Quant LetterNo. 95
174 items across 9 sections, as sent to readers on 30 April 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
29 items
ClusterLOB is a new method for grouping individual market events in financial markets, aiding in understanding market structure and participant behavior, and developing effective trading signals.
26 shares3 citations todaySource ↗
The article discusses the evolution and implementation of target-date funds in Chile's 2025 pension reform, suggesting ways to improve long-term retirement outcomes for Chilean workers.
25 shares1 citation todaySource ↗
The study introduces a Nash allocation rule, based on game theory, for distributing systemic risk among financial institutions, proving its effectiveness with numerical case studies.
17 sharesSource ↗
The research investigates the best dividend strategies for an insurance company dealing with natural disaster claims, indicating that a climate tipping point can benefit shareholders looking to maximize dividends.
16 shares2 citations todaySource ↗
The article introduces QuantBench, a benchmark platform for AI in quantitative investment, designed to speed up progress in the field by providing a common evaluation ground and promoting collaboration.
16 shares1 citation todaySource ↗
The research uses the Financial Chaos Index to study stock market volatility, identifying three market types and using sentiment predictors for volatility forecasting.
13 shares2 citations todaySource ↗
The performance of leveraged ETFs is shown to depend on return autocorrelation and dynamics, with daily-rebalanced LETFs boosting returns in momentum-driven markets.
12 shares1 citation todaySource ↗
A deep learning model outperforms the Black-Scholes model in pricing European options on Petrobras, reducing mean absolute error by 64.3%.
12 sharesSource ↗
The paper suggests a framework considering the impact of climate events on company assets, indicating the need for extra safe capital to counter losses from physical climate risks.
9 shares4 citations todaySource ↗
The research introduces a return prediction framework for intraday returns using Echo State Network models, providing efficient implementation and strong forecasting performance.
9 sharesSource ↗
Research shows that the effectiveness of large language models in health communication varies based on language, topic, and source, highlighting the need for comprehensive multilingual validation before use.
25 shares1 citation todaySource ↗
The study introduces a model that determines the frontier function in an outcome variable by considering the maximum outcome and distribution of deviations, useful for identifying inefficiencies.
19 sharesSource ↗
A study using Booking.com data provides an in-depth analysis of North Africa's tourism sector, showing a diverse range of accommodations and a preference for unclassified offers.
16 sharesSource ↗
The paper suggests a hybrid architecture combining Convolutional Neural Networks and Transformers for efficient short- and long-term financial time series data modeling, showing improved performance in intraday stock price prediction.
14 shares7 citations todaySource ↗
The article presents a hybrid model combining Convolutional Neural Networks and Transformers for improved intraday stock price forecasting by effectively modeling financial time series data.
13 shares7 citations todaySource ↗
The study uses Random Forest machine learning and econometric models to explore the link between GDP growth and Gross Fixed Capital Formation, highlighting regional differences and investment patterns.
12 shares2 citations todaySource ↗
The paper reveals that non-instrumental image concerns cause individuals to underuse AI recommendations, leading to disregarded AI advice and decreased task performance.
12 shares1 citation todaySource ↗
The research finds a link between trade openness and CO2 emissions in Vietnam, supporting the environmental Kuznets curve and pollution heaven hypotheses, and showing WTO membership's positive environmental impact.
12 shares1 citation todaySource ↗
The article emphasizes the importance of energy security and resilience amidst global challenges, suggesting policy changes for future energy system planning to prevent disruptions.
13 shares42 citations todaySource ↗
The study explores the use of the Technology Acceptance Model in AI innovations under a transnational governance system, suggesting ways to increase AI accountability and global market acceptance.
12 shares2 citations todaySource ↗
The research introduces a robust federated logistic regression-based framework for analyzing financial data in a distributed setting, showing its similar performance to traditional centralized algorithms.
11 sharesSource ↗
The article reveals results for the PDE related to the logHeston model, proving a verification theorem and a convergence theorem for approximating the solution using a combined method.
