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.
20 shares15 citations todaySource ↗
Quant LetterNo. 100
June 2025, Week 1
189 items across 10 sections, as sent to readers on 4 June 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 189
- Papers
- 123
- Sections
- 10
- Issue
- No. 100
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
24 items
Finance5
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.
15 shares1 citation todaySource ↗
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.
13 shares1 citation todaySource ↗
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.
12 sharesSource ↗
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.
11 sharesSource ↗
Economics6
Learning to Regulate: Event-Level Dataset of Capital Controls
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.
25 sharesSource ↗
Event-Level Dataset of Capital Controls
Research concludes that democratization in post-socialist countries in Central and Eastern Europe and Central Asia positively affected lower income groups from 2001 to 2016.
25 sharesSource ↗
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.
17 sharesSource ↗
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.
16 sharesSource ↗
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.
13 sharesSource ↗
Climate's Impact on Diets
Research shows that the cheapest healthy diet worldwide would emit 0.67 kg CO2e and cost $6.95 per day, emphasizing the potential for changes in agricultural policy and food choice to promote healthier and more sustainable diets in a cost-effective manner.
13 shares2 citations todaySource ↗
Miscellaneous7
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.
26 shares13 citations todaySource ↗
Mathematical Model for AI-Human Integration
The paper presents a mathematical model that uses Generative AI to enhance human skills rather than replace them, especially benefiting lower-skilled workers.
25 shares2 citations todaySource ↗
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.
19 shares1 citation todaySource ↗
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.
18 sharesSource ↗
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.
15 shares1 citation todaySource ↗
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.
14 sharesSource ↗
Analysis of Pseudo-Goodwin_cycles
The notes argue that pseudo goodwin cycles in wage-led models are not actual goodwin cycles, aiming to clarify this concept.
13 shares1 citation todaySource ↗
Crypto & Blockchain1
Blockchain Fraud Prevention: Transaction Proximity Approach
Transaction Proximity Approach: The article suggests a fraud prevention system for public blockchains that uses Transaction Proximity and Easily Attainable Identities to identify wallets linked to centralized exchanges. This could prevent most fraud cases while maintaining blockchain transparency and privacy.
17 shares1 citation todaySource ↗
Historical Trending5
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.
44 shares1 citation todaySource ↗
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.
34 shares4 citations todaySource ↗
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.
27 shares3 citations todaySource ↗
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.
23 shares9 citations todaySource ↗
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.
23 shares2 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
59 items
Quantitative30
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.
5 sharesSource ↗
Kelly Betting with Constraints
A revised Kelly optimization is proposed that includes a probabilistic recovery constraint, balancing long-term growth with short-term recovery risk, especially beneficial for strategies with skewed returns like short volatility or insurance underwriting.
6 sharesSource ↗
Venture Capitalists Impact
The performance of institutional investments is negatively affected by individual investments made by venture capital partners, with the effect being more significant for those with substantial institutional investment experience.
5 sharesSource ↗
Market News Attention Hype Index
The Hype Index is presented as a measure to quantify media attention towards large-cap equities, using Natural Language Processing to extract predictive signals from financial news.
3 sharesSource ↗
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.
3 shares1 citation todaySource ↗
Life Cycle Models Sequence-Space Jacobians
An efficient algorithm is introduced for calculating the sequence-space Jacobians of overlapping generations models, leveraging agents' finite planning horizons and predictable transitions between ages.
4 sharesSource ↗
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.
2 sharesSource ↗
HighDimensional Data Privacy
The article explores a new data analysis and protection method that merges principal component analysis with differential privacy for improved handling of high-dimensional data and privacy protection.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
2 sharesSource ↗
Machine Learning Rare Earth Alloys
The authors have created advanced machine learning models to expedite the research and development process of advanced RE Al alloys.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
2 sharesSource ↗
Fracture Characterization Hybrid HMA
The study uses AI and machine learning to detect and measure crack length development in semi-circular bending beam specimens, showcasing the effectiveness of the YOLOv8 algorithm in predicting crack lengths.
