OU Pairs Trading
A preliminary study shows that a pairs trading strategy using the Ornstein-Uhlenbeck process captures trends but underperforms due to non-stationary pairs and parameter tuning limitations.
8 shares1 citation todaySource ↗
Quant LetterNo. 79
December 2024, Week 3
187 items across 10 sections, as sent to readers on 18 December 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 187
- Papers
- 118
- Sections
- 10
- Issue
- No. 79
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
28 items
Finance9
Deep Covariance Forecasting
A new method for forecasting asset return covariance matrices using a Riemannian-geometry-aware deep learning framework outperforms traditional methods by considering the geometric properties of the matrices.
8 shares1 citation todaySource ↗
PolyModel Hedge Fund Portfolios
The use of machine learning and PolyModel feature selection in hedge fund investments improves returns and portfolio optimization, but also increases volatility, questioning the reliability of larger funds.
6 shares3 citations todaySource ↗
Deep Factor Residuals Trading
A replication of the Deep Learning Statistical Arbitrage methodology on recent U.S. equity data shows strong performance, suggesting potential overfitting, specific market conditions, or insufficient accounting for transaction costs and market impact.
5 sharesSource ↗
Interbank Market Analysis
The research explores the interdependence of banks in financial networks, revealing that smaller banks withdrew from high-value trades during the financial crisis.
5 shares1 citation todaySource ↗
SP 00 Prediction
The study uses machine learning to predict S&P 500 trends, concluding that KNN is best for short-term predictions and XGBoost for long-term forecasts.
5 shares1 citation todaySource ↗
Market-Neutral Strategy
The report outlines a market-neutral investment strategy for NYSE equities, demonstrating superior performance with risk parity.
4 sharesSource ↗
Complex Systems Distributions
The study introduces a statistical model to evaluate risk for rare events in complex systems, aiming to apply this model to financial markets.
4 shares3 citations todaySource ↗
AIEnhanced Factor Analysis
The project uses a blend of technical, market, and statistical factors with machine learning to predict stock market performance, emphasizing the benefits of merging financial expertise with computational tools.
4 sharesSource ↗
Economics8
Multiplexing and Diffusion
The study finds that multiplex social and economic networks can slow the spread of simple information but can either hinder or boost the spread of complex information, affecting inequality in outcomes.
13 shares3 citations todaySource ↗
Gender Identity Evolution
The analysis suggests that nonbinary gender identity could become dominant due to its adaptability, using a game-based approach and a genetic learning algorithm to study evolutionary dynamics.
8 sharesSource ↗
Youth Views on In-game Gambling
The report shows that Large Language Models can effectively identify patterns in digital games' gambling-like elements, but struggle with complex tasks.
7 shares1 citation todaySource ↗
Silver Monetization in Ming Dynasty
The article argues that silver monetization contributed to the Ming Dynasty's economic collapse by increasing wealth inequality and deflation.
7 shares1 citation todaySource ↗
Optimal Information Usage
The study creates a model to balance the use of beneficial information in competitive situations against the risk of getting caught.
6 sharesSource ↗
Power-Law Wealth Distributions
The research uses a feedback loop model to explain the differences in wealth distribution in the US and Japan, based on crowd interactions.
5 shares1 citation todaySource ↗
Organizational Culture and Industry
The paper finds a positive correlation between a progressive organizational culture and the use of Industry 4.0 technologies in Swiss companies.
4 shares13 citations todaySource ↗
Digital Technologies and Performance
The study reveals that Swiss firms that are more open to digital technologies tend to use performance incentives more often.
4 shares6 citations todaySource ↗
Miscellaneous5
Polarization in Similarity
Research indicates that digital platform recommendation systems can create echo chambers, reinforcing existing beliefs and limiting exposure to differing views.
13 shares2 citations todaySource ↗
Prediction-Enhanced Monte Carlo
The Prediction-Enhanced Monte Carlo framework uses machine learning to enhance the efficiency of Monte Carlo simulations, especially in large, path-dependent problems.
11 shares5 citations todaySource ↗
FinGPT for Stock Prediction
A data-driven method that includes news spread, contextual data, and explicit instructions enhances the accuracy of large language models in predicting short-term stock price movements.
10 shares5 citations todaySource ↗
CostAware Portfolios
Research suggests portfolio models that include transaction costs, highlighting the importance of considering these costs when rebalancing a portfolio.
