Quant LetterNo. 101
194 items across 10 sections, as sent to readers on 11 June 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
32 items
EDINET-Bench, a new open-source Japanese financial benchmark, is introduced to assess large language models' performance in financial tasks, showing these models' limitations in real-world financial applications.
25 shares9 citations todaySource ↗
A neural jump stochastic differential equation model is proposed for option pricing, combining neural networks with the traditional jump diffusion model, enhancing pricing accuracy.
7 shares1 citation todaySource ↗
A theoretical framework is developed for optimal hedging strategies for an informed broker dealing with multiple traders, using a mean-field game approach to establish equilibrium strategies.
6 shares1 citation todaySource ↗
The article investigates the predictability of individual equity options based on the volatility discrepancy, indicating that enhanced forecast error measurements can significantly improve portfolio performance.
6 sharesSource ↗
The study proposes a new theory to explain conflicting observations in market microstructure, attributing price formation to the average impact of metaorders and supporting the Order-Driven theory of excess volatility.
5 shares5 citations todaySource ↗
The research presents a new theoretical framework that resolves contradictions in market microstructure, suggesting that price formation is primarily influenced by the average impact of metaorders and endorsing the Order-Driven theory of excess volatility.
4 shares5 citations todaySource ↗
The study explores the asymptotic behaviour of Implied Volatility in the Bachelier setting, providing explicit expressions for the Bachelier Implied Volatility and linking these to the tail behaviour of the underlying's returns' distribution.
4 shares4 citations todaySource ↗
The research establishes a framework for stochastic portfolio theory that includes modern nonlinear price impact and impact decay models, deriving formulas for an investor's relative wealth and conditions for relative arbitrage in the price impact setting.
3 shares2 citations todaySource ↗
The paper tackles model uncertainty in quantitative finance by improving the conventional objective with an outer uncertainty measure, suggesting a subsampling strategy to approximate model uncertainty and introducing a modified stochastic gradient descent algorithm for efficient parallelization.
3 shares1 citation todaySource ↗
A study reveals that US bank failures from 1863 to 2024 are mainly due to worsening bank fundamentals like increasing asset losses and reliance on costly noncore funding.
11 shares18 citations todaySource ↗
A new framework based on deep reinforcement learning has been introduced to enhance the process of discrete choice modelling, adapting strategies dynamically without needing prior domain knowledge.
6 shares3 citations todaySource ↗
Research on Nusliko Park Ecotourism in North Maluku shows that tourist satisfaction and experience positively impact the decision to revisit, with satisfaction also acting as a mediator between experience and revisit decision.
6 shares8 citations todaySource ↗
The von Neumann-Morgenstern expected utility theorem has been thoroughly formalized using the Lean 4 interactive theorem prover, offering a solid base for applications in economic modeling, AI alignment, and management decision systems.
6 sharesSource ↗
Research shows that the Human Development Grant in Ecuador had no overall effect, but did improve economic resilience during COVID-19 for rural individuals who were eligible in their childhood.
6 shares1 citation todaySource ↗
A study of per capita output in 102 countries from 1970-2019 found a shift from a bimodal to a unimodal long-run distribution, indicating a single convergence club from 2000-2010.
6 shares1 citation todaySource ↗
A machine learning study found that private tutoring in Japan can have positive socioeconomic impacts, but these are undermined by economic disparities among households.
5 shares1 citation todaySource ↗
A paper introduces a multi-stage optimization framework to support investment decisions in flexible assets and enable reserve market participation, in response to increasing renewable energy sources and complex market conditions.
4 shares1 citation todaySource ↗
The article introduces flowOE, a new imitation learning framework that improves traditional financial market strategies, resulting in increased profits and lower risk.
13 shares2 citations todaySource ↗
The study presents flowOE, a unique imitation learning model that improves and learns from traditional financial market strategies, surpassing other models.
12 shares2 citations todaySource ↗
The research uses the Informer neural network for option pricing in financial markets, showing its improved performance over traditional models and improving financial forecasting.