11 sharesSource ↗
The Patched Channel Integration Encoder (PCIE) model, a new method using multiple stock channels and unique tokenization, has improved stock price forecasting and prediction.
13 shares1 citation todaySource ↗
The Bitcoin market generally follows the efficient market hypothesis, but occasional inefficiencies due to information gaps and behavioral anomalies can offer exploitable opportunities, though hard to consistently identify.
12 sharesSource ↗
The COVID-19 pandemic's impact on market efficiency varies across asset classes and markets, affecting returns in stock markets and multifractality in cryptocurrency markets.
10 shares8 citations todaySource ↗
The distribution of returns can be explained by the sum of conditionally independent random variables, with power-law tails in returns resulting from a power law tail in volatility distribution, as shown in data from the S&P 500, Apple, Paramount stocks, and Bitcoin.
9 sharesSource ↗
Research in two French mid-mountain regions suggests that diversifying tourism can lead to a larger, more varied tourism system, with different types of diversification coexisting within a territory.
32 shares11 citations todaySource ↗
A study on tourism diversification in French mid-mountain areas shows a pattern in diversification paths, with only one form leading to a larger, more diverse tourism system, and multiple paths can coexist within a territory.
32 shares11 citations todaySource ↗
A sentiment analysis system, using Natural Language Processing and machine learning, offers real-time interpretation of public opinion towards corporations, highlighting disparities in public sentiment and assisting stakeholders in strategic decision-making.
17 shares1 citation todaySource ↗
Working papers in finance and economics from SSRN.
60 items
The 2021 Amazon Last Mile Routing Research Challenge, backed by MIT, used real data to improve routing solutions, analyzing over 9000 historical routes.
7 sharesSource ↗
The article discusses how Natural Language Processing can help develop a simulation model for inventory management systems, improving upon traditional methods.
7 sharesSource ↗
GAVI, a new technique for reducing large state spaces, is introduced, capable of handling complex geometry and compressing large data sets.
8 sharesSource ↗
A joint model of implied volatility surface and its underlying asset is developed, offering a useful risk management tool and accurate VIX distribution forecasts.
4 sharesSource ↗
A model showing the interaction of monetary policy signals and market sentiment in driving financial tail risk is developed, indicating that aligned signals reduce risk and misaligned ones increase it.
6 sharesSource ↗
The research explores the effect of artificial intelligence on unemployment, predicting that AI will replace 85 million jobs by 2025 but also create over 95 million new ones.
4 sharesSource ↗
The study investigates if adding macroeconomic information to a Deep Learning Nelson-Siegel framework improves yield-curve forecasts, finding that including CPI inflation and M2 money supply improves prediction accuracy.
5 sharesSource ↗
Research shows travel time and crime rates affect consumer visits to Chicago locations, with high crime areas negatively impacting nearby low crime areas.
5 sharesSource ↗
The article explores the future of Service-Oriented Architecture (SOA) enhanced by Artificial Intelligence (AI) and Machine Learning (ML) for improved decision-making and data processing.
3 sharesSource ↗
The study reveals that investor attention, particularly from institutional investors, significantly predicts cryptocurrency volatility due to their superior market analysis skills.
2 sharesSource ↗
The paper introduces a statistical-methodological framework for commercial real estate market indicators to ensure consistency between individual property valuation and macro indicators.
3 sharesSource ↗
The article highlights innovative, cost-effective talent acquisition strategies like social media outreach and employer branding, using Indian Art Villa as a case study.
5 sharesSource ↗
The document uses statistical methods to estimate FC Barcelona's chances of winning the 2025 UEFA Champions League.
5 sharesSource ↗
The study introduces a deep learning framework, MR2TNet, to predict NIFTY50 index stock price movements by considering multiple information sources.
3 sharesSource ↗
The research uses machine learning to predict credit risk in supply chain financial services and examines the influence of supply chains on listed service companies.
