Realized Volatility
The article introduces the realized local volatility surface, a new concept that uses high-frequency trading data to predict market volatility, using Tesla's data as a successful example.
27 sharesSource ↗
Quant LetterNo. 94
April 2025, Week 4
191 items across 10 sections, as sent to readers on 23 April 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 191
- Papers
- 127
- Sections
- 10
- Issue
- No. 94
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
27 items
Finance6
LLMs Economic Forecasts
The study shows that large language models can remember exact economic figures from before their knowledge cutoff dates, which may skew their predictive abilities in forecasting and backtesting trading strategies.
16 shares36 citations todaySource ↗
Correlation Breakdown
The paper presents a new method, Nonparametric Angles-based Correlation (NAbC), for defining the finite-sample distributions of any dependence measure, improving the modeling of financial portfolios under various data conditions.
15 sharesSource ↗
Particle System for H-LSV Model
The article presents a Monte Carlo method for simulating the Heston-type local stochastic volatility model, addressing drift and diffusion coefficient challenges and proving a strong chaos propagation under certain conditions.
14 shares2 citations todaySource ↗
Optimal Capital Structure for Life Insurers
The study modifies Leland's dynamic capital structure model to explain life insurance contracts with guaranteed payment and surplus participation, emphasizing the impact of contract duration and tax rate on the optimal participation rate.
12 sharesSource ↗
LLM Views in Mean-Variance Optimization
The research investigates the use of large language models for estimating expected stock returns and integrating uncertainty into portfolio optimization via the Black-Litterman framework, comparing the effectiveness of various models.
12 shares9 citations todaySource ↗
Economics7
Rewiring Supply Chains
Research shows that strategically rearranging supplier-customer connections can significantly lower supply chain risk by 16-50% without affecting production.
17 shares5 citations todaySource ↗
EU Cohesion Fund Effects
A study measures the impact of the EU's Cohesion Fund on regional output and investment, showing its peak effect within the first seven years, particularly in poorer regions.
16 shares9 citations todaySource ↗
Donor Bias in Police Stops
A study indicates that private donations to police departments can affect officer behavior, with a rise in investigatory stops near 7-Eleven stores after the company sponsored a police gala, hinting at racial bias in donor-influenced policing.
16 shares1 citation todaySource ↗
LLMs for News Content Alignment
Researchers have created a language model that produces engaging news while controlling polarization levels, addressing issues of bias in language models.
13 shares2 citations todaySource ↗
Accessibility in Florence
A new method for assessing urban accessibility to services within a 10-minute walk has been proposed, using Florence, Italy as a case study, to address urban development disparities.
13 shares1 citation todaySource ↗
AI Collaboration with Experts
The paper discusses the paradox of professional expertise and AI, indicating that while automating professional roles may pose risks, it also presents opportunities for expertise evolution and new professional value.
13 shares1 citation todaySource ↗
Engagement vs. Polarization
A study offers a solution to news media polarization by developing a language model that generates engaging content while maintaining a preferred editorial stance, using a unique algorithm.
13 shares2 citations todaySource ↗
Miscellaneous8
Financial Market Forecasting
The article presents Cross-Modal Temporal Fusion (CMTF), a new transformer-based system that uses diverse financial data to enhance the precision of financial market predictions.
22 shares10 citations todaySource ↗
Divergent LLM Adoption
The research examines the effects of AI-assisted revisions on academic writing, showing differences in usage across fields, gender, and career level, and demonstrating that Large Language Models improve writing clarity and brevity.
20 shares6 citations todaySource ↗
Prioritizing AI Safety
The paper emphasizes the often ignored impact of AI on future work, suggesting extensive transition support for meaningful work and advocating for a worker-friendly global AI governance framework to promote shared wealth and economic fairness.
19 shares17 citations todaySource ↗
Trust in Decentralized AI Networks
The article explores the identification of nodes operating unauthorized or incorrect Large Language Models in a decentralized AI network through peer consensus, and proposes a validation system with financial rewards and penalties to promote honesty.
17 sharesSource ↗
Bayesian Optimization for Portfolio Management
A new Bayesian optimization framework has been developed to improve black-box portfolio management models, outperforming other models in backtest settings.
