ChatGPT Research in Accounting
The article reviews recent research on the use of Large Language Models in accounting and finance, highlighting three key trends and suggesting potential areas for future study.
24 shares99 citations todaySource ↗
Quant LetterNo. 78
159 items across 10 sections, as sent to readers on 12 December 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
24 items
The article reviews recent research on the use of Large Language Models in accounting and finance, highlighting three key trends and suggesting potential areas for future study.
24 shares99 citations todaySource ↗
The research uses AI to study tail risk in US financial markets, revealing a significant spillover effect from the credit market to the stock market.
6 shares33 citations todaySource ↗
The study introduces a new method for automating earnings reports analysis using Large Language Models, with promising initial findings.
5 shares4 citations todaySource ↗
The article presents a unique AI model for predicting future volatility in emerging stock markets, showing high accuracy and low error rates.
5 shares25 citations todaySource ↗
The paper introduces a new Natural Language Processing method for market forecasting, using a hype-adjusted probability measure to enhance forecast accuracy.
5 shares5 citations todaySource ↗
The study suggests using machine learning to fine-tune Fourier methods for pricing European options, leading to quicker, error-controlled algorithms.
5 sharesSource ↗
The article introduces an AI model that merges back-propagation neural network and genetic algorithm for precise prediction of future volatility in emerging stock markets.
5 shares25 citations todaySource ↗
The research introduces a microstructure model to examine the market impact of passive orders, replacing the constant information content assumption with a function based on the limit order book volume.
4 shares5 citations todaySource ↗
The paper investigates the potential of Leveraged Exchange Traded Funds (LETFs) in long-term investment strategies, using a neural network approach to devise strategies that beat standard benchmarks.
4 shares3 citations todaySource ↗
The study contrasts deep generative models (DGMs) and parametric models for creating financial time series, highlighting the advantages of DGMs in an implied volatility trading task.
3 shares1 citation todaySource ↗
A study shows a 292.4% increase in India's carbon emissions from residential cooling between 2000 and 2022, mainly due to fan use, suggesting energy-efficient building designs to help reach net-zero by 2070.
7 shares34 citations todaySource ↗
A Polish survey indicates that age, commuting method, perceived work productivity changes, and sector ownership significantly influence the likelihood of office workers moving to suburbs due to remote work opportunities.
7 shares3 citations todaySource ↗
The AI Startup Exposure index suggests that high-skilled jobs are not uniformly at high risk from AI, with AI adoption in workplaces being gradual and influenced by social factors and technical feasibility of AI applications.
7 shares3 citations todaySource ↗
The article discusses the potential impact of generative AI on law, suggesting it may decrease the need for court services in property and contract law, but increase litigation in areas like tort law.
7 shares1 citation todaySource ↗
Research involving 35 million Pandora listeners indicates that an increase in ad exposure leads to reduced listening time and a rise in paid ad-free subscriptions.
7 shares6 citations todaySource ↗
A study on Polish office workers shows that factors such as age, commuting mode, perceived work productivity changes, and sector ownership significantly affect their preference for moving to the suburbs due to remote work opportunities.
7 shares3 citations todaySource ↗
The Soccer Factor Model (SFM) is a new method for evaluating soccer players' performance independently from their team's influence, allowing for more accurate comparisons.
19 shares1 citation todaySource ↗
A proposed joint energy and data market allows retailers to buy private smart meter data from consumers to reduce market uncertainty, while maintaining privacy during the process.
11 shares1 citation todaySource ↗
A new implementation of continuous double auctions improves order matching speed and introduces an efficient automatic checker, beneficial for market regulators.
6 shares2 citations todaySource ↗
A study reveals the growing demand for ChatGPT-related skills in the U.S. labor market, identifying five key skill sets and emphasizing the widespread use of Generative AI in various sectors.
5 shares9 citations todaySource ↗
Researchers have developed a method to label unstructured text, using it to create a clinical trials census, questioning the perceived decline in pharmaceutical research productivity.
27 shares1 citation todaySource ↗
A proposed machine learning algorithm effectively solves complex, time-limited stochastic control problems, showing good convergence and efficiency without depending on the Bellman equation.
