Quant Letter: June 2025, Week-2

Weekly (95th Edition)

SSRN

Recently Published

Quantitative

Financial Optimization Strategies: The paper suggests a new approach to handle model uncertainty in quantitative finance, proposing an ad hoc subsampling strategy when a natural model distribution is absent. (2025-06-08, shares: 2.0)

Deep IV Factor Models: The Deep Implied Volatility Factor Model, combining neural networks and linear regression, is proposed for estimating the daily Implied Volatility surface of individual stock options, improving performance around earnings announcements. (2025-06-05, shares: 2.0)

Bayesian VAR Count Data Forecasting: The article introduces a new method for predicting and modeling time series data, capable of managing overdispersion, skewness, and changing volatility. (2025-06-09, shares: 5.0)

Market Power Abuse Electricity Markets: The study examines the relationship between hedging and potential market power abuse in wholesale electricity markets, calculating the hourly economic incentives for non-competitive behavior. (2025-06-09, shares: 4.0)

Mathematical Causal Graphs: The paper presents a mathematical framework for studying Causal Graphs with Dynamic Trace GCTD, aiming to pioneer a new research field in discrete mathematics and network theory. (2025-06-06, shares: 4.0)

Gamma Scalping American Option Valuation: The paper reassesses the strategy and value of American-style options contracts, highlighting the importance of gamma scalping profitability in the decision to stop. (2025-06-07, shares: 4.0)

Liquidity Flows Bank-Affiliated Broker Dealers: The paper studies the function of repo lending within the same bank holding company, discovering that internal liquidity channels aid in distributing liquidity from high-reserve banks to the broader financial system. (2025-06-09, shares: 3.0)

SP 500 Index Option Returns Market Reversals: The article presents new evidence supporting demand-based option pricing theory and the limits of arbitrage in option pricing, indicating that imperfect hedging or weekly rebalancing yield higher risk-adjusted returns for option writers. (2025-06-05, shares: 2.0)

Time Series Stationarity Testing: The article emphasizes the importance of the DickeyFuller Test and Augmented DickeyFuller ADF Test in confirming time series stationarity, crucial in actuarial science, quantitative finance, and machine learning. (2025-06-10, shares: 2.0)

Vision-Language Model Evaluation: The study introduces a surrogate model to assess the resilience of vision-language models to minor perturbations, using adversarial perturbations in text and image modalities. (2025-06-05, shares: 3.0)

Fraud Detection Diffusion Model: The paper presents a class-balanced diffusion model to enhance credit card fraud detection, using a two-stage process to improve the quality of minority-class samples and remove noisy synthetic samples. (2025-06-09, shares: 2.0)

Financial

Patent Descriptions: A new dataset has been developed using natural language processing and machine learning, providing detailed tech information about US public firms and patents over 30 years, aiding profitable trading strategies. (2025-06-07, shares: 5.0)

Safety in a Global World: A proposed portfolio theory framework models safety as a variable, investor-specific property that changes based on geographical, political, and institutional factors, rather than assuming a universally risk-free asset. (2025-06-07, shares: 3.0)

Firm Linkages: The new Characteristic Vector Linkages (CVLs) method estimates firm linkages and constructs profitable momentum spillover trading strategies, with Quantum Cognition Machine Learning outperforming Euclidean similarity. (2025-06-09, shares: 3.0)

Portfolio Skewness with Semidefinite Relaxation: A method to estimate higher portfolio moments like skewness using semidefinite relaxation is presented, showing that portfolio skewness can enhance the skewness of the optimal portfolio. (2025-06-06, shares: 2.0)

FAIR Framework for Financial Systems: The FAIR framework is expanded to tackle temporal challenges in financial operations, offering guidelines for financial institutions using Large Language Models and autonomous systems. (2025-06-08, shares: 2.0)

Climate Metrics for Investments: The integration of climate metrics into investment portfolios as optimization constraints is demonstrated, indicating that the MSCI World Index can handle high integration of climate metrics with minimal performance or tracking error losses. (2025-06-05, shares: 2.0)

Business Cycles and Information Networks: Network informativeness, or the ease of information flow across sectors, is a leading indicator of real business cycles, with increased information flow leading to stronger industrial production and real GDP. (2025-06-06, shares: 2.0)

Recently Updated

Quantitative

Optimizing Large Language Models: The article categorises and reviews the optimisation methods used in Large Language Models like ChatGPT, Claude LlaMA, and DeepSeek. (2025-05-01, shares: 16.0)