17 sharesSource ↗
Symmetry Solutions for Mean Reversion Process
The Lie symmetry method is applied to a Feynman-Kac formula for a more accurate assumption of short-term interest rate dynamics than the geometric Brownian motion.
14 sharesSource ↗
Threshold Resetting for Search Optimization
A new optimization method driven by threshold resetting is introduced, which can calculate search times for correlated stochastic processes and prevent larger losses.
13 shares19 citations todaySource ↗
Production Networks Formation Through Reinforcement Learning
A new model allows firms to determine their selling price, production volume, and inputs, leading to a flexible production network that can adapt to shocks.
10 sharesSource ↗
Crypto & Blockchain3
Detecting Spoofing in Crypto Exchanges
The article discusses a new real-time detection model for spotting potential market manipulation in cryptocurrency exchanges, with 31% of large orders identified as potential spoofs.
12 shares3 citations todaySource ↗
Price Pattern Differences: Crypto vs. Stocks
Crypto vs. Stocks: The study uses machine learning to compare trading behaviors and price patterns in cryptocurrencies and stocks, revealing significant differences between the two.
12 sharesSource ↗
Optimal Routing Paths in DEX
The research presents a new algorithm for finding the best trading paths in decentralized exchanges, showing its potential for industry use due to its efficiency and cost-effectiveness.
11 shares4 citations todaySource ↗
Historical Trending3
Universal Portfolios
The article explores a simplified approach to continuous-time version of Cover's universal portfolio strategies, confirming the existence and value process of the universal portfolio strategy.
19 sharesSource ↗
Model-Free Universal Portfolios
The article presents a direct method to a continuous-time version of Cover's universal portfolio strategies, verifying the existence and value process of the universal portfolio strategy.
19 sharesSource ↗
Prosocial AI Agents
The study investigates the influence of character and context on the behavior of large language models in social science scenarios, suggesting ways to examine and adjust an LLM's internal representations in a Dictator Game.
17 shares2 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
60 items
Quantitative30
Quantifying State Collapse Risk
The study presents a machine learning-based FivePillar Framework to predict the risk of state collapse, aiding policymakers in taking preventive measures.
9 sharesSource ↗
Loss Optimization for Machine Learning
The paper suggests new methods for predicting losses and optimizing machine learning solutions using various types of data.
3 sharesSource ↗
Risk Assessment through Certainty Equivalent
The paper examines the link between risk aversion, utility, and Certainty Equivalent (CE) using computational simulations, identifying potential improvements.
6 sharesSource ↗
International Reserves and Output Volatility
The study questions the traditional methods of managing international reserves, revealing that countercyclical management can significantly decrease output volatility.
4 sharesSource ↗
Board Power and Corporate Diversification
The study explores the impact of board characteristics on corporate diversification in Nigeria using regression models.
2 sharesSource ↗
Jet Noise Modeling for Military Aircraft
The study develops a machine learning-based framework to predict military aircraft noise levels, with highly accurate models showing strong linear correlation.
2 sharesSource ↗
Hate Speech Detection in Social Media
The paper introduces a machine learning technique for automated detection of hate speech on social media to curb the spread of harmful content.
3 sharesSource ↗
Intellectual Capital Reporting in Nigeria
The study explores the factors that affect how Nigerian firms listed on the Capital Market report their intellectual capital from 2014 to 2023.
2 shares4 citations todaySource ↗
Materials Discovery Interpretation
The article highlights the importance of integrating scientific interpretation in the process of discovering materials through machine learning.
2 sharesSource ↗
Making Work Meaningful
The research identifies social impact as the key factor in making work meaningful, based on an analysis of panel data.
6 sharesSource ↗
Provenance Tracking for ML Systems
The paper introduces yProv4ML, a framework designed to standardize the recording of provenance information in machine learning processes.
2 sharesSource ↗
Power Consumption Model for Data Centers
The article emphasizes the need for quick and accurate power consumption modeling to optimize energy use in cloud computing services.
2 sharesSource ↗
Attribute Reduction for Heterogeneous Data
The paper introduces a semisupervised method for reducing attributes in partially labeled heterogeneous data, based on misclassification cost and self-information.