12 shares1 citation todaySource ↗
A comparison study found that BERT performs better than Word2Vec in short-term contexts in social sciences text analysis, but has difficulty with slow semantic changes over longer periods.
11 shares3 citations todaySource ↗
A study on global food trade using net caloric flows reveals varied trade patterns and offers insights into the global food system's stability, highlighting the need for strategies to improve food trade network sustainability.
9 sharesSource ↗
Working papers in finance and economics from SSRN.
40 items
The article calls for a reassessment of Indian GDP nowcasting models due to COVID-19 related distortions and the influence of high-frequency indicators.
14 sharesSource ↗
The study evaluates different methods of estimating the State of Charge for Li-ion batteries in electric vehicles, including their error ratios and compatibility with machine learning models.
5 sharesSource ↗
AI Integration: The report details the creation of an AI-based hybrid system for SMART learning, using machine learning to predict student course completion success based on performance data.
4 sharesSource ↗
The piece argues that the traditional mutual fund performance measure, alpha, is unattainable for short-sale-constrained investors, suggesting a smaller, more achievable measure called achievable alpha.
3 sharesSource ↗
The paper introduces a control scheme using reinforcement learning to improve entanglement in a Rabi model, highlighting its resistance to dissipation and broad applicability.
6 sharesSource ↗
Research shows that social pension insurance in China enhances the efficiency of household financial portfolios due to changes in risk attitude and precautionary savings.
9 shares3 citations todaySource ↗
New Vulnerability Detection Method: A new system, DATVD, uses dynamic attention to improve the accuracy of detecting software vulnerabilities in complex code.
8 sharesSource ↗
AI and machine learning are revolutionizing big data processing by analyzing large data volumes and complex patterns, with a focus on automation, integration, and explainable AI.
2 sharesSource ↗
A new method using oblique-incidence reflectance difference technology and machine learning algorithms can detect Baijiu aroma and trace components faster and more sensitively than traditional methods.
2 sharesSource ↗
A new model, the dynamic heterogeneous closed-form factor copula, is proposed for characterizing asset dependence in investment portfolios, using RVaR as a risk measure for increased flexibility and accuracy.
3 sharesSource ↗
The article highlights Geoffrey Hinton's key contributions to neural networks, including backpropagation, deep learning, and Capsule Networks, and their role in current AI applications.
224 sharesSource ↗
The study reveals a lack of transparency in predictive machine learning studies in top business and economic journals, leading to fewer citations.
15 sharesSource ↗
S&P 500 Case Study: The research suggests that simple forecasts can effectively stabilize volatility in the SP 500 and Treasury bills, despite trading costs and constraints.
6 sharesSource ↗
The article discusses the potential of Big Data analytics in enhancing risk management in IT service delivery through real-time risk identification, assessment, and mitigation.
2 sharesSource ↗
The study examines the key success factors in risk management practices within the Nigerian banking system, using a mixed-method approach.
6 sharesSource ↗
Machine learning can enhance oil and gas production by accurately predicting multiphase flow models and uncertainties.
6 sharesSource ↗
Serverless computing in cloud data centers can be optimized using machine learning and feature engineering techniques to predict the best times for provisioning Azure Function Apps.
7 sharesSource ↗
Alpha-attractor quintessential inflation links inflationary observables and dark energy parameters, constrained by Cosmic Microwave Background measurements and low-redshift observations.
5 sharesSource ↗
Machine learning can predict the success of mergers and acquisitions based on accounting fundamentals and deal characteristics, leading to significant market returns.
3 sharesSource ↗
Mutual fund investor redemptions can reduce the liquidity of stocks, with investor sentiment and stock returns being key factors affecting liquidity.
6 sharesSource ↗
The study reveals that active debt management decisions, such as prepayment, are less beneficial for firms in emerging markets, particularly under tight global credit conditions.
14 sharesSource ↗
The research finds that accounting fraud significantly increases financial distress, with prior misinformed decisions worsening the distress after the fraud is revealed.
