Asset Pricing with Attention Models
The study finds that pretrained RNN attention models can effectively derive returns and hedge risks in asset pricing, even during extreme market conditions like the COVID-19 pandemic.
16 sharesSource ↗
Quant LetterNo. 111
August 2025, Week 5
108 items across 8 sections, as sent to readers on 29 August 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 108
- Papers
- 67
- Sections
- 8
- Issue
- No. 111
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
27 items
Finance10
ESG Risk Variables Algorithm
The research introduces a Hierarchical Variable Selection algorithm that outperforms traditional methods in identifying relevant ESG variables for corporate risk assessment.
10 sharesSource ↗
Dynamics of Stock Exchange
The paper uncovers the inherent bistability and complex dynamics of an artificial stock market exchange, which emerge from micro-level trading rules.
10 shares1 citation todaySource ↗
Pricing Random-Expiry Options
The study presents a new methodology for pricing random-expiry options, a type of nontraditional derivative contract, using an arbitrage-free trinomial tree approach.
10 sharesSource ↗
Forecasting Financial Returns with Neural Networks
The research shows that deep neural networks can accurately forecast financial return distributions and are competitive with traditional models for risk assessment and portfolio management.
9 sharesSource ↗
Forecast Combination for VaR and ES
The article discusses various methods for predicting Value-at-Risk and Expected Shortfall, highlighting the effectiveness of a trimmed mean approach, probability averaging method, and performance-based weighting combining.
8 sharesSource ↗
Decoupled LOB Representation for TBM Detection
The study suggests a learning framework to enhance the detection of trade-based manipulation in financial markets, with Transformer-based architectures proving most successful.
8 shares1 citation todaySource ↗
Combined ML for Stock Selection Strategy
The research proposes a stock selection strategy using combined machine learning algorithms, with Information Coefficients-based weighting showing superior results in returns and predictive performance.
7 sharesSource ↗
FinReflectKG: Financial Knowledge Graph Construction
Financial Knowledge Graph Construction: The paper introduces a large-scale financial knowledge graph dataset from SEC 10-K filings of S and P 100 companies, with a reflection-agent-based mode providing the best balance of efficiency, accuracy, and reliability.
7 shares22 citations todaySource ↗
THEME: Enhancing Thematic Investing
Enhancing Thematic Investing: The study presents THEME, a hierarchical contrastive learning framework for thematic investing, which surpasses baselines in multiple retrieval metrics and enhances portfolio construction performance.
7 shares2 citations todaySource ↗
Economics8
Ageing Populations & Economic Performance
Research indicates that countries with low or negative population growth tend to perform better in all indicators, contradicting the belief that fewer people result in a weaker economy and lower living standards.
121 shares1 citation todaySource ↗
Matching Market Integration & Child Welfare
A Japanese study suggests that partial integration of fragmented daycare markets can significantly offset losses from fragmentation, even if full integration isn't feasible.
14 sharesSource ↗
Punishment Impact on Cooperation
An experiment shows that the success of punishment in fostering cooperation greatly depends on the cooperative context, with communication being the most influential factor.
8 shares2 citations todaySource ↗
Carbon Disclosure & Financial Performance
A study using AI tools reveals that comprehensive carbon emissions disclosure positively affects the financial performance of Chinese A-share listed companies, emphasizing the significance of carbon transparency in financial markets.
7 shares3 citations todaySource ↗
Suspicious Transaction Reports and Money Laundering Convictions in the EU
A study suggests that an increase in suspicious transaction reports may initially lead to more money laundering convictions, but the effect diminishes with more reports, indicating that other factors are at play.
6 sharesSource ↗
Losing Public Health Insurance on Body Weight and Health Behaviors
A study on Tennessee's 2005 Medicaid contraction found that loss of public health insurance led to increased Body Mass Index and prevalence of overweight or obesity among childless adults, possibly due to unmanaged health conditions.
