Neural Network Pricing
The study uses neural network methods, Time Deep Gradient Flow and Deep Galerkin Method, to price multidimensional American put options, showing better accuracy and speed than traditional methods.
27 sharesSource ↗
Quant LetterNo. 107
July 2025, Week 4
109 items across 8 sections, as sent to readers on 25 July 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 109
- Papers
- 61
- Sections
- 8
- Issue
- No. 107
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
22 items
Finance7
Optimal Trading with Price Impact
The research tackles dynamic portfolio optimization, considering predictable returns, transaction costs, price impact, and stochastic volatility, and suggests a multi-scale volatility expansion, improving portfolio strategy's Profit and Loss through simulations.
19 sharesSource ↗
Machine Learning for Option Pricing
The article introduces a machine learning extension of the binomial option pricing model, using Random Forest classifiers on high-frequency market data, proving its efficiency in predicting price movements and estimating fair value.
8 sharesSource ↗
Stationary Market Dynamics
The article introduces a mathematical model that views the financial market as a communication system, aiming to minimize the joint information of risk-neutral pricing measure in relation to real-world probability measure.
8 shares1 citation todaySource ↗
LogOptimal Portfolio Analysis
The research applies the càdlàg rough paths theory to examine the stability and approximation properties of portfolios in financial markets, with a focus on the log-optimal portfolio in an investment-consumption optimization issue.
7 shares1 citation todaySource ↗
Evolutionary Factor Searching
The paper presents Evolutionary Factor Search (EFS), a new method that uses large language models to automatically generate and evolve alpha factors for sparse portfolio construction, showing its effectiveness in different market situations.
7 sharesSource ↗
Diversification Reversals
The research questions the traditional belief of diversification as a risk reduction strategy, identifying situations where diversification increases risk and offering a theorem that explains this unexpected result.
6 shares5 citations todaySource ↗
Economics4
Weather-Aware AI vs Route-Optimization AI
AI technology combining weather prediction and route optimization can potentially double taxi driver earnings, indicating a promising market in weather intelligence.
10 sharesSource ↗
Homeownership Benefits Over Time
Owning a home in developed countries can increase wealth by up to 9% and welfare by up to 23% compared to an all-equity investment strategy, with results varying based on income and market conditions.
7 sharesSource ↗
Financial Frictions in Agriculture: Stablecoins Solution
Stablecoins Solution: Fiat-collateralized stablecoins, a type of digital currency, could help solve financial issues in the global agricultural sector by reducing trade costs, increasing supply chain efficiency, and broadening credit access.
7 sharesSource ↗
Equity, Emissions, and the Inflation Reduction Act
The 2022 Inflation Reduction Act's incentives for buying preowned EVs could help low-income households, but up to 8.4 million might not qualify due to different vehicle procurement methods, potentially hindering significant emissions reduction.
6 sharesSource ↗
Miscellaneous5
Forecasting LFSM
A new method for predicting future changes in linear fractional stable motion (LFSM) has been proposed, which performs better than the fractional Brownian motion in predicting high-frequency FX rates and volatility time series.
19 shares2 citations todaySource ↗
AI Evaluation
Large language models used in economics are found to be more sensitive to issues like unemployment, inequality, financial stability, and environmental harm, and less responsive to traditional macroeconomic factors.
17 sharesSource ↗
Explainable GNNs
GraphEXT, a new explainability framework for Graph Neural Networks, improves their explainability by focusing on node interactions and the effect of structural changes on predictions.
12 shares4 citations todaySource ↗
iQRA for Electricity Markets
A new method, Isotonic Quantile Regression Averaging (iQRA), for generating probabilistic forecasts from point forecast ensembles in electricity markets, outperforms other methods in reliability and sharpness.
7 sharesSource ↗
Crypto & Blockchain3
Transformer vs LSTM in Financial Forecasting
The study uses Mean Absolute Directional Loss function to evaluate machine learning models in quantitative finance, revealing that Transformer models are superior to LSTM models.
