Quant LetterNo. 26
110 items across 11 sections, as sent to readers on 15 November 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
21 items
The research enhances a Deep Q-Network trading model using advanced methods, showing improved performance in automated trading and the potential of convolutional neural networks in trading systems.
6 shares3 citations todaySource ↗
The study introduces a multi-label topic model for financial texts, achieving high accuracy and showing that stock market reactions depend on the co-occurrence of specific topics.
5 shares1 citation todaySource ↗
The paper introduces Smart Agent-Based Modeling (SABM), a new framework that uses Large Language Models for more realistic simulations of complex systems.
5 shares22 citations todaySource ↗
The QLBS model is expanded to include a large trader's impact on exchange rates and contingent claim prices, using reinforcement learning to find an optimal hedging strategy, reducing transaction costs and aligning with the trader's fair price.
4 shares3 citations todaySource ↗
The likelihood of completing a specific investment and withdrawal schedule is maximized using adjustable portfolio weight functions, showing significant improvements when optimal weights are used instead of constant ones.
4 shares1 citation todaySource ↗
New mathematical techniques are used to determine the optimal portfolio size for investors of different abilities, suggesting that strong investors should have smaller portfolios, weak investors larger ones, and average investors a fluctuating optimal number.
4 shares3 citations todaySource ↗
The practical use of Deep PDE solvers for option pricing is examined, identifying three main error sources and concluding that the Deep BSDE method performs better and is more robust against option specification changes.
3 shares2 citations todaySource ↗
Deep Kernel Learning and variational inference are used to improve high-dimensional American option pricing in the regression-based Monte Carlo method, with successful performance under geometric Brownian motion and Merton's jump diffusion models.
3 shares4 citations todaySource ↗
The study presents a framework to understand price-mediated contagion in a system with endogenously determined market liquidity, showing the significant impact on system risk.
5 shares2 citations todaySource ↗
Tradeable Unit in Cross-Chain Finance: The paper investigates the Intermediating DFMM Asset in a multi-asset market, outlining its features, risk mitigation, and control levers, suggesting its potential to align the interests of various market participants.
5 sharesSource ↗
The research examines the optimal payout of dividends from an insurance portfolio with claims from natural disasters, identifying the best dividend strategies and potential benefits for shareholders.
5 shares3 citations todaySource ↗
The paper introduces Smart Agent-Based Modeling (SABM), a new framework that uses Large Language Models for more realistic simulations of complex systems.
5 shares22 citations todaySource ↗
Boosting Market Prosperity and Dismissing Depression Concerns: A study finds that generative AI can lower average prices in product markets, increase order volume and revenue, and potentially benefit artists rather than causing unemployment.
4 shares2 citations todaySource ↗
The study shows that Hedera Hashgraph platform has high wealth centralization and a shrinking core, but recent indexes indicate progress towards decentralization.
5 shares3 citations todaySource ↗
The paper presents new methods to improve non-life actuarial models with transformer models for tabular data, showing better results than benchmark models.
5 shares13 citations todaySource ↗
Democratizing Financial Data for LLMs: The Financial Generative Pre-trained Transformer (FinGPT), a new open-source framework, automates the collection and curation of real-time financial data from various online sources, aiming to make large-scale financial data more accessible for large language models.
43 shares124 citations todaySource ↗
A study proposes a multivariate utility-based mechanism for prediction markets, unifying existing market-making schemes and characterizing the limiting price through systems of equations reflecting agent beliefs, risk parameters, and wealth.
76 shares1 citation todaySource ↗
A new large-scale portfolio optimization framework, using shrinkage and regularization techniques, has been tested and proven effective using 50 years of US company return data.
27 shares6 citations todaySource ↗
A new Lillo-Mike-Farmer model, considering the diversity of traders' order-splitting behavior, emphasizes the importance of the ACF prefactor in data analysis.
15 shares9 citations todaySource ↗
A new estimator for average causal effects in binary treatment with panel data has been proposed, offering better performance and robustness than the traditional two-way estimator, even with a misspecified fixed effect model.
