Quant LetterNo. 69
149 items across 11 sections, as sent to readers on 9 October 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
7 items
Predicting Economic Indicators from Corporate Calls: The article discusses the use of Generative AI in analyzing over 120,000 corporate conference call transcripts to predict future economic indicators like GDP growth, production, and employment. This technology provides valuable insights for macroeconomic and microeconomic decision-making.
2 shares4 citations todaySource ↗
The study analyzes the impact of unexpected disruptions like the COSMOS-1408 anti-satellite missile test on partially-automated traffic systems in low-Earth orbit, offering insights for future space traffic disruption models.
3 sharesSource ↗
The research proves that the Fourier cosine formula for the inverse Fourier transform can be applied to discrete probability distributions, indicating its usefulness in computational statistics and quantitative finance.
3 shares1 citation todaySource ↗
The research shows that strategic bidding in electricity markets can boost producer profits and minimize lost opportunity costs, but may also raise consumer costs.
52 shares5 citations todaySource ↗
The study finds that electric carsharing only slightly raises power sector costs and can be compatible with variable renewable electricity generation.
8 shares14 citations todaySource ↗
The paper reveals that the shift to remote work during COVID-19 has improved amenity usage equality among different income groups, with lower and middle-income individuals visiting more amenities.
6 sharesSource ↗
The research introduces the neural term structure model for option pricing, providing benefits in creating the risk-neutral measure, pricing formula, and fitting the implied volatility surface.
6 shares2 citations todaySource ↗
Working papers in finance and economics from SSRN.
31 items
Geoffrey Hinton's contributions in neural networks, deep learning, and Capsule Networks have significantly influenced modern AI systems used in various fields like image and speech recognition, and natural language processing.
224 sharesSource ↗
The study presents a data-driven approach for inventory and financial hedging for new products, using return factors to predict demand and future returns, leading to a new decision-making framework.
4 sharesSource ↗
A new machine learning model for credit risk combines tree-boosting with a latent spatiotemporal Gaussian process model, offering more accurate predictions of default probabilities and loan portfolio losses.
2 sharesSource ↗
The article advocates for a specialized course on data science tools in business valuation in business schools' curriculum to enhance students' understanding of corporate finance.
2 sharesSource ↗
The paper applies Machine Learning techniques to predict the beneficiaries of EU development funding in Italy, providing insights into fund allocation and aiding in policy design.
10 sharesSource ↗
The study introduces a machine learning method for detecting saturation in Current Transformers using artificial neural networks and long short-term memory networks, enhancing anomaly detection in complex datasets.
5 sharesSource ↗
The article examines the influence of data split ratio in data science competitions, focusing on participants' model selection and their motivations.
3 sharesSource ↗
The paper proposes the fusion of machine learning and optimization theory, suggesting algorithms that ensure balance and stability in intricate decision-making systems.
3 sharesSource ↗
The research compares the liquidity and performance of open and closed-end funds, revealing that closed-end funds hold more illiquid municipal bonds, charge higher fees, but perform worse than open-end funds.
2 sharesSource ↗
The research explores the factors influencing the credited interest rate on universal life insurance in China, showing a positive long-term effect of insurance company operations and market interest rate trends on credited interest rates.
2 sharesSource ↗
The article discusses the use of high-frequency data to identify similar assets for statistical arbitrage strategies, testing various algorithms and trading rules on different asset classes.
7 sharesSource ↗
The paper presents an extended Black-Litterman model that allows fund managers to apply their subjective views to risk factors, simplifying the portfolio allocation process.
3 sharesSource ↗
The research applies machine learning models to predict future stock market indices, using data from the Nifty50 index and evaluating the models' effectiveness.
2 sharesSource ↗
The study proposes a framework for predicting Vietnamese macroeconomic indicators by combining traditional data with insights from news articles, highlighting the reliability of Gradient Boost Decision Tree models.
4 sharesSource ↗
The article examines the short and long-term effects of live streaming ecommerce on product sales, using data from Amazon, and finds that sales spike after live streaming but decline over time.