2 sharesSource ↗
Theory and Practice: Machine Learning From Theory to Practice is a book that bridges the gap between theoretical and practical aspects of machine learning, with a focus on real-world examples and ethics.
3 sharesSource ↗
A new methodology combining operational data and advanced modeling is proposed to improve NATO's system qualification processes.
6 sharesSource ↗
The paper suggests new methods for estimating expected losses and optimizing solutions for machine learning problems using various types of data.
3 sharesSource ↗
The article explores the use of machine learning in predicting stock market movements and timing market entry, addressing challenges in financial data mining.
2 shares1 citation todaySource ↗
Certainty Equivalent: The paper examines the relationship between risk aversion, utility, and Certainty Equivalent (CE) using computational simulations, studying the impact of different probability distributions.
6 sharesSource ↗
The study discusses the use of machine learning in SAP ERP systems for predictive finance management, highlighting its effectiveness in detecting compliance violations and predicting financial trends.
2 shares1 citation todaySource ↗
The study reveals lower stock volatility in Mainland China's market due to price limits, and the superior performance of the ARMA10-EGARCH11 model in calculation accuracy.
3 sharesSource ↗
The study suggests a new automated method for fine-tuning machine learning models using optimization techniques like Bayesian Optimization, Genetic Algorithms, and Reinforcement Learning.
2 sharesSource ↗
The research introduces a combined machine-learning model to predict customer turnover in the telecom sector, utilizing deep learning, ensemble learning, and feature engineering.
2 sharesSource ↗
The paper discusses the use and effectiveness of machine learning in detecting phishing attacks, along with the challenges faced.
2 sharesSource ↗
The study analyzes the influence of quantitative trading strategies on price efficiency, concluding that the impact varies based on the quality of information.
3 sharesSource ↗
The article offers an alternative to cross-validation in machine learning, proposing an interrogation-based method for optimal model calibration.
3 sharesSource ↗
The article studies the EU Emissions Trading System and China's New Energy Vehicle credit market, offering insights into green trading markets and price volatility.
3 sharesSource ↗
The paper investigates advanced machine learning techniques for stock market prediction, concluding that deep learning models combined with sentiment features perform better than traditional methods.
2 shares1 citation todaySource ↗
The study explores the connection between return and volatility among major Latin American markets and the US, showing moderate integration at the median with higher interconnectedness at both ends.
2 sharesSource ↗
Luxury watches from brands like Rolex, Patek Philippe, and Audemars Piguet provide significant diversification benefits to portfolios, outperforming stocks, bonds, and gold, with lower returns on Sundays.
3 sharesSource ↗
Brexit has caused a 49% increase in bond listings in the EEA30 countries compared to the UK, indicating the European capital market's adaptation to losing its largest financial center.
5 sharesSource ↗
Classical vs Demand: Both classical and demand system asset pricing models have flaws, but the latter better matches the shape of observed demand curves.
4 sharesSource ↗
Stock returns are exceptionally high on days of scheduled macroeconomic announcements, with increased uncertainty about future monetary policy paths heightening market sensitivity to these releases.
3 sharesSource ↗
Chaos Order: The unpredictability of U.S. tariff policy under President Trump's second administration aligns with momentum-style investing and reinforcement learning, suggesting a dynamic and reactive policy process.
3 sharesSource ↗
Returns: The crypto market has evolved into a mature financial ecosystem with a liquid derivatives market, but it shows significant risk premia for small maturities and at-the-money prices.
2 sharesSource ↗
Investors serve as a liquidity safety net in the corporate bond market, with dealers offering discounts to investors for past liquidity services to maintain liquidity provider networks, particularly during market stress.
2 sharesSource ↗
The study presents a new financial market prediction model that integrates stock market dynamics, macroeconomic factors, and predictive modeling for enhanced forecasting accuracy.
3 sharesSource ↗
The article introduces ClusterLOB, a method for categorizing individual market events into three clusters, offering insights into unique trading behaviors.
