 Trajectories: The 3MR Reactive Valuation Model is introduced as a dynamic, retrospective alternative to the dividend discount model, explaining how investors value earnings without using the discounting approach. (2025-06-02, shares: 2.0)

ESG Mania and Trading: The study explores the motivations and economic outcomes of institutional investors flocking to the ESG stock market, uncovering evidence of impact-washing rather than impact-chasing. (2025-06-01, shares: 2.0)

Recently Updated

Quantitative

Big Data Analytics in Finance: The piece highlights the benefits of using Big Data Analytics and predictive modeling in Risk Management within Banks and Financial Services Companies. (2020-12-16, shares: 2.0)

The Farah Model: An Extension of Kyle Model: The document presents the Farah Model, a new framework for modeling price dynamics in financial markets, linking price changes with volatility and volume dynamics. (2025-05-22, shares: 5.0)

Monte Carlo Simulation and Regression Analysis: The research highlights the use of Monte Carlo Simulation in projecting a company's financials for various corporate events, and the role of exotic derivatives in reducing cost of capital. (2015-01-01, shares: 3.0)

Generative AI for Synthetic Data Creation: The paper discusses the use of Generative AI models for synthetic data generation, and how synthetic data can enhance model performance and facilitate privacy-preserving data sharing. (2025-05-23, shares: 2.0)

Sentiment-driven Prices: The paper proposes a model where sentiment-driven asset prices are caused by reference-dependent preferences, solving some asset pricing puzzles. (2023-02-01, shares: 3.0)

Youngsters' Investment Trends: The study reveals a growing interest in investment among the youth, with mutual funds and stocks as their top choices. (2025-04-08, shares: 4.0)

Payout Volatility in Risk Pools: The paper explores the use of longevity risk-sharing pools in defined contribution plans, emphasizing the need for methods to reduce payout volatility. (2025-04-20, shares: 3.0)

AI and Machine Learning in Hedge Funds: The thesis compares the performance of an AI trading model with human-recommended trades, using a 200-trade dataset. (2025-05-24, shares: 2.0)

Financial

RealTime IV Surface Forecasting: A novel two-step real-time sequential forecasting framework is introduced for predicting option implied volatility surface, which performs better than random walk forecasts. (2025-05-26, shares: 3.0)

LSTM Neural Network for Finance: The research compares traditional computing logarithmic returns with the fractional differencing method in machine learning models, revealing that fractional differentiation methods enhance forecasting performance. (2025-05-25, shares: 3.0)

Crypto Portfolio Risk Assessment: The research compares various cryptocurrency portfolio selection strategies, concluding that the Minimum Variance Portfolio performs best but is heavily reliant on Bitcoin. (2025-05-21, shares: 3.0)

Commodity Derivatives Management: Hilary Till's talk to the Professional Risk Managers International Association discusses various risk management aspects, including institutional, proprietary trading, hedge fund diversification, and market risk management. (2008-06-17, shares: 2.0)

ESG Factors and Debt Costs: The paper explores the link between banks' ESG scores and their funding costs, revealing that banks with higher ESG ratings have lower funding costs and that changes in ESG ratings significantly impact banks' bond yields. (2025-05-27, shares: 4.0)

Public Pension Funds and Risk: A study reveals that U.S. public pension funds take on more risk when risk-free rates and funding ratios are low or their sponsors are financially weak. (2025-05-14, shares: 3.0)

Temperature Anomalies Impact Revenues: Companies with higher exposure to temperature anomalies yield higher risk-adjusted returns, indicating investors demand more returns for stocks with high temperature betas. (2025-05-27, shares: 3.0)

Green Investment Awareness in Salaried Women: A study in Ludhiana, India, shows women are generally open to green investments, but lack of information and perceived risks remain as barriers. (2025-05-23, shares: 2.0)

Commodities Returns and Alternatives: Hilary Till spoke at the Women Investment Professionals organization in Chicago, discussing commodity indices, futures contracts, and hedge funds. (2011-09-08, shares: 2.0)

Local Bias in Indian Funds: A study reveals that Indian mutual funds increased their investments in foreign stocks, especially US technology stocks, during the Covid-19 pandemic, resulting in high net returns. (2024-02-23, shares: 2.0)

Co-Jump Asymmetry in Equity Markets: Stocks with higher cojump asymmetry, indicating more left-skewed jump codependence, yield higher average monthly returns, a study using high-frequency stock return data shows. (2017-05-01, shares: 2.0)

Energy Fundamentals Inference from Price Data: Hilary Till spoke at the 7th Annual International Trading Conference in South Korea, discussing the potential and challenges of big data and insights from futures price data. (2017-10-24, shares: 2.0)