2 sharesSource ↗
A study proposes a new method for choosing factors in portfolio management, highlighting announcement return and earnings predictability as key, outperforming other methods.
2 sharesSource ↗
A fantasy cricket team generator tool has been created, using advanced algorithms and machine learning to evaluate players and create optimal teams.
2 sharesSource ↗
Research in Madhesh Province shows that women's entrepreneurial intentions are significantly influenced by financial literacy and behavioral traits.
2 sharesSource ↗
A new course has been developed to introduce artificial intelligence into the accounting information systems curriculum, using various teaching methods to aid understanding.
2 sharesSource ↗
A study reveals that social capital resources, proactive personality, and perceived organizational support influence work engagement during organizational socialization, with effective tactics leading to higher engagement.
2 sharesSource ↗
The study suggests that index stocks have higher prices, more volatility, stronger negative price autocorrelation, and higher trading volume due to sentiment spillover from index investors.
4 sharesSource ↗
The research shows that bank Credit Default Swaps (CDS) are influenced by regulatory capital ratios, with markets reacting more to changes in capital requirements if implemented via Pillar 1 risk weights.
3 sharesSource ↗
The research contradicts previous theories, stating that non-retail funding, particularly wholesale funding, significantly drives banks' contingent commitments, not traditional retail deposits.
2 sharesSource ↗
The study finds that in the Indian equity market, volatility-adjusted and information discreteness momentum strategies deliver higher risk-adjusted returns.
4 sharesSource ↗
The article presents a pricing formula for a ComEx option, which allows the exchange of two options, and compares its price evolution to the Margrabe option, which permits the exchange of two underlying assets.
4 sharesSource ↗
The research explores the relationship between prices in Australia's renewable energy certificate market, carbon offsets market, and electricity market from May 2018 to June 2023, using a portfolio approach for backtesting.
3 sharesSource ↗
The 3MR Reactive Price Model uses linear regression and yield prediction to forecast future values of the S&P 500 index, rejecting the martingale hypothesis and allowing for a retrospective yield estimate.
2 sharesSource ↗
The study reveals that factors like educated neighbors, local wealth inequality, professional financial advice, and personal crises significantly influence wealth accumulation and saving behavior.
2 sharesSource ↗
The study reveals that France's history with growth-contingent bonds shows the equity premium isn't just compensation for GDP risk, as it persists even when hedged against GDP changes.
2 sharesSource ↗
The research indicates that less than 1% of day traders consistently make profits, with most suffering major losses due to poor risk management, emotional control, and unrealistic expectations fueled by aggressive marketing.
2 sharesSource ↗
The study proposes that collusion in trading may not always be advantageous for informed investors, particularly when there's high uncertainty about other traders' actions, as individual profits in competition can surpass total profits in collusion.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
20 items
Research shows high-frequency and algorithmic trading in China enhances market liquidity and lowers slippage costs for investors, despite the country's unique market structure.
17 sharesSource ↗
Hedge funds with larger minimum investments and management fees are more effective at hedging geopolitical risks, while global macro hedge funds excel at timing these risks, offering crucial insights for private investors during high geopolitical risk periods.
16 sharesSource ↗
A new factor model system, capturing both return and risk dynamics, has been introduced, with U.S. market data indicating it offers a better out-of-sample Sharpe ratio than benchmark policies.
15 sharesSource ↗
The chapter discusses the application of reinforcement machine learning and quadratic optimization in determining risk limits and investable portfolios, especially during the 2007-2009 financial crisis.
31 sharesSource ↗
The SHARV-MGJR model, which includes volatility leverage effects and current return data, is suggested to enhance the precision of cryptocurrency market volatility forecasts, surpassing GARCH-type models.
22 sharesSource ↗
The article highlights the difficulties of using machine learning models in practical risk management in banking due to their opacity and lack of explainability, and introduces a framework for leading eXplainable AI methods.
20 sharesSource ↗
A study suggests that adding nonfinancial factors like narrative tone and corporate governance to financial prediction models can improve the accuracy of predicting company performance in the unpredictable Pakistani market.