2 sharesSource ↗
The paper highlights the improved forecast performance of a HAR model that uses the QLIKE loss for both out-of-sample forecast evaluation and in-sample parameter estimation.
2 sharesSource ↗
The research indicates that family equity investments in startups lead to lower returns and conservative strategies, implying that informal capital is driven by altruism.
2 sharesSource ↗
The author proposes an infinite rollover scheme in an economy with multiple bonds, demonstrating that deficit-financed fiscal stimulus is sustainable irrespective of the economic growth rate.
2 sharesSource ↗
The paper reviews the Federal Reserve's influence on the stock market, emphasizing its impact on average stock returns and the roles of yields and equity premia.
2 sharesSource ↗
The article contrasts the approaches of Canadian Prime Minister Mark Carney and the Trump administration to digital assets, underlining their differing philosophies and potential effects on financial systems.
2 sharesSource ↗
The paper presents a model that explores the interaction between small commodity producers and a dominant producer, identifying equilibrium conditions and potential impacts on the dominant player.
2 sharesSource ↗
Research shows advanced machine learning models are more accurate in predicting ultrahigh-frequency stock returns than simpler models, with accuracy decreasing over time.
7 sharesSource ↗
AI-generated articles on Seeking Alpha increase productivity but are less informative for capital market participants, benefiting only undercovered firms.
5 sharesSource ↗
The study explores how the need for transaction privacy in decentralized finance leads to the rise of powerful intermediaries.
11 sharesSource ↗
Research indicates mutual fund managers hold high prospect theory value stocks to attract more fund flows, with increased ownership weakening prospect theory preferences.
4 sharesSource ↗
The presentation emphasizes the importance of accurate fundamental data in understanding crude oil market trends through price-relationship data.
3 sharesSource ↗
The study finds that the local volatility model's restriction is not applicable to continuous-time models in stock price, interest rate, currency, and volatility data.
2 sharesSource ↗
The paper reviews studies on systematic cryptocurrency investment strategies, highlighting market inefficiencies and the superior performance of machine learning in capturing nonlinear price patterns.
2 sharesSource ↗
The article investigates the use of genetic algorithms in portfolio management, particularly in single-asset optimization and multi-asset portfolios.
3 sharesSource ↗
The research enhances the Black-Litterman asset allocation model by integrating the normal variance-mean mixture distribution for more accurate market representation and optimal portfolio decisions.
5 sharesSource ↗
The study uses machine learning models to predict industry-level returns, with a Hybrid model incorporating industry membership performing best.
3 shares2 citations todaySource ↗
The article highlights the growing popularity of Exchange Traded Funds (ETFs) among professional investors and private households due to their transparency, low costs, and continuous intraday trading.
3 sharesSource ↗
The paper studies the effects of interest rate increases by the European Central Bank and the Federal Reserve on Eurozone and U.S. banks and insurers' stocks and credit default swaps amid inflation and geopolitical tensions.
3 sharesSource ↗
The research investigates the creation of replicating portfolios using algorithms and heuristics, noting that these portfolios' stocks have a higher turnover rate.
3 sharesSource ↗
The paper explores how hedge funds use public information about interfirm links, revealing that they actively trade based on insights from their investor learning networks and exploit temporary pricing inefficiency in linked stocks.
3 sharesSource ↗
The article presents OptionMC, a Python package that uses Monte Carlo methods for European option pricing, and demonstrates its application and convergence behavior through systematic testing against established Black-Scholes solutions.
4 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The rise of algorithmic trading and passive investing has caused issues during market downturns, but a new Automated Adaptive Trading System could help stabilize emerging markets during such periods.
27 sharesSource ↗
Machine learning has been used to identify assets contributing to market declines in the Pakistan Stock Exchange, suggesting a portfolio optimization scheme for efficient asset allocation.
25 sharesSource ↗
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 ↗
The research compares Sharpe Ratio trading strategies with the buy-and-hold strategy across global markets, finding the former consistently outperforms the latter.