17 sharesSource ↗
The study shows that monetary policy shocks in open economies lead to a shift in assets, with wealthier clients showing a stronger shift from fixed income securities to riskier options.
5 sharesSource ↗
The research identifies 21 significant historical events that increased volatility in oil-based commodity prices, with geopolitical events having a more consistent impact than economic or natural events.
7 sharesSource ↗
The study warns that relying on short-term metrics or a single simulation method can lead to misleading conclusions about a portfolio strategy's ability to outperform a benchmark due to market volatility and structural shifts.
7 sharesSource ↗
The article presents a framework for using SturmLiouville theory in quantitative finance, suggesting its use in areas like credit risk modeling and portfolio optimization.
2 sharesSource ↗
The study shows that global GDP growth increases export and import concentration, internal rates of return diversify exports but not imports, and European uncertainty decreases concentration of product countries’ origin/destination.
5 sharesSource ↗
The analysis reveals a rise in politically influenced consumer purchases from 2007 to 2020, with companies catering to both 'red' and 'blue' political factions.
10 sharesSource ↗
The paper discusses the factors leading to the approval of Ethereum exchange-traded funds in 2024, its impact on digital asset adoption, and Ethereum's changing role in traditional finance.
2 sharesSource ↗
The study resolves the paradox of end users reducing their VIX call options during market downturns by examining the demand curves for market makers and end users, emphasizing the market makers' role in market equilibrium.
2 sharesSource ↗
The research compares four investment strategies, finding that none consistently outperforms the others, indicating the need for ongoing development of investment approaches.
570 sharesSource ↗
The article discusses the challenges of trend-following strategies, suggesting they can be mitigated by replicating a broad index of such funds, but warns of the risk of simple replication.
205 sharesSource ↗
The paper reviews the main machine learning methods used in portfolio decision-making, discussing their limitations and potential future developments.
8 sharesSource ↗
The study argues that substantial investments in hedge funds can be justified due to their diversification benefits, even with minimal or no alpha, but cautions that optimal allocations are highly dependent on alpha assumptions.
7 sharesSource ↗
The article suggests that collateralized debt obligations backed by asset-backed securities significantly contributed to the distress of large commercial banks during the 2007-2009 crisis.
62 sharesSource ↗
The study indicates that the design of machine learning models for predicting stock returns greatly affects their performance, with nonstandard errors surpassing standard ones by 59.
12 shares5 citations todaySource ↗
The research reveals that US banks' reactions to interest rate changes in 2022-23 were shaped by financial and regulatory constraints, with banks reluctant to sell devalued bonds at a discount.
6 sharesSource ↗
The paper assesses the performance of Large Language Models (LLMs) for time series forecasting, emphasizing the effectiveness of specialized models in complex data situations.
21 sharesSource ↗
The study suggests that self-proclaimed sustainability statements in fund prospectus, not external sustainability ratings, primarily influence retail and institutional fund flows.
22 sharesSource ↗
The research introduces a portfolio optimization framework for the top 500 U.S. stocks, showing that efficient use of characteristic information and risk management can surpass value-weighted portfolios.
3 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
23 items
The article presents a method for optimizing portfolios in a volatile financial market, using an approximation method to control error and create an optimal portfolio.
17 sharesSource ↗
The paper introduces a data-driven approach using reinforcement learning to improve the correlation and covariance matrix, demonstrating superior performance in volatility, Sharpe ratio, and downside risk.
16 sharesSource ↗
The study uses Entropy CRITIC IDDWS and PROMETHEE methodologies to create an ideal stock portfolio from BIST Retail Trade Sector data, identifying six efficient frontier companies.
14 sharesSource ↗
A study on the Turkish Stock Exchange from 2009-2020 found that the Capital Asset Pricing Model (CAPM) best explains average excess weekly returns.
14 sharesSource ↗
Research on mean-deviation portfolio optimization indicates that unique Pareto-optimal profit sharing in cooperative investment and unique solutions in the Black–Litterman asset allocation model cannot be expected.
13 sharesSource ↗
A study on capital inflows and outflows in emerging markets found that a common global factor accounts for most variations, with regional differences.