18 sharesSource ↗
The book provides insights into the current status of artificial intelligence and machine learning in finance, tracing the origins of AI to early human automation efforts.
17 sharesSource ↗
Research shows that investors in AI and big data token markets tend to follow the crowd during stable, low-volume market conditions, but act independently during volatile, high-volume conditions, which has implications for market regulation and stability.
17 sharesSource ↗
A new model, LG-SVM, has been developed to better detect bot activities on Twitter, using a multi-level framework that reduces complexity and learns key short-term traits, achieving a high accuracy and correlation rate in predicting the effect of bot tweets on stock market volatility.
15 sharesSource ↗
Sentiment Analysis is being utilized in finance to predict market trends and identify investment opportunities, with different algorithms having varying strengths and weaknesses.
31 sharesSource ↗
Reinforcement learning techniques in machine learning are transforming finance, especially portfolio management, despite current limitations and future uncertainties.
29 sharesSource ↗
Machine learning techniques like gradient boosting or regularised regression can accurately forecast CPI inflation, as shown with Russian data.
27 sharesSource ↗
Deep reinforcement learning algorithms can be used to solve portfolio allocation problems in finance where analytical solutions are not available.
25 sharesSource ↗
Machine learning has been used to predict German business cycles, showing fewer indicators are needed to model recessions, especially during quantitative easing periods.
23 sharesSource ↗
A new algorithm has been developed to detect collusion in auctions using public procurement data, identifying a significant number of contracts with high collusion likelihood.
18 sharesSource ↗
The chapter discusses Decentralized Finance (DeFi), its potential impact on centralized finance, and its market efficiency, volatility, leverage effects, and return volume relationship.
18 sharesSource ↗
Traditional vs. Modern Approaches: A predictive model using linguistic features has been proposed to detect fake news, with a logistic regression model using feature hashing vectorisation proving 99% accurate.
16 sharesSource ↗
The article explores AI techniques for credit scoring to predict borrower creditworthiness, emphasizing the importance of credit risk management in banks.
14 sharesSource ↗
This article discusses the application of machine learning and deep learning to analyze financial news headlines, aiming to select low volatility stocks that perform better than the Standard and Poor’s 500 Index.
18 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
20 items
The Diff Transformer is a new language model architecture that enhances attention to relevant context and reduces noise, outperforming the standard Transformer in long-context modeling and key information retrieval.
102 shares1 citation todaySource ↗
GS-VTON improves 3D virtual try-on by transferring knowledge from 2D models, ensuring consistency across different viewpoints and enhancing the quality of 3D geometry.
78 shares15 citations todaySource ↗
A study on Conformal Prediction intervals shows that asymmetric adjustments are unaffected by bias and maintain the same validity as if the bias never occurred, unlike symmetric adjustments.
10 shares1 citation todaySource ↗
The MA-RLHF framework integrates macro actions into the learning process of large language models, enhancing learning efficiency and performance in tasks like text summarization and dialogue generation.
10 shares15 citations todaySource ↗
GenSim2 is a scalable framework for robotic simulation that uses large language models for task creation and a multi-task language-conditioned policy architecture to learn from demonstrations, improving policy performance and enabling zero-shot transfer.
8 shares66 citations todaySource ↗
Data Filtering System with GPT-4o Accuracy: The article introduces SIEVE, a cost-effective method for filtering web-scale data that matches the accuracy of GPT-4o and is efficient in curating large datasets for language model training.
8 shares2 citations todaySource ↗
The paper presents LintSeq, a synthetic data generation algorithm that refactors code into a sequence of edits, resulting in more diverse programs and improved code synthesis performance.
7 sharesSource ↗
Efficient LVLM for Bilingual OCR: The study introduces TextHawk2, a bilingual Large Vision-Language Model that provides efficient fine-grained perception and superior performance with 16 times fewer image tokens than previous models.