9 shares8 citations todaySource ↗
Ethereum blockchain data shows 85% of transaction fees are from exclusive transactions, causing user transaction delays, and two bots are trading more efficiently than Binance.
19 shares2 citations todaySource ↗
Deep Reinforcement Learning algorithms, specifically DDQN and PPO, are effective in stock market trading, providing better risk-adjusted returns than traditional methods.
17 shares1 citation todaySource ↗
Simpler models with data preprocessing and hyperparameter tuning can match or surpass complex networks in short-term cryptocurrency price forecasting.
12 sharesSource ↗
Centralized markets typically lead in Ethereum price discovery compared to decentralized exchanges, affecting liquidity, arbitrage, and market efficiency.
4 shares29 citations todaySource ↗
By designing suitable funding rates, the perpetual future price of cryptocurrencies can align with the target value, providing issuers an effective hedging method.
3 shares1 citation todaySource ↗
A new AI framework has been created to quickly produce prebunking strategies against misinformation, which has been shown to decrease belief in election rumors and boost faith in election integrity across political divides.
237 shares4 citations todaySource ↗
Research using a unique open-source electricity market model indicates that transitioning to a zonal market in Great Britain could lead to substantial consumer savings and socioeconomic advantages, despite potential rises in capital costs.
29 sharesSource ↗
A study provides theoretical and empirical evidence for understanding the circumstances and methods through which machine learning achieves predictive success in finance, suggesting that successful predictions are more likely to come from simpler factors rather than complex mechanisms.
20 shares3 citations todaySource ↗
Research shows wholesale electricity markets are manipulated by companies to alter prices based on hourly profitability, indicating market power abuse.
15 shares2 citations todaySource ↗
A review of Large Language Models in credit risk estimation provides a classification of model structures, data types, and application areas to guide future AI and finance research.
15 shares16 citations todaySource ↗
A study with a European bank reveals customers are more likely to follow investment advice from a human-AI collaboration than pure AI, indicating human involvement can improve consumer outcomes.
14 shares9 citations todaySource ↗
A study on the Turkish banking sector identifies operation diversity, credit risk, and operating costs as key factors influencing net interest margin, with impacts varying across different bank types.
14 shares15 citations todaySource ↗
Working papers in finance and economics from SSRN.
54 items
The article introduces a new method for predicting and modeling time series data, capable of managing overdispersion, skewness, and changing volatility.
5 sharesSource ↗
The paper reassesses the strategy and value of American-style options contracts, highlighting the importance of gamma scalping profitability in the decision to stop.
4 sharesSource ↗
The study examines the relationship between hedging and potential market power abuse in wholesale electricity markets, calculating the hourly economic incentives for non-competitive behavior.
4 sharesSource ↗
The article explores the legal consequences of predictive uncertainty in machine learning systems under UK anti-discrimination law, stressing the significance of policy and design decisions.
4 sharesSource ↗
The paper studies the function of repo lending within the same bank holding company, discovering that internal liquidity channels aid in distributing liquidity from high-reserve banks to the broader financial system.
3 sharesSource ↗
The paper uses a unique dataset to measure the effect of first-time Buy Now Pay Later (BNPL) use on non-BNPL consumer debt and repayment ability, finding no negative consequences.
4 sharesSource ↗
The article presents new evidence supporting demand-based option pricing theory and the limits of arbitrage in option pricing, indicating that imperfect hedging or weekly rebalancing yield higher risk-adjusted returns for option writers.
2 sharesSource ↗
The paper presents a mathematical framework for studying Causal Graphs with Dynamic Trace GCTD, aiming to pioneer a new research field in discrete mathematics and network theory.
4 sharesSource ↗
The article highlights the need to quantify the interannual variability in climatological time series for accurate El NiñoSouthern Oscillation predictions, questioning current methodologies' effectiveness in a changing climate.
4 sharesSource ↗
The article emphasizes the importance of the DickeyFuller Test and Augmented DickeyFuller ADF Test in confirming time series stationarity, crucial in actuarial science, quantitative finance, and machine learning.