6 shares2 citations todaySource ↗
Integrative Market Sentiment Analysis
The combination of Convolutional Neural Networks and Gated Recurrent Units offers a comprehensive analysis of stock market sentiment and effective early warnings of future risks.
3 shares10 citations todaySource ↗
Historical Trending6
Productivity Measurement with Large Language Models
Researchers have developed a method to label unstructured text, which was used to analyze clinical trials, showing that the number and type of trials have remained consistent since 2010, contradicting the perceived decrease in pharmaceutical research.
27 shares1 citation todaySource ↗
ChatGPT Research in Accounting and Finance
The article reviews recent research on Large Language Models (LLMs) in accounting and finance, highlighting three main themes, suggesting areas for future research, and offering technical advice for researchers using LLMs.
24 shares99 citations todaySource ↗
Portfolio Selection Game with Partial Information
The study investigates mean-variance portfolio selection under relative performance criteria, discovering that such criteria can cause a self-perpetuating decrease in investors' wealth, particularly when information is incomplete.
23 shares5 citations todaySource ↗
Soccer Skill Evaluation Model
The Soccer Factor Model (SFM) uses data from over 33,000 matches to accurately evaluate a soccer player's performance, separating individual skill from team strength.
19 shares1 citation todaySource ↗
Costefficient RLHF Data Construction
An auction mechanism is introduced to enhance cost-efficiency in fine-tuning large language models using Reinforcement Learning from Human Feedback, focusing on quality feedback and model performance.
14 shares3 citations todaySource ↗
Stochastic Control ML Algorithm
A machine learning algorithm is presented for solving complex stochastic control problems using a deep neural network, showing good convergence properties without depending on the Bellman equation.
12 shares1 citation todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
52 items
Quantitative30
Bitcoin Price Forecasting
The new model predicts Bitcoin's price based on factors like institutional adoption and supply shock, emphasizing the role of these factors in Bitcoin's price increase.
415 sharesSource ↗
Monetary Policy Impact
The study reveals that companies with access to big data adjust their capital investment more in response to monetary policy shocks, especially if the data feedback loop is strong.
6 sharesSource ↗
Cryptocurrency Arbitrage Trading
The paper offers advice on creating a high-frequency trading system that capitalizes on arbitrage opportunities in the cryptocurrency market.
3 sharesSource ↗
Mutual Fund Liquidity Fees
A theoretical model indicates that liquidity management tools are essential in reducing redemption pressures and maintaining market stability, with liquidity fees increasing redemption incentives and exit risks.
11 sharesSource ↗
Updating Online Reviews
The study observes the review updating phenomenon where consumers alter their existing reviews, demonstrating that updates usually lessen the severity of the review ratings and content.
130 sharesSource ↗
Portfolio Variable Selection
Machine learning methods can choose predictors for optimal portfolio choice, improving portfolio performance and decreasing portfolio risk, leading to high Sharpe ratios.
5 sharesSource ↗
Corporate ESG Narrative Transmission
The study uses Latent Dirichlet Allocation and the XGBoost algorithm to predict the link between the topics in ESG reports and the investment decisions of institutional investors, providing guidance for institutional investors and corporations.
6 sharesSource ↗
Warranty Accuracy: Machine Learning vs Human Estimates
Machine Learning vs Human Estimates: Machine learning models have been found to be more accurate than human experts in predicting warranty provisions in accounting due to human errors like aggregation bias and historical cost anchoring.
4 sharesSource ↗
Data Optimization for Large-Scale Industries
The article explores the use of machine learning models and cloud environments to optimize the processing of telemetry data in massively multiplayer gaming platforms.
2 sharesSource ↗
Enhanced Hybrid IDS for Zero-Day Attacks
A hybrid approach combining deep learning and machine learning is suggested for detecting common cyberattacks in computer network intrusion detection systems.
2 sharesSource ↗
Topological Quality Using Persistence Matching Diagrams
The article suggests that the quality of a dataset for machine learning models can be gauged and the performance of a supervised learning model can be predicted using topological data analysis techniques.
4 sharesSource ↗
FX Dealer Constraints and External Imbalances
The study examines the theory that changes in a country's external capital dependence can reprice currencies, using a new intermediary constraints index.
13 sharesSource ↗
Stock Lending, Retail Trading, and Liquidity
The halt of the security relending service in China resulted in an overvaluation of shortable stocks and increased liquidity due to more retail trading.
2 sharesSource ↗
Creditor Rights and Corporate Investment in India
The introduction of the Insolvency and Bankruptcy Code in India has improved investment efficiency and eased financial constraints, especially for business group-linked firms.