6 shares33 citations todaySource ↗
The research proposes ProCALM, a method for generating proteins conditionally using adapters to protein language models, capable of generating sequences from target enzyme families and generalizing to rare and unseen ones.
6 shares9 citations todaySource ↗
Enhancing Language-Image Pre-training: The article reveals that language-image pre-training models struggle with long text due to training images being paired with short captions, and suggests a solution that improves long-text image retrieval by 11.1%.
5 shares35 citations todaySource ↗
SCoRe, a new online reinforcement learning approach, enhances the self-correction ability of large language models, showing top performance with Gemini 1.0 Pro and 1.5 Flash models.
585 shares460 citations todaySource ↗
MMLU-Pro, an improved dataset, expands the Massive Multitask Language Understanding benchmark by adding tougher questions and more choices, serving as a better benchmark to monitor progress in the field.
244 shares2,199 citations todaySource ↗
The SaySelf training framework instructs large language models to provide more precise confidence estimates and self-reflective rationales, effectively reducing confidence calibration error while maintaining task performance.
231 shares125 citations todaySource ↗
FastCLIP, a new CLIP training framework, optimizes the training of Contrastive Language-Image Pretraining models on large-scale data with limited resources, showing significant improvement in resource-limited settings.
69 shares8 citations todaySource ↗
AgentStudio, a combination of environments, tools, and benchmarks, aids in the development and evaluation of general virtual agents in real-world settings, offering a range of online tasks and datasets to assess fundamental agent abilities.
67 shares47 citations todaySource ↗
The article explores the enhancement of weight nowcaster networks (WNNs) through neuron interaction and nowcasting (NiNo) networks, resulting in a 50% speed increase in neural network training for vision and language tasks.
62 shares10 citations todaySource ↗
Language Model Prediction: The paper presents a new method called Data-Augmented Prediction (DAP) for using Large Language Models (LLMs) in classification tasks, achieving over 90% accuracy in some tests.
29 shares2 citations todaySource ↗
The paper introduces scattering spectra models for stationary fields, offering precise and robust statistical descriptions for various physics fields, aiding in data exploration, classification, parameter inference, symmetry detection, and component separation.
19 shares23 citations todaySource ↗
The article examines Membership Inference Attacks (MIAs) against Large Language Models (LLMs), suggesting potential solutions and comprehensive benchmarks for sequence- and document-level MIAs against LLMs.
17 shares67 citations todaySource ↗
Object Swapping: The paper presents SwapAnything, a new framework that allows for the swapping of any objects in an image with personalized concepts while maintaining the original context, showing significant improvement over previous methods in personalized swapping.
16 shares14 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
14 items
The article explores the slow data processing of large autoregressive models like Transformers, which need K serial runs to decode K tokens.
3,578 shares
The article presents a new base model for zero-shot metric monocular depth estimation.
2,186 shares
The article showcases a case study where PyGlove drastically cut down the lines of code in a large codebase by 80%.
528 shares
The article emphasizes the importance of Face AntiSpoofing (FAS) in enhancing the security of face recognition technology.
282 shares
Accelerating Language Models: The LLaMA7B model with W2A8 quantization configuration outperformed AffineQuant by achieving a WikiText2 perplexity of 7.59.
175 shares
The article discusses the limitations of existing VO methods, which require extensive hyperparameter tuning by human experts, affecting their generalizability and robustness.
145 shares
Serving Language Models: The article highlights the effectiveness of tensor parallelism, as shown by the TPILLM system, over pipeline on low-resource devices for serving 70B-scale models.
131 shares
Regulatory efforts addressing the risks of foundation models are increasing their popularity and driving interest in open-source versions.
116 shares
Quantization is a widely used technique to accelerate model inference, with a majority of methods concentrating on optimizing the linear layer.
111 shares
Current studies on LLM weights are advocating for ultra low-bit weight-only quantization, going as low as 2 bits.
103 shares
The article explores the increasing interest in 3D hand pose estimation techniques for use in human-computer interaction, virtual reality, and robotics.