2 sharesSource ↗
Chinese Real Estate Firms Behavior
The research investigates how banks owning equity stakes in firms influences the debt behavior of Chinese real estate firms from 2008 to 2022.
3 sharesSource ↗
Tastes, Productivities, and Macroeconomic Volatility
The paper uses a general equilibrium model to examine how differences in product tastes and firm technologies impact macroeconomic fluctuations.
2 sharesSource ↗
Trade-In Acquisition Modeling for Automotive Retail with AI
Novosteer Technologies has created an AI model to improve lead generation and vehicle sourcing for dealerships in fluctuating retail markets.
6 sharesSource ↗
Economics of Big Data: Acquiring Large-Scale Data Sets
Acquiring Large-Scale Data Sets: The article examines the economic aspects of acquiring and managing large datasets, focusing on AI methods and cloud storage.
4 sharesSource ↗
Machine Learning for Wormhole Attack Detection in IoT Networks
The research investigates the use of machine learning to detect wormhole attacks in IoT networks, a new cybersecurity issue.
3 sharesSource ↗
Corporate Tax Avoidance, Market Power, and Wealth Concentration
The paper studies the role of tax avoidance in corporate inequality and market power, using data from US firms including Apple, Tesla, and Johnson & Johnson.
4 sharesSource ↗
NextGen Deep Learning for Handwritten Recognition
The article highlights the difficulties in Handwritten Text Recognition (HTR) due to varying handwriting styles and complexities like cursive writing and irregular spacing.
5 shares1 citation todaySource ↗
Bias in Securities Litigation Event Studies with Volatility Shifts
The paper suggests a regime switching model to estimate beta and volatility for different regimes, overcoming the shortcomings of traditional event study methodology.
2 sharesSource ↗
Investigating VIX Index Relationship with Bond Spreads
The study explores the link between implied equity volatility (VIX) and corporate bond spreads, using data from three recent periods of high volatility.
3 sharesSource ↗
DisasterScope
DisasterScope is an AI system that predicts disasters in real-time and offers emergency assistance using open-source data and machine learning.
4 sharesSource ↗
Financial Data & Python Code
Researchers provide raw financial report data and Python code to aid in downloading and parsing these filings, introducing two new word lists.
3 sharesSource ↗
Indian Market Price Discovery
A study shows that about 90% of information exchange between the Nifty index spot and futures markets occurs within two weeks, with volatility being crucial for informational efficiency.
2 sharesSource ↗
ID Decision Making Algorithm
The Dichotomiser 3 (ID3) algorithm, combined with decision tree models, improves decision-making in machine learning applications, especially with categorical data.
2 sharesSource ↗
ML Risk Assessment in Finance
Machine learning enhances risk assessment and valuation in the financial sector, as shown by case studies in auditing and operational risk.
2 sharesSource ↗
Short Selling Liquidity
A study on Chinese stock markets reveals that short selling decreases liquidity commonality in stocks, with increased information disclosure being a significant factor.
2 sharesSource ↗
Firm Uncertainty Spending
Firm-specific uncertainty leads to reduced future spending and increased precautionary savings, particularly among lower and top earners, as per a study using daily banking and credit card data.
4 sharesSource ↗
Kolmogorov-Arnold Forecasting Networks
Kolmogorov-Arnold Networks (KANs) are a strong alternative to MultiLayer Perceptron (MLP) for time series analysis and forecasting, as detailed in a comprehensive survey.
3 sharesSource ↗
Financial30
Financial Machine Learning Dynamics
Advanced machine learning models are more effective in predicting ultrahighfrequency stock returns than simpler models, a study reveals.
7 sharesSource ↗
Generative AI in Capital Markets
AI use in financial analysis on Seeking Alpha platform boosts productivity and liquidity for undercovered firms, but provides less information to capital market participants than human articles.
5 sharesSource ↗
Market Power in Defi
The need for transaction privacy in decentralized finance (DeFi) leads to the rise of powerful intermediaries, a Staff Report suggests.
11 sharesSource ↗
Liquidity Adjustment in Volatility
A new liquidity-sensitive multivariate volatility framework enhances the estimation of time-varying covariance structures, especially for cryptocurrency portfolios.