2 sharesSource ↗
Active Flow Control for Confined Square Cylinder Wake
The article introduces a deep learning surrogate model-based reinforcement learning approach for active control of two-dimensional wake flow, which reduces computational costs while maintaining reliability.
4 sharesSource ↗
Dynamic FX Hedging
Dynamic foreign exchange hedging strategies, considering factors like trend and interest rate differential, can improve returns and manage risk better than static ones.
41 sharesSource ↗
SP 00 Volatility
Simple volatility forecasts can stabilize volatility as effectively as complex models, enhancing stock market investment strategies.
6 sharesSource ↗
Legal Challenges in AI
The rise of AI-generated content online may corrupt data sets, potentially causing the failure of new AI models, suggesting reliance on pre-2022 data.
44 sharesSource ↗
ML Forecasting for Investments
The MLAGRUPPO model, combining machine learning and attention mechanism, can improve stock risk prediction and intelligent investment decision-making.
11 sharesSource ↗
Optimal Scaling in Computing
Machine learning can aid in predicting optimal scaling decisions for Azure Function Apps, reducing cold starts and improving resource use.
7 sharesSource ↗
SoC Estimation for Batteries
Comparing different estimation methods for Li-ion battery charge in electric vehicles can enhance Battery Management Systems, making them safer and more energy-efficient.
5 sharesSource ↗
Mutual Fund Redemptions
Mutual fund investor redemptions can reduce the liquidity of their equity holdings, with investor sentiment and stock returns being factors that negatively affect liquidity.
6 sharesSource ↗
Adversarial Attacks on Encrypted ML
The article explores the susceptibility of encrypted machine learning models to attacks and suggests ways to improve data security and model reliability.
2 sharesSource ↗
Fundamental and Non-Fundamental Volatility in GCC Stock Markets
The study analyzes the factors influencing stock price fluctuations in Gulf countries, focusing on the role of oil prices.
2 sharesSource ↗
Frugal Machine Learning: Efficiency and Accessibility
Efficiency and Accessibility: The paper provides an overview of frugal machine learning, techniques designed to make machine learning models more efficient and affordable.
3 sharesSource ↗
Capital Structure and Financial Performance in Nigeria's Oil and Gas Sector
The study investigates the link between capital structure and financial performance of Nigerian oil and gas companies over the past decade.
7 sharesSource ↗
Theoretical Uncertainty and the Low-Carbon Transition
The research questions traditional assumptions in Energy-Economy-Environment modeling, suggesting they may hide the varied effects of decarbonization policies.
21 sharesSource ↗
Quantum Computing Threats to Encrypted ML
The paper discusses the potential threats of quantum computing to encrypted machine learning systems, highlighting the need for quantum-resistant encryption.
2 sharesSource ↗
AI for Proactive Data Quality Assurance
The study introduces an AI-based framework for proactive data quality assurance, showing its effectiveness in enhancing data integrity and reliability.
2 sharesSource ↗
Improving Smart Learning with AI in Big Data
The project creates an AI-powered system for SMART learning that uses advanced machine learning to analyze student data and predict course completion success.
4 sharesSource ↗
Financial22
Investor Response to Exchange Rate Shocks
Monetary policy changes cause a shift in asset allocation, with wealthier individuals more likely to invest in risky securities, according to a study on household finance in open economies.
5 sharesSource ↗
Index Inclusion and Corporate Actions
Inclusion in a stock index increases market attention, influencing company investments and stock-based management pay, with companies investing more to minimize shareholder losses and reduce management compensation risk.
2 sharesSource ↗
Portfolio Optimization with GOPALS
The traditional method for portfolio optimization is prone to errors, resulting in suboptimal portfolios, and current techniques fail to fully address these issues.
3 sharesSource ↗
Investor Types & Asset Price Comovement
The study suggests that asset price comovement can significantly change if an investor type expands their investment universe due to an external shock.
3 sharesSource ↗
Bitcoin Price Forecasting
The research introduces a CNNLSTM model with various indicators for better Bitcoin price prediction, indicating potential for stable Bitcoin investment.
3 sharesSource ↗
Generative AI in Financial Info Processing
The paper shows that nearly half of retail investors use generative AI for financial information processing, with more advanced investors utilizing it more effectively.
3 sharesSource ↗
Iterated Combination Method for Risk Measure Forecasting
The study introduces an innovative technique, iterative combination, for forecasting Value-at-Risk and Expected Shortfall, proving it to be more effective than traditional methods.