12 sharesSource ↗
Anomaly Detection in Crypto Order Books
Research comparing statistical methods and machine learning for anomaly detection in cryptocurrency limit order books shows the Empirical Covariance model is the most effective, beating a standard Buy-and-Hold benchmark by 6.70%.
9 shares3 citations todaySource ↗
Optimal Entry and Exit in Liquid Staking
The study examines optimal entry and exit decisions for investors in a liquid staking protocol and automated market maker, suggesting a fee mechanism that encourages staking and liquidity provision, and showing a stop-loss strategy often yields the highest expected payoff for the investor.
8 shares3 citations todaySource ↗
Historical Trending3
Dynamic Portfolio Selection
The article discusses a new dynamic mean-variance portfolio selection method using generative diffusion models, which performs better than several established methods including the Markowitz portfolio, the equal weight portfolio, and S&P 500.
21 shares5 citations todaySource ↗
Experimental Economics with Language Models
The research offers guidelines for creating economic experiments for large language models, improving the design, replicability, and general applicability of these experiments in the digital era.
18 shares1 citation todaySource ↗
Policy Optimization for Multi-Asset Portfolios
The paper presents the Pontryagin-Guided Direct Policy Optimization (PG-DPO) framework, a new method for solving large-scale, continuous-time portfolio optimization problems, showcasing its capability to manage high-dimension problems.
17 shares4 citations todaySource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
Enhanced EM Portfolios with AATS
A new Automated Adaptive Trading System may help stabilize emerging markets during downturns, addressing issues caused by algorithmic trading and passive investing.
27 sharesSource ↗
Efficient Volatile KSE-30 Equities Identification
Machine learning has been utilized to identify assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization strategy for effective asset allocation.
25 sharesSource ↗
Dynamic Correlations in Risk Parity Portfolio Optimization
Using expected shortfall as the risk measure in risk parity portfolio optimization can lessen sensitivity to volatility shocks, decrease portfolio turnover during market turmoil, and enhance risk-adjusted returns.
16 sharesSource ↗
Adaptive Market Hypothesis
The research finds that trading strategies based on the Sharpe Ratio are more profitable than the buy-and-hold strategy in global markets, supporting the Adaptive Market Hypothesis.
15 sharesSource ↗
Window Analysis for High-Frequency Trading
The study introduces a new method for assessing decision-making efficiency over time, using the Whale Optimization Algorithm, and applies it to foreign exchange investment strategies and utility companies.
11 sharesSource ↗
Monitoring Poverty in Lebanon
The paper uses a new data augmentation technique to study poverty in the Middle East and North Africa, specifically Lebanon, using alternative data sources when traditional income data is scarce or unavailable.
10 sharesSource ↗
Statistical5
BRM for Incomplete Data Prediction
The BRM method is introduced for analyzing missing data patterns, using ensemble models to reduce data imputation, and showing better predictive performance for various models.
20 sharesSource ↗
New Momentum Strategy for Equity Premium
A new N-MDIS strategy using machine learning is proposed for better equity premium prediction, outperforming both MDIS and N-MDIS with logistic regression.
19 sharesSource ↗
Product Market Competition and Zero-Leverage
The study shows that firms are more likely to adopt zero-leverage policies as product market competition increases, especially in firms with higher earnings volatility.
18 sharesSource ↗
News Sentiment Impact on Risk Management
The study shows that both negative and positive firm-specific and macroeconomic news significantly influence intraday stock return volatility.
16 sharesSource ↗
Stochastic ML for Production Technologies
A new adaptation of Stochastic Gradient Boosting is proposed for estimating production possibility sets in DEA, reducing overfitting and showing competitive performance compared to C2NLS.
16 sharesSource ↗
Machine Learning7
Machine Learning for M&A
A study shows machine learning models are more effective than traditional methods in predicting Chinese corporate mergers and acquisitions using 60 variables.
