TimesFM Volatility Forecasting
The study finds that the TimesFM model, with incremental fine-tuning, is effective for volatility forecasting in financial risk management, outperforming traditional models.
23 shares6 citations todaySource ↗
Quant LetterNo. 98
May 2025, Week 3
181 items across 9 sections, as sent to readers on 21 May 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 181
- Papers
- 113
- Sections
- 9
- Issue
- No. 98
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
23 items
Finance3
Financial Empowerment of Women in France
The research identifies factors such as founder status, spouse involvement, high income, and diverse professional networks as key to empowering women entrepreneurs in France by improving their access to external finance.
18 shares1 citation todaySource ↗
Hazard Rate Change-Point Model
The paper presents a new framework for estimating a hazard rate with an unobservable change-point, demonstrating its application in pricing credit-sensitive financial instruments and the potential for mispricing due to partial information.
16 sharesSource ↗
Economics7
Gender Disparities in Mental Load
Research from the TIMES Observatory in Italy shows that women in heterosexual relationships carry a greater mental load due to household and childcare tasks, causing emotional fatigue and impacting their work, a burden often overlooked by their male partners.
31 shares12 citations todaySource ↗
Human Behavior in Multi-Player Games
A study found that humans tend to choose lower numbers when playing strategic games against Large Language Models (LLMs), influenced by those with high strategic reasoning skills and their perceptions of LLM's reasoning and cooperation abilities.
19 shares3 citations todaySource ↗
CAGRU Model for Purchase Prediction
A new model, Clustering and Attention mechanism GRU (CAGRU), has been proposed for predicting customer buying intentions, using customer characteristics and a GRU neural network to provide more accurate predictions across different customer groups.
16 shares3 citations todaySource ↗
AI GDP Impact
The research shows a positive link between artificial intelligence growth and GDP per Capita, suggesting a 23.9% AI increase is needed for a 1% GDP per Capita rise.
16 shares2 citations todaySource ↗
Multivariate GARCH Portfolio Optimization
The paper introduces a model that tracks changing volatility and dynamic correlation in asset returns, underlining the significant losses from overlooking changing correlation and tail risk.
14 sharesSource ↗
Weather Uncertainty Energy Storage
The study creates a model for fully decarbonized energy systems with long-duration energy storage in Europe, indicating that solar PV increases in system value due to its predictability.
13 shares4 citations todaySource ↗
Unified Asset Dynamics Framework
The research formulates a model that monitors fluctuating volatility and dynamic correlation in asset returns, stressing the considerable losses from neglecting fluctuating correlation and tail risk.
13 sharesSource ↗
Miscellaneous6
Scalable Optimization for Sparse Portfolios
The article introduces a quick and scalable gradient-based method for portfolio optimization, transforming the complex selection problem into a simpler task, with results comparable to commercial solvers and minimal error in portfolio variance.
30 shares3 citations todaySource ↗
Cosmos 1.0: Emerging Technologies Mapping
Emerging Technologies Mapping: The paper introduces a unique method to map emerging technologies, creating a comprehensive dataset and indices, with extensive metadata from various platforms to ensure the relevance and accuracy of the constructed indices.
24 shares3 citations todaySource ↗
SetSequence Model for Time Series
The article presents a Set-Sequence model for financial predictions, eliminating the need for manually created features, learning a shared summary at each period and predicting outcomes, performing better than benchmarks on stock return prediction and mortgage behavior tasks.
14 shares1 citation todaySource ↗
Algorithmic Hiring and Diversity Impact
A study reveals that algorithms designed to ensure gender-balanced candidate shortlists do not necessarily result in more diverse hires, especially when the algorithm's criteria aligns with the hiring manager's preferences.
13 shares4 citations todaySource ↗
Managerial Insights on Cybersecurity Strategy
A survey of over 1,000 managers in Europe, UK, and US shows that despite cybersecurity being viewed as a competitive edge, companies still struggle with limited resources, talent scarcity, and cultural resistance.
13 sharesSource ↗
Geometric Formalization of Stochastic Dominance
A new geometric framework for first-order stochastic dominance (FSD) in multiple dimensions has been developed, providing a simpler and more intuitive method for formal verification in economics and finance.
11 sharesSource ↗
Crypto & Blockchain4
Stablecoin in Monetary Ecosystems
Stablecoins, valued over USD 200 billion by 2025, are crucial to the global monetary structure, and a combined model of decentralized finance and payment innovation could improve financial inclusivity and resilience in digital ecosystems.