10 sharesSource ↗
Formula Investing
The research compares four investment strategies, finding that none consistently outperforms the others and that their effectiveness has declined since 2000.
570 sharesSource ↗
Regulation CDO
The article explains how the Recourse Rule made top-rated ABS CDO tranches more attractive to BHCs during the 2007-2009 crisis, resulting in higher average estimated debt guarantees.
62 sharesSource ↗
Stock Returns
The study uses over a thousand machine learning models to predict stock returns, finding that design choices significantly affect predictions, with nonstandard error being 59% higher than standard error.
12 shares5 citations todaySource ↗
Sturm-Liouville Theory
The paper introduces a new approach to applying SturmLiouville theory in quantitative finance, offering innovative methods for spectral decomposition and new applications for credit risk modeling, interest rate derivatives, and portfolio optimization.
2 sharesSource ↗
Portfolio Optimization
The research suggests a portfolio optimization method that effectively uses information about the top 500 U.S. stocks, resulting in more stable weights and consistently better performance than value-weighted portfolios.
3 sharesSource ↗
Corporate Debt
The study examines the factors influencing active debt management for global firms, finding significant variation in prepayment across bonds and loans and decreased effectiveness of debt refinancing in tight global credit conditions.
14 sharesSource ↗
Memory in Markets
The paper investigates how memory affects the belief formation of financial market participants, finding significant recall distortions in consensus earnings forecasts of sell-side stock analysts, with analysts over-recalling distant historical episodes and selectively forgetting past positive events.
7 sharesSource ↗
Market Beta Assessment
A novel method for comparing market beta estimates to unobserved true betas is introduced, applicable to any beta estimate and requiring few assumptions about the true asset pricing model.
5 sharesSource ↗
Ethereum ETFs and Institutional Adoption
The 2024 approval of Ethereum exchange-traded funds is a pivotal moment for institutional involvement in digital assets, potentially improving market liquidity, attracting institutional capital, and changing views on cryptocurrency as an asset class.
2 sharesSource ↗
Event-Driven Connectedness Timing
A study of nearly 900 oil-related events from 1987 to 2022 shows that geopolitical events consistently cause more volatility in energy commodities than economic or natural events.
7 sharesSource ↗
DCCS Model Dynamics
The Dynamic Covenant Capital Structure model integrates Debt/EBITDA covenants into capital structure decisions, providing insights into how covenants influence corporate finance policies and helping firms optimize leverage and financial flexibility.
2 sharesSource ↗
Hybrid Model Calibration
The calibration of cross asset hybrid models for valuing and simulating exposure of complex financial instruments is explored, with a focus on understanding volatilities and correlations of interest and exchange rates.
3 sharesSource ↗
Gold in Decision-Making
An educational framework is proposed for studying gold's role in economic theory, focusing on its functions as a safe-haven asset, store of value, alternative to fiat currency, and its relationship with inflation and market volatility.
2 sharesSource ↗
Overconfidence and Trading Volume
A study finds a strong positive correlation between investor overconfidence and trading volume, indicating that overconfident investors tend to trade more, even when advised otherwise.
2 sharesSource ↗
Fraud and Financial Health
Accounting fraud significantly exacerbates financial distress among individuals exposed to it, with uninformed financial decisions made prior to fraud revelation increasing individuals' financial distress post revelation.
17 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
21 items
Finance4
Optimal Portfolio Analysis
The article presents a method for optimizing financial portfolios in markets with unpredictable volatility, using an approximation method and controlling errors with utility function expansion.
17 sharesSource ↗
Wealth Bias in Sin Stocks
The research reveals a correlation between the wealth of European societies and their investment in sin stocks, with wealthier Northern European countries yielding higher returns and familiarity leading to less rejection of sin stocks.
16 sharesSource ↗
Solution Uniqueness in Portfolio
The paper discusses the lack of solution uniqueness in mean-deviation portfolio optimization, suggesting that uniqueness cannot be expected in cooperative investment and proposing a resolution based on law-invariance.
13 sharesSource ↗
Portfolio Optimization with Transfer Entropy
The study incorporates transfer entropy into portfolio optimization to account for asset dependencies, showing that this method can effectively manage portfolio stability and provide a strong alternative to traditional risk measures.
11 sharesSource ↗
Statistical7
Equity Premium Forecasting
Machine learning methods show strong in-sample forecasting for equity premium but struggle to beat the historical average benchmark out-of-sample due to small datasets and low signal-to-noise ratio.