87 shares
The article assesses the efficiency of value networks in logic-heavy LLM tasks, showing their significant limitations and slight improvement over a random baseline.
53 shares
The article introduces a method to uphold the low-rank constraint in the optimizer while achieving full-rank training for enhanced performance.
52 shares
The article emphasizes the role of cellular automata in studying emergence and self-organization in fields like neuroscience, artificial life, and theoretical physics.
49 shares
Repositories the letter featured.
10 items
The article emphasizes the need for a universal standard to ensure compatibility among different machine learning systems.
17,723 shares
This article offers a detailed guide on constructing a straightforward and efficient data stack.
30 shares
The piece describes how Interactive Brokers delivers essential data in a way that is easy for users to understand and use.
28 shares
The article outlines the method of calculating VIX and other related volatility indices.
97 shares
This article introduces TimeMoE, a base model designed to manage billion-scale time series data using a combination of experts.
151 shares
The article discusses a macOS system monitor that can be easily accessed from the menu bar for convenient system tracking.
25,126 shares
The 2021 roundup suggests a variety of books beneficial for engineers in diverse fields such as computer science, entrepreneurship, philosophy, and more.
7,493 shares
Ethereum Rust Toolkit: Foundry, a toolkit for Ethereum application development, is highlighted for its speed, portability, and modularity, and is written in Rust programming language.
8,185 shares
Billing Platform: The article explores an open-source platform designed to manage subscription billing and payments efficiently.
4,582 shares
The piece presents a collection of open-source, frequently updated web apps specifically designed for LLM applications.
326 shares
Industry news: funds, hiring, markets and regulation.
20 items
Bloomberg has launched OpenHighLowClose Bar, a new tool that allows users to create custom intraday pricing datasets, simplifying quant workflows.
5 shares
Dennis Li, a specialist in investment funds and digital assets, has been named a partner at Ogier's Hong Kong office.
4 shares
At the Quant Strats 2024 in London, experts discussed the impact of AI and geopolitics on financial disruption.
4 shares
Digital asset investment products saw a third week of inflows, totalling 1.2bn, likely due to expectations of a continued dovish US monetary policy, says CoinShares data.
3 shares
Emerging markets hedge funds recorded gains in Q3 2024, as managers adapted to geopolitical risks, fluctuating interest rates, and global economic uncertainties, according to HFR data.
3 shares
Nickel Digital Asset Management's research indicates that institutional investors and wealth managers expect an increase in new digital assets funds in 2021 due to growing interest from traditional financial institutions.
3 shares
Segantii Capital Management, a hedge fund facing insider trading charges, has reportedly moved out of its large Hong Kong office, according to Bloomberg.
3 shares
Columbia Threadneedle is collaborating with DBS Bank to offer its tech-focused hedge fund strategy, managed by Seligman Investments, to affluent clients in Asia, as per CityWire.
3 shares
Greg Coffey, founder of Kirkoswald Asset Management, is exploring new investment opportunities in Turkey, following discussions with local bankers and economists, Bloomberg reports.
3 shares
The Quants in the Wild seminar at Ateneo de Manila University offered insights into the practical application of theoretical concepts.
2 shares
In September, EventDriven hedge funds led industry gains due to the US Federal Reserve's interest rate cuts, despite Middle East and Eastern Europe conflicts.
2 shares
Trend-following hedge funds saw positive returns in September, driven by gold and coffee, record commodity prices, rising equities, and falling interest rates.
2 shares
The top 20 stocks held by hedge fund managers, including some tech giants, underperformed compared to the S&P 500 in Q3 2024.
2 shares
Australia's Future Fund cut its allocation with Man Group Plc by around AUD1.5bn in the first half of 2024.
2 shares
InvestorWire has been named the Official NewsWire for Quant Strats London, as reported by The Manila Times.
2 shares
The article reflects on the era when Google was the dominant platform for online searches.
2 shares
Due to escalating Middle East tensions and an approaching Gulf of Mexico hurricane, oil prices have surged over $80 per barrel, prompting hedge funds to modify their positions.