2 sharesSource ↗
Enterprise Risk Management Mergers & Acquisitions
The article discusses the discrepancy between the theoretical and practical value of Enterprise Risk Management, emphasizing the need to concentrate on ERM's potential to improve strategic decision-making.
2 sharesSource ↗
Optimising Large Language Models
The article categorises and reviews the optimisation strategies used in Large Language Models like ChatGPT, Claude LlaMA, and DeepSeek.
16 sharesSource ↗
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.
2 sharesSource ↗
Machine Learning for Predicting Market Crashes
The research discusses the role of Machine Learning in predicting market crashes and flash crashes, and the complexities involved.
2 sharesSource ↗
The Farah Model: An Extension of Kyle 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.
5 sharesSource ↗
AIDriven Financial Advisory
The study explores the impact of artificial intelligence on personal finance through robo-advisors, discussing their functionalities, industry impact, and challenges.
4 sharesSource ↗
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.
3 sharesSource ↗
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.
2 sharesSource ↗
Online Gambling Forums
The research explores the use of a Reddit gambling forum as a data source for reducing harm in online gambling.
3 sharesSource ↗
Sentiment-driven Prices
The paper proposes a model where sentiment-driven asset prices are caused by reference-dependent preferences, solving some asset pricing puzzles.
3 sharesSource ↗
Asset Supply in Economies
The study enhances an asset pricing model by adding dynamic asset supply, which significantly changes asset pricing outcomes.
3 sharesSource ↗
Malicious Mobile Apps
The research introduces a method for detecting Android malware through permission analysis, using linear regression models.
3 sharesSource ↗
Youngsters' Investment Trends
The study reveals a growing interest in investment among the youth, with mutual funds and stocks as their top choices.
4 sharesSource ↗
Crime Prediction with Data Mining
The paper employs machine learning and deep learning models to predict and categorize crime, with the RNN-LSTM model proving most accurate.
2 sharesSource ↗
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.
3 sharesSource ↗
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.
2 sharesSource ↗
Financial29
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.
8 sharesSource ↗
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.
4 sharesSource ↗
Relationship & Housing Choices
The research uses a life cycle model to study how market conditions affect individuals' relationship and housing choices, indicating different experiences for single individuals and those in relationships.
3 sharesSource ↗
Quantum ML Estimation
The study introduces two new methods for estimating stochastic volatility diffusions using Quantum-Inspired Classical Hidden Markov Models and Quantum Hidden Markov Models, with the quantum model showing tighter bounds.
2 sharesSource ↗
Sovereign Debt Post Downgrades
The research explores how governments adjust their funding structure in response to changes in credit ratings, with a shift from bonds to loans mainly occurring in countries with low ratings.
2 sharesSource ↗
Intangible Intensity & Performance
The study examines the link between intangible asset intensity and abnormal net hiring in U.S. firms, finding a positive correlation with both intangible asset intensity and annual intangible investment.
2 sharesSource ↗
Economists' Criticisms of Crypto
The article assesses criticisms of cryptocurrencies by top economists, juxtaposing them with recent advancements and counterarguments in the field.
3 sharesSource ↗
LP Profitability Analysis
The paper explores the profitability of automated market maker liquidity providers in ETH/USD pools, suggesting a protocol to mitigate impermanent loss.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
3 sharesSource ↗
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.
3 sharesSource ↗
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.
2 sharesSource ↗
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.
2 sharesSource ↗
Hybrid Financial Models
The research uses a blend of traditional econometric models, machine learning, and deep learning to predict financial time series, using SP 500 and Bitcoin data.
3 sharesSource ↗
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.
3 sharesSource ↗
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.
3 sharesSource ↗
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.
3 sharesSource ↗
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.
2 sharesSource ↗
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.
4 shares7 citations todaySource ↗
Multiverse Asset Pricing Model
The study critiques the Capital Asset Pricing Model for its free parameter problem and proposes a multiverse asset pricing model, which allows for multiple equilibria and is based on investment beliefs.
2 sharesSource ↗
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.
3 sharesSource ↗
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.
3 sharesSource ↗
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.