15 sharesSource ↗
The study introduces a new window analysis method for assessing decision-making units' efficiency over time, using the Whale Optimization Algorithm to evaluate foreign exchange investment strategies and utility industry companies.
11 sharesSource ↗
The paper uses a new data augmentation technique to analyze poverty in the Middle East and North Africa, specifically Lebanon, using alternative data sources when traditional income data is scarce or unavailable.
10 sharesSource ↗
The blockwise reduced modeling (BRM) method, which pretrains models on incomplete data subsets, is introduced for analyzing blockwise missing data patterns, showing improved predictive performance for both linear and nonlinear models.
20 sharesSource ↗
A new machine learning-based momentum-determined indicator-switching (N-MDIS) strategy is proposed for improving equity premium prediction, outperforming both MDIS and N-MDIS strategies with logistic regression.
19 sharesSource ↗
A study shows that firms, particularly those with high earnings volatility, are more likely to adopt zero-leverage policies as product market competition increases, emphasizing the influence of earnings volatility on capital structure decisions.
18 sharesSource ↗
The research suggests a modified version of Stochastic Gradient Boosting for estimating production possibility sets in Data Envelopment Analysis, which reduces overfitting and meets shape constraints, as proven by simulations and an empirical example using PISA data.
16 sharesSource ↗
The research reassesses the influence of news sentiment on stock return volatility, demonstrating that both negative and positive firm-specific and macroeconomic news significantly impact intraday stock return volatility, with GPT-4 classification potentially outperforming RavenPack.
16 sharesSource ↗
The research seeks to enhance the expected goal model in football analytics by integrating various data sources and using a supervised machine learning method, showing notable improvements in sensitivity, F1 metrics, and AUC metric compared to the standard.
10 sharesSource ↗
A study reveals machine learning models, using 60 variables, are more efficient in predicting Chinese corporate mergers and acquisitions than traditional methods.
28 sharesSource ↗
New probabilistic deep learning frameworks have been introduced for estimating financial risk measures, potentially aiding financial institutions in better capital allocation.
27 sharesSource ↗
Machine learning methods using the volatility of long-term treasury bond contracts can enhance the precision of stock market volatility predictions in China.
24 sharesSource ↗
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 ↗
The paper introduces a new machine learning technique for decomposing and analyzing complex time series, providing an alternative to the Box-Jenkins methodology, especially in financial data during the COVID-19 pandemic.
13 sharesSource ↗
The study uses financial news and machine learning to create a monetary policy frictions index, showing a significant positive impact on the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
The research uses quantile connectedness models and machine learning to study the international housing market, emphasizing the significant role of the US housing market and its interest rates on global spillover intensities.
10 sharesSource ↗
Machine Learning vs Deep Learning: The study reveals that deep learning techniques are more effective than traditional machine learning methods in predicting oil prices, especially during crises, due to their strong accuracy in medium to long-term forecasts.
31 sharesSource ↗
The article discusses a machine learning approach to predict the CBOE Volatility Index, highlighting weekly jobless claim data as a significant factor.
23 sharesSource ↗
The study reveals that traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices.
13 sharesSource ↗
The paper suggests that AI capability directly influences firm performance, with a data-driven culture and AI infrastructure being key resources.
5 sharesSource ↗
The study uses machine learning to examine social media discussions on climate change, advocating for a comprehensive approach and varied policies for effective action.
4 sharesSource ↗
The review investigates the link between e-governance initiatives and citizen participation, highlighting the importance of technological infrastructure, digital literacy, and government trust.
2 sharesSource ↗
The article explores the use of artificial intelligence in improving resource management in cloud environments for better DevOps workflows.
2 sharesSource ↗
The paper investigates the use of dark patterns in retail investment, suggesting the use of AI and behavioral sciences for better regulation.
2 sharesSource ↗
The study profiles young informal workers in the EU27, aiming to understand the impact of Covid-19 on youth informality in the labour market.
2 sharesSource ↗
The paper suggests new research areas in understanding banks' performance, considering digital transformation, AI, and the impact of COVID-19.
