Quant LetterNo. 22
115 items across 11 sections, as sent to readers on 18 October 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
27 items
The article suggests a new method for portfolio construction using preference relation graphs, which can improve the performance of statistical arbitrage methods by reconciling contradictory trading signals.
6 shares1 citation todaySource ↗
The article presents a new robust trading paradigm, multi-double linear policies, within a generalized lattice market model, demonstrating its effectiveness using data from the top 30 S&P 500 companies.
6 shares1 citation todaySource ↗
The article proposes a new method to detect significant changes in liquidity in an order-driven market using a market liquidity model and Marked Hawkes processes, validated with real market data.
3 shares4 citations todaySource ↗
The research introduces a method using high-frequency data to detect early signs of potential bank crises, proving that certain indicators can predict periods of high volatility in banking.
3 shares3 citations todaySource ↗
The article introduces X-Trend, a new time-series trend-following forecaster that adapts quickly to market changes, showing improved performance and faster recovery from the COVID-19 downturn than other models.
3 shares10 citations todaySource ↗
The article introduces a numerical asset-liability management model based on the multi-dimensional mean-field Libor market model, which can calculate future discretionary benefits in line with Solvency II regulation, using public life insurance data.
5 shares1 citation todaySource ↗
The research expands the rational approximation of the rough Heston fractional ODE solution to the Mittag-Leffler kernel case, demonstrating numerical proof of the solution's convergence.
2 shares5 citations todaySource ↗
The study emphasizes the significance of structural aspects in energy system models over input uncertainties, suggesting that temporal resolution greatly impacts results and should be prioritized over spatial resolution.
2 sharesSource ↗
The study assesses the financial understanding of Large Language Models (LLMs) like ChatGPT and GPT-4 using CFA Program mock exam questions to improve their use in finance.
8 shares32 citations todaySource ↗
The paper investigates the role of Large Language Models (LLMs) in speeding up data-centric R&D evolution, using quantitative investment research as a case study, showing promising results on the open-source research platform, Qlib.
4 shares1 citation todaySource ↗
The paper showcases the use of Large Language Models (LLMs) for precise and efficient extraction of information from the Q&A section of company financial reports, proving their method's superiority through various metrics.
2 shares25 citations todaySource ↗
Open-Source Text Digitization: EffOCR, a new open-source OCR package, is presented as an efficient, cost-effective solution for digitizing large amounts of public domain documents, successfully applied to historical U.S. newspapers and Japanese documents.
5 shares10 citations todaySource ↗
A study reveals that humans enhance their Go game skills after learning from an AI-powered program, with younger players and those from AI-exposed countries showing more improvement.
4 shares40 citations todaySource ↗
A study examines how sanctions affect a country's global economic standing, suggesting sanctioned countries may redirect trade to neutral or friendly nations, forming an alternative 'core'.
4 shares4 citations todaySource ↗
A proposed model indicates that agents are biased towards theories with strong supporting evidence and weak opposing evidence, causing skewed beliefs among less sophisticated agents.
5 sharesSource ↗
A proposed pricing model for Mobility-as-a-Service platforms could benefit all parties involved - the platform, travelers, and transit operators.
4 sharesSource ↗
The article introduces a risk management framework for blockchain protocol risks, created with financial institutions, blockchain developers, and regulators, to guide DLT adoption in finance.
7 shares2 citations todaySource ↗
The study establishes that every DeFi market has an invariant linked to arbitrage and completeness, offering a condition for no-arbitrage and completeness in nonlinear DeFi theory.
5 sharesSource ↗
The research conducts an economic analysis of Bitcoin, examining its impact, transaction volume, market capitalization, mining activities, and effects on traditional finance.
3 shares1 citation todaySource ↗
The paper explores the use of Natural Language Processing in analyzing crypto-asset white papers for regulatory compliance under the EU's crypto-asset regulation, discussing the potential and challenges of this integration.