2 sharesSource ↗
Quantitative Alpha in Crypto
Systematic cryptocurrency investment strategies are statistically valid, with machine learning methods showing superior performance in capturing nonlinear price patterns, a review of studies shows.
2 sharesSource ↗
Black-Litterman Model Extension
The Black-Litterman asset allocation model is improved to better reflect market reality by incorporating the normal variance-mean mixture distribution, allowing for skewness, heavy tails, and asymmetric dependence in financial returns.
5 sharesSource ↗
Machine Learning and Sector Expertise
A Hybrid model incorporating industry membership outperforms other machine learning models in predicting industry-level returns, offering higher Sharpe ratios and lower risk.
3 shares2 citations todaySource ↗
Banks and Insurers Response to Rate Hikes
Interest rate hikes by central banks due to COVID19 and Ukraine crisis significantly impact Eurozone and U.S. banks and insurers' stocks and credit default swaps.
3 sharesSource ↗
DualRisk Valuation
A new valuation theory introduces a second risk dimension, expectational risk, to the traditional discounted cash flow model.
2 sharesSource ↗
AI Impact on Investments
AI technology adoption by mutual fund managers leads to superior returns and lower expenses, especially in discretionary funds.
2 sharesSource ↗
Entangled Markets Theory
The Efficient Markets Hypothesis fails to consider the effect of poor investment decisions and asset interrelationships on asset prices.
2 sharesSource ↗
The Musk Effect on Tesla
Investor sentiment, driven by social media and news, can cause significant short-term stock price fluctuations, as shown in a Tesla Inc. case study.
2 sharesSource ↗
GenAI in Stock Market
Chinese stock market participants use Generative AI to process investment information, with firm size, short-term performance, and media coverage being key factors.
3 shares2 citations todaySource ↗
Geopolitical Risk in Indian Stocks
Indian stock market indices are significantly affected by global and country-specific geopolitical risks, with different sectors reacting differently to various types of shocks.
2 sharesSource ↗
Recovery Time from 1929 Crash
The recovery time for investments in the Dow Jones Industrial Average made at the 1929 peak varies between 16 and 29.75 years, depending on dividend reinvestment and inflation/deflation considerations.
3 sharesSource ↗
Data Privacy Risk Impact on Firm Performance
The research finds that companies with higher data privacy risks have lower earnings and increased bank loan costs, using earnings call transcripts to measure data privacy risk.
7 sharesSource ↗
Videogame Attributes for Investment
The study reveals that investing in video game attributes, specifically CSGO skins, yields higher returns than most traditional assets, with strong seasonality patterns and independence from equity market risk factors.
7 sharesSource ↗
Climate Risks Impact on Bond Markets
The paper shows that physical climate risks and inflation expectations transmit risk across bond classes during high-volatility phases, impacting bond markets.
4 sharesSource ↗
Equity Risk Premium Analysis in India
The paper presents a wide range of estimates for India's Equity Risk Premium (ERP), showing how India's volatile inflation environment distorts nominal risk premiums.
4 sharesSource ↗
Future Data Impact on Crude Oil Markets
The presentation emphasizes the importance of futures price data and accurate fundamental data in understanding crude oil market fundamentals through price-relationship data.
3 sharesSource ↗
Intraday Volatility Forecasting with Deep Learning
The paper introduces a new deep learning model for forecasting high-frequency intraday return densities and volatility, which outperforms empirical nonparametric forecasting rules.
3 sharesSource ↗
Short Selling Constraints Impact on Corporate Investments
The study demonstrates that while a cost on short sellers can increase firm value, a large cost or a short-sale ban always harms it, analyzing the impact of short selling constraints on corporate investment decisions.
3 sharesSource ↗
Genetic Asset Management
The article explores the use of genetic algorithms in portfolio management, specifically in single-asset optimization and Genetic Asset Management (GAM).
3 sharesSource ↗
Intraday Jumps and Options
The study investigates the effect of intraday jumps on ultra-short-term options pricing and hedging strategies, revealing significant jump risk premia.
2 sharesSource ↗
Index Sampling Turnover
The research uses algorithms to create replication portfolios, noting that stocks in these portfolios have higher turnover rates than other index constituents.