14 shares3 citations todaySource ↗
Causal Networks in Time Series Systems
A new method for fitting acyclic vector autoregressive processes provides a flexible way to identify hierarchical causal networks in time series systems, useful in econometrics and social network analysis.
13 sharesSource ↗
Cryptocurrency and Equity Markets
The relationship between cryptocurrency and equity markets is changing, with Bitcoin being the main information source, emphasizing the need for dynamic hedging ratios for risk management and portfolio diversification.
13 shares2 citations todaySource ↗
Tether's Impact on Treasury Yields
Tether, the biggest stablecoin, holds a large portion of U.S. Treasury bills, affecting their yields and potentially lowering sovereign funding costs, showing the influence of stablecoin demand on financial markets.
12 sharesSource ↗
Historical Trending3
Economic Policies and Housing Prices
The article discusses a machine learning model that accurately predicts house prices using macro-economic factors, outperforming existing indices.
18 shares4 citations todaySource ↗
Robust Inference for Financial Portfolios
The paper presents a new method called Nonparametric Angles-based Correlation (NAbC) that defines finite-sample distributions, aiding in better financial portfolio management.
18 sharesSource ↗
Energy Optimization in Production Systems
The study proposes a Simulation-Based Approach (SBA) for energy-intensive production systems, potentially reducing energy input by 14-25%, providing valuable insights for industry leaders.
15 shares1 citation todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
60 items
Quantitative30
Global Economic Uncertainty & Oil Market
The research shows a predictable two-way relationship between the Global Economic Policy Uncertainty index and global crude oil prices, mainly seen in volatility correlation.
2 sharesSource ↗
RLDAUNCE: Reinforcement Learning for Data
Reinforcement Learning for Data: The article presents RLDAUNCE, a method that improves data assimilation using physical constraints, focusing on uncertainty quantification and computational efficiency.
2 sharesSource ↗
Machine Learning IV Estimators
The paper highlights the challenges of nonparametric instrumental variable estimation, proposing machine learning instrumental variable algorithms for better performance through advanced regularization techniques.
4 sharesSource ↗
RealTime Earthquake Intensity ML
The research suggests a machine learning model for quick earthquake damage assessment using operational data from base station service providers, showing high accuracy and real-time functionality.
2 sharesSource ↗
Liquidity Risk in Bank Failures
The article examines the failures of Silicon Valley Bank and Credit Suisse, advocating for a revision of current liquidity risk metrics to better reflect the pace and size of stress outflows in modern banking.
2 sharesSource ↗
Predicting Work Accidents with ML
The study assesses the effectiveness of dimensionality reduction methods in predicting occupational accidents in retail, finding that Forward Feature Selection combined with the Gradient Boosting Classifier is most effective.
2 sharesSource ↗
CBDC & Financial Stability in Dual-Currency Economies
The summary introduces a framework for evaluating the financial stability implications of Central Bank Digital Currencies in dual-currency savings economies, using a robust scenario-driven methodology.
3 sharesSource ↗
Arbitrage in Perpetual Contracts
The study finds that price differences in cryptocurrency markets are influenced not only by transaction fees but also by the funding swap mechanism's clamping function.
3 sharesSource ↗
Challenges of Data Encryption in Emerging Economies
The paper explores the difficulties and potential solutions for implementing strong data encryption technologies in developing economies for secure and efficient big data marketing.
2 sharesSource ↗
Undetected Accounting Fraud Implications
The study uses machine learning to identify non-fraud instances in financial fraud research, improving inference and addressing undetected frauds.
2 sharesSource ↗
πDelocalization in Hydrazines
The research examines and compares four substituted carbazoles with NN bonds, offering insights into the differences between the four main NN bonds in hydrazine derivatives.
2 sharesSource ↗
Optimizing UHTC Oxidation Resistance
The study introduces an intelligent optimization framework using generative adversarial networks and active learning to tackle issues in the high-temperature oxidation resistance of ultrahigh temperature ceramics.
2 sharesSource ↗
Product Reliability from Customer Reviews
The article suggests using customer feedback from online reviews as a database for evaluating product reliability, a currently under-researched area.
2 sharesSource ↗
AI Agent for SME Loan Origination
The study presents a hybrid multiagent architecture that uses structured financial metrics and unstructured borrower intent to address the loan acquisition challenges faced by SMEs.