6 sharesSource ↗
Monthly Inter-Industry Payment Flows in the UK
The UK Office for National Statistics has released a new dataset of monthly inter-industry payment flows from 2017 to 2024, which can be used for economic research and policy advice, updating previous empirical results.
6 sharesSource ↗
General AI Agents for Predicting Human Behavior
Modern AI agents can be used to apply social science theories to new settings with little or no modification, and have been found to predict human behavior more accurately than traditional methods in a sample of new games.
6 shares13 citations todaySource ↗
Miscellaneous3
FinCast: Time-Series Forecasting Model
Time-Series Forecasting Model: FinCast, a new model for financial time-series forecasting, outperforms existing methods by effectively capturing diverse patterns without needing domain-specific adjustments.
10 shares19 citations todaySource ↗
Bias-Adjusted LLM Agents for Decision-Making
A persona-based approach using individual-level data from behavioral economics shows potential in adjusting biases in large language models, enabling them to simulate human-like decision patterns.
9 shares3 citations todaySource ↗
The Coherent Multiplex: Wavelet Coherence Architecture
Wavelet Coherence Architecture: The Coherent Multiplex system uses a multilayer graph to identify and analyze coherence among multiple time series in real-time, with potential uses in neuroscience, finance, and biomedical signal analysis.
6 sharesSource ↗
Historical Trending6
Structural Function Identification
The article introduces a model that calculates results based on inputs and an unseen deviation, using this to estimate a company's production function and inefficiency.
21 sharesSource ↗
Neural Operators for Convex Programs
The research demonstrates how generative equilibrium operators, a type of Neural Operator, can solve complex optimization problems with a realistic number of parameters, bridging the gap between theory and practice.
16 shares7 citations todaySource ↗
Generative Neural Operators
The article confirms the efficiency of generative equilibrium operators in solving complex optimization problems, including nonlinear PDEs, stochastic optimal control problems, and mathematical finance hedging problems.
16 shares7 citations todaySource ↗
Super-Heston-Rough Model
The article proposes a bivariate Quadratic Hawkes process to model Time-reversal asymmetry in asset prices, accounting for differences in buying and selling actions.
13 sharesSource ↗
Option Pricing with Non-Markovian Volatility
The paper introduces a deep signature approach to asset pricing that simplifies rough stochastic differential equations into classical ones, addressing issues with non-Markovian stochastic volatility models.
12 shares1 citation todaySource ↗
Multi-Action Market Making with Hawkes Processes
The study combines Adversarial Reinforcement Learning, Hawkes Processes, and variable volatility to enhance market-making strategies, showing improved adaptability in high-volatility conditions and better market simulations.
11 shares3 citations todaySource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
Enhanced Emerging Market Portfolio Performance
A second-generation Automated Adaptive Trading System may stabilize emerging markets during downturns, countering challenges posed by algorithmic trading and passive investing.
27 sharesSource ↗
Volatile KSE-30 Equities Allocation
Machine learning has been utilized to identify assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization scheme for efficient asset allocation.
25 sharesSource ↗
Risk Parity Optimization
Using expected shortfall as the risk measure in risk parity portfolio optimization can lessen sensitivity to volatility shocks, decrease portfolio turnover during market turmoil, and enhance risk-adjusted returns with a sophisticated time series model.
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 method for assessing decision-making units' efficiency over time, using the Whale Optimization Algorithm to identify stable trading strategies and 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, highlighting the significance of using alternative data sources for poverty analysis.
10 sharesSource ↗
Statistical5
BRM for Predictions with Missing Patterns
The BRM method is introduced for analyzing data with blockwise missing patterns, improving speed and reducing data imputation by pretraining models on subsets of complete data.
20 sharesSource ↗
New Momentum Indicator for Equity Premium Prediction
A new machine learning strategy, N-MDIS, is proposed for improving equity premium prediction, outperforming existing strategies.