2 sharesSource ↗
The paper suggests a new approach to handle model uncertainty in quantitative finance, proposing an ad hoc subsampling strategy when a natural model distribution is absent.
2 sharesSource ↗
The study introduces a surrogate model to assess the resilience of vision-language models to minor perturbations, using adversarial perturbations in text and image modalities.
3 sharesSource ↗
The paper presents a class-balanced diffusion model to enhance credit card fraud detection, using a two-stage process to improve the quality of minority-class samples and remove noisy synthetic samples.
2 sharesSource ↗
The article discusses the potential of AI, particularly NLP, ML, and intelligent chatbots, to improve tax administration, while also considering the ethical and regulatory challenges of AI deployment.
2 shares5 citations todaySource ↗
The article categorises and reviews the optimisation methods used in Large Language Models like ChatGPT, Claude LlaMA, and DeepSeek.
16 sharesSource ↗
The study investigates the use of quantum machine learning to optimise high-frequency trading strategies in US treasuries and forex markets.
3 sharesSource ↗
A proposed framework uses deep reinforcement learning to optimise hedging of specific risk factors in financial instruments.
5 sharesSource ↗
The paper suggests a modified Kelly optimization that balances long-term growth with short-term recovery risk in skewed return environments.
6 sharesSource ↗
The study shows a negative impact of individual investments by venture capital partners on their institutional investments' performance.
5 sharesSource ↗
The research discusses the impact of AI on personal finance through robo-advisors, their evolution, functionalities, industry impact, and challenges.
4 sharesSource ↗
The article reviews the use of Big Data Analytics and predictive modeling in Risk Management for optimising transactions and operations in banks and financial services companies.
2 sharesSource ↗
The article investigates the use of Machine Learning for predicting market crashes, highlighting the challenges and techniques involved.
2 sharesSource ↗
The study suggests a hybrid quantum-classical machine learning model to improve the accuracy of credit default predictions in emerging markets.
2 sharesSource ↗
The article introduces the Hype Index, a tool that measures media attention towards large-cap equities using Natural Language Processing.
3 sharesSource ↗
The study presents a model that uses reference-dependent preferences to explain sentiment-driven asset prices and other asset pricing anomalies.
3 sharesSource ↗
The article discusses the limitations of Large Language Models in specialized areas and recommends fine-tuning techniques using domain-specific data.
3 shares1 citation todaySource ↗
The study suggests a new approach combining reinforcement learning, behavioral analytics, and natural language processing for personalized financial advice.
3 sharesSource ↗
The article explores the application of data analytics and machine learning in ecommerce for predicting customer behavior and optimizing marketing strategies.
2 sharesSource ↗
The study presents a portfolio strategy using the Markov-Modulated Shifted Wishart process to maintain diversification benefits during stable periods and lessen the impact of correlation spikes during crises.
2 sharesSource ↗
A new dataset has been developed using natural language processing and machine learning, providing detailed tech information about US public firms and patents over 30 years, aiding profitable trading strategies.
5 sharesSource ↗
A proposed portfolio theory framework models safety as a variable, investor-specific property that changes based on geographical, political, and institutional factors, rather than assuming a universally risk-free asset.
3 sharesSource ↗
The new Characteristic Vector Linkages (CVLs) method estimates firm linkages and constructs profitable momentum spillover trading strategies, with Quantum Cognition Machine Learning outperforming Euclidean similarity.
3 sharesSource ↗
The Deep Implied Volatility Factor Model, combining neural networks and linear regression, is proposed for estimating the daily Implied Volatility surface of individual stock options, improving performance around earnings announcements.
2 sharesSource ↗
Anti-ESG policies in Texas and Oklahoma have not significantly affected municipal bond markups or yields, contradicting the idea that such policies raise borrowing or transaction costs.
3 sharesSource ↗
A method to estimate higher portfolio moments like skewness using semidefinite relaxation is presented, showing that portfolio skewness can enhance the skewness of the optimal portfolio.