1 sharesSource ↗
The study looks into the relevance of the Work Need Satisfaction Scale among online gig workers, proposing modifications to suit the nature of online work.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
The article emphasizes the need for reliability in large language models, suggesting platinum benchmarks to reduce errors and highlights the models' struggle with simple tasks.
53 shares54 citations todaySource ↗
Tokenizers for Diffusion Models: The paper proposes MAETok, an autoencoder that enhances image synthesis by learning a semantically rich latent space in latent diffusion models.
35 shares94 citations todaySource ↗
Representing Monocular Videos: The study presents NutWorld, a framework that converts monocular videos into 3D Gaussian representations for high-quality video reconstruction and real-time applications.
29 shares8 citations todaySource ↗
Humanoid Platform: The research introduces ToddlerBot, an affordable, open-source humanoid robot for policy learning and research in robotics and AI, facilitating high-quality data collection.
19 shares21 citations todaySource ↗
Browser Agent Learning: The paper introduces NNetNav, a method for unsupervised website interaction that generates synthetic demonstrations for training browser agents, improving performance on WebArena and WebVoyager benchmarks.
15 shares57 citations todaySource ↗
The article presents Dress-1-to-3, a new method that creates realistic, simulation-ready 3D garments from a single image, improving the alignment of the 3D garments with the human figure in the image.
12 shares28 citations todaySource ↗
The research explores ways to speed up small language models, discovering that layer-wise adaptive pruning (Adapt-Pruner) is effective in large language models and outperforms existing pruning methods.
9 shares10 citations todaySource ↗
The paper introduces SG-RwR, a new framework for reasoning and planning with scene graphs, using two large language model agents to generate task plans and information queries.
7 shares6 citations todaySource ↗
The study presents SKI models, which incorporate 3D skeletons into the vision-language embedding space, using a skeleton-language model to enhance Vision Language Models and Large Vision Language Models.
3 shares6 citations todaySource ↗
The article introduces an artificial race driver (ARD) that learns vehicle dynamics and performs minimum-time maneuvers on a 3D track, using a new vehicle model for trajectory planning with economic nonlinear model predictive control.
1 shares9 citations todaySource ↗
Repositories the letter featured.
10 items
The article explores a high-powered Python engine designed for data processing and AI applications.
253 shares
The piece discusses the outdated version of QuantCoder, a tool for transforming financial research into trading strategies.
67 shares
This article offers tutorials from QuantConnect on using Jupyter notebook for Python Finance and LEAN.
583 shares
The article conducts a comprehensive benchmark assessment of change point detection algorithms on real-world data.
140 shares
The piece examines Test-Time Reinforcement Learning (TTRL), a technique used in machine learning.
286 shares
The Pocket Flow Tutorial Project uses AI to convert complex GitHub repositories into user-friendly tutorials.
6,672 shares
The repository provides an in-depth guide on building AI projects with the Raspberry Pi AI Kit.
211 shares
The article explores the application of OpenAI Realtime API on Arduino ESP32 for uninterrupted global AI speech conversations.
822 shares
The article presents a thoroughly developed, tested, and optimized support library for SQLAlchemy.
516 shares
Industry news: funds, hiring, markets and regulation.
19 items
Cboe Global Markets has begun trading in its new Cboe FTSE Bitcoin Index futures, based on the FTSE Bitcoin Reduced Value Index.
15 shares
Fund managers and institutional investors are reassessing their FX hedging infrastructure due to high volatility in global stock and currency markets, says MUFG Investor Services' Global Head of FX Services.
8 shares
Norges Bank Investment Management is expanding its hedge fund programme by awarding new mandates to long-short equity managers in Asia, Europe, and the US.
8 shares
Dymon Asia Capital has hired former Millennium Management portfolio manager Shao Ying to enhance its relative-value equity trading capabilities.
6 shares
ArthAlpha has launched a new MEQ Quant Investment Strategy for small and medium-sized businesses in India.