2 shares
Activist hedge fund Starboard Value has bought a $1bn stake in Pfizer and intends to push for strategic changes amid the company's declining post-pandemic revenues.
1 shares
Jody Gunderson has been appointed as the new Board Chair of MFA, and new board members for the 2025 fiscal year have been announced, including executives from alternative asset management firms and service providers.
1 shares
Episodes on markets, quant methods and economics.
10 items
Global FX Strategists analyze the effect of robust US employment data on currency markets, including the dollar and funding currencies, and recent European FX developments.
7 shares
Marc Rovers, LGIM's Head of Euro Credit, discusses recent fluctuations in the European debt market, potential impacts of the US election, and the high rate of bond issuance.
7 shares
Abraham Thomas of Quandl explores the influence of AI and LLMs on the alternative data and hedge fund sectors, predicting potential winners, losers, and future scenarios.
6 shares
Rates strategists Jay Barry and Srini Ramaswamy discuss how recent labor market data influences the debate on Fed policy, its implications for the rates curve and volatility, and funding market developments.
6 shares
The podcast covers expected large moves for the election and unemployment report, the effect of earnings season volatility on the market, overall options volume trends, and listener queries about long straddles, leap options, and high skew stocks.
6 shares
The last episode of the Data Skeptic podcast's Animal Intelligence season features a recap and a goodbye to cohost Becky, who shares her future plans and the podcast's influence on her learning.
5 shares
Weston Nakamura examines Japan's surprising political changes, their effect on financial markets, and the influence of individual strategies, focusing on the yen carry trade and China's reaction to global monetary policies.
4 shares
Brad Gerstner, Altimeter Capital's founder, talks about his investment journey, AI's impact on technology, and his Invest America initiative, which aims to improve financial literacy and inclusion for U.S. children.
3 shares
Warren Pies, founder of 3Fourteen Research, discusses the potential negative effects of a Fed rate cut on bonds and the advantages for commodities, offering strategies to benefit from these market changes.
2 shares
MacroVoices hosts Erik Townsend and Patrick Ceresna invite Luke Gromen back to discuss the dollar, inflation, monetary policy, China, energy, and precious metals.
2 shares
Posts from quant and economics blogs and newsletters.
6 items
A study has found that a deep learning model can effectively predict the Shanghai Containerized Freight Index using the prices of Chinese commodity futures.
10 shares
Research indicates that return volatility and liquidity volatility are more significant irregularities in machine learning compared to momentum.
10 shares
The NAAIM Exposure Index is increasingly being used as a method to monitor investor sentiment.
3 shares
The Ergodic Oscillator is a technical analysis tool that traders use to incorporate statistical methods into their strategies.
2 shares
Traders use different methods such as indicators and price movement studies to analyze financial markets.
1 shares
Traders are always on the lookout for advanced tools to help them better understand and navigate the volatile financial markets.
1 shares
Posts from quant researchers on X.
9 items
New research in quantitative investing explores predicting option returns, sentiment and equity predictability, mutual fund strategies, and the application of large language models in trading.
4 shares
Generative AI solutions for time series prediction are available, with the smallest pre-trained model, Chronos T5 Tiny, trained on a vast amount of public and synthetic data.
3 shares
A momentum investing study indicates a shift to reversal after high past 1-month volatility, showing strong results in the US, China, Brazil, and India, but cautions about high turnover.
2 shares
A white paper from Quantica suggests that trend following investments are more appealing during periods of high interest rates.
1 shares
The article delves into a significant episode on alternative risk premia by Choffstein.
1 shares
The piece focuses on an interesting episode on alternative risk premia by Choffstein.
1 shares
The article evaluates a new study proposing that smaller, domain-specific language models excel in trading, particularly for small-cap stocks.
1 shares
The article presents an interactive data visualization from NYT that simplifies intricate weather model results for Hurricane Milton.
0 shares
The article concurs with a melancholic sentiment, offering a link for additional context.
0 shares
Threads from r/quant, r/algotrading and friends.
2 items
652 shares
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