3 sharesSource ↗
Stock Investment p-index Approach
The paper uses a European put option to measure asset risk, finding that stocks in the materials sector yield the highest annualized returns.
3 sharesSource ↗
OptionMC Monte Carlo Pricing
The article introduces OptionMC, a Python package for European option pricing using Monte Carlo methods, and validates its use against Black-Scholes solutions.
4 sharesSource ↗
Trading Inter-firm Links
The study explores how hedge funds use public information about interfirm links, finding that they actively trade based on this information, especially when information frictions are high.
3 sharesSource ↗
Export Proceeds Repatriation
The research examines the effect of repatriated export proceeds on exchange rate volatility in Indonesia, finding no evidence of its ability to mitigate short-term capital flow impacts.
2 sharesSource ↗
Asset Pricing Covid-19 Deposit Glut
The paper uses Liquidity Preference Theory to analyze the impact of Covid-related growth in household deposits, finding a significant increase in nonmonetary wealth for each additional unit of monetary wealth.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
EM Portfolios Enhanced with AATS
A second-generation Automated Adaptive Trading System may stabilize emerging markets during downturns, countering challenges posed by algorithmic trading and passive investing.
27 sharesSource ↗
Efficient Volatile KSE-30 Equity Identification
Machine learning has been utilized to pinpoint assets causing downward trends in the Pakistan Stock Exchange, suggesting an effective asset allocation scheme.
25 sharesSource ↗
Dynamic Correlations in Risk Parity Portfolio Optimization
Using expected shortfall as a risk measure in risk parity portfolio optimization can lessen sensitivity to volatility shocks, decrease portfolio turnover during market turmoil, and enhance risk-adjusted returns with a sophisticated time series model.
16 sharesSource ↗
Adaptive Market Hypothesis and Sharpe Ratio Strategies
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 for High-Frequency Trading
The study introduces a new window analysis method using the Whale Optimization Algorithm to evaluate the efficiency of decision-making units in foreign exchange investment strategies and utility companies.
11 sharesSource ↗
Monitoring Poverty in Lebanon
The paper uses a new data augmentation technique to analyze poverty in the Middle East and North Africa, demonstrating the effectiveness of using alternative data sources with Lebanese data.
10 sharesSource ↗
Statistical5
BRM for Predictions with Missing Patterns
The blockwise reduced modeling (BRM) method is introduced for better analysis of missing patterns in data, providing faster and more accurate predictions by reducing data imputation.
20 sharesSource ↗
New Momentum Indicator for Equity Premium Prediction
A new machine learning strategy, momentum-determined indicator-switching (N-MDIS), is proposed to improve the accuracy of equity premium prediction, outperforming previous methods.
19 sharesSource ↗
Product Market Competition and Earnings Volatility
The study suggests that increased product market competition leads firms to adopt zero-leverage policies, especially those with higher earnings volatility, providing new insights into market competition and financial decisions.
18 sharesSource ↗
News Sentiment Impact on Risk Management
The study reevaluates the impact of news sentiment on stock return volatility, indicating that more accurately measured news sentiment significantly affects volatility dynamics, potentially outperforming RavenPack with GPT-4 classification.
16 sharesSource ↗
Stochastic Machine Learning for Production Technologies
A new adaptation 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 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 Forecasting
Machine learning can accurately predict Chinese stock market volatility using the volatility of long-term 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 with uncertain product arrival times.
16 sharesSource ↗
Dynamics in Chinese Financial Markets
The paper introduces a novel statistical machine learning method for decomposing and modeling complex time series, providing an alternative to the Box-Jenkins method for financial modeling.
13 sharesSource ↗
Monetary Policy Frictions and Nonperforming Loans
The study uses machine learning to analyze the impact of a monetary policy frictions index on commercial banks' nonperforming loans, advocating for more transparency in monetary policy transmission.
12 sharesSource ↗
Housing Market Connectedness
The research uses machine learning and quantile connectedness models to study the global influence of the US housing market and its interest rates, emphasizing their significant impact on international housing market spillovers.
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 has shown higher accuracy and flexibility in predicting carbon trading prices in China's largest carbon trading market compared to other models.