2 sharesSource ↗
The FAIR framework is expanded to tackle temporal challenges in financial operations, offering guidelines for financial institutions using Large Language Models and autonomous systems.
2 sharesSource ↗
The integration of climate metrics into investment portfolios as optimization constraints is demonstrated, indicating that the MSCI World Index can handle high integration of climate metrics with minimal performance or tracking error losses.
2 sharesSource ↗
Network informativeness, or the ease of information flow across sectors, is a leading indicator of real business cycles, with increased information flow leading to stronger industrial production and real GDP.
2 sharesSource ↗
The research compares the relationship between petroleum prices and stock sector indices in Canada, Saudi Arabia, the US, and China, showing varying volatility and optimal portfolio weights.
4 sharesSource ↗
A new forecasting framework is proposed for predicting the option implied volatility surface, which performs better than random walk forecasts on SP 500 IV surfaces.
3 sharesSource ↗
A study reveals that mispricing in currency markets is common and is more influenced by currency characteristics than macroeconomic fundamentals.
3 sharesSource ↗
Hilary Till discusses the commodity investment universe, covering topics like investment focus, return rationale, portfolio construction, and risk management.
3 sharesSource ↗
Banks with better ESG ratings have lower funding costs, with governance being the most significant factor, and changes in ESG ratings significantly affect banks' bond yields.
4 shares7 citations todaySource ↗
The paper outlines a framework for blended finance funds, highlighting the strategic use of concessional capital with private investment to promote sustainable development goals.
3 sharesSource ↗
A life cycle model shows that market returns significantly impact individuals' decisions on consumption, savings, housing, and relationships, leading to different life cycle profiles.
3 sharesSource ↗
A study reveals that U.S. public pension funds take on more asset risk due to low interest rates and underfunding, but these factors don't significantly affect net worth risk.
3 sharesSource ↗
The FOMO Capital Asset Pricing Model suggests that investors' fear of underperforming peers significantly influences stock returns, based on an analysis of U.S. equities from 1980 to 2024.
2 sharesSource ↗
Research shows that temperature anomalies impact firm-level risk and stock returns, leading firms to increase their green revenues to mitigate this risk.
3 sharesSource ↗
Two new methods for estimating stochastic volatility diffusions, using Quantum-Inspired Classical Hidden Markov Models and Quantum Hidden Markov Models, provide easy-to-calculate likelihood functions and filtering algorithms.
2 sharesSource ↗
Mandatory export proceeds repatriation doesn't significantly affect exchange rate volatility in Iran, Sri Lanka, and Turkey, as per a study using the Generalized Synthetic Control framework.
2 sharesSource ↗
The growth of AI in finance, especially in investment advisory, is boosting retail investor participation and financial inclusion, but also raises concerns about algorithmic bias, data privacy, and regulatory adequacy.
3 sharesSource ↗
A new classification system for environmental scores used by financial institutions and policymakers is proposed in a study, which reveals significant discrepancies among scores from different providers.
3 sharesSource ↗
A paper explores the role of repo contracts in central bank policies and banking system funding, the factors influencing euro-area repo market dynamics, and the potential benefits of central clearing services and new client clearing models for market efficiency and resilience.
4 shares4 citations todaySource ↗
Economics working papers from RePEc's NEP field reports.
30 items
A second-generation Automated Adaptive Trading System may stabilize emerging markets during downturns, despite challenges from algorithmic trading and passive investing.
27 sharesSource ↗
Machine learning has been used to identify assets causing downward trends in the Pakistan Stock Exchange, proposing a portfolio optimization scheme for effective asset allocation.
25 sharesSource ↗
Using expected shortfall as the risk measure in risk parity portfolio optimization reduces sensitivity to volatility shocks and improves risk-adjusted returns, especially during market turmoil.
16 sharesSource ↗
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 ↗
The study introduces a new method for assessing decision-making efficiency over time, using the Whale Optimization Algorithm, and applies it to forex investment strategies and utility firms in the Ho Chi Minh City Stock Exchange.
