Quant LetterNo. 114
110 items across 8 sections, as sent to readers on 3 October 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
20 items
The Santa Fe model, used for analyzing the dynamics of the limit order book, is reevaluated using kinetic theory, leading to a new equation for the order-book density profile and identifying a previous error by E. Smith and colleagues.
24 sharesSource ↗
STRAPSim, a new method for assessing portfolio similarity, surpasses existing measures by using semantic similarity, portfolio share weighting, and residual-aware greedy alignment, proving beneficial in ETF benchmarking, portfolio creation, and systematic execution.
12 shares1 citation todaySource ↗
A novel approach to using neural networks on linear parabolic variational inequalities shows the potential of neural networks in solving optimal stopping and control problems in finance.
9 shares1 citation todaySource ↗
A new deep learning framework for portfolio optimization, which combines LSTM networks, Graph Attention Networks, and financial news sentiment analysis, outperforms traditional benchmarks by directly learning portfolio weights, resulting in higher cumulative returns and Sharpe ratios.
9 sharesSource ↗
The study delves into Meyer risk measures, their structure, applications, and existence, and uncovers a deeper connection between monetary risk measures and second-order stochastic dominance.
8 sharesSource ↗
The review offers practical advice on using machine learning tools in portfolio weight formation, stressing the importance of combining these tools with portfolio choice-objective functions for optimal outcomes.
7 shares1 citation todaySource ↗
The research explores the predictive power of textual features in earnings press releases on stock returns, concluding that press release content is as informative as earnings surprise, with FinBERT being the most predictive.
7 sharesSource ↗
The study investigates the impact of textual features in earnings press releases on stock returns, finding that press release content is as informative as earnings surprise, and that using combined models improves the interpretation of press release content.
7 sharesSource ↗
The AI Productivity Index (APEX) is a new benchmark for evaluating the economic value of AI models in sectors like investment banking, consulting, law, and medical care.
64 shares10 citations todaySource ↗
The article discusses the negative effects of neoliberalism on organized labour in Turkey and Egypt, emphasizing the role of suppressing labour unions in neoliberal restructuring.
26 shares11 citations todaySource ↗
A study reveals a performance gap favoring private schools in Latin America, with home resources and school autonomy being key efficiency determinants.
15 sharesSource ↗
A paper uses PISA 2022 data and machine learning to identify factors affecting student performance in Latin America, emphasizing the need for strategies to address educational inequalities.
15 shares1 citation todaySource ↗
The research highlights household resources, gender, homework, and teaching quality as key factors influencing academic resilience among disadvantaged Latin American students, especially during the pandemic.
14 sharesSource ↗
The paper uses machine learning and PISA 2022 data to identify factors such as language barriers, digital device scarcity, poverty, and poor school conditions as causes of low academic performance in Latin America.
14 shares1 citation todaySource ↗
The study reveals a 'rich-get-richer' trend in earnings of content creators on platforms like Instagram and YouTube, suggesting a need for policies to ensure fair content distribution.
11 sharesSource ↗
The paper introduces a theoretical framework for detecting and estimating treatment effect boundaries across space and time, offering tools to identify when local treatments become systemic and require policy intervention.
10 sharesSource ↗
The article uses advanced mathematical methods to measure the overlap between two large empirical covariance matrices over intersecting time periods. The findings are then applied to financial data.
8 shares1 citation todaySource ↗
The study uses SMOTE and advanced ensemble learning models like XGBoost and LightGBM to effectively detect pump and dump manipulation in cryptocurrency markets, enhancing market transparency and stability.
10 shares1 citation todaySource ↗
Alpha Mining: AlphaSAGE, a new framework for automated alpha mining in quantitative finance, uses a structure-aware encoder and Generative Flow Networks to overcome challenges and outperforms existing methods in creating a diverse and predictive portfolio of alphas.
6 shares14 citations todaySource ↗
A Fresh Perspective: The article introduces a new way to assess mergers after they occur, finding that while major airline mergers may increase efficiency, they also increase coordination. This often results in anti-competitive effects, particularly in later mergers.
17 shares2 citations todaySource ↗
Economics working papers from RePEc's NEP field reports.
30 items
Algorithmic trading and passive investing have caused issues during market downturns like the COVID-19 pandemic and Russia-Ukraine conflict, but a new Automated Adaptive Trading System could stabilize these markets.
27 sharesSource ↗
Machine learning has been used to identify assets contributing to downward trends in the Pakistan Stock Exchange, proposing an optimal asset allocation scheme.
25 sharesSource ↗
Risk parity portfolio optimization using expected shortfall as a risk measure can improve risk-adjusted returns and reduce drawdowns during market stress, especially when accounting for 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, using the Whale Optimization Algorithm, and applies it to forex investment 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 a new approach for analyzing incomplete data, offering faster analysis and less data imputation, and outperforming existing models in predictive performance.