28 sharesSource ↗
Tail Risk Management
New probabilistic deep learning frameworks have been proposed for estimating financial risk measures, improving capital allocation in financial institutions.
27 sharesSource ↗
Bond Market Volatility in China
Machine learning methods accurately predict Chinese stock market volatility using the volatility of long-term treasury bond contracts, outperforming traditional models.
24 sharesSource ↗
Lot Streaming and Scheduling
The article proposes a new algorithm and machine learning model to improve efficiency and accuracy in the Lot Streaming and Scheduling Problem with stochastic product arrival times.
16 sharesSource ↗
Dynamics in Chinese Financial Markets
The paper introduces a new machine learning technique for analyzing and modeling complex time series, providing a potential alternative to the Box-Jenkins methodology in financial modeling.
13 sharesSource ↗
Monetary Policy Frictions and Nonperforming Loans
The study uses machine learning to create a monetary policy frictions index from financial news, revealing significant impacts on nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
Housing Market Connectedness
The research uses machine learning and quantile connectedness models to study the international housing market, identifying the US market as the main source of systematic shocks.
10 sharesSource ↗
Deep Learning2
Oil Price Forecasting: ML vs. DL
ML vs. DL: Deep learning methods have been found to be more effective than traditional machine learning in predicting oil prices, especially during crises.
31 sharesSource ↗
Multifrequency Data Fusion for Carbon Price Prediction
The newly introduced MFF-CPPM model in China has shown higher accuracy and flexibility in predicting carbon trading prices compared to standard models.
10 sharesSource ↗
Historical Trending10
Predicting VIX Trends
The research uses machine learning to predict the CBOE Volatility Index, highlighting the importance of weekly jobless claim data for trading strategies.
23 sharesSource ↗
Stock Price Prediction
The study shows traditional machine learning models are better than deep learning models at predicting stock prices in the Eurozone banking sector.
13 sharesSource ↗
AI Capability Impact
The research indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure being key factors.
5 sharesSource ↗
Climate Discussions
The study emphasizes the role of communication and a comprehensive approach in addressing climate change, using machine learning to analyze social media discussions on the issue.
4 sharesSource ↗
Dark Patterns in Retail
The research investigates the problem of dark patterns in retail investment, studying the use of behavioral sciences and AI to improve regulation and safeguard investors.
2 sharesSource ↗
Understanding Young Informal Workers in the EU
The research profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
Intelligent Resource Management in Cloud Computing
The article discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
EGovernance Initiatives and Citizen Participation
The review investigates the link between e-governance initiatives and citizen participation, emphasizing the need for interdisciplinary research for effective evaluation.
2 sharesSource ↗
Bank Performance Determinants
The paper analyzes literature on factors affecting banks' performance, proposing new research areas, particularly in digital transformation, artificial intelligence, and FinTechs.
1 sharesSource ↗
Work Need Satisfaction Scale in Online Gig Work
The study explores the Work Need Satisfaction Scale's factor structure among online gig workers, suggesting modifications to the scale to better reflect online platform work.
1 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
9 items
Historical Trending9
QLASS: Language Agent
Language Agent: QLASS system enhances language agents' performance by offering detailed guidance and creating annotations automatically with minimal supervision.
189 shares19 citations todaySource ↗
Large Language Model
Platinum benchmarks are introduced to assess the dependability of large language models, showing that even sophisticated models have difficulty with basic tasks.
55 shares54 citations todaySource ↗
Masked Autoencoders
MAETok system boosts high-resolution image synthesis by learning a semantically rich latent space, leading to quicker training and increased inference throughput.
38 shares94 citations todaySource ↗
Unanswerability Evaluation
UAEval4RAG framework assesses the capacity of retrieval-augmented generation systems to manage unanswerable queries, emphasizing the significance of component selection and prompt design.
29 shares10 citations todaySource ↗
NutWorld: 3D Gaussian Video
3D Gaussian Video: NutWorld is a new framework that turns monocular videos into 3D Gaussian representations, enhancing video quality and allowing real-time applications.