2 sharesSource ↗
Commodities Returns and Alternatives
Hilary Till spoke at the Women Investment Professionals organization in Chicago, discussing commodity indices, futures contracts, and hedge funds.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
2 sharesSource ↗
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.
3 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
EM Portfolios Enhanced with AATS
The rise of algorithmic trading and passive investing has caused issues during market downturns, but a new Automated Adaptive Trading System could stabilize emerging markets during such periods.
27 sharesSource ↗
Efficient Volatile KSE-30 Equities Identification
Machine learning has been used to identify assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization scheme for effective asset allocation.
25 sharesSource ↗
Dynamic Correlations in Risk Parity Portfolio Optimization
Using expected shortfall as the risk measure in risk parity portfolio optimization reduces sensitivity to volatility shocks and decreases portfolio turnover during market turmoil, with a time series model enhancing risk-adjusted returns.
16 sharesSource ↗
Adaptive Market Hypothesis
The research finds that trading strategies based on the Sharpe Ratio are more profitable than the buy-and-hold strategy in global markets, supporting the Adaptive Market Hypothesis.
15 sharesSource ↗
Novel Window Analysis
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 firms in the Ho Chi Minh City Stock Exchange.
11 sharesSource ↗
Monitoring Poverty in Lebanon
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 ↗
Statistical5
BRM for Predictions with Missing Patterns
The blockwise reduced modeling (BRM) method improves the analysis of incomplete data sets by pretraining models on subsets, increasing speed and reducing data imputation.
20 sharesSource ↗
New Momentum Indicator for Equity Premium Prediction
A new machine learning strategy, momentum-determined indicator-switching (N-MDIS), enhances equity premium prediction, outperforming existing strategies.
19 sharesSource ↗
Product Market Competition on Zero-Leverage Policies
Increased product market competition (PMC) leads to more firms adopting zero-leverage (ZL) strategies, particularly those with high earnings volatility.
18 sharesSource ↗
News Sentiment and Risk Management
Accurately measured news sentiment has a significant impact on intraday stock return volatility, reevaluating its role in explaining stock return volatility persistence.
16 sharesSource ↗
Stochastic Machine Learning for Production Technologies
An adaptation of Stochastic Gradient Boosting helps estimate production possibility sets in Data Envelopment Analysis (DEA), reducing overfitting and providing a useful tool for scenarios requiring generalization.
16 sharesSource ↗
Machine Learning7
Machine Learning for M&A
Machine learning models are more effective than traditional methods in predicting Chinese corporate mergers and acquisitions.
28 sharesSource ↗
Tail Risk Management
Two new deep learning frameworks have been proposed for estimating financial risk measures, improving capital allocation in financial institutions.
27 sharesSource ↗
Bond Market Volatility in China
Machine learning methods accurately predict Chinese stock market volatility using the volatility of longer maturity treasury bond contracts.
24 sharesSource ↗
Lot Streaming and Scheduling
The article proposes a new algorithm and machine learning model to enhance efficiency and accuracy in the Lot Streaming and Scheduling Problem (LSSP) with unpredictable product arrival times.
16 sharesSource ↗
Dynamics in Chinese Financial Markets
The paper introduces a novel statistical machine learning method for decomposing and analyzing complex time series, providing a potential alternative to the Box-Jenkins method in financial modeling.
13 sharesSource ↗
Monetary Policy Frictions and Nonperforming Loans
The study uses machine learning to create a monetary policy frictions index from financial news, revealing that these frictions significantly impact the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
Housing Market Quantile Connectedness
The research uses machine learning to study the global housing market's interconnectedness, identifying the US market as the primary source of systematic shocks and its interest rate as a key predictor of spillover intensities.
10 sharesSource ↗
Deep Learning2
Oil Price Forecasting: ML vs. DL
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 ↗
Multifrequency Data Fusion for Carbon Price Prediction
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 ↗
Historical Trending10
Predicting VIX Trends
The article discusses a machine learning approach to predict the CBOE Volatility Index, highlighting the importance of weekly jobless claim data.