2 sharesSource ↗
Hybrid Framework for Dam Breach Prediction
The research introduces a hybrid framework that combines the BREACH model's physical mechanisms with machine learning to accurately predict dam breach parameters for disaster risk reduction.
2 sharesSource ↗
Validation Network
The article suggests transforming money into a 3D computational network using decentralized systems, smart contracts, and incentives to track property rights and liquidity in real-time.
12 sharesSource ↗
Data to Decisions
The wealth management sector is evolving due to machine learning, cloud computing, and data proliferation, improving processes, client interactions, and competitive edge.
2 sharesSource ↗
Hybrid Trading Framework
The article presents a hybrid trading framework that merges deep learning and candlestick pattern recognition to improve trading accuracy and order management.
2 sharesSource ↗
AI in Risk Management
The article examines the role of AI in financial risk management, focusing on its use in identifying, evaluating, and reducing various risks.
3 sharesSource ↗
Portable Alpha Implementation
The article explores the use of a convolutional neural network-technical analysis model and unsupervised learning in implementing the portable alpha strategy, allowing investors to isolate returns from market index exposure.
2 sharesSource ↗
Factor Investing
The lecture notes discuss the challenges and opportunities of factor investing in the big data and machine learning era, stressing the need to incorporate economic theory to prevent overfitting.
3 sharesSource ↗
Credit Score Analytics
The article discusses the application of machine learning techniques, specifically Artificial Neural Networks, in credit scoring, allowing efficient management of large, complex datasets and in-depth analysis.
2 sharesSource ↗
Machine Learning for GDP
Machine learning, specifically MultiLayer Perceptron, improves economic forecasting accuracy during volatile periods compared to traditional methods.
2 sharesSource ↗
Business Strategy Dynamics
Corporate diversification strategies greatly influence financial structure and market value, with product diversified firms being less risky due to increased liquidity.
2 sharesSource ↗
Leveraging Endowments with Debt
The Ford Foundation and others plan to increase charity donations over two years, partly funded by issuing 1.2 billion in social bonds.
4 sharesSource ↗
ERM and Currency Derivatives
Companies with advanced enterprise risk management are more likely to use currency derivatives for hedging, especially multinational and global firms.
2 sharesSource ↗
LowRank Matrix Completion
A new Gradient Descent-based solution for low-rank matrix completion in data science and machine learning provides efficient recovery and robust convergence guarantees.
3 sharesSource ↗
Comparing Mutual Fund Performance
There was no significant difference in the performance of stock mutual funds managed by domestic and foreign investment companies in Indonesia from 2010 to 2013.
2 sharesSource ↗
Predicting Supply Chain Disruptions
Machine learning can predict disruptions and optimize recovery strategies in supply chains, improving resilience and reducing costs.
2 sharesSource ↗
Feature Engineering in ML
Real-time machine learning strategies based on fundamental signals provide significant results, highlighting the importance of feature engineering in investment strategies.
2 sharesSource ↗
Financial30
Active Management Value
Only a small percentage of active US equity and bond funds, which investors pay a premium for, actually increase the investor's utility.
45 sharesSource ↗
Public Information Costs
An AI analyst can generate significant trading gains using public data, outperforming most mutual fund managers.
7 sharesSource ↗
Multivariate Affine GARCH
A specific financial model can capture time-varying volatility and dynamic correlation across asset returns, useful for portfolio optimization and option pricing.
3 sharesSource ↗
Portfolio Gyrations
Portfolio adjustments in equity mutual funds are influenced by various factors, with their importance varying based on market conditions and investment strategies.
2 sharesSource ↗
Biodiversity Risk
Current methods of measuring a firm's impact on biodiversity are flawed due to incomplete data, inconsistent methodologies, and lack of understanding.
3 sharesSource ↗
Overthe-Counter Trading
A model predicts that changes in inventory and transaction costs can shift trading methods and affect market indicators in over-the-counter markets.
2 sharesSource ↗
Financing Costs
Family-owned firms' financing costs and credit ratings are more sensitive to market stress levels, with costs fluctuating more compared to non-family-owned firms.
2 sharesSource ↗
AI Shrinkage for Portfolios
The article introduces a new AI-based tool that enhances the efficiency and performance of risk-optimized portfolios by correcting biases in traditional estimates.