11 sharesSource ↗
The paper uses a new data augmentation technique to study 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 is introduced for analyzing incomplete data sets, showing improved predictive performance for both linear and nonlinear models.
20 sharesSource ↗
A new machine learning strategy, N-MDIS, is proposed for predicting equity premiums, demonstrating more accurate forecasts than previous methods.
19 sharesSource ↗
The study suggests that firms are more likely to adopt zero-leverage policies as product market competition increases, especially if they have higher earnings volatility.
18 sharesSource ↗
The impact of news sentiment on stock return volatility is reevaluated, indicating that both positive and negative news significantly affect intraday stock volatility.
16 sharesSource ↗
A version of Stochastic Gradient Boosting is proposed for estimating production possibility sets in Data Envelopment Analysis, showing better performance in high-dimensional settings and reducing overfitting.
16 sharesSource ↗
Machine learning models are more effective than traditional methods in predicting Chinese corporate mergers and acquisitions.
28 sharesSource ↗
Two new deep learning frameworks have been proposed for estimating financial risk measures, improving capital allocation in financial institutions.
27 sharesSource ↗
Long-term treasury bond contract volatility can predict Chinese stock market volatility, with machine learning methods offering more accurate forecasts.
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 statistical machine learning technique for analyzing and modeling complex time series, providing a potential alternative to the Box-Jenkins method in financial modeling.
13 sharesSource ↗
The study uses machine learning to analyze the impact of a monetary policy frictions index on commercial banks' nonperforming loans, advocating for more information transparency in monetary policy transmission.
12 sharesSource ↗
The research uses quantile connectedness models and machine learning to study the global influence of the US housing market and its interest rates, emphasizing their significant impact on international housing market spillovers.
10 sharesSource ↗
ML vs. DL: Deep learning methods have been found to be more effective than traditional machine learning in predicting oil prices, especially during crises.
31 sharesSource ↗
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 ↗
The article discusses a study that uses machine learning to predict the CBOE Volatility Index, with weekly jobless claim data being 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 research indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
The article emphasizes the need for communication and a comprehensive approach to address climate change, using machine learning to analyze social media discussions on the subject.
4 sharesSource ↗
The study investigates the use of dark patterns in retail investment, suggesting the use of behavioral sciences and AI to improve regulation.
2 sharesSource ↗
The research profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
The article discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
The review investigates the link between e-governance initiatives and citizen participation, emphasizing the need for interdisciplinary research to assess these initiatives' effectiveness.
2 sharesSource ↗
The paper analyzes literature on factors affecting banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the COVID-19 pandemic.
1 sharesSource ↗
The study tests the Work Need Satisfaction Scale's (WNSS) suitability among online gig workers, suggesting modifications to the scale to better reflect the specifics of online platform work.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
QLASS system enhances language agents' performance and decision-making by providing step-by-step guidance using Q-values, even with minimal supervision.
188 shares19 citations todaySource ↗
Platinum benchmarks are introduced to assess the reliability of large language models, showing that even sophisticated models struggle with basic tasks.
55 shares54 citations todaySource ↗
MAETok, an autoencoder-based system, learns a semantically rich latent space for high-resolution image synthesis, offering top-tier performance with quicker training and increased inference throughput.
38 shares94 citations todaySource ↗
NutWorld is a framework that converts monocular videos into dynamic 3D Gaussian representations, enabling high-quality video reconstruction and real-time applications.
29 shares8 citations todaySource ↗
A novel gradient descent algorithm with adaptive randomness enhances the global convergence rate for nonconvex optimization problems, proving its efficiency and robustness in complex situations.
28 shares6 citations todaySource ↗
The article introduces UAEval4RAG, a framework for evaluating the ability of retrieval-augmented generation (RAG) systems to handle unanswerable queries, emphasizing the role of component selection and prompt design.
27 shares10 citations todaySource ↗
The report discusses DeepSeek's new reasoning model, DeepSeekR1, which is cost-effective and competitive with OpenAI's models, impacting the field of Generative AI.