3 shares1 citation todaySource ↗
The study develops a LAtent Causal Socioeconomic Health index at a national level, using spatial and statistical causal modeling to understand the impact of an observational variable on a spatially correlated latent trait.
43 shares1 citation todaySource ↗
The research examines the effect of big winner stocks on investment strategies, suggesting that passive investing is more likely to achieve long-term financial goals due to the risk of active managers missing substantial returns.
25 shares2 citations todaySource ↗
The research compares two randomizing methods in Quasi Monte Carlo applications, finding the Randomized QMC method to be superior in performance with better convergence rates and error bounds.
67 shares3 citations todaySource ↗
The study introduces faster and more energy-efficient algorithms for option pricing under various models, outperforming existing methods.
23 shares4 citations todaySource ↗
The article suggests a new method for valuing illiquid securities using the concept of micro-price and Fair Transfer Price, applicable in illiquid or one-sided markets.
21 shares3 citations todaySource ↗
The paper presents a solution for the multi-asset Merton investment problem under drift uncertainty, exploring the influence of drift distribution and ambiguity preferences on investment strategies.
20 shares10 citations todaySource ↗
The paper presents a new method using kernel ridge regression for nested simulation, which improves the convergence rate in high-dimensional problems, given a sufficiently smooth conditional expectation.
16 shares9 citations todaySource ↗
Working papers in finance and economics from SSRN.
28 items
The study proposes a Nonlinear Functional Autoregression framework for forecasting implied volatility in financial markets, proving its effectiveness in predicting the S&P 500 Index from 2009 to 2021.
2 sharesSource ↗
ML and Theory Integration: The article introduces a new model that merges deep learning and structural models for better prediction of equity returns and covariances, leading to higher returns and sharpe ratios.
3 shares1 citation todaySource ↗
A new method measuring financial intermediaries' residual interest rate risk found that U.S. life insurers are more sensitive to changes in long-term interest rates than property and casualty insurers.
9 sharesSource ↗
Banks are at risk of liquidity issues due to unpredictable payment flows, which can hinder lending and monetary policy, particularly during financial crises.
2 sharesSource ↗
Solo-managed hedge funds perform better than team-managed ones in terms of abnormal returns and market volatility skills, but they also have higher idiosyncratic and tail risk, and are less likely to be liquidated.
2 sharesSource ↗
Sentiment Analysis uses social media comments to understand people's opinions on various subjects, assisting in decision-making processes like product purchases or investments.
3 sharesSource ↗
Researchers suggest new methods for mutual information of tensors, applying it to k-means algorithm in 2D and 3D datasets.
3 sharesSource ↗
The article highlights the role of data science in identifying patterns for decision-making, and how changes like economic and political shocks can alter these patterns.
2 sharesSource ↗
A study presents a method to reduce the size of machine learning models, making research more accessible for those with limited hardware.
2 sharesSource ↗
The paper introduces a privacy-preserving k-means clustering algorithm for data mining, ensuring data privacy while using cloud servers.
2 sharesSource ↗
A survey reviews different machine learning techniques and their uses, emphasizing the need for appropriate technique selection for data analysis.
2 sharesSource ↗
The study reveals that funds focusing on climate change or decarbonisation strategies do not significantly reduce their portfolio's carbon intensity, suggesting potential greenwashing in responsible investing.
550 sharesSource ↗
The research shows that stock market volume decreases before FOMC announcements and increases afterwards due to discretionary liquidity trading and information asymmetry, especially for stocks with higher market betas.
75 sharesSource ↗
The research examines the effect of enhanced managerial reporting quality on investment decisions, concluding that it improves investment efficiency mainly by reducing internal information asymmetry.
2 sharesSource ↗
The research highlights a paradox in corporate risk management, where firms' diversification efforts to hedge against risk result in reduced growth, equity value, and inefficient resource allocation.
2 sharesSource ↗
The paper presents an asset pricing model that links stock market volatility to information, indicating a negative relationship between past volatility and future expected returns.