28 sharesSource ↗
Predicting Stock Market Crises
Extreme gradient boosting (XGBoost) is the best machine learning algorithm for predicting African stock market crises, with historical stock prices and exchange rates as key predictors.
22 sharesSource ↗
Factors Affecting Investor Decision
A study found that the decision to sell government retail bonds and the hold period are greatly influenced by their comparative return performance against other investments, as shown by logistic regression analysis and decision tree classification.
21 sharesSource ↗
Green Finance in Economic Forecasting
The research assesses the effectiveness of different machine learning models in economic forecasting, highlighting the deep multi-layer perceptron model as the most accurate and adaptable, and the decision tree as the best with bootstrap bagging technique.
18 sharesSource ↗
Systemic Risk in FinTech and Traditional Institutions
The research applies machine learning to study systemic risk factors in FinTech and traditional financial institutions, revealing that feature importance changes with market conditions and macroeconomic variables significantly influence systemic risk.
14 sharesSource ↗
Corporate Governance in Financial Distress in China
The research uses the LightGBM machine learning method to study the effect of corporate governance indicators on financial distress in Chinese public firms, identifying institutional ownership, managerial ownership, and executive compensation disparity as key indicators.
13 sharesSource ↗
Digital Platform Capabilities in Data Value Unlocking
The research identifies data integration, data analytics, and data productization as crucial digital platform capabilities, explaining their role in unlocking data value and promoting digital servitization in digital enterprises.
11 sharesSource ↗
Machine Learning8
Machine Learning in Credit Scoring
Research in a Chinese internet company shows machine learning credit scoring models prioritize data trails over default risk, reducing human experts' role to machine learning facilitators.
43 sharesSource ↗
Pricing Volatility Swaps with Machine Learning
The study introduces machine learning methods for pricing capped volatility swaps using unique data sets, also useful as a validation tool for external swap prices.
32 sharesSource ↗
Machine Learning Clustering in Finance
The article reviews machine learning clustering techniques used in financial markets and stock investing, emphasizing their potential to improve processes and reduce human errors, but also acknowledging their limitations.
27 sharesSource ↗
Automated Web Content Filtering
A machine learning system was created to filter and block inappropriate web content, capable of sending real-time alerts to guardians, logging objectionable content, and working in private browsing modes.
24 sharesSource ↗
Hybrid Machine Learning for Stock Volatility Prediction
A study uses machine learning to analyze stock market volatility, finding the RF-LASSO model to be the most effective predictor.
24 sharesSource ↗
Country Equity Returns: Insights from ML
Insights from ML: Machine learning is used to study fluctuations in country equity returns, revealing significant predictability and a varying sparse factor structure.
15 sharesSource ↗
Early Detection of Child Violence with ML
A paper uses machine learning to predict child abuse in Argentina, suggesting these models could help identify at-risk households early.
10 sharesSource ↗
Stock Price Reaction to Managerial Soft Info
A study uses unsupervised machine learning to analyze the effect of spontaneous information shared during conference calls on company stock prices.
9 sharesSource ↗
Deep Learning1
Predicting Salmon Prices with Deep Learning and Sentiment Analysis
The article discusses a study that uses deep learning models and sentiment analysis to predict salmon prices. The study found that the accuracy of predictions improved when sentiment scores from salmon-related news were included. The hybrid CNN-LSTM model performed the best in these predictions.
19 sharesSource ↗
Historical Trending1
Impact of Innovation News on Illiquid Stocks
The study finds that news on product innovations significantly influences the return of illiquid stocks, unlike other innovation-related news. Only news about significant corporate announcements positively impacts these returns, as determined through machine learning and expert analysis.
5 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
17 items
Recently Published10
CAPD: Portrait Avatars
Portrait Avatars: CAP4D is a method that uses a unique model to create and animate realistic 4D portrait avatars from any number of reference images in real time.
228 shares60 citations todaySource ↗
Temporal Gaussian Video Hierarchy
The paper introduces Temporal Gaussian Hierarchy, a new 4D representation that efficiently models long volumetric videos, reducing the number of Gaussian primitives and maintaining constant GPU memory usage.
135 shares80 citations todaySource ↗
Stereo4D: Learning Motion from Videos
Learning Motion from Videos: The authors have developed a system that mines high-quality 4D reconstructions from internet videos, allowing for the prediction of structure and 3D motion from real-world image pairs.