19 sharesSource ↗
Product Market Competition on Zero-Leverage Policies
The study suggests that firms are more likely to adopt zero-leverage policies as product market competition increases, especially in firms with high earnings volatility.
18 sharesSource ↗
News Sentiment and Risk Management
The study shows that accurately measured news sentiment significantly impacts intraday stock return volatility.
16 sharesSource ↗
Stochastic Machine Learning for Production Technologies
A version of Stochastic Gradient Boosting is proposed to estimate production possibility sets in DEA, reducing overfitting and providing a tool for scenarios requiring generalization.
16 sharesSource ↗
Machine Learning7
Machine Learning for M&A
The study shows machine learning models are more accurate than traditional methods in predicting Chinese corporate merger and acquisition activities, with some variables significantly affecting prediction accuracy.
28 sharesSource ↗
Tail Risk Management
The paper introduces two new probabilistic deep learning frameworks for estimating Value at Risk and Expected Shortfall measures, improving capital allocation in financial institutions according to the Basel Capital Accord.
27 sharesSource ↗
Bond Market Volatility in China
The research indicates that the volatility of 10-year treasury bond contracts can accurately predict Chinese stock market volatility, with machine learning methods providing more precise forecasts than traditional models.
24 sharesSource ↗
Lot Streaming and Scheduling
The article proposes a new algorithm and machine learning model to improve the efficiency and accuracy of the Lot Streaming and Scheduling Problem with stochastic product arrival times.
16 sharesSource ↗
Dynamics in Chinese Financial Markets
The paper introduces a new machine learning technique for decomposing and analyzing complex time series, providing an alternative to the Box-Jenkins methodology.
13 sharesSource ↗
Monetary Policy Frictions and Nonperforming Loans
The study uses machine learning to create a monetary policy frictions index, revealing that these frictions significantly impact the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
Housing Market Connectedness
The research uses machine learning to study the global housing market, finding that the US market and its interest rate are key in predicting global spillover intensities.
10 sharesSource ↗
Deep Learning2
Oil Price Forecasting: ML vs. DL
ML vs. DL: Research shows deep learning methods outperform 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 demonstrated higher accuracy and flexibility in predicting carbon trading prices compared to current models.
10 sharesSource ↗
Historical Trending10
Predicting VIX Trends
The article discusses a study that uses machine learning to predict the CBOE Volatility Index, highlighting weekly jobless claim data as a significant factor.
23 sharesSource ↗
Stock Price Prediction
The paper finds traditional machine learning models to be more effective than deep learning models in predicting Eurozone banking sector stock prices.
13 sharesSource ↗
AI Capability Impact
The article suggests that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure being key factors.
5 sharesSource ↗
Climate Discussions
The research highlights the role of communication and a holistic approach in addressing climate change, using machine learning to analyze social media discussions on the topic.
4 sharesSource ↗
Dark Patterns in Retail
The study investigates the use of dark patterns in retail investment, and how behavioral sciences and AI can improve regulation and investor protection.
2 sharesSource ↗
Young Workers in the EU: Pre-Pandemic Dynamics
Pre-Pandemic Dynamics: The research profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
AI Resource Management in Cloud Computing
The article 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: Review and Future Research
Review and Future Research: The paper analyzes literature on factors affecting banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the COVID-19 pandemic.
1 sharesSource ↗
Online Gig Work Satisfaction
The study tests the Work Need Satisfaction Scale's (WNSS) suitability 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 system enhances the performance of language agents by offering step-by-step guidance, leading to better decision-making in complex tasks.
189 shares19 citations todaySource ↗
Decision Theory for Prediction
The Risk-Averse Calibration algorithm improves decision-making in risk-sensitive areas like medicine by linking prediction uncertainty with risk-averse decision-making.
20 shares46 citations todaySource ↗
RoPEs Learning
STRING, an extension of Rotary Position Encodings, offers exact translation invariance and low computational footprint, enhancing performance in robotics and object detection.