10 sharesSource ↗
Historical Trending10
Predicting VIX Trends
The study uses machine learning to predict the CBOE Volatility Index, highlighting weekly jobless claim data as a significant factor in market volatility.
23 sharesSource ↗
Stock Price Prediction in Eurozone
Traditional machine learning models are found to be more effective than deep learning models in predicting stock price direction in the Eurozone banking sector.
13 sharesSource ↗
AI Capability and Performance
The research indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
Climate Discussions on Social Media
The study uses machine learning to analyze social media discussions on climate change, emphasizing the need for communication and a comprehensive approach.
4 sharesSource ↗
Dark Patterns in Retail Investors
The research investigates the use of dark patterns in retail investment, suggesting the use of behavioral sciences and AI for improved regulation and investor protection.
2 sharesSource ↗
Understanding Young Informal Workers in the EU
The study profiles young informal workers in the EU27, aiming to understand their pre-pandemic situation and contribute to research on Covid-19's impact on youth labor market informality.
2 sharesSource ↗
Resource Management in Cloud Computing
The paper discusses how artificial intelligence can enhance resource management in cloud environments, improving the performance of DevOps workflows.
2 sharesSource ↗
EGovernance and Citizen Participation
The review explores the relationship between e-governance initiatives and citizen participation, identifying knowledge gaps, especially regarding the sustainability and impact of these initiatives.
2 sharesSource ↗
Bank Performance Determinants
The paper reviews literature on the factors influencing banks' performance, suggesting new research avenues in the context of digital transformation, artificial intelligence, and FinTechs.
1 sharesSource ↗
Online Gig Work Satisfaction Scale
The study assesses the applicability of the Work Need Satisfaction Scale to online gig workers, suggesting the scale needs adaptation to better understand online platform work and promote worker well-being.
1 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
10 items
Historical Trending10
QGuided Stepwise Search for Language Agents
QLASS system enhances language agents' performance by offering step-by-step guidance, enabling them to adapt to long-term value and manage limited supervision.
191 shares19 citations todaySource ↗
Decision Theoretic Foundations for Conformal Prediction
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 increasing utility.
20 shares46 citations todaySource ↗
Training-Free Cross-Model Adaptation
LoRA-X enables the transfer of parameters across models without original or synthetic training data, making the fine-tuning process for large foundation models easier.
13 shares11 citations todaySource ↗
Open-Vocabulary 3D Object Modeling
Articulate Anymesh is an automated system that transforms any rigid 3D mesh into an articulated object, broadening the scope of 3D articulated object datasets and aiding in the development of new object manipulation skills in robotics.
10 shares53 citations todaySource ↗
Particle Trajectory Representation Learning
PoLAr-MAE uses self-supervised learning for 3D particle trajectory analysis in Time Projection Chambers, achieving the same performance as supervised baselines without any labeled data.
10 shares9 citations todaySource ↗
Hierarchical Sparse Bayesian Multitask Model
The study introduces a hierarchical Bayesian multitask model for binary classification learning, proving its efficiency in predicting health status from microbiome profiles across various datasets.
8 shares1 citation todaySource ↗
Improved Position Encodings for Data
The paper presents STRING, an improved version of Rotary Position Encodings, offering exact translation invariance and low computational cost, proving its utility in robotics and object detection.
7 shares20 citations todaySource ↗
COCONut-PanCap: Panoptic Segmentation and Captions
Panoptic Segmentation and Captions: The COCONut-PanCap dataset is introduced, improving panoptic segmentation and image captioning by providing detailed captions linked to segmentation masks, enhancing vision-language model performance.
6 shares14 citations todaySource ↗
AADDCE: Multimodal Attention for MRI Synthesis
Multimodal Attention for MRI Synthesis: The study proposes AAD-DCE, a generative adversarial network for creating Dynamic Contrast-Enhanced MRI images, showing its superior performance compared to other DCE-MRI synthesis methods.
5 shares2 citations todaySource ↗
Language Models and Optimization Problems
The paper investigates the ability of Large Language Models in managing Sequential Optimization Problems, introducing WorldGen for generating new SOPs, and suggesting ACE to enhance LLM performance without additional training.
5 shares1 citation todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
13 items
Trending6
Microsoft BitNet
The creation of large language models such as BitNet b1.58 has increased interest in ternary language models.