2 sharesSource ↗
Performance Comparison: The study evaluates asset pricing models in the Chinese Ashares market, concluding that a modified FamaFrench sixfactor model and a fourfactor model perform best, especially when transaction costs are factored in.
2 sharesSource ↗
The research explores capital allocation efficiency in developing countries, revealing that factors like limited finance access, bureaucracy, information asymmetry, and gender inequality obstruct efficient capital allocation.
2 sharesSource ↗
Attribution Framework: The study introduces a framework for assessing the ESG performance of a portfolio, indicating that U.S. public pensions' positive ESG performance is largely due to their underlying holdings.
2 sharesSource ↗
A study on the Heston stochastic volatility model shows challenges in producing accurate parameter estimates and limitations in capturing tail behavior with high-frequency financial data.
2 sharesSource ↗
New: A new asset pricing model, the generalized ACB, is introduced, enhancing the autoregressive conditional beta model by driving dynamic interaction effects among beta coefficients.
5 shares1 citation todaySource ↗
The study suggests a method to calculate ESG risk premiums using market data, revealing a significant link between ESG scores and asset process volatility and drift terms, indicating ESG factors impact company value.
16 sharesSource ↗
The research introduces a model where the same investor prices government and corporate bonds, causing credit spread variations beyond credit quality changes, driven by credit quality variation, risk-neutral correlation of risk factors, and portfolio rebalancing.
5 sharesSource ↗
Talk vs. Walk: The study finds that investors favor internal ESG labels over external sustainability ratings, significantly influencing fund flows, but high sustainability rating funds don't necessarily rebrand as ESG funds due to regulatory pressure and limited benefits.
15 shares3 citations todaySource ↗
The paper offers explicit formulas for the no-arbitrage price of various perpetual contracts, demonstrating that the futures price is determined by the risk-neutral expectation of the spot sampled at a random time reflecting the intensity of the price anchoring.
4 sharesSource ↗
The article discloses that liquidity conditions in the U.S. Treasury securities market deteriorated suddenly in March 2023 following two banks' failures, but quickly recovered, with liquidity continuing to closely follow the level expected by the path of interest rate volatility.
6 sharesSource ↗
Wine: Research indicates that adding a unique South African wine index to a portfolio can enhance risk reduction and diversification.
2 sharesSource ↗
The article suggests that improved assessment of required risk premia and fundamental values can significantly enhance the efficiency of financial markets.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
8 items
Profitability and Behavior: The research finds that algorithmic traders profit while non-algorithmic traders lose, with market volatility influencing their trading behaviors differently.
29 sharesSource ↗
Digital assets offer higher average returns than equity and commodities, but are more susceptible to short-term external shocks, according to a study.
28 sharesSource ↗
The paper introduces a new framework for dynamic bond portfolio optimization over multiple periods, proving it to be more effective than single-period optimization.
26 sharesSource ↗
The research finds that considering volatility clustering reduces hedging demands in dynamic multiperiod portfolio choices, while non-normalities have minor effects on allocations.
23 sharesSource ↗
The article introduces a new method for portfolio optimization using f-divergence induced coherent risk measures, showcasing its effectiveness through numerical experiments with selected stocks against the S&P 500 market index.
18 sharesSource ↗
The study reveals that credit card data can enhance the accuracy of real-time nowcasting of Japan's GDP, particularly in the early stages of forecasting when traditional data is unavailable.
15 sharesSource ↗
The paper proposes a new portfolio optimization method that uses multiple characteristic information to predict stock returns and risk exposures, demonstrating its effectiveness in achieving higher Sharpe ratios, smaller standard deviations, and lower turnover.
15 sharesSource ↗
The research finds that ESG equity ETFs in the U.S. generally outperform the S&P 500 Index, with approximately 16% providing positive and significant alphas.