13 shares20 citations todaySource ↗
Particle Trajectory Learning
PoLAr-MAE uses self-supervised learning to analyze complex data from Liquid Argon Time Projection Chambers, achieving high performance with less labeled data.
13 shares9 citations todaySource ↗
LoRAX: Model Adaptation
Model Adaptation: LoRA-X enables the transfer of fine-tuning parameters across different models without original or synthetic training data, enhancing the efficiency of text-to-image generation tasks.
13 shares11 citations todaySource ↗
Articulate Anymesh
Articulate Anymesh is a new technology that transforms any 3D mesh into a movable object, improving 3D modeling and robotic manipulation.
10 shares53 citations todaySource ↗
Hierarchical Sparse Bayesian Model
A new model for multi-task binary classification learning has been proposed, showing improved performance in predicting health status based on microbiome profiles.
8 shares1 citation todaySource ↗
COCONut-PanCap
The COCONut-PanCap dataset, featuring advanced panoptic masks and detailed captions, improves panoptic segmentation and image captioning, setting a new standard for multi-modal learning models.
6 shares14 citations todaySource ↗
GitHub
Repositories the letter featured.
10 items
Finance5
Vectorized Backtesting Python Framework
Python pandas has launched a vectorized backtesting framework to streamline and speed up the backtesting process.
817 shares
Finnhub Python API
Finnhub Python API Client provides real-time, high-quality financial data to investors, fintech startups, and investment firms.
775 shares
Efficient AlphaEval Framework
AlphaEval, a thorough and efficient evaluation system for formula alpha mining, has been put into operation.
31 shares
AlphaEval Implementation LeoDingggg
AlphaEval, a comprehensive and efficient evaluation framework for formula alpha mining, has been implemented.
41 shares
NucleusCloud Neosync Security Platform
A new open-source data security platform allows developers to monitor, detect PII, anonymize production data, and synchronize it across different environments.
4,100 shares
Trending5
Agile Ai Breakthrough
The article explores a novel approach to creating more adaptable and efficient AI systems.
11,051 shares
Postgres MCP Pro
The piece highlights the features of Postgres MCP Pro, such as customizable read/write access and performance evaluation for AI agents.
981 shares
DeepCode Agentic Coding
The article showcases DeepCode's unique method of turning text into web and backend code.
4,008 shares
Asterisk Toolkit
The article presents a powerful GUI app and toolkit for managing Claude Code, including the creation of custom agents and execution of secure background tasks.
14,849 shares
OpenMower Upgrade
The piece suggests an upgrade for budget-friendly robotic mowers, converting them into advanced, RTK GPS-enabled lawn mowing robots.
5,704 shares
News
Industry news: funds, hiring, markets and regulation.
13 items
Quantitative6
Numerai Secures JPMorgan Allocation
Numerai, a San Francisco hedge fund supported by Paul Tudor Jones, has received up to $500m from JPMorgan Asset Management, potentially increasing its assets to nearly $1bn within a year.
5 shares
GIPR Added to Quant Screener
GIPR has been included in the Custom Quant Screener, however, there has been an error in data retrieval.
2 shares
Hedge Funds Increase China Stock Buying
According to a Morgan Stanley report, global hedge funds are escalating their investments in Chinese stocks, with August predicted to have the largest monthly inflows since February.
2 shares
Windward Cineplex Buybacks
Windward Management is urging Cineplex Inc to implement aggressive share buybacks, sell non-essential assets, and prepare for a possible sale.
2 shares
Court Orders SEC Shortselling Review
A US appeals court has ordered the Securities and Exchange Commission to reevaluate its cost-benefit analysis of short-selling disclosure rules, marking a minor win for hedge fund groups.
2 shares
Urban Gro Inc. Quant Tools Ranking
According to a market trend report, Quant Tools has classified Urban Gro Inc. as a high-risk, high-reward investment based on AI-powered market entry strategies.