20 sharesSource ↗
A new machine learning strategy, momentum-determined indicator-switching (N-MDIS), is proposed for predicting equity premiums, providing more accurate forecasts than previous methods.
19 sharesSource ↗
The study suggests that increased product market competition leads firms to adopt zero-leverage policies, particularly those with high 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 modified version of Stochastic Gradient Boosting is proposed for estimating production possibility sets in Data Envelopment Analysis (DEA), reducing overfitting and providing a useful tool for scenarios requiring generalization.
16 sharesSource ↗
Machine learning models outperform traditional methods in predicting Chinese corporate mergers and acquisitions, with certain variables significantly impacting prediction accuracy.
28 sharesSource ↗
Two new probabilistic deep learning frameworks have been introduced for estimating financial risk measures, outperforming existing methods and aiding in better capital allocation.
27 sharesSource ↗
Machine learning methods effectively use the volatility of 10-year treasury bond contracts to improve the accuracy of stock market volatility forecasts in China.
24 sharesSource ↗
The article proposes a new algorithm and machine learning model for the Lot Streaming and Scheduling Problem (LSSP) with unpredictable product arrival times, aiming to increase efficiency and accuracy.
16 sharesSource ↗
The paper introduces a new machine learning method for decomposing and analyzing complex time series, providing a potential alternative to the Box-Jenkins method, as shown with COVID-19 financial data.
13 sharesSource ↗
The article develops a monetary policy frictions index using financial news and machine learning, demonstrating that these frictions significantly impact the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
The paper investigates the global housing market's interconnectedness using machine learning and quantile connectedness models, revealing the US market as the primary source of systematic shocks with its interest rate as the key 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 newly introduced MFF‐CPPM model in China has shown higher accuracy and flexibility in predicting carbon trading prices compared to standard models.
10 sharesSource ↗
The research uses machine learning to predict the CBOE Volatility Index, highlighting the importance of weekly jobless claim data in improving trading 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 research indicates that AI capability directly influences firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
The study emphasizes the need for 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 issue of deceptive tactics in the retail investment sector, suggesting the use of behavioral sciences and AI to improve regulation and safeguard investors.
2 sharesSource ↗
The research profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
The article 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, emphasizing the need for interdisciplinary research to assess these initiatives' effectiveness.
2 sharesSource ↗
The paper analyzes literature on factors affecting banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the impact of COVID-19.
1 sharesSource ↗
The study tests the applicability of the Work Need Satisfaction Scale (WNSS) to online gig workers, suggesting modifications to the scale to better reflect the specifics of online platform work.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
Language Agent: QLASS system enhances language agents' performance by offering step-by-step guidance, leading to better decision-making 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 with 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 low computational footprint, enhancing performance in robotics and object detection.
13 shares20 citations todaySource ↗
PoLAr-MAE uses self-supervised learning to analyze complex point cloud data from Liquid Argon Time Projection Chambers, delivering high performance with minimal labeled data.
13 shares9 citations todaySource ↗
Adaptation: LoRA-X enables the transfer of parameters across models without original or synthetic training data, simplifying the fine-tuning process and proving effective in text-to-image generation tasks.
13 shares11 citations todaySource ↗
Open-Vocabulary 3D 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 the development of robotic object manipulation skills.
10 shares53 citations todaySource ↗
Video Restoration with Diffusion Transformer: SeedVR, a diffusion transformer, is capable of restoring real-world videos of any length and resolution, outperforming previous methods in both synthetic and real-world tests.
8 shares70 citations todaySource ↗
A new hierarchical Bayesian multitask learning model has been developed for multi-task binary classification learning, showing superior performance in predicting human health status based on microbiome profiles.
8 shares1 citation todaySource ↗
Dataset for Open-Vocabulary 3D Segmentation: Mosaic3D, a new data generation and training framework, has been introduced for understanding 3D scenes, creating a large-scale dataset and achieving top results in 3D semantic and instance segmentation tasks.
7 shares24 citations todaySource ↗
Panoptic Segmentation and Grounded Captions: The COCONut-PanCap dataset provides detailed descriptions for panoptic segmentation and grounded image captioning, setting a new standard for evaluating models in these areas.
6 shares14 citations todaySource ↗
Repositories the letter featured.
10 items
The article provides the full text of the Python Data Science Handbook in Jupyter Notebook format.
45,621 shares
The article presents the official programming code for the QuantAgent software.
122 shares
The article discusses a language model for analyzing complex medical text and time-series data.
435 shares
The article details the quantization support for native ComfyUI models in GGUF.