4 sharesSource ↗
Risks of Passive Investing
The article suggests that the popularity of passive capitalization-weighted index funds may increase systemic risk and distort prices, and recommends rebalancing to non-price-based weights for better long-term returns.
3 sharesSource ↗
Index Investing Incentives
The paper discusses the impact of index investing on executive compensation, recommending that contracts should consider the index's price to increase effort sensitivity.
2 sharesSource ↗
Behavioral Portfolios
The study reveals that ignoring downside asymmetries in portfolio choice under disappointment aversion can lead to significant welfare loss, and that psychological factors can alter risk attitudes.
3 sharesSource ↗
Tether's Influence on Yields
The paper finds that an increase in Tether's market share of U.S. Treasury bills can significantly lower yields.
3 sharesSource ↗
Discount Factors Spillovers
The article presents a framework for estimating the stochastic discount factor by combining firm-level signals, highlighting the importance of large, low-turnover firms in the information network.
3 sharesSource ↗
Asset Prices and Wage Inertia
The study finds that considering fluctuations in unemployment and new hires in a model of endogenous wage inertia and growth can deepen the economic impact of recessions and increase the fall in asset prices.
2 sharesSource ↗
Manufacturing Cost Disclosure
The paper finds that detailed manufacturing cost information provides varied information to equity investors, affecting prices.
2 sharesSource ↗
Biomass Futures for Aquaculture
The article introduces a model using machine learning to help fish farmers hedge against production risks through biomass futures contracts.
4 sharesSource ↗
Multifactor Model for Fund Performance
A multifactor model is developed to assess the financial performance of global mutual funds, considering factors like return, risk, size, diversification, and transaction costs.
4 sharesSource ↗
Volatility Patterns in Continuous Trading
The research investigates volatility patterns in continuously traded assets, revealing a flat volatility profile.
3 sharesSource ↗
Interest Rate Sensitivities and Stock Returns
The paper explores the link between stock return sensitivity to interest rate changes and firm growth, showing a strong negative correlation with expected inflation sensitivity.
3 sharesSource ↗
Expected Returns Intersection
The study reveals that a few stocks significantly influence the performance of cross-sectional asset pricing anomalies, indicating potential mispricing.
3 sharesSource ↗
Derivatives on CO2-Emission Allowances in Italy
The research examines the Italian market for CO2-emission allowances derivatives, discussing its evolution, characteristics, price dynamics, and term structure.
2 sharesSource ↗
REIT Factors
The article presents and analyzes six REIT return factors, demonstrating that REIT-specific factors significantly outperform general equity asset pricing factors and show unique behaviors across economic regimes.
2 sharesSource ↗
Mutual Fund Naming and Investor Behavior
Despite regulations, mutual funds whose names don't reflect their holdings are rarely penalized by the market.
4 sharesSource ↗
Ambiguity Preference in Catastrophe Bonds
Economic outlook and natural disasters can predict price movements in catastrophe bonds, especially during crises and conflicts.
3 sharesSource ↗
Municipal Bond Auctions and Dealer Actions
Dealers in municipal bond auctions bid higher when they expect to gain new clients, leading to lower yields and expanded trading networks.
3 sharesSource ↗
Risk Sharing with Recursive Utility
A model with translation invariant recursive utility allows for optimal risk sharing and a closer look at the mutuality principle in syndicates.
3 sharesSource ↗
Hierarchical Risk Clustering vs Portfolios
Hierarchical risk clustering strategies in portfolio allocation can be affected by covariance matrix misspecification, despite their diversification benefits.
2 sharesSource ↗
Venue Participation in China Govt Bonds
Centralized trading in China's interbank government bonds market reduces costs, but Over-the-Counter venues are still used for their unique benefits.
2 sharesSource ↗
DualRisk Framework for DCF Valuation
Traditional valuation methods can obscure valuation deviations, a dual-risk framework can clarify how different beliefs cause persistent misvaluation.
2 sharesSource ↗
Commodities Investment Overview
Hilary Till's presentation at a conference covered the case for commodities, portfolio construction, and risk management in an actively managed commodity program.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
Enhanced Emerging Market Portfolio Performance
A new Automated Adaptive Trading System may help stabilize emerging markets during downturns, addressing issues caused by the rise of algorithmic trading and passive investing.
27 sharesSource ↗
Efficient Volatile KSE-30 Equity Identification
Machine learning has been utilized to identify assets driving downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization strategy 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 considering fat-tailed returns.