29 shares8 citations todaySource ↗
Stochastic Gradient Descent Optimization
A new gradient descent algorithm with adaptive randomness is proposed for global optimization of nonconvex problems, proving its effectiveness and stability with numerical examples.
28 shares6 citations todaySource ↗
Deep Linear Training Dynamics
The paper explores the dynamics of gradient descent in deep linear networks, discussing the impact of network width and depth, and comparing various training dynamics.
26 shares17 citations todaySource ↗
Rankify: Python Retrieval Toolkit
Python Retrieval Toolkit: Rankify, an open-source toolkit, is introduced to streamline retrieval, re-ranking, and retrieval-augmented generation processes, aiming to improve retrieval methods while maintaining consistency, scalability, and user-friendliness.
24 shares11 citations todaySource ↗
DeepSeek R1: Generative AI Implications
Generative AI Implications: The article discusses DeepSeekR1, a new reasoning model by DeepSeek, emphasizing its strong performance despite lower development costs and US restrictions on GPU exports.
23 shares43 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
15 items
Trending7
Transformer Explainer
Despite the significant impact of Transformers on machine learning, their workings remain unclear to many people.
4,954 shares
Superhuman Reasoning
The article discusses the challenge of surpassing human cognitive limitations in the training of Large Language Models (LLMs).
4,612 shares
Workflow Generation Models
The article presents a curated dataset of 4K workflows used to create comprehensive reasoning data, including aspects like node selection, workflow planning, and code-level workflow representation.
2,204 shares
GLM4 vs Qwen2.5VL7B
The article discusses a model that performs better than Qwen2. 5VL7B in 28 public benchmarks and equals or surpasses Qwen2. 5VL72B in 18 benchmarks.
833 shares
NVIDIA Audio Flamingo
The article emphasizes the importance of enhancing large language models to understand audio, including non-speech sounds and non-verbal speech, for various real-world applications.
605 shares
Streaming 4D VGT
The article introduces a streaming 4D visual geometry transformer, similar to autoregressive large language models, designed to support interactive and real-time applications.
399 shares
IQLearn: Inverse softQ
Inverse softQ: The article highlights the availability of human or expert data in sequential decision-making tasks like robotics control and game playing, which offers valuable task-related information.
365 shares
Rising8
Benchmarking Autonomous Agents
The article presents REAL, a tool for assessing multiturn agents' performance on simulations of actual websites.
233 shares
Mathematical Deep Learning Introduction
The book offers a beginner-friendly guide to understanding deep learning algorithms.
210 shares
HackSynth LLM Agent
The article introduces HackSynth, an agent based on Large Language Model for independent penetration testing.
169 shares
PhysX Asset Generation
The article explores the shift of 3D modeling from a virtual environment to a physical one.
119 shares
Dynamic 4D Scene Forecasting
The article introduces a method that divides scene tokenization into two parts: intrascene and interscene tokenizers.
102 shares
Conv3x3 Designs in Diffusion Models
The article emphasizes the exceptional performance of diffusion models in tasks related to visual generation.
86 shares
AutoSteering Trajectories
The article points out problems with anchorfree methods leading to visual artifacts and anchorbased methods relying on heuristic selection of anchor concepts.
66 shares
Safety Vulnerability of Diffusion LLMs
The article presents DIJA, a system that uses adversarial interleaved masktext prompts to control the text generation processes of dLLMs.
45 shares
GitHub
Repositories the letter featured.
9 items
Finance4
Prob. & Stats for Data Science
The article delves into the importance of probability and statistics in data science.
442 shares
Free DB tool & SQL client
The article presents a free universal database tool and SQL client for users.
44,502 shares
Estimating L3 order book on Binance
The article explores the use of L2 data changes over time to estimate a L3 order book microstructure on Binance.
108 shares
MCP Server for Jupyter Model Context Protocol
The article introduces the Model Context Protocol MCP Server for Jupyter.
