Quant LetterNo. 113
108 items across 8 sections, as sent to readers on 22 September 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
26 items
Options Optimization: DeltaHedge, an AI-based framework that combines portfolio management with options trading, outperforms traditional strategies and improves risk-adjusted returns in various market conditions.
19 shares5 citations todaySource ↗
Myopic Optimization (MO) outperforms Reinforcement Learning (RL) in portfolio management, resulting in lower costs, increased profits, and reduced model risk.
19 shares1 citation todaySource ↗
The paper highlights the limitations of rough path theory in modeling continuous non-semimartingale assets, suggesting that markets based on this theory are limited to the semimartingale paradigm.
11 sharesSource ↗
The research reveals that the optimal train-test split ratio for large covariance matrix estimation is proportional to the square root of the matrix dimension.
11 shares1 citation todaySource ↗
The study shows that the level of government income support significantly affects the retirement decisions of low-income individuals facing income disaster.
10 sharesSource ↗
The research indicates that adding timing data to machine learning models can enhance the prediction of volume-weighted average price (VWAP).
9 shares1 citation todaySource ↗
The study presents a new reinforcement learning framework for portfolio optimization, which performs well under financial stress and supports dynamic asset allocation.
9 shares2 citations todaySource ↗
The paper proposes a new model for pricing exotic options and structured products, which is more profitable than traditional models but underestimates extreme risks.
8 sharesSource ↗
The research reveals a new characteristic of value at risk (VaR), stating that its subadditivity holds for any confidence level only if the loss random variables are comonotonic.
6 shares5 citations todaySource ↗
The paper discusses the best time to convert retirement savings into a lifetime annuity, considering market and longevity risks, and demonstrates the effect of a health shock on annuitization timing through a numerical example.
6 shares3 citations todaySource ↗
Large Language Models like ChatGPT have boosted earnings for workers in certain occupations without affecting unemployment rates, indicating they enhance income rather than replace jobs.
19 shares2 citations todaySource ↗
A Monte Carlo simulation study suggests that combining human and machine skills is most effective for tasks requiring high generalization, but only if true augmentation is achieved; otherwise, it can be costly due to its dual skill structure.
13 sharesSource ↗
A simulation of the 2024/25 UEFA Champions League reform shows that the tournament format can greatly influence team behavior, with the new incomplete round-robin phase encouraging more offensive play.
10 shares7 citations todaySource ↗
Research shows that European Central Bank interest rate hikes result in a depreciation of the Canadian dollar and a contraction in economic activity, mainly through international trade, while U.S. Federal Reserve shocks impact Canadian financial conditions more directly.
8 sharesSource ↗
The article critically reviews the traditional method of measuring total factor productivity in the public sector, highlighting inconsistencies and advocating for a shift towards non-market valuation methods based on economic theory.
8 sharesSource ↗
The paper presents a deep learning algorithm designed to estimate functional rational expectations equilibria in dynamic stochastic economies, demonstrating its effectiveness through three progressively complex economies.
7 shares3 citations todaySource ↗
The research suggests a U-shaped relationship between electoral integrity and poverty, supported by data from the 2016 U.S. Presidential election and the 2018 U.S. congressional election.
6 sharesSource ↗
The article examines the impact of Generative AI on employment and the macroeconomy, noting significant but context-dependent productivity gains, and calls for more research into adoption dynamics and effects on expertise.
6 shares8 citations todaySource ↗
The report emphasizes the significant benefits of AI for SMEs, with 91% reporting increased revenue, and potential for reducing operational costs by 30% and saving over 20 hours monthly.
8 sharesSource ↗
The study suggests using large language models to process financial news and small models to encode historical context, resulting in improved simulated investment performance.
6 shares2 citations todaySource ↗
Dominant Source of Builder Revenues: The study shows that exclusive transactions, found only in blocks from one builder, make up 84% of total fees paid by transactions in winning blocks on Ethereum's blockchain. This makes them the main source of builder revenues.
12 shares5 citations todaySource ↗
The research evaluates the reliability of Large Language Models in finance and accounting studies, showing they are highly consistent and can surpass human experts in this aspect.