16 sharesSource ↗
Sharpe Ratio & 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 for HFT Strategies
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 study poverty in the Middle East and North Africa, showing how alternative data sources can be used for poverty analysis when traditional income data is scarce or unavailable.
10 sharesSource ↗
Statistical5
BRM for Predictions with Missing Patterns
The BRM method is introduced for analyzing missing data patterns, reducing data imputation and enhancing predictive performance.
20 sharesSource ↗
New Momentum Indicator for Equity Premium Prediction
A new machine learning strategy, N-MDIS, is proposed for better equity premium prediction, outperforming existing methods.
19 sharesSource ↗
Product Market Competition on Zero-Leverage Policies
Research shows that increased market competition leads firms to adopt zero-leverage strategies, especially those with higher earnings volatility.
18 sharesSource ↗
News Sentiment and Risk Management
The study indicates that accurately measured news sentiment significantly impacts stock return volatility, with GPT-4 potentially outperforming RavenPack.
16 sharesSource ↗
Stochastic Machine Learning for Production Technologies
A version of Stochastic Gradient Boosting is suggested to prevent overfitting in Data Envelopment Analysis, useful 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, with certain variables significantly impacting prediction accuracy.
28 sharesSource ↗
Tail Risk Management
The paper introduces two probabilistic deep learning frameworks for estimating financial risk measures, which outperform current methods and improve capital allocation in line with the Basel Capital Accord.
27 sharesSource ↗
Bond Market Volatility Forecasting
The volatility of 10-year treasury bond contracts can predict Chinese stock market volatility, with machine learning methods offering more accurate forecasts than traditional models.
24 sharesSource ↗
Lot Streaming and Scheduling
The article proposes a new algorithm and machine learning model to improve efficiency and accuracy in 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 Quantile Connectedness
The research uses machine learning to study the international housing market, finding that the US market is the main source of systematic shocks and its interest rate is the most influential global factor.
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, particularly during crises.
31 sharesSource ↗
Multifrequency Data Fusion for Carbon Price Prediction
The newly introduced MFF-CPPM model in China has shown higher accuracy and flexibility in predicting carbon trading prices compared to standard models.
10 sharesSource ↗
Historical Trending10
Predicting VIX Trends
The article discusses a machine learning study that uses weekly jobless claim data to predict the CBOE Volatility Index (VIX).
23 sharesSource ↗
Stock Price Prediction
The study reveals that traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices.
13 sharesSource ↗
AI Capability Impact
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
The article emphasizes the role of communication and a holistic approach, aided by machine learning, in addressing climate change and achieving net-zero goals.
4 sharesSource ↗
Dark Patterns in Retail Protection
The study investigates the use of behavioral sciences and AI in regulating and reducing dark patterns in the retail investment sector.
2 sharesSource ↗
Understanding Young Informal Workers in the EU
The research profiles young informal workers in the EU27, aiming to understand how the Covid-19 pandemic has impacted youth employment informality.
2 sharesSource ↗
Resource Management in Cloud Computing
The article discusses how artificial intelligence can improve resource management in cloud environments, boosting the efficiency of DevOps workflows.
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 their effectiveness.
2 sharesSource ↗
Bank Performance Determinants
The paper analyzes literature on factors influencing banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the COVID-19 pandemic.
1 sharesSource ↗
Online Gig Work Satisfaction Scale
The study tests the applicability of the Work Need Satisfaction Scale (WNSS) among online gig workers, suggesting modifications to the scale to better reflect the specifics of online platform work.
1 sharesSource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
12 items
Trending6
Building AI Agents
The article explores the difficulties in ensuring consistency in extended dialogues due to the limited context windows of Large Language Models.
31,263 shares
Evaluating Language Models in Healthcare
The article presents HealthBench, a freely available benchmark for evaluating the efficiency and safety of large language models in the healthcare sector.
3,390 shares
Open Source Moxin7B Report
The article emphasizes the recent major changes and increasing popularity of Large Language Models.
240 shares
Unified Multimodal Models
The team has created BLIP3o, a set of sophisticated multimodal models, through innovative training methods and datasets.
195 shares
Humanlike Episodic Memory
Large language models (LLMs) show great potential but struggle with handling extensive contexts, which impacts their consistency and precision over lengthy sequences.
182 shares
Scaling Atomistic Potential
Molecular dynamics simulations need a special combination of precision and scalability to tackle major issues in catalysis and materials design.