Quantum Machine Learning for Trading: The study investigates the use of quantum machine learning to optimise high-frequency trading strategies in US treasuries and forex markets. (2024-12-25, shares: 3.0)

Hedging Risks with Reinforcement Learning: A proposed framework uses deep reinforcement learning to optimise hedging of specific risk factors in financial instruments. (2025-06-02, shares: 5.0)

Kelly Betting with Recovery Constraints: The paper suggests a modified Kelly optimization that balances long-term growth with short-term recovery risk in skewed return environments. (2025-06-03, shares: 6.0)

Venture Capitalists: The study shows a negative impact of individual investments by venture capital partners on their institutional investments' performance. (2025-05-29, shares: 5.0)

AIDriven Financial Advisory: The research discusses the impact of AI on personal finance through robo-advisors, their evolution, functionalities, industry impact, and challenges. (2025-05-24, shares: 4.0)

Big Data Analytics for Risk Management: The article reviews the use of Big Data Analytics and predictive modeling in Risk Management for optimising transactions and operations in banks and financial services companies. (2020-12-16, shares: 2.0)

Machine Learning in Market Prediction: The article investigates the use of Machine Learning for predicting market crashes, highlighting the challenges and techniques involved. (2024-06-01, shares: 2.0)

NLPdriven Market News Measure: The article introduces the Hype Index, a tool that measures media attention towards large-cap equities using Natural Language Processing. (2025-05-30, shares: 3.0)

Sentiment-driven Asset Prices: The study presents a model that uses reference-dependent preferences to explain sentiment-driven asset prices and other asset pricing anomalies. (2023-02-01, shares: 3.0)

Ontological Reasoning for Financial Markets: The article discusses the limitations of Large Language Models in specialized areas and recommends fine-tuning techniques using domain-specific data. (2025-05-29, shares: 3.0)

Reinforcement Learning for Financial Wellness: The study suggests a new approach combining reinforcement learning, behavioral analytics, and natural language processing for personalized financial advice. (2025-03-18, shares: 3.0)

Portfolio Optimization with MMSW Processes: The study presents a portfolio strategy using the Markov-Modulated Shifted Wishart process to maintain diversification benefits during stable periods and lessen the impact of correlation spikes during crises. (2025-06-01, shares: 2.0)

Financial

Modelling Volatility Spillovers: The research compares the relationship between petroleum prices and stock sector indices in Canada, Saudi Arabia, the US, and China, showing varying volatility and optimal portfolio weights. (2025-05-29, shares: 4.0)

RealTime Forecasting of Volatility Surfaces: A new forecasting framework is proposed for predicting the option implied volatility surface, which performs better than random walk forecasts on SP 500 IV surfaces. (2025-05-26, shares: 3.0)

Commodity Futures Investment: Hilary Till discusses the commodity investment universe, covering topics like investment focus, return rationale, portfolio construction, and risk management. (2004-09-02, shares: 3.0)

FOMO-CAPM for Stock Returns: The FOMO Capital Asset Pricing Model suggests that investors' fear of underperforming peers significantly influences stock returns, based on an analysis of U.S. equities from 1980 to 2024. (2025-05-31, shares: 2.0)

Temperature Exposure and Firm Revenues: Research shows that temperature anomalies impact firm-level risk and stock returns, leading firms to increase their green revenues to mitigate this risk. (2025-05-27, shares: 3.0)

Quantum Estimation of Volatility: Two new methods for estimating stochastic volatility diffusions, using Quantum-Inspired Classical Hidden Markov Models and Quantum Hidden Markov Models, provide easy-to-calculate likelihood functions and filtering algorithms. (2025-05-29, shares: 2.0)

AI Revolution in Investment: The growth of AI in finance, especially in investment advisory, is boosting retail investor participation and financial inclusion, but also raises concerns about algorithmic bias, data privacy, and regulatory adequacy. (2025-05-26, shares: 3.0)

ArXiv

Finance

Japanese Financial Benchmark: EDINET-Bench, a new open-source Japanese financial benchmark, is introduced to assess large language models' performance in financial tasks, showing these models' limitations in real-world financial applications. (2025-06-10, shares: 25)

Neural Jump Model: A neural jump stochastic differential equation model is proposed for option pricing, combining neural networks with the traditional jump diffusion model, enhancing pricing accuracy. (2025-06-05, shares: 7)