14,305 shares
Reinforcement Learning
The use of human feedback in reinforcement learning is now essential for developing advanced machine learning systems.
736 shares
The AI Scientistv2
AI is playing a significant role in transforming the methods of scientific discoveries.
613 shares
Tencent InstantCharacter Framework
The article details the development of a massive character dataset with over 10 million samples for efficient framework training.
529 shares
Lizonghang PRIMA: Breaking Barriers for LLMs
Breaking Barriers for LLMs: The article emphasizes the exceptional performance of DeepSeek R1 and QwQ 32B in operating large language models on personal devices.
445 shares
KRLabsOrg LettuceDetect: Hallucination Detection
Hallucination Detection: The article discloses that despite utilizing external knowledge sources, Retrieval Augmented Generation (RAG) systems can still produce hallucinated answers.
369 shares
Rising7
SimpleAR: Visual Generation Framework
Visual Generation Framework: The article presents SimpleAR, a straightforward visual generation framework that doesn't require complex architectural modifications.
213 shares
Syzygy of Thoughts: Improving CoT
Improving CoT: The piece explores ChainofThought (CoT) prompting, a method that enhances the reasoning of large language models by simplifying problems into sequential steps, thereby minimizing errors.
178 shares
VSLAMLAB: Visual SLAM Framework
Visual SLAM Framework: The text underscores the difficulties in Visual Simultaneous Localization and Mapping (VSLAM) research, caused by disjointed toolchains, intricate system setups, and inconsistent assessment techniques.
159 shares
DeepMath103K
The article emphasizes the role of complex mathematical reasoning in enhancing artificial intelligence.
129 shares
EndEndDiffusion
The article introduces a technique to enhance AI model training through representationalignment (REPA) loss.
76 shares
rlhflow
The article provides an in-depth analysis of the fundamental elements of GRPO from the viewpoint of reinforcement algorithms.
73 shares
spcl
The article underscores the significance of structured task-relevant knowledge in assisting low-cost models to solve intricate tasks.
61 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Mean Reversion Strategy
The article explains the development and testing of a mean reversion trading strategy using statistical methods in backtrader.
56 shares
GAN Options Simulator
The article explores the functionalities and uses of the ganoptionssimulator tool.
12 shares
Equity Compensation
The article offers a comprehensive guide on the taxation of stock options and RSUs, as per www.holloway.
10,969 shares
DeepSeek Algorithm
The article provides a step-by-step guide on how to build the DeepSeek R1s GRPO algorithm from the ground up.
943 shares
Maple Mono Font
The article presents Maple Mono, a customizable open-source monospace font designed for IDE and terminal use.
14,608 shares
Trending5
Terminal Agent
The article introduces a new lightweight coding agent that functions within your terminal.
12,859 shares
Codebase AI
The piece discusses the potential of AI in converting complex codebases into user-friendly tutorials.
4,432 shares
Browser Server
The article details how the Browser MCP server allows AI applications to manage your browser.
954 shares
Video Tool
The piece promotes the idea of making video diffusion more user-friendly and widely accessible.
3,268 shares
News
Industry news: funds, hiring, markets and regulation.
15 items
Quantitative8
Man Group AUM Drop
Man Group's assets under management fell by £4.2bn in early April due to market volatility.
4 shares
Ninepoint Hires PM
Samarjit Sam Mitter will become Senior Portfolio Manager at Ninepoint Partners LP in May 2025.
4 shares
QuantVision Conference 2025
Rebellion Research is hosting Fordham's QuantVision 2025, a quantitative conference and data summit.
4 shares
Trump Media Seeks SEC Probe
Trump Media & Technology Group has asked the US SEC to probe possible suspicious short selling of its stock.
4 shares
JPMorgan Boosts Defence Team
JPMorgan Chase is bolstering its shareholder engagement and activism defense team with two new managing directors, in response to increased hedge fund activism.
3 shares
Whale Rock Drops in Q1
Whale Rock Capital Management experienced a 20% loss in Q1 2025 due to renewed trade tensions under the Trump administration, impacting public equities, particularly tech and growth stocks.
3 shares
Citadel Securities Research Study
The article outlines the qualifications and skills needed to land a quant research job at CitadelSec.