102 shares
Rising6
Novel Alphas in Quantitative Investment
The paper presents a new type of alphas for improving the modeling of scalar vector and matrix features.
91 shares
MultiAgent Simulation Scaling for Portfolio Construction
The article discusses the growing interest in LLM-based multiagent systems for their potential in simulation and performance improvement.
83 shares
Parallel Scaling Law for Language Models
The research uses P diverse transformations on the input, runs the model's forward passes simultaneously, and dynamically combines the P outputs.
73 shares
Novel Alphas in Quantitative Investment
The article investigates the presence of scaling laws in preference modeling, comparing them to those in language modeling, and how they relate to model and dataset sizes.
65 shares
MultiAgent Simulation Scaling for Portfolio Construction
The article examines the high performance of Reasoning Language Models that are capable of performing complex logical reasoning.
42 shares
Parallel Scaling Law for Language Models
The article emphasizes the success of Retrieval-Augmented Generation (RAG) in improving the accuracy of large language models by using information from retrieved documents.
19 shares
GitHub
Repositories the letter featured.
10 items
Finance5
MLTT - Machine Learning Trading Toolkit
Machine Learning Trading Toolkit details how machine learning can improve trading strategies.
25 shares
AIfinBERT - Financial Sentiment Analysis with BERT
Financial Sentiment Analysis with BERT examines the use of the BERT model in financial sentiment analysis.
1,671 shares
Quantsbin - Quantitative Finance tools
Quantitative Finance tools gives a rundown of different tools used in quantitative finance.
550 shares
HelixDB - Powerful opensource graphvector database
HelixDB is a powerful opensource graphvector database built in Rust for intelligent data storage for RAG and AI outlines the capabilities and applications of HelixDB, a smart data storage database.
1,505 shares
FinancialDataScienceinPython - Scripts and notebooks for financial data science
This collects the scripts and notebooks required to reproduce my published work is a collection of scripts and notebooks for replicating the author's published work.
48 shares
Trending5
Elegant Python API for Google Gemini
The article presents a new asynchronous Python API for the Google Gemini web application.
603 shares
Fully Local Manus AI
The piece introduces Manus AI, an artificial intelligence that operates independently of APIs and runs solely on electricity.
2,674 shares
AI companion for reading papers
The article showcases an AI tool that aids in comprehending academic papers.
1,378 shares
Visualization library for Rust
The article highlights a visualization library created specifically for the Rust programming language.
2,218 shares
Continuous Thought Machines
The piece discusses the idea of Continuous Thought Machines, highlighting the continuous nature of thought and reasoning.
722 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Algo Trading Platform Launch
Trading Technologies International has introduced TT Strategy Studio, a multiasset algorithmic trading platform for financial and energy firms.
12 shares
Standard Chartered Expands Hedge Fund Coverage
Standard Chartered has formed a global financial sponsors team to cater to hedge funds, private equity firms, and sovereign wealth funds, enhancing its investment banking services.
7 shares
Permutable Introduces LNG Data Feed
Permutable has launched a new liquefied natural gas sentiment data feed, adding to its Trading CoPilot suite for energy market players.
5 shares
BGC's FMX Exchange Debuts Treasury Contracts
FMX Futures Exchange, a subsidiary of BGC Group Inc, has started trading in US Treasury futures, broadening its product range and targeting a significant portion of the global fixed income market.
5 shares
Reinforcement Learning with Quant Strategies
Nerdbot is merging Reinforcement Learning with Quantitative Strategies to enhance their operations.
4 shares
Blue Diamond's April Loss
Blue Diamond Asset Management, a Swiss hedge fund, suffered its biggest monthly loss in April due to global tariff issues.
4 shares
Scion Asset Management's Bearish Moves
Scion Asset Management, led by Michael Burry, has nearly sold off all its listed equity holdings in Q1, betting against Nvidia and major Chinese tech stocks.
4 shares
Investors Shift to Hedge Fund Strategies
According to a bfinance report, institutional investors are increasing their hedge fund allocations to manage rising macroeconomic and geopolitical risks.
3 shares
Citadel Securities Trading Head Joins Jump Trading
Marcin Siwicki has resumed work following a hiatus of two years.
3 shares
Miscellaneous10
Energy PM leaves
Brian O'Hara has reportedly left his position as Senior Energy Portfolio Manager at Millennium Management after nearly three years.