Methodological Issues in Environmental Scores: A paper suggests a new classification system for environmental scores used by financial institutions and policymakers, pointing out significant differences among existing scores. (2024-10-18, shares: 3.0)

ArXiv

Finance

Deep Learning for GARCH: A new volatility modeling framework, LSTM-BEKK, is introduced, integrating deep learning into multivariate GARCH processes for improved robustness and forecasting in financial return data. (2025-06-03, shares: 13)

Dynamic Fees in AMMs: The research investigates the best dynamic fees in Automated Market Makers, suggesting fees that are linear in inventory and sensitive to price changes are optimal. (2025-06-03, shares: 20)

Derivative Valuation with ML: A Machine Learning framework for pricing derivative products is introduced, providing accurate results and real-time risk analytics, dynamic hedging, and large-scale scenario analysis. (2025-05-29, shares: 15)

Option Pricing with MPDATA: A method for evaluating path-dependent Asian-style options using a non-oscillatory forward-in-time second-order MPDATA finite-difference scheme is discussed, emphasizing the importance of the MPDATA corrective steps. (2025-05-30, shares: 12)

Drawdowns in Markov Models: A unified framework for computing five key drawdown quantities under general Markov models is proposed, offering efficient algorithms with the same complexity order as those for path-independent problems. (2025-05-31, shares: 11)

Economics

Learning to Regulate: Event-Level Dataset of Capital Controls: The study finds that democracy reduced income inequality in post-socialist countries in Central and Eastern Europe and Central Asia from 2001 to 2016. (2025-05-29, shares: 25)

Analysis and Findings of Capital Controls Dataset: The article introduces a new dataset on Capital Control Measures for 196 countries from 1999 to 2023, showing that inward capital control measures significantly decrease fund inflows within a month, as evidenced by studies on China, Australia, and the US. (2025-05-29, shares: 17)

ESG Strategies: The study introduces a new momentum framework that adjusts to changing ESG sentiment, showing that portfolios with poor ESG performance outperform those with good ESG performance in pro-ESG regimes due to market overreaction, challenging traditional ESG investment beliefs. (2025-05-30, shares: 16)

Bank of England Tweets: Research on 3.13 million tweets related to the Bank of England shows that content quality, timing, and media-rich posts are more effective in engaging audiences than post frequency, indicating that central banks need to update their digital communication strategies. (2025-06-03, shares: 13)

Miscellaneous

AI Agents for ERP Systems: The article discusses an AI-based framework for ERP systems that combines AI and business process modeling to automate complex tasks, reducing processing time and errors. (2025-06-02, shares: 26)

Balancing Profit and Fairness in Pricing: The study introduces a new tax schedule and an open-source simulator, MarketSim, aimed at improving fairness in markets like health insurance and consumer credit by aligning private incentives with social objectives. (2025-05-30, shares: 19)

Pricing and Cost Allocation: The article introduces a new pricing model for electricity markets that enhances power system reliability and efficiently allocates operating reserve costs. (2025-05-30, shares: 18)

Dynamics of Random Surfaces: The study explores the behavior of conformal field theories on random surfaces, which could help replicate multifractal scaling in financial markets. (2025-05-29, shares: 15)

Learning to Optimize Risk Measures: The paper focuses on the estimation and optimization of two convex risk measures, extending them to unbounded random variables and proposing gradient estimators. (2025-06-01, shares: 14)

Historical Trending

AI Threshold for UBI Funding: The study suggests that AI systems need to be 5-6 times more productive than current automation to fund a universal basic income equivalent to 11% of GDP without extra taxes or jobs. (2025-05-24, shares: 44)

Financial Market Trends: The research finds that financial market trends fluctuate over various time periods and asset classes, with trends lasting from a few hours to years, and reversions happening on shorter and longer timescales. (2025-01-28, shares: 34)

Farm Size and Agriculture: The study uses a model to explore the relationship between landscape structure, pesticide use, biodiversity, and farmers' profits, highlighting the importance of considering farm size in environmental policies. (2025-05-23, shares: 27)

Valuation in LLM Summaries: The paper suggests using Shapley values to assess the worth of individual documents in Large Language Model-generated summaries, and introduces an efficient algorithm, Cluster Shapley, to reduce computation while maintaining quality. (2025-05-28, shares: 23)

Fairness in Decision-Making: The research presents marginal fairness, a new concept for fair decision-making considering protected attributes, and proposes a two-step process to ensure decisions are not affected by changes in the distribution of protected attributes. (2025-05-24, shares: 23)