35 shares42 citations todaySource ↗
The article presents Trading-R1, a finance-focused AI model that aligns with trading principles, showing it offers better risk-adjusted returns and fewer drawdowns than other models.
35 shares17 citations todaySource ↗
The study introduces EMDLOT, a new framework for predicting multi-class bond defaults in China's bond market, which outperforms traditional and deep learning models by combining numerical and textual data.
12 sharesSource ↗
The research measures the effect of Hurricane Harvey on Texas' construction industry wages and employment, showing a significant wage increase and a steady rise in employment post-disaster.
12 sharesSource ↗
The article examines consumer preference between human and robot service in last-mile delivery, finding that product privacy sensitivity, product value, and environmental complexity significantly influence consumer choice.
11 shares1 citation todaySource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The rise of algorithmic trading and passive investing has caused issues during market downturns, but a new Automated Adaptive Trading System could help stabilize emerging markets during these times.
27 sharesSource ↗
Machine learning has been used to pinpoint assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization plan for effective asset allocation.
25 sharesSource ↗
Using expected shortfall as the risk measure in risk parity portfolio optimization can lessen sensitivity to volatility shocks, decrease portfolio turnover during market turmoil, and enhance risk-adjusted returns considering fat-tailed returns.
16 sharesSource ↗
The research finds that Sharpe Ratio Minimae and Maximae trading strategies are more profitable than the buy-and-hold strategy in global markets, supporting the Adaptive Market Hypothesis.
15 sharesSource ↗
The study introduces a new window analysis method for assessing decision-making units' efficiency over time, using the Whale Optimization Algorithm, and applies it to foreign exchange strategies and utility companies in the Ho Chi Minh City Stock Exchange.
11 sharesSource ↗
The paper uses a new data augmentation technique to study poverty in the Middle East and North Africa, specifically Lebanon, using alternative data sources when traditional income data is scarce or unavailable.
10 sharesSource ↗
The blockwise reduced modeling (BRM) method is introduced for better analysis of missing patterns in data, offering faster and more accurate predictions by minimizing data imputation.
20 sharesSource ↗
A new machine learning strategy, momentum-determined indicator-switching (N-MDIS), is proposed for improving equity premium prediction, outperforming previous methods.
19 sharesSource ↗
Research shows that increased product market competition (PMC) prompts firms to adopt zero-leverage (ZL) strategies, especially those with higher earnings volatility, emphasizing the influence of earnings volatility on capital structure decisions.
18 sharesSource ↗
The paper reassesses the impact of news sentiment on stock return volatility, demonstrating that accurately measured news sentiment significantly influences intraday stock return volatility, with GPT-4 classification outperforming RavenPack.
16 sharesSource ↗
A version of Stochastic Gradient Boosting is suggested to prevent overfitting in Data Envelopment Analysis (DEA), providing a useful tool for scenarios requiring generalization and showing strong performance in high-dimensional settings.
16 sharesSource ↗
Machine learning models are more effective than traditional methods in predicting Chinese corporate merger and acquisition activities.
28 sharesSource ↗
Two new probabilistic deep learning frameworks have been proposed for estimating financial risk measures, aiding in better capital allocation in financial institutions.
27 sharesSource ↗
Machine learning methods can accurately predict Chinese stock market volatility using the volatility of long-term treasury bond contracts, particularly those of 10 years.
24 sharesSource ↗
The article proposes a new algorithm and machine learning model to improve efficiency and accuracy in the Lot Streaming and Scheduling Problem with stochastic product arrival times.
16 sharesSource ↗
The paper introduces a new machine learning technique for analyzing and modeling complex time series, providing an alternative to the Box-Jenkins methodology.
13 sharesSource ↗
The study uses machine learning to create a monetary policy frictions index, revealing that these frictions significantly impact the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
The research uses machine learning to study the international housing market, finding that the US market is the main source of systematic shocks and its interest rate is the most influential global factor.
10 sharesSource ↗
ML vs. DL: Deep learning methods have been found to be more effective than traditional machine learning in predicting oil prices, especially during crises.
31 sharesSource ↗
The MFF-CPPM, a new model tested in China's largest carbon trading market, has shown superior accuracy and flexibility in predicting carbon trading prices compared to standard models.