Optimal Hedging: A theoretical framework is developed for optimal hedging strategies for an informed broker dealing with multiple traders, using a mean-field game approach to establish equilibrium strategies. (2025-06-10, shares: 6)

Predicting Realized Variance: The article investigates the predictability of individual equity options based on the volatility discrepancy, indicating that enhanced forecast error measurements can significantly improve portfolio performance. (2025-06-09, shares: 6)

Model Uncertainty: The study proposes a new theory to explain conflicting observations in market microstructure, attributing price formation to the average impact of metaorders and supporting the Order-Driven theory of excess volatility. (2025-06-09, shares: 5)

Bachelier Volatility: The research presents a new theoretical framework that resolves contradictions in market microstructure, suggesting that price formation is primarily influenced by the average impact of metaorders and endorsing the Order-Driven theory of excess volatility. (2025-06-09, shares: 4)

Stochastic Portfolio: The study explores the asymptotic behaviour of Implied Volatility in the Bachelier setting, providing explicit expressions for the Bachelier Implied Volatility and linking these to the tail behaviour of the underlying's returns' distribution. (2025-06-09, shares: 4)

Price Impact: The research establishes a framework for stochastic portfolio theory that includes modern nonlinear price impact and impact decay models, deriving formulas for an investor's relative wealth and conditions for relative arbitrage in the price impact setting. (2025-06-09, shares: 3)

Uncertainty-Aware Finance: The paper tackles model uncertainty in quantitative finance by improving the conventional objective with an outer uncertainty measure, suggesting a subsampling strategy to approximate model uncertainty and introducing a modified stochastic gradient descent algorithm for efficient parallelization. (2025-06-08, shares: 3)

Economics

Bank Failures Prediction: A study reveals that US bank failures from 1863 to 2024 are mainly due to worsening bank fundamentals like increasing asset losses and reliance on costly noncore funding. (2025-06-06, shares: 11)

Reinforcement Learning for Choice: A new framework based on deep reinforcement learning has been introduced to enhance the process of discrete choice modelling, adapting strategies dynamically without needing prior domain knowledge. (2025-06-06, shares: 6)

Mechanized Proofs of vNM Utility: The von Neumann-Morgenstern expected utility theorem has been thoroughly formalized using the Lean 4 interactive theorem prover, offering a solid base for applications in economic modeling, AI alignment, and management decision systems. (2025-06-08, shares: 6)

Industrial Flexibility Investment: A paper introduces a multi-stage optimization framework to support investment decisions in flexible assets and enable reserve market participation, in response to increasing renewable energy sources and complex market conditions. (2025-06-10, shares: 4)

Miscellaneous

Imitation Learning for Optimal Execution: The article introduces flowOE, a new imitation learning framework that improves traditional financial market strategies, resulting in increased profits and lower risk. (2025-06-06, shares: 13)

Transformer-Based Option Pricing: The study presents flowOE, a unique imitation learning model that improves and learns from traditional financial market strategies, surpassing other models. (2025-06-06, shares: 12)

Enhancing Financial Forecasting with Informer: The research uses the Informer neural network for option pricing in financial markets, showing its improved performance over traditional models and improving financial forecasting. (2025-06-05, shares: 9)

Crypto & Blockchain

Ethereum Analysis: Ethereum blockchain data shows 85% of transaction fees are from exclusive transactions, causing user transaction delays, and two bots are trading more efficiently than Binance. (2025-06-05, shares: 19)

AI Trading: Deep Reinforcement Learning algorithms, specifically DDQN and PPO, are effective in stock market trading, providing better risk-adjusted returns than traditional methods. (2025-06-05, shares: 17)

Order Book Dynamics: Simpler models with data preprocessing and hyperparameter tuning can match or surpass complex networks in short-term cryptocurrency price forecasting. (2025-06-06, shares: 12)

Price Discovery: Centralized markets typically lead in Ethereum price discovery compared to decentralized exchanges, affecting liquidity, arbitrage, and market efficiency. (2025-06-10, shares: 4)

Futures Funding Rates: By designing suitable funding rates, the perpetual future price of cryptocurrencies can align with the target value, providing issuers an effective hedging method. (2025-06-10, shares: 3)

Historical Trending

AI Misinformation: A new AI framework has been created to quickly produce prebunking strategies against misinformation, which has been shown to decrease belief in election rumors and boost faith in election integrity across political divides. (2024-10-25, shares: 237)