13 sharesSource ↗
Machine learning methods, despite their strong forecasting abilities, often underperform in predicting the equity premium due to small datasets and low signal-to-noise ratios.
28 sharesSource ↗
The sale of government retail bonds in the secondary market and the holding period are greatly influenced by their return performance compared to other investment options.
21 sharesSource ↗
The deep multi-layer perceptron (DMLP) and k-nearest neighbor (KNN) machine learning models can improve economic forecasting accuracy, especially when used with cross-validation and bootstrap bagging techniques.
18 sharesSource ↗
The study uses machine learning to identify key factors affecting systemic risk in FinTech and traditional financial institutions, including market volatility, individual stock volatility, and market capitalization, especially under extreme market conditions.
14 sharesSource ↗
A forecasting model reveals that German real estate stocks have high idiosyncratic risk and are more influenced by changes in the economy and stock market than the real estate market, with listed real estate having less downside risk than general stocks.
13 sharesSource ↗
The research indicates that dynamic strategies based on timing volatilities and correlations can enhance the economic gains of non-diversified portfolios involving only crude oil or gold, due to the predictability of their volatilities and correlations.
12 sharesSource ↗
The article discusses the use of machine learning in determining the prices of capped volatility swaps, using unique data for validation.
32 sharesSource ↗
The article suggests symmetric and asymmetric trading algorithms for stablecoin markets, using machine learning to determine optimal profit margins.
31 sharesSource ↗
The article reviews the use of machine learning clustering techniques in financial markets and stock investing, discussing their potential and limitations.
27 sharesSource ↗
The article explores the use of LSTM and rough volatility in a volatility prediction framework, showing its effectiveness in predicting cryptocurrency volatility.
27 sharesSource ↗
The research is focused on developing a machine learning system to block inappropriate web content and alert parents when children encounter such content.
24 sharesSource ↗
The article uses machine learning and macroeconomic indicators to predict China's business cycle, with Logistic Regression being the most effective.
18 sharesSource ↗
The study uses machine learning to forecast country equity returns based on market traits, identifying significant predictability and key predictors.
15 sharesSource ↗
The research uses machine learning to analyze the effect of dollarization on Turkey's monetary policy, revealing a slight impact on economic growth and potential positive correlation with financial deepening.
13 sharesSource ↗
A study using machine learning found that news about product innovation significantly impacts the returns of illiquid stocks, unlike other innovation-related news.
5 sharesSource ↗
A comparison between decision tree and logistic regression models in analyzing loan data found that logistic regression is more effective in identifying defaulted loans.
4 sharesSource ↗
A study on the impact of artificial intelligence on education and jobs, focusing on the chatbot ChatGPT, explores the attitudes of Romanian corporate employees towards AI's potential effects.
0 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
15 items
The manuscript offers a detailed review of deep reinforcement learning and sequential decision making, covering value-based RL, policy-gradient methods, and model-based methods.
1,040 sharesSource ↗
The study suggests using discrete-state models to connect Masked Generative and Non-autoregressive Diffusion models, and to redefine tasks like image segmentation as an unmasking process.
89 shares10 citations todaySource ↗
The paper presents InternVL 2.5, a sophisticated multimodal large language model that performs well on various benchmarks, exceeding 70% on the MMMU benchmark.
75 shares1,775 citations todaySource ↗
The article presents Coconut, a new approach that uses the last hidden state of large language models for reasoning in an unrestricted latent space, proving its effectiveness in enhancing the LLM on multiple reasoning tasks.
73 shares742 citations todaySource ↗
The article introduces Warm-start RL (WSRL), a new reinforcement learning approach that doesn't require offline data, leading to quicker learning and better performance than previous algorithms.
37 shares70 citations todaySource ↗
The research presents a technique for creating temporal object intrinsics like a blooming rose from pre-existing 2D diffusion models, allowing for the depiction of dynamic objects from any angle and lighting.
33 shares7 citations todaySource ↗
The paper suggests Chimera, a system for creating highly precise reaction models for chemical syntheses, which outperforms all major models by combining predictions from various sources using a learning-based ensembling strategy.