38 shares94 citations todaySource ↗
GenEx: Explorable World
Explorable World: GenEx is a system that plans complex world exploration, guided by its generative imagination about the surrounding environments, enabling AI agents to perform complex tasks.
25 shares24 citations todaySource ↗
FeatGS: Visual Foundation Models
Visual Foundation Models: Feat2GS is a framework that extracts 3D Gaussians attributes from unposed images, allowing for the probing of 3D awareness for geometry and texture through novel view synthesis.
22 shares29 citations todaySource ↗
Causal Diffusion Transformers
The article discusses Causal Diffusion, a framework that enhances diffusion models' performance and allows a seamless shift between autoregressive and diffusion generation modes, achieving top results on the ImageNet generation benchmark.
20 shares34 citations todaySource ↗
Spectral Image Tokenizer
The paper suggests a novel method for tokenizing images for autoregressive transformer-based image generation, using a discrete wavelet transform for a coarse-to-fine representation, offering benefits like improved next-token prediction and the ability to reconstruct varying resolution images.
20 shares15 citations todaySource ↗
PanSplat
The paper introduces PanSplat, a feed-forward method for wide-baseline panorama view synthesis supporting up to 4K resolution, featuring a unique spherical 3D Gaussian pyramid with a Fibonacci lattice arrangement for improved image quality and reduced information redundancy.
14 shares26 citations todaySource ↗
Apollo
The study explores the mechanisms behind video understanding in Large Multimodal Models (LMMs), showing that smaller models' design and training decisions effectively transfer to larger models, and introduces Apollo, a family of LMMs that excel across different model sizes.
14 shares97 citations todaySource ↗
Historical Trending7
Robot Motion Generation Review
The paper reviews 50 years of robotics research, discussing the evolution of methods for generating robot motion and the potential for integrating different techniques.
139 shares7 citations todaySource ↗
FlashRNN: Hardware-Optimized
Hardware-Optimized: The article introduces FlashRNN, a hardware-optimized version of traditional RNNs, which improves speed and processing capabilities for sequence modeling, outperforming existing models.
120 shares6 citations todaySource ↗
FlowEdit: Text-Based Editing
Text-Based Editing: The study presents FlowEdit, a new text-based editing method for pre-trained text-to-image models, which outperforms the inversion approach by offering superior results at a lower transport cost.
52 shares232 citations todaySource ↗
ObjectMate: Object Insertion Recurrence
Object Insertion Recurrence: The article introduces ObjectMate, a method for creating photorealistic compositions without altering the object's identity, eliminating the need for tuning.
40 shares19 citations todaySource ↗
Efficient Online Reinforcement Learning
The study introduces Warm-start RL (WSRL), a method for improving reinforcement learning initializations without offline data, leading to faster learning and better performance.
37 shares70 citations todaySource ↗
Length Optimization in Conformal Prediction
The research presents Conformal Prediction with Length-Optimization (CPL), a framework that creates optimal prediction sets while maintaining conditional validity under different covariate shifts.
33 shares46 citations todaySource ↗
Concept Bottleneck Language Models
The paper presents Concept Bottleneck Protein Language Models (CB-pLM), a generative language model that provides control and interpretability in protein generation tasks without affecting performance.
24 shares24 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
9 items
Trending4
Byte Latent Transformer for Language Modeling
The article presents Byte Latent Transformer (BLT), a new language model that offers efficient and robust performance at byte-level.
812 shares
Language Modeling in Semantic Space
The paper introduces a new architecture that works on a 'concept', a higher-level semantic representation.
310 shares
Replicating OpenAI's O1 Model for Coding
The report explores O1CODER, a replication of OpenAI's o1 model, designed specifically for coding tasks.
212 shares
Gaze Target Estimation with Learned Encoders
The article discusses gaze target estimation, a method to predict where a person is looking in a scene.
132 shares
Rising5
BoN Jailbreaking: High Attack Success Rates
High Attack Success Rates: The BoN Jailbreaking method successfully attacks closed-source language models like GPT4o and Claude 3.5 Sonnet.
131 shares
LLMs as Judges: Evaluation Methods
Evaluation Methods: The article critically analyzes the shortcomings of LLM judges and explores potential future improvements.
117 shares
SaT Universal Sentence Segmentation
A new model, Segment any Text (SaT), is introduced to address a specific issue.
108 shares
Lyra Speech-Centric Framework
The development of Multimodal Large Language Models (MLLMs) is crucial for a more versatile and efficient AI.
101 shares
Evolved Universal Transformer Memory
Earlier methods propose cost reduction in modern foundation models by selectively removing context parts while preserving original performance.