303 sharesSource ↗
Research shows that the position of industries in supply chains significantly influences the transmission of final demand shocks, with upstream industries reacting up to three times more than final goods producers.
73 shares5 citations todaySource ↗
Working papers in finance and economics from SSRN.
25 items
The research examines the link between deep and delta hedging, suggesting a risk-minimizing strategy that combines both with statistical arbitrage, and discusses the effects of statistical arbitrages on deep hedging.
2 sharesSource ↗
A new neural network model is introduced for macroeconomic forecasting, designed to prevent overfitting and improve accuracy.
3 sharesSource ↗
A trading system using salience theory and deep learning is applied to Chinese new energy stocks, proving the effectiveness of these methods.
2 sharesSource ↗
US. macroeconomic news impacts the SP 500 more when long-term stock market volatility is high.
3 shares2 citations todaySource ↗
The article presents a study on the use of LSTM neural networks and linear regression for stock market prediction, showing superior performance over traditional models.
4 shares2 citations todaySource ↗
The study presents a model of the U.S. housing finance system, illustrating the benefits and challenges of the securitization market.
2 sharesSource ↗
The article shares a survey of 110 corporate risk managers on hedging foreign exchange rate risk, revealing that changes in forward and future FX rates greatly influence hedge ratios, and managers are most satisfied when FX risk doesn't affect cash flows.
2 sharesSource ↗
The article debates the issue of mutual fund management fees, arguing that mutual funds are controlled by the investment management firms that create them and manage their portfolios, resulting in the charging of excessive management fees.
2 sharesSource ↗
The study challenges the belief that data mining always improves price efficiency, suggesting it can actually reduce price informativeness due to complexity costs and diminishing data efficacy returns.
2 sharesSource ↗
The SPPC methodology can determine individual predictors' contributions to portfolio performance, shedding light on the sources of economic value from return predictability.
3 sharesSource ↗
The paper presents a new method for predicting future implied volatility surfaces using historical data, employing a conditional variational autoencoder and a long short-term memory network.
17 shares2 citations todaySource ↗
The article introduces a day trading strategy based on Volume Weighted Average Price (VWAP) that can identify market imbalances, resulting in a 671% return on a $25,000 investment.
1,355 shares6 citations todaySource ↗
Credit sentiments from conference calls affect bond market returns, with positive sentiments leading to better credit ratings and lower future debt costs.
2 sharesSource ↗
China's consumption risk significantly influences U.S. equity returns, with a two-factor model explaining 40% of the variation.
4 sharesSource ↗
Auto Debiased ML: A new machine learning method has been developed to identify risk factors in asset pricing, performing better than traditional methods by eliminating biased estimation and overfitting.
2 sharesSource ↗
The research finds that green energy ETFs offer better diversification compared to grey and conventional investment strategies.
4 sharesSource ↗
Liquidity & Performance: The study suggests that ETFs may not be more liquid than mutual funds and can be subject to short-term mispricing and illiquidity.
2 sharesSource ↗
The paper proposes improvements to the order size algorithm for better tracking of retail and institutional purchases in the Chinese stock market.
4 shares4 citations todaySource ↗
The yearbook provides a comprehensive analysis of the return and risk characteristics of stocks, government bonds, and credit bonds in the Chinese capital market.
3 sharesSource ↗
Machine learning models considering nonlinearities and interactions offer better predictions of corporate bond behavior in emerging markets with high transaction costs, with key predictors tied to low-risk macro and momentum factors.
2 shares1 citation todaySource ↗
The predictability of retail order imbalance on future returns for meme stocks increases during Reddit outages, indicating that intense discussions can disrupt individual investors' decisions.
3 shares1 citation todaySource ↗
A new model using a Gaussian one factor copula is suggested for simulating spread risk in banks' risk models, ensuring consistency between simulated and actual historical spreads.
2 sharesSource ↗
Machine learning is used to identify and correct errors in household finance survey data, with Gradient Boosting Trees being the most effective method.