10 sharesSource ↗
The article discusses a machine learning approach to predict the CBOE Volatility Index, highlighting the importance of weekly jobless claim data for investment and risk management strategies.
23 sharesSource ↗
The study reveals that traditional machine learning models outperform deep learning models in predicting stock price direction in the Eurozone banking sector.
13 sharesSource ↗
The paper suggests that AI capability directly influences firm performance, with a data-driven culture and AI infrastructure playing significant roles.
5 sharesSource ↗
The article emphasizes the role of communication and a holistic approach in addressing climate change, using machine learning to analyze social media discussions on the topic.
4 sharesSource ↗
The research investigates the problem of dark patterns in retail investment, suggesting the use of behavioral sciences and AI to improve regulation and protect investors.
2 sharesSource ↗
The study profiles young informal workers in the EU27 pre-pandemic, aiming to inform future research on Covid-19's impact on youth labor market informality.
2 sharesSource ↗
The paper discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
The review investigates the link between e-governance initiatives and citizen participation, highlighting e-governance evolution and knowledge gaps, especially concerning long-term sustainability and impact.
2 sharesSource ↗
The paper analyzes literature on factors affecting banks' performance, proposing new research areas, particularly around digital transformation, artificial intelligence, and FinTechs.
1 sharesSource ↗
The study tests the Work Need Satisfaction Scale's (WNSS) suitability for online gig workers, suggesting the scale's adaptation to better understand online platform work and improve worker satisfaction and well-being.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
QLASS is a new method for language agents that enhances performance in complex tasks through generating annotations in a stepwise manner, even with limited supervision.
189 shares19 citations todaySource ↗
The Risk-Averse Calibration algorithm improves decision-making in risk-sensitive areas like medicine by linking prediction uncertainty to risk-averse decision-making, ensuring safety while maximizing utility.
20 shares46 citations todaySource ↗
STRING, an upgrade of Rotary Position Encodings, offers exact translation invariance and reduced computational footprint, enhancing performance in robotics and object detection.
13 shares20 citations todaySource ↗
PoLAr-MAE uses self-supervised learning to analyze complex data from Liquid Argon Time Projection Chambers, achieving high performance with less labeled data compared to supervised methods.
13 shares9 citations todaySource ↗
Cross-Model Adaptation: LoRA-X enables the transfer of parameters across models without requiring original or synthetic training data, making the fine-tuning process easier for large foundation models.
13 shares11 citations todaySource ↗
3D Object Modeling: Articulate Anymesh is a new system that transforms any 3D mesh into a movable object, broadening the scope of 3D modeling and assisting in robotic manipulation training.
10 shares53 citations todaySource ↗
Video Restoration with Diffusion Transformer: SeedVR, a diffusion transformer, excels at restoring real-world videos of any length and resolution, surpassing other methods in preserving quality and retrieving details from damaged videos.
8 shares70 citations todaySource ↗
A hierarchical Bayesian multitask learning model has been developed for multi-task binary classification, showing superior results in predicting human health from microbiome profiles, even with varied datasets.
8 shares1 citation todaySource ↗
Dataset for 3D Segmentation: Mosaic3D, a new data generation and training system, has been launched for understanding 3D scenes, achieving top results in 3D semantic and instance segmentation tasks.
7 shares24 citations todaySource ↗
Panoptic Segmentation and Captions: The COCONut-PanCap dataset, featuring advanced panoptic masks and detailed captions, improves panoptic segmentation and image captioning, setting a new standard for evaluating models in multi-modal learning.
6 shares14 citations todaySource ↗
Repositories the letter featured.
10 items
A new open-source financial machine learning library, utilizing Numba, has been created for quick processing of trades and advanced quantitative research.
33 shares
A new Web Data API for AI has been launched, enabling websites to be transformed into LLM-ready markdown or structured data.
57,460 shares
The Model Context Protocol (MCP) has been introduced for Financial Modeling Prep, facilitating AI assistants to access and analyze financial data and market insights.
49 shares
A new toolkit for Deep Reinforcement Learning has been developed, allowing the recording, replaying of cryptocurrency limit order book data, and training of a DDQN agent.