15 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
12 items
The research analyzes the 'centroid' property using Bregman divergences under a monotonic embedding of the density function, linking common divergences with intermediate densities and highlighting the relationship between parametric families, quasi-arithmetic means, and divergence functions.
92 shares3 citations todaySource ↗
The research explores depthwise parametrizations in deep residual networks, identifying Depth-$\mu$P as the best parametrization for feature learning and diversity, but notes limitations in deeper blocks.
53 shares103 citations todaySource ↗
Hallucination Detection for Language Models: The study introduces SelfCheckGPT, a method for fact-checking black-box model responses without an external database, showing its ability to detect and rank factual and non-factual sentences, and outperforming grey-box methods in hallucination detection and factuality assessment.
99 shares1,236 citations todaySource ↗
Continuous Story Visualization Benchmark: The article presents StoryBench, a new benchmark for evaluating text-to-video models, including three video generation tasks and guidelines for human evaluation of video stories, emphasizing the need for improved automatic metrics for video generation.
62 shares28 citations todaySource ↗
Ferret, a new Multimodal Large Language Model, is introduced, excelling in understanding spatial references in images and grounding descriptions, surpassing existing models in multimodal chatting.
52 shares604 citations todaySource ↗
Open Math Language Model: The article discusses Llemma, a superior language model for mathematics that can prove theorems without additional fine-tuning.
434 shares497 citations todaySource ↗
Language Agent Platform: OpenAgents, a platform for utilizing and developing language agents in daily life, is introduced, providing a user-friendly interface and a basis for future research.
62 shares166 citations todaySource ↗
LLMs as OS: The article suggests MemGPT, a virtual context management method that enhances the context window of large language models, improving document analysis and multi-session chat performance.
33 shares1,373 citations todaySource ↗
Modeling Beyond Documents: The paper introduces In-Context Pretraining, a novel method that improves language models' performance by pretraining them on related documents, enhancing their contextual reasoning skills.
19 shares101 citations todaySource ↗
The 4DGS model is introduced, capable of reconstructing dynamic 3D scenes from 2D images and generating diverse views over time, providing real-time rendering efficiency.
16 shares627 citations todaySource ↗
A new framework is proposed that uses language models for interactive task planning, allowing for easy adaptation to different tasks and precise replanning based on new user requests.
11 shares68 citations todaySource ↗
A theoretical framework is provided that examines supervised pretraining for in-context reinforcement learning, offering insights into training transformers for reinforcement learning algorithms and the impact of distribution mismatch in offline training data.
10 shares90 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
4 items
The article suggests a new approach to time series forecasting by converting it into a numerical string and predicting it as the next token in text.
98 shares
A Superior Language Model: The article introduces Mistral 7B v0.1, a highly efficient language model with 7 billion parameters designed for superior performance.
3,407 shares
Privacy Revealed: The article investigates how much private information can be exposed by text embeddings from the original text.
129 shares
A Survey: The article addresses the crucial topic of factuality in Large Language Models (LLMs).
64 shares
Repositories the letter featured.
6 items
Resources for Quantitative Finance lists various tools and resources for conducting quantitative financial analysis.
464 shares
Fast BestSubset Selection: The piece presents a library designed for efficient selection of the best subset.
320 shares
A nextgeneration Python notebook explore data build tools deploy apps introduces a new Python notebook for data analysis, tool creation, and app development.
115 shares
Label Studio is a multitype data labeling and annotation tool with standardized output format presents Label Studio as a tool for data labeling and annotation with a uniform output format.
14,463 shares
Machine Learning Engineering Guides and Tools provides a range of guides and tools for machine learning engineering.
1,156 shares
🧠💬 Supercharged Custom Instructions for ChatGPT noncoding and ChatGPT Advanced Data Analysis coding presents improved custom instructions for non-coding and advanced data analysis using ChatGPT.
1,558 shares
Industry news: funds, hiring, markets and regulation.