23 shares43 citations todaySource ↗
Theorem Proving: The paper presents BFS-Prover, a framework for automatic theorem proving using Lean4, showing that Best-First Tree Search can perform well in large-scale theorem proving tasks.
22 shares92 citations todaySource ↗
Python Toolkit for Retrieval: The article introduces Rankify, an open-source toolkit designed to integrate retrieval, re-ranking, and RAG processes, aiming to improve retrieval and re-ranking methodologies while ensuring consistency and ease of use.
21 shares11 citations todaySource ↗
The paper establishes a connection between prediction uncertainty and risk-averse decision-making, leading to an algorithm, Risk-Averse Calibration (RAC), which optimizes action policies from predictions, showing its benefits in areas like medical diagnosis and recommendation systems.
20 shares46 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
14 items
Automated LLM Framework: AutoAgenta is a new framework that enables users to build and launch Language Learning Model agents using natural language only.
4,632 shares
The Sequential Synthetic Data Vault (SDV) was utilized to produce synthetic data, and its quality was compared to a non-sequential model named CTGAN.
3,008 shares
RL System for Language Reasoning: Majority of large-scale Reinforcement Learning systems for Language Learning Models alternate between generation and training in a batch setting, with each batch being generated by the same model.
1,575 shares
The Godel machine is a self-enhancing AI that can make beneficial self-modifications.
1,078 shares
The Redundancy-aware KV Cache Compression (RKV) technique focuses on redundant tokens in reasoning models.
239 shares
Advances in text-to-speech synthesis have greatly enhanced the production of high-quality short utterances for specific speakers.
210 shares
The article critiques the limitations of generative models for Time Series Embedding (TSE), particularly in relation to perceptual quality and comprehension.
166 shares
The paper presents a new research area centered on automated identification of failures in Large-scale Learning Multiagent (LLM) systems.
155 shares
The article emphasizes the challenges in deriving significant biological understanding from intricate genomic data through Artificial Intelligence.
154 shares
Current AI models used for predicting Earth system dynamics are unstable during long-term simulations.
125 shares
The growing computational needs of large language models require efficient inference and activation strategies.
120 shares
Despite their excellent document processing capabilities, the high training costs of long-context language models often limit their use in custom applications.
84 shares
Cache Compression: Transformer-based language models store context as key-value pairs during the inference process.
65 shares
Repositories the letter featured.
10 items
The article shares the coding content from the 'Data Science From Scratch' book.
9,036 shares
The article explores the use of Python interactive dashboards for data science education.
1,653 shares
The article details an MCP server's interaction with the Financial Datasets stock market API.
321 shares
The article introduces an AI framework for stock analysis and prediction, incorporating various data sources and compatible with web pages and MCP SERVER.
123 shares
The article reiterates the introduction of an AI framework for stock analysis and prediction, using multiple data sources and compatible with web pages and MCP SERVER.
106 shares
The article explores a toolkit designed for the model context protocol on Apple devices.
1,733 shares
The piece introduces a cutting-edge open-source technology for text-to-speech conversion.
5,712 shares
The article presents an AI-based framework for handling complex projects, modeled after real-world team management.
432 shares
The article provides a guide on creating Fullstack Agents using the Gemini 2 platform.
5,139 shares
The piece discusses a web application for managing Scrapy clusters, analyzing logs, and sending alerts via a mobile interface.
3,292 shares
Industry news: funds, hiring, markets and regulation.
20 items
Hedge fund strategies like event-driven equity hedge and cryptocurrency led performance gains in May due to reduced volatility and improved macro sentiment, as per HFR data.
9 shares
BMO Global Asset Management and Goldman Sachs Asset Management are launching a new hedge fund product for accredited Canadian investors seeking low volatility uncorrelated returns.
7 shares
Korea Post has entrusted Mirae Asset Global Investments with managing a new overseas hedge fund mandate, starting with an investment of KRW500bn ($368m).