89 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Answers for Exercises in Financial ML
A detailed solution guide for the exercises in Dr Marco Lopez de Parodo's book 'Advances in Financial Machine Learning'.
631 shares
Stocks Portfolio Tracker
A portfolio tracker for stocks, futures, and options with potential integration of Interactive Brokers IBKR TWS API.
58 shares
AI Jupyter Notebook
An AI-powered Jupyter Notebook capable of generating and editing code, fixing errors, and interacting with data.
1,074 shares
FilterNet Time Series Forecasting
The official implementation of the 'FilterNet: Harnessing Frequency Filters for Time Series Forecasting' research paper.
102 shares
Ready Datasets for ML
A hub offering ready-to-use datasets for machine learning models and efficient data manipulation tools.
19,348 shares
Trending5
StackBlitz Bolt
The article explores the use of LLM in quickly editing and deploying full-stack web applications.
5,582 shares
Thammo4uva Tradier Wrapper
The article presents a Python wrapper specifically designed for the Tradier brokerage API.
19 shares
HashiCorp Nomad Orchestrator
The article details Nomad, a versatile workload orchestrator that can deploy different types of applications, integrated with Consul and Vault.
15,031 shares
VRCAR VMD Python
The article discusses the application of Variational Mode Decomposition (VMD) using Python.
349 shares
Google OR Tools
The article gives a comprehensive overview of the Operations Research tools provided by Google.
11,354 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Subjectivity in AI Predictions
The Machine Learning Times article explores the difficulty of incorporating subjectivity in AI's predictive value for quantitative analysis.
10 shares
Quant Capital Closure
Business Insider reports that Seven Eight Capital, a quantitative hedge fund, is closing due to substantial investor withdrawals.
7 shares
Hedge Funds Cut Bearish Bets
According to CFTC data, hedge funds and leveraged investors have minimized their negative positions on US five-year Treasury futures to the lowest since July.
7 shares
Quant Hilbert merges with Liberty AI
Following its recent acquisition, Hilbert Group AB has incorporated Liberty Road Capital's advanced AI technology into its trading and analytics system.
6 shares
UConn Changes Hedge Fund
BNN Bloomberg reports that the University of Connecticut's endowment is transitioning from hedge funds to buffer ETFs for a more cost-effective risk management approach in its $634m portfolio.
5 shares
Statar Capital's Return
Statar Capital, a Miami-based hedge fund managed by Ron Ozer, has recovered from a 13% loss in Q2 with a 23% increase by mid-December.
4 shares
Digital Assets Funds Expand
Digital asset investment products experienced $3.2bn inflows last week, pushing the year-to-date total to $44.5bn, a fourfold increase from any previous year, says CoinShares.
4 shares
Hedge Funds Favor Ether
Hedge funds have reached a record high in short positions on ether futures at the Chicago Mercantile Exchange, with contracts hitting an all-time high of 6349, reports BeinCrypto.
3 shares
Marshall Wace Ventures to Abu Dhabi
Marshall Wace, a London-based hedge fund managing $69bn in assets, has expanded its operations to Abu Dhabi, joining the increasing number of finance firms in the UAE.
3 shares
New Hedge Fund Launches Decrease
The number of new hedge fund launches is expected to hit a 24-year low, with only 123 funds launched globally by the end of September this year, according to Reuters.
3 shares
Miscellaneous10
Third Point Options
Third Point hedge fund is exploring strategic options to address the significant discount between its share price and asset value due to pressure from activist investors.
3 shares
British Founder Sentenced
Sanjay Shah, founder of Solo Capital Partners, has been sentenced to 12 years in prison by a Danish court for a £1.3bn tax fraud scheme.
3 shares
Two Seas Capital Appointments
Two Seas Capital has appointed Altaf Mackeen as Managing Director and Head of Research, effective from 1 January 2025.
3 shares
Magellan PM Resigns
Portfolio Manager Britney Lam has left Dubai-based hedge fund firm Magellan Capital just before its anticipated $700m launch.
3 shares
Citadel Hires Elliott PM
Citadel has hired a second Portfolio Manager from Elliott Investment Management, suggesting a possible shift towards activist strategies.
3 shares
MFA Calls for Form PF Deadline Extension
The MFA and three other trade associations have requested the SEC and CFTC to delay the compliance deadline for the revised Form PF requirements by six months.
3 shares
Tech Jobs in Hedge Funds: Demand High, Pay Low
Demand High, Pay Low: The popularity of hybrid roles in hedge funds is decreasing.