9 items
Bloomberg has launched Portfolio Manager Workspace, a tool that combines portfolio data with industry data, risk analytics, and liquidity insights in real time.
8 shares
Priya Kodeeswaran, formerly of Man Group and Millennium Management, is set to establish and lead his own hedge fund, Katamaran Capital, as Founder and Chief Investment Officer.
5 shares
The US SEC has introduced new regulations requiring hedge funds to disclose more details about their short-selling activities.
5 shares
Dynamic Funds has launched the Dynamic Credit Opportunities Fund, aiming to generate returns through long and short positions in primarily corporate debt securities.
4 shares
UBS has hired the MD responsible for trading products in London.
3 shares
Acadian Asset Management, a Boston-based firm with $100bn in assets, has begun using BNY Mellon’s Middle Office services platform.
3 shares
Bank of America's trading revenue has risen following investment, however, dealmaking fees are still underperforming.
3 shares
Fintech firm Trumid has hired Jason Quinn, ex-portfolio manager at Millennium Management, as its Global Head of Sales.
3 shares
FN has published its yearly ranking of the most influential women in European finance.
2 shares
Episodes on markets, quant methods and economics.
7 items
In an Interactive Brokers podcast, Cassidy Clement and Kevin Davitt discuss hedging as a method to reduce investment risks.
13 shares
A podcast discusses the use of real-time data, GPS, and advanced algorithms, including AI and machine learning, in modern transportation forecasting.
6 shares
In a podcast with IBKR’s Jeff Praissman, Market Chameleon cofounders discuss the five trading sessions in the equity market.
6 shares
In a MacroHive podcast, Charlie McElligott of Nomura Securities International discusses the effect of low real yields on recent market correction.
3 shares
Matt Barrett, CEO of Adaptive Financial Consulting, discusses the pros and cons of buying versus building trading systems and the future of cloud-based trading technology in a podcast.
3 shares
Scott Rechler and Stijn Van Nieuwerburgh analyze the risks associated with the commercial real estate crisis, influenced by rising interest rates and reduced lending from regional banks.
2 shares
Ian Jones' thesis explores how Barclays Group Archives have helped Barclays PLC achieve its strategic goals, particularly during 2012-2015 when the bank used its history to manage and recover from scandals.
1 shares
Talks, lectures and tutorials.
2 items
The University of Chicago Booth School of Business held a discussion on probabilistic surveys and inflation risk market, with speakers from different universities and financial institutions.
1 shares
The article offers methods to tackle complex quantitative finance issues, such as taking breaks, online research, peer consultation, and textbook study.
33 shares
Posts from quant researchers on X.
9 items
A new method breaks down SP500 volatility into long, medium, and short-term elements, uncovering hidden predictive factors.
2 shares
Llemma's open language models, using Llama 7Band and 34B parameters, show advanced mathematical abilities suitable for various tasks in math and financial market modeling.
1 shares
Time Series Forecasting: Article 3: LLMTime, a large language model, translates numbers into text and predicts possible extrapolations for time series forecasting.
1 shares
A recent study proposes a long-short strategy based on future positive return probabilities, resulting in higher Sharpe ratios and fewer crashes than the conventional momentum strategy.
1 shares
Costs and Market Impact: The article explores the costs and market effects of strategies that involve only buying and holding corporate bonds.
0 shares
Can it be Scientific?: Marcos M. López de Prado's article discusses the possibility of making factor investing a scientific process.
0 shares
Transfer Learning Unlocked: Microsoft's paper suggests that multimodal GPT models could enhance immersive experiences by enabling transfer learning from visuals to text.
0 shares
Introducing 2 Model Architectures: A new research paper presents a new benchmark for timeseries forecasting and two new model architectures, and discusses the limitations of popular models like DeepAR and LSTM.
0 shares
Impact of Social Media: The article investigates the influence of Wall Street Bets and social media on the financial market.
0 shares
Threads from r/quant, r/algotrading and friends.
3 items