23 sharesSource ↗
Stock Price Prediction
The study reveals that traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices due to dataset limitations.
13 sharesSource ↗
AI Capability Impact
The paper suggests that AI capability directly influences firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
Climate Discussions
The article emphasizes the role of communication and a comprehensive approach in addressing climate change, using machine learning to analyze social media discussions on the subject.
4 sharesSource ↗
Dark Patterns in Retail
The research investigates the issue of dark patterns in retail investment, focusing on the use of behavioral sciences and AI to improve regulation.
2 sharesSource ↗
Young Informal Workers in the EU
The study profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
Resource Management in Cloud Computing
The paper discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
EGovernance and Citizen Participation
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 ↗
Bank Performance Determinants
The paper analyzes literature on factors influencing banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the impact of COVID-19.
1 sharesSource ↗
Online Gig Work Satisfaction Scale
The study tests the applicability of the Work Need Satisfaction Scale (WNSS) among online gig workers, suggesting modifications to the scale to better reflect the specifics of online platform work.
1 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
10 items
Historical Trending10
QLASS: Language Agent
Language Agent: QLASS is a new system designed to enhance the performance of language agents by offering stepwise guidance and auto-generating annotations, even with minimal supervision.
188 shares19 citations todaySource ↗
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.
20 shares46 citations todaySource ↗
RoPEs: Position Encodings
Position Encodings: STRING, an upgrade of Rotary Position Encodings, is launched to offer exact translation invariance and efficient 3D token representation, beneficial in robotics and object detection.
13 shares20 citations todaySource ↗
LoRAX: Model Adaptation
Model Adaptation: LoRA-X is a new adapter that enables the transfer of LoRA parameters across models without requiring original or synthetic training data, making the fine-tuning process easier.
13 shares11 citations todaySource ↗
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.
10 shares9 citations todaySource ↗
AnyMesh: Open-Vocabulary 3D Modeling
Open-Vocabulary 3D Modeling: The article introduces Articulate Anymesh, a system that transforms any 3D mesh into an articulated object, enhancing 3D object datasets and improving robotics' object manipulation skills.
10 shares53 citations todaySource ↗
Sparse Bayesian Multitask Model for Microbiome Analysis
The authors present a hierarchical Bayesian multitask learning model for binary classification, proving its effectiveness in predicting health status from microbiome profiles and its resilience against heterogeneity in combined datasets.
8 shares1 citation todaySource ↗
COCONut-PanCap: Segmentation and Captions Dataset
Segmentation and Captions Dataset: The COCONut-PanCap dataset is introduced, improving panoptic segmentation and image captioning by including detailed, region-level captions, establishing a new standard for model evaluation in these areas.
6 shares14 citations todaySource ↗
Multi-Preference Optimization for Diffusion Models
The paper introduces Calibrated Preference Optimization (CaPO), a method for aligning text-to-image models with multiple reward models without human-annotated data, showing its improved performance over previous methods.
5 shares44 citations todaySource ↗
SeedVR: Video Restoration with Diffusion Transformer
Video Restoration with Diffusion Transformer: The article presents SeedVR, a diffusion transformer for real-world video restoration of any length and resolution, demonstrating its superior performance over current methods for generic video restoration.
5 shares70 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
13 items
Trending6
sktime ROCKET
Current methods for classifying time series data are accurate but computationally complex, making them inefficient for large datasets.
8,929 shares
microsoft RDAgentQuant
Predicting asset returns is challenging due to the high dimensionality, nonstationarity, and persistent volatility of financial markets.
5,326 shares
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.
1,424 shares
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.
221 shares
CodeEnhanced Reasoning
The article discusses how code and reasoning work together in large language models, with code providing a structure for reasoning and reasoning turning high-level objectives into executable steps, improving code intelligence.
202 shares
Pareto-Optimal AI
The article emphasizes the role of Retrieval-Augmented Generation pipelines in using large language models for proprietary or constantly changing data.
174 shares
Rising7
AudioTrust: Trustworthiness of ALLMs
Trustworthiness of ALLMs: AudioTrust is a new evaluation framework and benchmark specifically created for assessing the trustworthiness of Automatic Language Learning Models (ALLMs).