2 shares
Brazilian Hedge Funds Outperforming
In November, Brazilian hedge funds, which usually oppose local markets, experienced substantial profits due to fiscal worries causing market instability.
2 shares
Point72s Asia Trading Head Moves to Hong Kong Quant Fund
The article From Cubist to Qube lacks additional information.
2 shares
Gasoline Boosts Energy Bets for Hedge Funds
Speculators are growing more hopeful about gasoline futures due to low costs and possible supply limitations in the coming year.
2 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Fabio Ruggeri: Market Strategies
Market Strategies: The podcast explores the transition from traditional to technical data in market strategies, the evolution of options trading, and MenthorQ's tools for complex options data analysis.
27 shares
AI and Machine Learning
The CQF Institute will host an AI and Machine Learning in Quant Finance Conference on 17th September 2025, with speaker and agenda details pending.
17 shares
Seth Cogswell: Legacy Strategies
Legacy Strategies: Seth Cogswell from Running Oak Capital discusses his investment strategy aimed at maximizing earnings growth and minimizing large drawdowns, and the principles behind the Running Oaks ETF RUINN launch.
13 shares
Spreadbites: Credit Trends
Credit Trends: The Spreadbites podcast discusses key trends in credit markets, featuring insights from Stephen Dulake, Daniel Lamy, Nelson Jantzen, and Samantha Azzarello.
9 shares
Matthias Hanauer: Value Investing
Value Investing: Matthias Hanauer discusses the complexities of value investing, the influence of various factors, the potential of emerging markets and small cap stocks, and the integration of machine learning in investment strategies.
9 shares
Related5
AI Warfare & Autonomous Weapons
The Data Science at Home podcast discusses the use of AI in the military, including autonomous drones and surveillance tech, and the ethical concerns surrounding these advancements.
8 shares
Global Trade & Security in a Trump World
In the Tyranny Today podcast, Tomasz from Amvest Capital discusses global trade, security, and the potential outcomes of the Russia-Ukraine conflict.
7 shares
Modernizing Risk Management in Finance
Martim Rocha and Luis Jesus from SAS discuss on how financial institutions can use AI, cloud, and integration to improve risk management in a volatile market.
6 shares
Scaling AI Systems Like OpenAI
The Data Science at Home podcast explores how top AI companies like OpenAI scale their systems to handle millions of requests per minute.
6 shares
Global FX Strategy Update
The Global FX Strategy team at JPMorgan Chase discusses key market events and previews the upcoming week's economic calendar.
5 shares
X / Twitter
Posts from quant researchers on X.
10 items
Quantitative5
Statistical Arbitrage Review
The article reviews research on statistical arbitrage in various financial markets like equities, fixed income, and commodities.
5 shares
Human Intuition in ML
The article emphasizes the role of human intuition in the successful application of machine learning, outlining nine common scenarios.
4 shares
Synergizing Mean Reversion with TrendFollowing
The article investigates the advantages of combining mean reversion and trend-following strategies in a portfolio, with a focus on risk management.
3 shares
Fresh Research on Investing
The article provides a weekly summary of new research in the fields of investing and trading.
1 shares
News Sentiment for Stock Returns Prediction
The blog post explores the impact of news sentiment on stock returns, presenting research findings, testing a sentiment-based signal, and providing insights for investors.
1 shares
Miscellaneous5
Large Language Models for Time Series
The article explores the potential of using large language models as a basis for time series models.
1 shares
Insider Trades and Stock Alphas
The paper examines a vast dataset of global insider trades, generating a collective signal for each stock using different insider trade indicators.
0 shares
Curated Investing Research
The author offers a free weekly summary of the most recent investment research.
0 shares
Entropy Perspectives
The article discusses the concept of entropy and the various ways it has been defined over the years.
0 shares
PostEarnings Drift in Political Presidencies
The study shows a notable difference in post-earnings announcement drift during Republican and Democratic presidencies, suggesting it's due to investors' biased expectations of tax cuts.
0 shares
Threads from r/quant, r/algotrading and friends.
10 items
Quantitative5
Return Comparison
91 shares
Rate Options
20 shares
Volatility Query
13 shares
Masters Decision
12 shares
Low Latency Importance
70 shares
Rising5
ETF Market Making
101 shares
MT5 Quant Server Tutorial
48 shares
Hudson River Trading Interview
19 shares
First Job After University
17 shares
Alternatives to yfinance
69 shares