2 shares
Miscellaneous7
ExodusPoint Hires Gen AI Expert
The article offers advice on how to appeal to leading investment funds.
2 shares
Citadel Hires Teenagers for $200
The article explores Citadel Securities' inclination towards a particular kind of young talent.
2 shares
Ex-BoA Quant Finds LLM Traders Avoid Trading
The article conveys the annoyance of having your Master of Laws (LLM) adhere to simple instructions.
1 shares
Elliott Leads Citgo Auction
An affiliate of Elliott Investment Management leads the auction for PDV Holding, Citgo Petroleum's parent company, with a bid higher than Dalinar Energy's previous $7.4bn offer.
1 shares
Barclays Hires Deutsche Bank MD
A tech managing director has resumed work following a long hiatus.
0 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Arrowpoint CEO Jonathan Xiong Insights
Jonathan Xiong, CEO of Arrowpoint Investment Partners, shares his investment strategies and experiences in the finance sector in a podcast.
12 shares
GraniteShares YieldBOOST ETFs Explanation
In a LeadLag Live episode, William Rhind, CEO of GraniteShares, outlines the firm's YieldBOOST ETF strategy that generates high weekly distributions by trading options on volatile assets.
8 shares
French Political Scenarios Market Implications
A podcast features Meera Chandan, Aditya Chordia, and Raphael Brun-Aguerre discussing the potential impacts of French politics on economic, fiscal, rates, and FX markets.
5 shares
NanoConda Founder Roman Bansal Interview
Roman Bansal, founder of NanoConda, talks about his Russian upbringing, passion for reading, and how his company aids smaller firms with high-frequency trading setup in a podcast.
3 shares
China's Growth Drivers with LouisVincent Gave
In a MacroVoices podcast, Louis-Vincent Gave discusses China's global economic role, infrastructure goals, and the challenges of attracting foreign capital.
2 shares
Related5
Fantasy vs Fundamentals
Seth Cogswell from Running Oak talks about the current market trends, the prevalence of passive investing, and the possibility of a significant market correction on Lead-Lag Live.
2 shares
Built to Last?
Scott Bauer from Prosper Trading Academy discusses the market's robust recovery following Powell's Jackson Hole speech and the potential for sustained momentum.
2 shares
What's at Stake
Neil Azous from Rareview Capital talks about President Trump's increasing criticism of the Federal Reserve and its potential impact on interest rates, employment data, and the credibility of U.S. institutions.
1 shares
The Next Big Play?
Michael Normyle from NASDAQ discusses the potential benefits of investing in sports franchises, which are currently outperforming the stock market.
1 shares
Reviving the Economy?
Jose Torres, Senior Economist at Interactive Brokers, discusses potential Federal Reserve rate cuts and their possible effects on struggling sectors such as housing and manufacturing.
0 shares
X / Twitter
Posts from quant researchers on X.
2 items
Quantitative1
Latest Investing Research: Crude Oil, FX, SP 500, Portfolio, Blogs
Crude Oil, FX, SP 500, Portfolio, Blogs: The article discusses recent investment research on various topics including predicting crude oil returns, using media tone in foreign exchange trading, put writing strategies on the SP 500, and portfolio construction.
3 shares
Miscellaneous1
Fast Trading Signals: Noise Over Alpha
Noise Over Alpha: Daniel Bloch's article argues that fast trading signals, often seen as alpha, are typically just small sample noise. He suggests that what is perceived as speed is often just a faster response to randomness.
3 shares
Threads from r/quant, r/algotrading and friends.
6 items
Quantitative5
Quant Interview Guide
90 shares
Big vs Small Firm
32 shares
Affordable Trading Data
81 shares
Profitable Strategy
59 shares
Algorithm Market Monitoring
36 shares
Rising1
Small Fund
35 shares