2 shares
Banxia reduces China bank risk
Banxia Investment Management, based in Shanghai, is withdrawing from its China bank positions due to the country's escalating property crisis threatening the financial system.
2 shares
Hedge funds bullish on yen
Hedge funds are increasing their long yen positions in anticipation of potential currency discussions at the forthcoming G7 meeting.
2 shares
Greenlight's Einhorn bullish on gold
David Einhorn, the founder of Greenlight Capital, is increasing his investments in gold and inflation-linked trades due to fiscal irresponsibility and long-term macroeconomic risks.
2 shares
Baiont's Feng Ji: AI adoption key
AI adoption key: Feng Ji from Baiont warns that quant managers who fail to incorporate AI into their strategies will be outcompeted in the market.
2 shares
Hedge Funds Boost CLO Market
Hedge funds like Arini, led by ex-Credit Suisse trader Hamza Lemssouguer, are entering the $1.3tn US collateralised loan obligation market, intensifying competition for leveraged loan supply.
2 shares
Digital Assets Funds Gain Inflows
Digital asset inflows hit $785m last week, raising the year-to-date total to $7.5bn, counterbalancing the outflows seen from February to March, as per CoinShares' report.
1 shares
Activist Targets Swatch Board
Steven Wood, founder of GreenWood Investors, is trying to secure a board seat at Swatch Group, a rare case of shareholder activism at the Swiss watchmaker.
1 shares
Starboard Value Ends Oorvo Campaign
Activist hedge fund Starboard Value has gained board representation at Qorvo, with the semiconductor firm planning to nominate Peter Feld, Starboard’s Head of Research, to its board.
1 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Investment Strategies
Kurv Investments is utilizing volatility harvesting strategies to convert tech stocks into income-generating assets, providing a potential solution for investors seeking growth and income.
11 shares
EM Fixed Income
In a podcast, Jonny Goulden and Saad Siddiqui discuss the effects of recent market developments on the emerging markets fixed income asset class.
10 shares
Global Rates
Khagendra Gupta and Ipek Ozil discuss the factors influencing US and Eurex futures roll and their predictions for Jun25Sep25 bond futures rollover in a podcast.
8 shares
Grant Cardone Real EstateBTC Fund
In a podcast episode, real estate tycoon Grant Cardone shares his strategies for wealth, risk, and business growth, including his Bitcoin-backed real estate fund and views on AI leverage.
7 shares
Global FX Tariff Reset
Patrick Locke and James Nelligan discuss the FX implications of tariff deescalation, US fiscal developments, data surprises, and central bank meeting risk in a podcast.
6 shares
Related5
Private Markets Outlook
Rob Martin and Lushan Sun discuss the economic environment's impact on private markets in a podcast on LampG's Private Markets platform.
5 shares
Quant Community Improvement
The Quaint Quant Conference 2025 emphasizes the need for collaboration within the quantitative finance community.
5 shares
Market Mayhem Update
Michael Gayed highlights the fragility of the market recovery, pointing out the disparity between credit spreads and struggling small caps, and foresees a correction for gold.
5 shares
Gold as Wealth Preserver
Lynette Zhang advocates for physical gold as a safe haven during monetary uncertainty, claiming it's undervalued and the current monetary system is nearing its end.
4 shares
Global Macro Recession Risk
Philipp Carlsson-Szlezak presents a framework for evaluating macroeconomic risk, focusing on the effects of tariffs, AI, and technology on global economies and currencies.
3 shares
X / Twitter
Posts from quant researchers on X.
6 items
Quantitative3
Factor Investing by Chuan Shibrbr
The article offers detailed lecture notes on Factor Investing, covering areas such as Portfolio Sort Analysis, Regression-Based Tests, and Multiple Hypothesis Testing.
1 shares
Short-Term Reversals in Commodities
Rossi's new paper explores short-term basis reversals in commodity futures markets, suggesting a potential for significant risk-adjusted returns.
1 shares
AIs Integration into Workflow
The article emphasizes the increasing significance and quick incorporation of AI into workflow, backed by notable usage statistics.
0 shares
Miscellaneous3
Unpopular Opinion on AI
Google's ex-CEO, Eric Schmidt, discusses his perspective on artificial intelligence in a TED talk.
0 shares
AI Transformation of SDLC
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Interview with Peter Brandt
The article presents the first half of an interview with Peter L. Brandt, covering a range of thought-provoking subjects.
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Threads from r/quant, r/algotrading and friends.
10 items
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