3 shares
Iress Sells QuantHouse
Iress is selling its fast market data business, QuantHouse, to Vienna-based BAHA Tech Holding AG for €17.5m.
2 shares
Miscellaneous7
Hedge Funds Reduce Exposure
Hedge funds have lowered their stakes in the 'Magnificent Seven' tech giants to a two-year low, anticipating a crucial earnings season, as per a Morgan Stanley note.
2 shares
Unlimited Adds Global Macro Hedge Fund ETF
Unlimited has introduced the Unlimited HFGM Global Macro ETF, a new actively managed ETF that provides access to global macro hedge fund strategies in a cost-effective, tax-efficient structure.
2 shares
SimCorp Appoints New COO
Financial technology firm SimCorp has elevated Ronan Donnelly to the role of Chief Operations Officer, effective immediately.
2 shares
AMG Stake in Verition
Affiliated Managers Group has bought a minority share in the fast-expanding hedge fund, Verition Fund Management.
1 shares
JPMorgan Tech MD at Meta
A person has rejoined the banking sector, but with a different organization.
0 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Volatility
The article highlights the return of market volatility as a potential opportunity for young investors to buy discounted assets, stressing the need for diversification across various asset classes and regions.
20 shares
Jon Hodges
Jon Hodges of FIS Global discusses the lead of Asia-Pacific firms in adopting AI and the crucial role of data in a podcast.
9 shares
US Credit
The podcast explores the policy uncertainty from the Trump administration leading to a shift away from US risk assets and its global and domestic economic impact.
7 shares
Jeffrey Perlman
Jeffrey Perlman, CEO of Warburg Pincus, discusses navigating the private equity landscape, the firm's diversification strategy, and potential investment opportunities on a Goldman Sachs podcast.
6 shares
The End of The Monetary System
Daniel Lacalle is hosted on MacroVoices to discuss Trump's tariffs from a European investment perspective and the potential for new US-Europe monetary and economic policy cooperation.
3 shares
Related5
USChina Tensions & Xi Jinping's Worldview
Zongyuan Zoe Liu talks about US-China relations, Xi Jinping's perspective, and China's strategic retaliation in a Council on Foreign Relations podcast.
3 shares
Global Commodities Price Projections
A 2025 podcast predicts a decrease in US crude production in 2026 due to trade policy uncertainty and OPEC's response, leading to a reassessment of oil price projections.
2 shares
Django Ledger Accounting Software
Talk Python podcast episode discusses Django Ledger, a tool for building personal accounting systems, developed by Miguel Sanda.
1 shares
Understanding Made in America
The IBKR Podcast examines the challenges of categorizing global companies for index inclusion, with a focus on the Made in America label.
1 shares
The Small World Hypothesis
In a podcast, Kyle delves into the history and evidence supporting the small world hypothesis.
0 shares
X / Twitter
Posts from quant researchers on X.
6 items
Quantitative3
The Role of Patience
ManGroup emphasizes the significance of patience in successful trend following strategies.
1 shares
The Memorization Problem
Research indicates that GPT-4o's extensive memory of economic and market data could bias its back-test results.
1 shares
Earnings Momentum in Stocks
Hou et al.'s research suggests earnings momentum works best in overlooked stocks, whereas price momentum is more potent in well-known stocks.
0 shares
Miscellaneous3
Agents
The article explores the influence of proprietary software on the operations of agents and agencies.
0 shares
Trend Paper
The study suggests that a single Exponential Moving Average (EMA) is sufficient for identifying trends, eliminating the need for multiple complex indicators.
0 shares
Crypto Pipeline
The article reports the open-sourcing of a crypto market data pipeline, used to create a database for a new research on cryptocurrency trends.
0 shares
Threads from r/quant, r/algotrading and friends.
10 items
Quantitative5
Realistic Sharpe Ratios
57 shares
OMM Position Taking
40 shares
Invest in Fund
82 shares
Brother's Pure Math PhD
136 shares
Misinformation from QuantInsider
74 shares
Rising5
Insider Scam
80 shares
Bot Time
121 shares
Offer Evaluation
54 shares
F Filings Scraped
70 shares
Idea Discovery
162 shares