2 sharesSource ↗
The research introduces a machine learning model for predicting the number of Incurred But Not Reported (IBNR) claims, proving its effectiveness through a study using both simulated and real data.
2 sharesSource ↗
The research examines market efficiency in blockchain-enabled marketplaces, revealing significant inefficiencies despite complete information transparency.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
10 items
The paper reveals that certain algorithmic trading strategies can lower liquidation costs but may negatively affect market indicators in a multi-asset artificial stock market.
18 sharesSource ↗
The research finds that exchange rate option-implied volatilities can more accurately predict future global equity market correlations.
15 sharesSource ↗
Time-Variation in Push and Pull Factors: The research shows that the importance of push factors in portfolio flows during crises has increased over time, especially for EU countries, and identifies several key push and pull factors.
14 sharesSource ↗
The research indicates that REIT preferred stocks offer significant diversification benefits and enhance portfolio performance during economic expansion.
21 sharesSource ↗
A new framework for multi-period dynamic bond portfolio optimization is proposed in the study, which shows it performs better than single-period optimization.
26 sharesSource ↗
The SHAP technique is used to clarify bond excess return predictions made by machine learning models in a study.
21 sharesSource ↗
A study finds that high-quality political signals can predict increased stock market volatility.
16 sharesSource ↗
Research into the Chinese equity market shows a belief-based momentum indicator can predict market volatility.
16 sharesSource ↗
High-Dimensional Method: The article explores the use of machine learning to improve demand prediction and restocking decisions in newsvendor problems, using complex historical data.
27 sharesSource ↗
The article discusses how supervised machine learning models assign weights to input parameters to achieve the desired outcome, stressing the importance of reliable weights early in the model development process.
13 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
7 items
The research introduces an outlier-robust framework for decision-making under data perturbations, providing optimal risk bounds and efficient computation, and validating the theory through standard regression and classification tasks.
7 shares26 citations todaySource ↗
The article introduces α-SVRG, a new method for optimizing neural networks that improves training loss reduction across various architectures and datasets.
16 shares8 citations todaySource ↗
Cloud Removal and Urban Change Detection: Diffusion models in AI can improve Earth observation data, aiding in tasks like cloud removal, change-detection dataset creation, and urban replanning.
69 shares7 citations todaySource ↗
The study examines the abilities of Large Multimodal Models (LMMs), particularly GPT-4V, in understanding social multimedia content, noting challenges in multilingual comprehension and trend generalization.
13 sharesSource ↗
Feature Attribution: The authors suggest a unified discrete optimization framework for feature attribution and selection in deep learning models, introducing an adaptive method called Greedy PIG that performs well in various tasks.
11 sharesSource ↗
Survival: Offline reinforcement learning algorithms can still create effective policies even with incorrect reward labels due to their inherent pessimism and biases in data collection.
110 shares26 citations todaySource ↗
The paper introduces the Data Contamination Quiz, a method for detecting and estimating data contamination in large language models, demonstrating improved detection and accurate contamination estimation.
8 shares58 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
5 items
The article assesses a technique's effectiveness on different public models and complex tasks.
237 shares
Real-Time Segmentation Model: The article highlights the increasing need for semantic segmentation techniques in practical applications.
3,697 shares
The article presents a data curriculum learning scheme that enhances alignment in contrastive posttraining by progressing from simpler to more complex pairs.
2,755 shares
The study explores the use of structured pruning to develop smaller LLMs from larger pre-existing models.
194 shares
The article presents SLoRA, a system engineered for the scalable usage of multiple LoRA adapters.
190 shares
Repositories the letter featured.
9 items
The article explores the application of Polars in large-scale timeseries machine learning, particularly in parallel feature extraction and panel data forecasts.
626 shares
Deep Learning Operations Reinvented: The article discusses the transformation of deep learning operations across various platforms like Pytorch, Tensorflow, Jax, etc.
7,379 shares
High Level API for DL in JAX: The article presents a new high-level API designed specifically for deep learning in JAX.