140 shares
BizFinBench: Financial Benchmark for LLMs
Financial Benchmark for LLMs: An assessment shows unique ability patterns in numerical calculation, reasoning, information extraction, and prediction recognition across different models.
131 shares
Training a Search Agent via RL
Retrieval-augmented generation (RAG) systems allow large language models (LLMs) to utilize external knowledge during the inference process.
120 shares
ToolStar LLMBrained MultiTool
The article explores the difficulties in applying the RL algorithm to improve multitool collaborative reasoning in large language models.
93 shares
Phi Report
The article presents phi4, a language model with 14 billion parameters that prioritizes data quality during training.
89 shares
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.
82 shares
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.
52 shares
GitHub
Repositories the letter featured.
10 items
Finance5
MCP Server
The article talks about an MCP server that enables LLM agents to easily connect and retrieve data from any database.
85 shares
Tensor2Tensor Library
The article introduces a collection of deep learning models and datasets designed to simplify deep learning and accelerate machine learning research.
16,174 shares
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.
13 shares
KLlamaGym
The article provides guidance on how to optimize LLM agents using online reinforcement learning.
1,191 shares
LightlyTrain Framework
The article presents LightlyTrain, the first PyTorch framework created to pretrain computer vision models on unlabeled data for industrial applications.
328 shares
Trending5
StableBaselines Tutorial
StableBaselines tutorial for Journées Nationales de la Recherche en Robotique 2019 is a guide on how to use StableBaselines for a robotics research event.
676 shares
Successor of UndetectedChromedriver
Successor of UndetectedChromedriver talks about the new version of the UndetectedChromedriver.
2,507 shares
AppleMCP Tools Collection
Collection of applenative tools for the model context protocol compiles Apple's native tools for the model context protocol.
1,683 shares
Minimal JS InfrastructureasCode Library
A minimal embeddable JSnative InfrastructureasCode library designed with genAI in mind describes a small JavaScript library for Infrastructure as Code, designed for genAI.
469 shares
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.
8,203 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Acheron Trading gets CASP license
Acheron Trading is the first market maker to receive a CryptoAsset Service Provider license from the Dutch Authority for the Financial Markets.
6 shares
Evolution Asset fund up 20%
Evolution Asset Management's flagship fund, Multi-Strategy No1, has seen a nearly 20% increase this year and a total return of 1485% since 2015.
5 shares
Hedge funds back in emerging markets
Hedge funds and asset managers are investing more in high-yield emerging market currencies due to decreased FX volatility and less concern over US trade policy.
5 shares
Arrowpoint's top monthly gains
Singapore-based hedge fund Arrowpoint Investment Partners made significant gains in May by taking advantage of market dislocations across different sectors.
4 shares
Hedge funds raise oil shorts
Hedge funds are making more bearish bets on crude oil, expecting potential supply increases from OPEC and negative geopolitical developments.
4 shares
Jupiter's GEARx Strategy
Jupiter Asset Management has launched GEARx, a high-leverage version of its Merian Global Equity Absolute Return GEAR strategy, targeting professional investors via its new Cayman Islands-based hedge fund platform.
4 shares
Balyasny Hires Trader
Balyasny Asset Management has recruited Jamie Mansell, a former Deutsche Bank bond trader, to expand its macro team, as reported by Bloomberg.
3 shares
Future Funds US
The annual Hedgeweek® Funds of the Future US event in New York is designed for both emerging and established hedge funds, providing strategies for capital raising, investor relations, operational efficiency, regulatory compliance, and technology.
3 shares
Two Sigma in London
Despite facing challenges, a certain hedge fund's London office has successfully continued its operations.
3 shares
Quant Fund Titan Cliff Asness
According to the Financial Times, Quant fund giant Cliff Asness claims that we have increasingly 'surrendered to the machines'.
2 shares
Miscellaneous10
Robeco and Technology
Robeco celebrates over 25 years in quantitative investing, highlighting the role of technology in the industry.