Zonal Electricity Markets: Research using a unique open-source electricity market model indicates that transitioning to a zonal market in Great Britain could lead to substantial consumer savings and socioeconomic advantages, despite potential rises in capital costs. (2025-06-04, shares: 29)

HighDimensional Finance: A study provides theoretical and empirical evidence for understanding the circumstances and methods through which machine learning achieves predictive success in finance, suggesting that successful predictions are more likely to come from simpler factors rather than complex mechanisms. (2025-06-04, shares: 20)

Market Power in Electricity Markets: Research shows wholesale electricity markets are manipulated by companies to alter prices based on hourly profitability, indicating market power abuse. (2025-06-04, shares: 15)

Interpretable LLMs for Credit Risk: A review of Large Language Models in credit risk estimation provides a classification of model structures, data types, and application areas to guide future AI and finance research. (2025-06-04, shares: 15)

Human-AI Collaboration in Financial Advice: A study with a European bank reveals customers are more likely to follow investment advice from a human-AI collaboration than pure AI, indicating human involvement can improve consumer outcomes. (2025-06-04, shares: 14)

ArXiv ML

Rankify: Python Toolkit for Retrieval: The article introduces Rankify, an open-source toolkit designed to integrate retrieval, re-ranking, and RAG processes, aiming to improve retrieval and re-ranking methodologies while ensuring consistency and ease of use. (2025-02-04, shares: 21)

Decision Theory for Conformal Prediction: The paper establishes a connection between prediction uncertainty and risk-averse decision-making, leading to an algorithm, Risk-Averse Calibration (RAC), which optimizes action policies from predictions, showing its benefits in areas like medical diagnosis and recommendation systems. (2025-02-04, shares: 20)

GitHub

Finance

Interactive Python Dashboards: The article explores the use of Python interactive dashboards for data science education. (2024-03-26, shares: 1653.0)

AI Stock Analysis Framework: The article introduces an AI framework for stock analysis and prediction, incorporating various data sources and compatible with web pages and MCP SERVER. (2025-05-08, shares: 123.0)

AI Stock Analysis Github: The article reiterates the introduction of an AI framework for stock analysis and prediction, using multiple data sources and compatible with web pages and MCP SERVER. (2025-05-08, shares: 106.0)

Trending

Agentic PM Framework: The article presents an AI-based framework for handling complex projects, modeled after real-world team management. (2025-05-12, shares: 432.0)

Google Quickstart: The article provides a guide on creating Fullstack Agents using the Gemini 2 platform. (2025-05-22, shares: 5139.0)

ScrapydWeb Management: The piece discusses a web application for managing Scrapy clusters, analyzing logs, and sending alerts via a mobile interface. (2018-09-30, shares: 3292.0)

Twitter

Quantitative

Investing Research Roundup: The latest investment research roundup discusses topics including cryptocurrency volatility, stock return sentiments, ESG's value indication, and volatility forecasting. (2025-06-10, shares: 4)

Advances in Econometrics Reading List: ChristineCai27 has curated a reading list featuring recent developments in the field of applied econometrics. (2025-06-06, shares: 1)

Miscellaneous

VShaped Recoveries Rising: Article 1: The article explores the growing trend of V-shaped recoveries in the economy. (2025-06-10, shares: 0)

Timing the Market: A Bad Idea: Article 2: The article challenges the argument against market timing, dismissing the fear of missing the best days, but cautions about its complexity. (2025-06-05, shares: 0)

Reddit

Quantitative

Trendfollowing CTAs Underperformance (2025-06-07, shares: 60.0)

Platform Sharing Backtesting (2025-06-06, shares: 189.0)

Prop Trader vs Optiver Trader Skills (2025-06-08, shares: 111.0)

XGBoost Experience (2025-06-06, shares: 70.0)

Bank Quant vs Prop Trading Firm (2025-06-08, shares: 42.0)

Rising

IB API Issues (2025-06-09, shares: 59.0)

Linear vs NonLinear Contrast (2025-06-07, shares: 78.0)

Exiting Subreddit (2025-06-05, shares: 396.0)

Latest Project Share (2025-06-04, shares: 133.0)

Transferring to Lesser-Known College's Impact on Quant Recruiting (2025-06-04, shares: 47.0)

Paper with Code

AutoAgent: Automated LLM Framework (2025-06-08, shares: 4632.0)

Sequential Models in Data Vault (2025-06-10, shares: 3008.0)

Automated Failure Attribution (2025-06-10, shares: 155.0)

Earth System Forecasting (2025-06-08, shares: 125.0)