455 shares
The article lists full-time job opportunities for fresh graduates in Software Engineering, Quantitative Analysis, and Project Management.
8,395 shares
Updated Quant Interview Prep Guide: The article provides an updated guide to help prepare for quantitative interviews.
581 shares
Papers, Code, and Resources: The article compiles a list of important codes, academic papers, and other key resources.
764 shares
Resource: The article serves as a guide for those wanting to explore and improve the OpenAI Vision API.
880 shares
Customizing Repo: The article provides a collection of tailored instructions for utilizing ChatGPT.
738 shares
CLI Tool API for Python Libraries: The article presents a CLI tool API for the most popular 1221 Python libraries.
340 shares
Industry news: funds, hiring, markets and regulation.
2 items
Industry leaders suggest that large payouts by some multistrategy majors are triggering a talent war in the global hedge fund industry.
2 shares
VC-backed hedge fund firm, Hunterbrook, is recruiting financial journalists to help its research team identify potential investments.
2 shares
Episodes on markets, quant methods and economics.
10 items
Michael Kramer discusses treasury tail events, the need for a suitable investment strategy, and the potential risks and rewards in investing.
10 shares
Fadi Zaher reveals the results of a study on long-term ESG trends, highlighting improvements and differences across regions and sectors.
4 shares
Lyn Alden explores the history of money systems, problems with current systems, and the potential of Bitcoin and other digital assets for a fairer economy.
4 shares
Leigh Goehring talks about the link between monetary policy and commodities investing, and the idea of gold-backed digital currencies on a podcast.
3 shares
Jonny Goulden and Saad Siddiqui discuss the impact of recent market developments on the EM fixed income asset class in a 2023 podcast.
3 shares
The podcast discusses the future of the Federal Reserve's balance sheet, considering the monetary policy and expected changes in reserves by 2024.
3 shares
Quant Investing Pioneer: Barry Ritholtz interviews Linda Gibson, CEO of PGIM Quantitative Solutions, about her career and insights into quantitative investing on Bloomberg Radio.
3 shares
Giuseppe Sette, President of Toggle AI, shares insights on using options to enhance investment outcomes in an interview with IBKR's Jeff Praissman.
3 shares
Fundraiser in Chief: Brendan Doherty's new book examines the relationship between campaigning and governing, with a focus on presidential fundraising in the past 60 years.
2 shares
In his podcast, Meb discusses the potential in global value stocks using a shareholder yield approach.
1 shares
Talks, lectures and tutorials.
2 items
Are They Different? Evidence from Retail Trading: The ABFR forum, a group of scholars studying AI and big data's impact on society, plans monthly discussions on economics and finance, with the next one on October 26, 2023.
0 shares
Raw & Unedited Recording: A raw screen recording from the Workshop on AI in Finance at Texas State University San Marcos on October 27, 2023, is accessible on GitHub.
4 shares
Posts from quant researchers on X.
9 items
The study uses LSTM and RFSV techniques to analyze the volatility of digital assets during a period of significant decline in cryptocurrency values.
2 shares
Analyzing Economic Data Statistically: Econometrics, a field that combines economics, statistics, and math, is offering a free PDF download for data analysis.
2 shares
Research indicates that the performance of equity and currency anomalies decreases after their publication, implying that market players use these publications to correct mispricing.
1 shares
LLM-based data transformation: Towhee is a pipeline orchestration tool that uses Large Language Models to convert raw multimodal data into specific formats.
1 shares
DeepMind's opensource weather model: Google Deep Mind has made its advanced weather forecasting model, GraphCast, open-source.
0 shares
Investment funds are utilizing algorithms to analyze earnings call transcripts, leveraging audio for more comprehensive information than text.
0 shares
The study delves into the basics of fractal geometry and its use in understanding market structures.
0 shares
The piece explores the best use of k-means clusters through the k-scorer algorithm.
0 shares
The Financial Times offers a detailed examination of the current problems in the bond market.
0 shares
Threads from r/quant, r/algotrading and friends.
10 items
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