ArXiv ML

Decision Theory for Prediction: The article presents a decision-theoretic foundation that links prediction uncertainty with risk-averse decision-making, resulting in a Risk-Averse Calibration (RAC) algorithm that optimizes action policies from predictions, especially in risk-sensitive areas like medicine. (2025-02-04, shares: 20)

Particle Trajectory Learning: PoLAr-MAE, a self-supervised masked modeling framework, is introduced for 3D particle trajectory analysis in Time Projection Chambers, achieving high classification results without any labeled data. (2025-02-04, shares: 10)

GitHub

Finance

Tensor2Tensor Library: The article introduces a collection of deep learning models and datasets designed to simplify deep learning and accelerate machine learning research. (2017-06-15, shares: 16174.0)

US Stock Notebooks: The article provides a series of notebooks for compiling a comprehensive database of all US stocks and some ETFs at different frequencies. (2023-10-18, shares: 13.0)

KLlamaGym: The article provides guidance on how to optimize LLM agents using online reinforcement learning. (2024-03-01, shares: 1191.0)

LightlyTrain Framework: The article presents LightlyTrain, the first PyTorch framework created to pretrain computer vision models on unlabeled data for industrial applications. (2025-04-10, shares: 328.0)

Trending

Successor of UndetectedChromedriver: Successor of UndetectedChromedriver talks about the new version of the UndetectedChromedriver. (2024-02-20, shares: 2507.0)

Google AI Edge Gallery: A gallery that showcases ondevice MLGenAI use cases and allows people to try and use models locally presents on-device machine learning and AI use cases, with options for local model testing and use. (2025-03-31, shares: 8203.0)

Twitter

New Report on Systematic Strategies and Quant Trading: HedgeNordic has published a report discussing the future of systematic strategies and quantitative trading for 2025, including insightful interviews and discussions. (2025-06-04, shares: 2)

Investing Research Roundup: The article summarizes recent investment research on topics like anomalies, phacking, commodity signals, stock return predictability, and various online resources. (2025-06-03, shares: 0)

Reddit

Quantitative

Trading Book Recs (2025-05-31, shares: 134.0)

Thriving in Trading (2025-05-29, shares: 175.0)

FLOX Trading System (2025-05-29, shares: 66.0)

Georgia Tech vs Manchester (2025-06-02, shares: 47.0)

Citadel Quant Interview (2025-05-29, shares: 38.0)

Rising

NQ Algo Results (2025-05-28, shares: 96.0)

Transitioning to Non-PnL Quant PM (2025-06-02, shares: 71.0)

London Quant Meetups (2025-05-31, shares: 83.0)

FLOX (2025-05-29, shares: 46.0)

Quants and Identities (2025-05-28, shares: 167.0)

Paper with Code

Trending

sktime ROCKET: Current methods for classifying time series data are accurate but computationally complex, making them inefficient for large datasets. (2025-05-29, shares: 8929.0)

microsoft RDAgentQuant: Predicting asset returns is challenging due to the high dimensionality, nonstationarity, and persistent volatility of financial markets. (2025-05-30, shares: 5326.0)

paper2poster: A new benchmark and metric suite for poster generation assesses visual quality, textual coherence, aesthetics, informational criteria, and the poster's effectiveness in conveying the main content of the paper. (2025-06-02, shares: 1424.0)

Alita Generalist Agent: The article explores how Alita uses general-purpose components to independently develop and improve its capabilities from open source, aiding in scalable decision-making. (2025-05-30, shares: 221.0)

Pareto-Optimal AI: The article emphasizes the role of Retrieval-Augmented Generation pipelines in using large language models for proprietary or constantly changing data. (2025-05-30, shares: 174.0)

Rising

BizFinBench: Financial Benchmark for LLMs: An assessment shows unique ability patterns in numerical calculation, reasoning, information extraction, and prediction recognition across different models. (2025-06-02, shares: 131.0)

AudioTrust: Trustworthiness of ALLMs: AudioTrust is a new evaluation framework and benchmark specifically created for assessing the trustworthiness of Automatic Language Learning Models (ALLMs). (2025-05-29, shares: 140.0)

Phi Report: The article presents phi4, a language model with 14 billion parameters that prioritizes data quality during training. (2025-05-29, shares: 89.0)

Oneshot Entropy Minimization: The article shows that training over 13,000 large language models with entropy minimization can significantly improve performance using only one unlabeled data and a 10-step optimization. (2025-06-02, shares: 82.0)

ChartGalaxy Dataset: The article highlights the importance of a dataset in enhancing infographic chart comprehension, setting code generation standards, and facilitating example-based infographic chart creation. (2025-06-02, shares: 52.0)