6 shares
Ukraine and creditors, including Aurelius Capital Management LP and VR Capital Group, have not reached an agreement on restructuring $3.2bn of debt.
4 shares
According to Morgan Stanley, Asia-focused hedge funds are cautiously reentering markets after a retreat due to tariffs imposed by the Trump administration.
4 shares
Valiant Capital Management, led by Chris Hansen, is experiencing strong returns from bearish bets in April due to market volatility caused by Trump's renewed tariff push.
4 shares
Alfonso Peccatiello, Founder & CIO of Palinuro Capital, shares his experiences as an emerging manager ahead of the Funds of the Future Summit.
3 shares
Landing a graduate job at a leading prop shop or hedge fund has become increasingly challenging.
3 shares
Robert Gibbins, founder of Autonomy Capital Research, plans to reopen his hedge fund to external investors after a performance increase due to a tech disruption strategy.
3 shares
CoinShares' weekly report reveals that digital asset investment products saw their largest inflows since mid-December 2024, amounting to 3.4bn.
2 shares
Ken Griffin, Citadel's founder and CEO, cautions that the Trump administration's trade policies might harm the US Treasury market's credibility.
2 shares
To prevent a potential proxy fight, Penn Entertainment will nominate two board candidates backed by activist hedge fund HG Vora.
2 shares
H Partners Management is encouraging HarleyDavidson shareholders to vote against three board members at the annual meeting on 14 May.
1 shares
Bill Ackman, CEO of Pershing Square, suggests China is compelled to negotiate a deal due to the ongoing tariff war with the US.
1 shares
Point72 is offering a base salary of up to $400,000 plus bonus to recruit a senior AI/ML staff engineer in the US.
1 shares
The Hedgeweek® European Awards 2025, honoring outstanding hedge fund performance and service, were presented in London on 29 April.
1 shares
Episodes on markets, quant methods and economics.
10 items
Carl Kawaja shares his investment approach, the influence of AI on semiconductor demand, and the changing dynamics of sports betting.
7 shares
Ben Bennett examines the market's response to tensions with the Federal Reserve, the trajectory of the dollar, and the possible end of American exceptionalism amid US asset volatility.
6 shares
A podcast predicts the future of the wider euro bloc and key FX insights from systematic models, setting a new EUR/USD target at 1.20.
5 shares
Michael Howell talks about the cyclical nature of credit markets and the significance of seeing them as a refinancing system, not a credit origination system.
5 shares
PhD candidate Manita Pote presents her study on identifying coordinated manipulation campaigns on social media, with a focus on the role of machine learning models.
4 shares
Sajjid Chinoy, Rajiv Batra, and Arindam Sandilya analyze the future of equity and fixed income markets in Emerging Market Asia after the IMF WB meetings in Washington DC.
2 shares
Despite Trump's tariff-induced market instability, Chinese tech stocks are outperforming US ones due to a valuation gap and China's potential AI leadership.
2 shares
Bertie Haskins from Capco discusses the difficulties of commercializing data in the Middle East and Asia-Pacific regions.
2 shares
Jack Copley explores the growth of the financial sector globally, with a focus on financial liberalization in Britain during the 70s and 80s.
1 shares
Marco Poletti of Goldman Sachs talks about the expansion and innovation in the cybersecurity sector in a recent episode of Goldman Sachs Exchanges.
1 shares
Posts from quant researchers on X.
4 items
The recent investment research roundup discusses various topics including the role of commodities in diversification, detection of mispriced stocks, quantitative techniques, and option anomalies.
2 shares
A study by Cartea et al. indicates that the success of intricate models largely relies on the quality of data, with a high chance of overfitting when data is scarce and noise levels are high.
2 shares
Article: Antti Ilmanen explores the concept of expected returns, focusing on the rational and irrational ways people form them.
0 shares
Article: ManGroup releases a new piece discussing the subject of market timing.
0 shares
Threads from r/quant, r/algotrading and friends.
2 items
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