20 shares9 citations todaySource ↗
The study introduces the first Extrapolated Urban View Synthesis (EUVS) benchmark for assessing the performance of photorealistic simulators for self-driving vehicles, emphasizing the need for more robust methods and large-scale training.
19 shares14 citations todaySource ↗
The article presents Prescriptive Point Priors for Policies (P3-PO), a new framework that creates a unique state representation of the environment to enhance out-of-distribution generalization for robot manipulation, showing significant improvement over previous methods.
18 shares27 citations todaySource ↗
The article introduces NVILA, a new family of Visual Language Models (VLMs) that balances efficiency and accuracy, reducing training costs and latency while maintaining or improving accuracy.
271 shares251 citations todaySource ↗
The article presents 'capacity density' as a new metric for evaluating Large Language Models (LLMs), showing that LLMs' capacity density doubles approximately every three months.
116 shares58 citations todaySource ↗
The article discusses a deep visual SLAM framework that enables accurate, quick, and robust estimation of camera parameters and depth maps from casual monocular videos.
51 shares252 citations todaySource ↗
The article provides an organized benchmark and analysis of Gaussian-splatting-based methods for converting multi-view image data into scene representations, offering comparisons not previously available.
28 shares7 citations todaySource ↗
The article introduces Right on Time (RioT), a method that helps correct confounders in time series models by interacting with model explanations across both the time and frequency domain.
26 shares9 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
5 items
Machine learning surrogate models are being utilized to enhance the efficiency of simulation-based workflows.
397 shares
The ICL approach uses a selection method based on named entity recognition to prevent excessive focus on entities.
142 shares
The article explores the difficulties in automatically separating the stem and leaves of young maize plants using 3D imaging technology.
89 shares
The article criticizes the conventional competition mechanism for only selecting the best from various channels, neglecting the spatial data of the features.
65 shares
The article highlights the crucial role of hands in human interaction with the environment.
53 shares
Repositories the letter featured.
10 items
The article explores how a trading bot utilizes machine learning to simultaneously conduct trades and improve its performance.
82 shares
This piece discusses how quantitative finance plays a crucial role in determining the price of derivatives.
13 shares
The article provides a step-by-step guide on how to implement the Pairs Trading Algorithm in Quantitative Strategies.
130 shares
OpenMetadata is a platform that offers data discovery, observability, and governance, along with a central metadata repository and tools for team collaboration.
5,687 shares
The article presents a vast hub of ready-to-use datasets for machine learning models, along with tools for efficient data manipulation.
19,348 shares
The article provides a guide on editing and deploying fullstack web applications using Low-Level Machine (LLM).
5,582 shares
The piece discusses a Python wrapper specifically designed for the Tradier brokerage API.
19 shares
The article details the process of implementing Variational Mode Decomposition (VMD) using Python.
349 shares
The article presents RAGLite, a Python toolkit for Retrieval-Augmented Generation (RAG) compatible with PostgreSQL or SQLite.
416 shares
The piece gives a comprehensive overview of the Operations Research tools offered by Google.
11,354 shares
Industry news: funds, hiring, markets and regulation.
20 items
Seven Eight Capital, a quantitative hedge fund, is closing due to significant investor withdrawals.
7 shares
Hedge funds and asset management firms are showing increased optimism in the US dollar due to a robust US economy and rising geopolitical tensions.
7 shares
According to a Preqin report, hedge funds have proven to be valuable in investor portfolios, providing double-digit returns and risk mitigation.
6 shares
Bree Taylor has been promoted to Partner at Greenbrook, a communications advisor to the investment industry.
5 shares
A study by Beacon Platform suggests that many hedge funds are considering changing software vendors to enhance efficiency in risk management processes.
5 shares
Bandhan Mutual Fund is seeking approval from Sebi to launch a quant fund.
4 shares
Broadridge Financial Solutions has launched an AI-based algorithm service for NYFIX to improve accuracy and cost-efficiency for hedge funds.
4 shares
London-based hedge fund Marshall Wace has expanded its operations with a new office in Abu Dhabi.
3 shares
Susquehanna has a preference for certain quants, but experiences tension with other major firms.