924 shares
LEANN has launched a RAG application that saves storage space and maintains privacy on personal devices.
2,654 shares
GUI App and Toolkit: The Claude Code Toolkit is a GUI app that enables the creation and management of custom agents and secure sessions.
16,413 shares
Powerful Agent Framework: An agent framework is available that provides advanced features using open-source models.
2,952 shares
Using Claude: Various notebooks and recipes show innovative and efficient ways to use the Claude platform.
20,038 shares
Free Domain: DigitalPlat FreeDomain provides free domain services to all its users.
98,688 shares
Industry news: funds, hiring, markets and regulation.
15 items
The Commodity Futures Trading Commission (CFTC) has allowed Japan Securities Clearing Corp (JSCC) to clear yen-denominated interest rate swaps for US clients, benefiting hedge funds.
6 shares
Hedge funds have rapidly increased optimistic investments in crude oil due to escalating geopolitical conflicts in the Middle East and Eastern Europe.
5 shares
Jain Global, a hedge fund owned by Bobby Jain, has bolstered its investment team by appointing ex-BlackRock partner and specialist, Joseph Kansao, as a Portfolio Manager.
3 shares
The US SEC has postponed new hedge fund disclosure requirements until October 2026.
3 shares
Getting an internship in electronic trading market making or high-frequency trading is difficult.
3 shares
Little Harbor Advisors is launching a multi-manager short-only hedge fund targeting financials, real estate, private equity, and solar energy.
3 shares
AlphaQuest, a quantitative hedge fund, reported an 11.4% decrease in 2025 until the end of August.
2 shares
The Managed Funds Association is urging the SEC to alter regulations restricting hedge funds' involvement in public offerings after shorting the same stock.
2 shares
From SecDB to Databricks explores the shift or comparison between two data management platforms.
1 shares
Five Rings' London branch has seen a substantial decline in performance over the previous year.
1 shares
A US court has backed Elliott Investment Management's bid to purchase Citgo Petroleum’s parent company, PDV Holding, via a court-directed share auction.
1 shares
LSEG DampA has integrated REDI into Workspace, enhancing execution management on its main platform for investor's frontoffice workflows.
1 shares
Digital asset products saw $3.3bn inflows, increasing AuM to $239bn, nearing August's record due to improved bitcoin and ether sentiments, according to CoinShares' report.
1 shares
Episodes on markets, quant methods and economics.
10 items
Gordillo, Philbrick, and Butler explore the potential advantages of managed futures in the current economic climate, emphasizing diversification and their ability to add value in different market situations.
14 shares
The article explores the role of AI in finance, emphasizing its efficiency in automating tasks but warns against making it the primary focus of a business.
12 shares
Dr. Erikson's book Investable critically analyzes how pandemics are turned into investment opportunities by international bankers and investors, raising ethical concerns.
9 shares
Goulden, Ramsey, Hong, and Mejabi discuss the impact of the Fed cut on Emerging Markets and share insights from a conference in London.
8 shares
Brandon Thor, in a LeadLag Live episode, discusses the lack of gold in modern portfolios and advocates for its role in wealth protection.
7 shares
Traders Greg and Eric explain the collar strategy for risk management in trading, using Apple and Nvidia as examples.
6 shares
Dr. J Calvin Schermerhorn's book examines the racial wealth gap in America through the experiences of seven Black families.
6 shares
US and European Rates strategists, Phoebe White and Frida Infante, discuss August inflation data and future inflation market predictions in a 2025 podcast.
6 shares
AI Unicorn Pre-IPO Exposure: Derek Yan from KraneShares explains how the AGIX ETF is changing AI investing by providing exposure to private AI companies in a webinar.
6 shares
Fed Cutting Cycle Outcomes: Natasha Kaneva and Greg Shearer analyze the impact of previous and current Fed cutting cycles on commodity performance.
5 shares
Posts from quant researchers on X.
1 items
The latest investing research roundup discusses topics including the impact of news sentiment on commodity returns, volatility decay in leveraged ETFs, post-FOMC drift in option returns, and predictions for commodity option returns.
3 shares
Threads from r/quant, r/algotrading and friends.
6 items
1 shares
102 shares
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23 shares