2 shares
Elliott Exec Joins Honeywell
Honeywell International appoints Marc Steinberg from Elliott Investment Management to its board, marking a key moment in the hedge fund's activist investments.
2 shares
Uncertainty for US Student Visas
The barring of Chinese students from the US is creating problems in the financial services industry.
2 shares
Forteus Appoints Partner
The Numeus Group hires Bill Daley, ex-Vice Chairman of JPMorgan and Wells Fargo, as a Partner in its digital asset management division, Forteus.
2 shares
Macro Hedge Funds Top Allocator Wishlists
Discretionary global macro hedge funds are now a top focus for institutional allocators due to ongoing economic uncertainty and geopolitical tensions, says a Société Générale survey.
2 shares
Toyo Tire strategy review urged
Activist fund Palliser Capital has bought a 3% stake in Toyo Tire, potentially leading to capital returns or a sale of the Japanese tyre company.
2 shares
Shareholders back Lamb Weston board overhaul
Jana Partners, an activist hedge fund, is gearing up for a possible proxy fight at Lamb Weston due to dissatisfaction with the company's board.
1 shares
Greenlight founder warns of trade war impact
David Einhorn, founder of Greenlight Capital, warns of economic risks due to rising US-China tensions, suggesting the US is underestimating China's readiness for a trade war.
1 shares
Morgan Stanley engineers solve coding problem
Morgan Stanley has created a new type of LLM (Master of Laws).
0 shares
Justin Gmelich driving Goldman Sachs crazy
A former favored individual at Goldman Sachs has now become its opponent.
0 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Hidden Bus
Brad Barrie argues that true investment diversification is about diversifying return drivers, not just asset classes.
15 shares
Trading Psychology Revealed
JJ Kinahan emphasizes the accessibility of options trading and the need to understand personal risk tolerance in retail trading.
10 shares
Power Law Investing
Cole Wilcox highlights the effectiveness of trend-following in stock investments and the importance of accepting losses in investing.
8 shares
Episode
Helen Thomas discusses the resurgence of political risk in financial markets, derivative risks in the S&P 500, and Trump's strategic approach.
8 shares
EM Fixed Income Focus
Jonny Goulden and Saad Siddiqui discuss the impact of recent market developments on the EM fixed income asset class in a May 2025 podcast.
8 shares
Related5
Money Market Funds Overview
Ross McDonald discusses the significance and future of money market funds in a podcast, emphasizing their role in an investor's portfolio.
6 shares
Global FX Tariffs Analysis
Meera Chandan and Patrick Locke analyze the impact of the latest CIT ruling on tariffs, payroll report expectations, and fiscal-driven rates on the dollar and FX markets.
5 shares
ECB Preview and Curve Analysis
In a podcast, Francis Diamond and Khagendra Gupta provide insights on Euro area rate markets and EUR and GBP curves ahead of the June ECB meeting.
5 shares
AI in Cyber Defense
A podcast episode delves into the use of AI in cyber and electronic warfare, highlighting the shift from physical to code-based conflicts.
4 shares
Food Bank Forecasting with Prof. Davis
Professor Lauren B. Davis talks about her research on using stochastic modeling and forecasting in food bank operations, stressing the importance of equity and practical impact in humanitarian supply chains.
4 shares
X / Twitter
Posts from quant researchers on X.
3 items
Quantitative1
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.
2 shares
Miscellaneous2
Investing Research Roundup
The article summarizes recent investment research on topics like anomalies, phacking, commodity signals, stock return predictability, and various online resources.
0 shares
Interview
The article includes a significant interview but lacks specific information about the content or the people involved.
0 shares
Threads from r/quant, r/algotrading and friends.
10 items
Quantitative5
Trading Book Recs
134 shares
Thriving in Trading
175 shares
FLOX Trading System
66 shares
Georgia Tech vs Manchester
47 shares
Citadel Quant Interview
38 shares
Rising5
NQ Algo Results
96 shares
Transitioning to Non-PnL Quant PM
71 shares
London Quant Meetups
83 shares
FLOX
46 shares
Quants and Identities
167 shares