6 shares
A recruiter in the field of quantitative finance has expressed dissatisfaction with his colleagues.
5 shares
Saba Capital's founder, Boaz Weinstein, plans to invest billions more into UK investment trusts, which he believes are undervalued and mismanaged, as reported by Bloomberg.
4 shares
Hedge funds have rapidly increased their equity exposure, leading to the most successful May for global stock markets in decades.
4 shares
Dan Fletcher has been appointed as Transaction Reporting Manager at Qomply, a provider of regulatory technology solutions for financial markets.
3 shares
Jorn Grodeland, a long-time veteran of Brevan Howard, has moved to ExodusPoint Capital Management, a New York-based hedge fund firm.
3 shares
The European Energy Exchange plans to launch a new liquidity programme to stimulate trading activity in the Nordic power market, starting from 1 September 2025.
3 shares
The article explores the advantages and difficulties associated with undertaking a data transformation role.
2 shares
Teton Capital, under David Sokol, is pushing for governance and cost reforms at Atlantic Union Bank after buying a significant stake.
2 shares
Man Group has asked 150 London-based quants to return to the office full-time due to AHL's underperformance.
2 shares
Active Ownership Capital is pressuring HelloFresh SE over executive pay issues before its annual general meeting.
2 shares
Elliott Management and Silver Point Capital are spearheading a £10bn restructuring plan to prevent Thames Water from going bankrupt.
2 shares
SocGen reports that quantitative strategies are regaining popularity amidst the economic turmoil in 2025.
2 shares
Deem Global, a macro hedge fund, has increased its assets to approximately 1bn in the first half of 2025, according to Bloomberg.
2 shares
The article It was nice while it lasted C indicates the end of a previously positive situation or condition.
1 shares
The article From one QIS team to another discusses a transition or comparison between two Quantitative Investment Strategies teams.
1 shares
The hedge fund industry is now adopting the trend of UI engineering.
1 shares
Episodes on markets, quant methods and economics.
10 items
Mike Philbrick and Rodrigo Gordillo from ReSolve Asset Management discuss alternative assets, gold, bitcoin, portfolio diversification, and global investment strategies on the ReSolve Riffs podcast.
11 shares
Phillip Toews, founder of Toews Asset Management, advocates for portfolio designs that address both economic and psychological needs, aiming to limit downturn participation and capitalize on recoveries.
11 shares
Ralph Sueppel of Macrosynergy discusses the difference between academic and real-world quant, 'quantamental' strategies, and the benefits of socially responsible macro trading strategies.
9 shares
Stu Hitchcock from LampG talks about 'crossover credit', the market between investment-grade and sub-investment-grade credit, its size, deal types, and its role in a portfolio.
9 shares
Teresa Ho and Ipek Ozil discuss recent changes in rates markets, including the impact of eliminating IORB, the lifting of Wells Fargo’s asset cap, and Michelle Bowman’s confirmation as the Fed Vice Chair of Supervision.
9 shares
The podcast explores the potential risks and future prospects of the global agricultural market.
7 shares
In a podcast, Kim Flynn discusses the potential of interval funds and the democratization of alternative investments.
7 shares
Kai Wu suggests that traditional value investing metrics need to be revised to include intangible assets.
7 shares
The podcast discusses the future prospects for Emerging Markets in the latter half of 2025.
6 shares
The podcast covers the strategic dollar view, the impact of the ECB on the EUR, and the outlook for EM FX in the second half of 2025.
6 shares
Posts from quant researchers on X.
4 items
The latest investment research roundup discusses topics including cryptocurrency volatility, stock return sentiments, ESG's value indication, and volatility forecasting.
4 shares
ChristineCai27 has curated a reading list featuring recent developments in the field of applied econometrics.
1 shares
The article explores the growing trend of V-shaped recoveries in the economy.
0 shares
A Bad Idea: Article 2: The article challenges the argument against market timing, dismissing the fear of missing the best days, but cautions about its complexity.
0 shares
Threads from r/quant, r/algotrading and friends.
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