2,622 shares
The article describes a fast property graph database with built-in vector and full-text search capabilities.
3,361 shares
AutoHotkey is a software that allows users to automate tasks and create macros on Windows.
11,131 shares
Draw's official electron build, a framework for creating desktop applications, is now accessible.
57,046 shares
Llmd improves the efficiency of distributed LLM inference on the Kubernetes platform.
1,813 shares
ShinkaEvolve is designed to evolve programs in an open-ended and sample-efficient manner.
468 shares
Fmtlog is a fast logging library, similar to fmtlib, that offers nanosecond latency.
932 shares
Industry news: funds, hiring, markets and regulation.
20 items
Hedge funds like Epic Partners and K2 Asset Management are planning to capitalize on Japan's close leadership contest.
6 shares
Edmond De Rothschild is incorporating quantitative investment skills into its WealthBriefing.
4 shares
TrustStrategy has launched an AI Quant upgrade that supports high frequency trading.
4 shares
CoinShares plans to buy London's Bastion Asset Management to boost its active management skills.
3 shares
Hudson River Trading's UK and Ireland staff received an average pay of £652k last year.
3 shares
Irenic Capital Management, a shareholder in Workiva Inc, suggests strategies to increase the software company's share value.
3 shares
Denmark's tax authority, SKAT, loses a £1.9bn lawsuit against hedge fund manager Sanjay Shah over cumex dividend tax schemes.
2 shares
Brevan Howard expands its New York team with Portfolio Manager Hsu from Two Sigma, starting in December.
2 shares
A new investment firm is investing billions in high-performance computing centers.
2 shares
Global Payments has added Patricia Watson and Archana Deskus to its board of directors, following stakebuilding by Elliott Investment Management.
2 shares
MasterQuant's AI trading bot, The Trade Machine, is transforming the landscape of smart investing.
2 shares
Despite a $812m outflow last week, digital asset investment products have seen strong YTD inflows of $39.6bn, nearly equalling last year's record, says CoinShares.
2 shares
Ex-Greenlight Capital analyst, James Fishback, has admitted to leaking confidential information and agreed to cover the hedge fund's legal expenses in a lawsuit against him.
2 shares
Hedge funds have turned bearish on London cocoa for the first time in three years, anticipating increased global supplies after a major crunch in West Africa.
2 shares
Qube Research has seen substantial growth due to a year of aggressive recruitment.
1 shares
The article provides a comparative analysis of prop shops and pod shops.
1 shares
The article explores the subject of pandas and other associated topics.
1 shares
The article delves into the concept of a one in, one out policy or scenario.
0 shares
Nomura boosts its technology team by recruiting another leading technologist from HSBC.
0 shares
Episodes on markets, quant methods and economics.
10 items
Mark Longo and Matt Amberson discuss the growth of options trading, the emergence of zeroDTE trading, and the potential influence of AI on this sector.
12 shares
Jonny Goulden, Anezka Christovova, and Ben Ramsey analyze recent market trends and their effects on the EM fixed income asset class.
8 shares
Colin Reedie and Jason Shoup highlight the advantages of a global strategy in managing fixed income assets and the current market dynamics impacting investors globally.
6 shares
In a Goldman Sachs podcast, Neema Raphael and George Lee explore the role of data in either facilitating or hindering the advancement of AI.
6 shares
Wealth Shipwright: Marty Bicknell, CEO of Mariner, shares his experiences on the expansion of his wealth advisory firm and his thoughts on entrepreneurship, leadership, and the future of wealth management.
6 shares
Kai Wu discusses the AI-driven capital cycle and its potential risks in the LeadLag Live podcast.
4 shares
Alex Gunz talks about the investment potential in longevity science, including genomics and personalized medicine, in an interview with Andrew Wilkinson.
3 shares
Lyn Alden shares her perspective on the current economic situation and potential solutions in the MacroVoices podcast.
2 shares
Andrew Wilkinson, Max Chen, and Derek Yan debate the pros and cons of investing in AI startups versus established tech companies.
2 shares
Andrew Wilkinson, Steve Sosnick, and Steve Sears discuss the SpiderMan Market trend, where investors overlook negative news and continue investing.
2 shares
Posts from quant researchers on X.
4 items
The recent weekly research recap covers topics like predictability of crypto returns, estimation of inflation risk premium, intraday stock-bond correlations, and equity style allocation.
1 shares
Bridgewater's main macro fund experienced a 26.4% growth in the first three quarters of this year.
0 shares
The article discloses that 153 MIT executives with substantial AI budgets favor an AI partner who comprehends their workflows and offers effective advice over one that merely provides advanced technology.
0 shares
Threads from r/quant, r/algotrading and friends.
6 items
55 shares
77 shares
57 shares
132 shares
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66 shares