3 shares
The Bank of England has expressed concern over the growing influence of hedge funds in the UK government bond market and the potential financial risks they could pose.
3 shares
Edouard Robbes is now the President and Chief Strategy Officer at Pan Capital, an investment firm focused on energy markets.
3 shares
The article explores the difficulties encountered by senior quant professionals.
3 shares
Activist investor Barington Capital Group is advocating for a leadership overhaul at Matthews International Corp, including the CEO's replacement.
2 shares
There has been a recent resignation at the London Stock Exchange, as reported in the article.
2 shares
Hedge funds saw a major boost in November due to the US election results, with expectations of a more business-friendly government.
2 shares
Synergy launched a new Swaps Lifecycle Management service to enhance post-trade efficiency for various market participants including hedge funds.
2 shares
Billionaire Quant is using NVIDIA Jomfruland's AI technology to make significant profits.
2 shares
The piece questions if Godbolt can make significant improvements at Hudson River Trading.
1 shares
Episodes on markets, quant methods and economics.
10 items
Market Strategies & Options: Fabio Ruggeri talks about the shift from traditional to technical market strategies, emphasizing the role of options and the tools offered by MenthorQ for retail traders.
27 shares
Leveraged ETF Tactics: Matt Markiewicz and Paul Schatz discuss the complexities of leveraged ETFs, stressing the need for a strong strategy, risk management, and tactical asset allocation during market downturns.
19 shares
Smart Beta Strategies: Jason Hsu explores the rise of index-based investing, the challenges of investing in China and Japan, and the potential benefits of investing in entrepreneurial ventures despite political and market risks.
11 shares
Political Impact & Volatility: Porter Collins discusses the unpredictable effects of political outcomes on investments, the impact of military and immigration policies, and the future of corporate tax strategies, drawing lessons from the 1970s inflation era.
8 shares
ETFs in 2024: Michael Venuto talks about the growth of the ETF industry, various investment strategies including crypto ETFs and the FIRE movement, and the potential of investing alongside Nancy Pelosi.
7 shares
The BCOM Index is predicted to remain steady in 2024 and 2025, with energy declines balanced by price rises in metals and agriculture, and a positive forecast for gold, silver, and platinum.
6 shares
The Global FX Strategy team explores the impact of future central bank decisions on foreign exchange and the USD's reaction to the US payrolls report.
5 shares
Rodrigo Gordillo suggests that merging trend following and carry strategies can offer diversification and steady returns in a complicated market scenario.
5 shares
The third part of a series on sports business dynamics explores the physical fan experience, funding of sports-entertainment complexes, and the LA Clippers' new venue, the Intuit Dome.
4 shares
Market analyst Michael Belkin examines the global stock market, potential turning points, the effect of tariffs, tax cuts, and fiscal stimuli on bond yields, and the potential of gold as a safe haven.
4 shares
Posts from quant researchers on X.
10 items
The latest investment research explores topics like factor investing, FX hedging, alternative data, stock return predictability, and machine learning.
8 shares
A recent study suggests that global equity investors can enhance their FX hedging strategies by incorporating currency predictors like carry value and momentum.
4 shares
The article explores various position sizing methods in trend-following, such as volatility targeting, volatility parity, and pyramiding.
4 shares
A new study merges deep learning with rough volatility models in the field of finance.
3 shares
Investment firms a16z and Y Combinator are looking for investment opportunities in AI, FinTech, Digital Assets, and tech and vertical infrastructure.
1 shares
Republican vs Democratic Presidencies: The study shows that investors tend to overestimate expected tax cuts during Republican presidencies, leading to a significant difference in postearnings announcement drift.
0 shares
The author shares the latest research and insights on investing through a weekly newsletter.
0 shares
The article suggests a thorough review by Tobias Wiest on momentum strategies in investing.
0 shares
The blog post investigates the low-volatility effect in stocks and how it can be combined with other strategies for better performance.
0 shares
Two Months: The author expresses joy for consistently writing blog posts for two months straight.
0 shares
Threads from r/quant, r/algotrading and friends.
2 items
70 shares
48 shares