517 shares
Trending5
Mathiasdotfiles
The article provides an in-depth explanation on the functionality and application of wrench .files.
30,899 shares
ShareAIanalysiscode
The article offers insights into the Claude Code v1.0 repository and its features.
4,005 shares
Rbaronparasite
The article presents a DIY project on creating an open-source soil moisture sensor.
2,234 shares
RoyaltyCrux
The article explores the latest advancements and trends in the field of intelligence.
83 shares
News
Industry news: funds, hiring, markets and regulation.
9 items
Quantitative4
EDS 'Fusion' AI Platform Launch
Equity Data Science has introduced Fusion, an AI-based platform aimed at transforming data management and decision-making for institutional investors.
5 shares
Yen Bearish Hedge Funds
Hedge funds have taken a net bearish position on the Japanese yen for the first time in almost four months, ahead of Japan's upper house election.
5 shares
Merger Arb Funds Profit from ChevronHess
Merger arbitrage hedge funds are benefiting from Chevron's $53bn purchase of Hess Corp, marking one of the most profitable event-driven deals of the year.
4 shares
Record Hedge Fund AUM
Global hedge fund assets hit a record $4.74tn in Q2 2025, due to the largest quarterly inflows since 2014, with institutional investors contributing nearly $25bn, as per the HFR Global Hedge Fund Industry Report.
3 shares
Miscellaneous5
Kodai Capital Founder at Millennium
Neville Shah, former co-founder of Kodai Capital Management, has been appointed as a senior member of the equities management team at Millennium Management.
3 shares
Citadel Securities Quant at UBS
The article talks about a significant event or period that an individual has missed.
2 shares
Millennium Allocates 4
Millennium Management has invested $4.2bn in two independent hedge fund managers, emphasizing its strategy of investing in high-quality external talent.
1 shares
Morgan Stanley Head at HFT Firm
The article mentions a significant change or move, but lacks specific details.
1 shares
UMG Files for US Listing
Universal Music Group has confidentially filed for a US listing, in line with an agreement with Bill Ackman’s hedge fund firm Pershing Square to enhance shareholder value.
1 shares
Podcasts
Episodes on markets, quant methods and economics.
9 items
Quantitative4
AI Stocks Talk
Raphael Douady, a French mathematician, shares his journey from academia to quantitative finance, his knowledge in chaos theory and financial mathematics, and the influence of AI in finance.
13 shares
US Rates Preview
Ben Bennett, Head of Investment Strategy Asia, talks about the effects of tariffs on US inflation, instability in Japanese government bonds, and the elements influencing AI stocks.
8 shares
Global FX Implications
Senior J.P. Morgan research and trading staff share their predictions for the refunding announcement and its potential effect on the Treasury market and swap spreads.
7 shares
MacroVoices Dr. Malmgren Interview
Arindam Sandilya, James Nelligan, and Patrick Locke discuss the FX outlook concerning Japan's elections, US policy instability, and an impending ECB meeting.
7 shares
Related5
US Tariffs Impact
Brad Setser discusses the economic implications and potential global disruptions caused by US tariffs in a podcast.
1 shares
Trump's Chinese Tariffs
Leonid Mironov argues on a show that Trump's Chinese tariffs are beneficial for China and makes a bold prediction about a specific country.
1 shares
Maximizing Returns
The article offers an investment strategy to maximize returns in fluctuating markets.
1 shares
Investors' Tariff Response
Jan Hatzius and Dom Wilson from Goldman Sachs discuss the effects of tariffs on inflation and growth, and share their predictions for the latter half of 2025.
0 shares
Collaborations Among Guests
Kyle and Asaf talk about a project that connects former podcast guests through their joint authorship of academic papers.
0 shares
Threads from r/quant, r/algotrading and friends.
6 items
Quantitative1
Backtesting Data
13 shares
Rising5
July Losses
106 shares
Statistical Arbitrage
702 shares
Advice Seeker
19 shares
Trader Letting Go
46 shares
Polymarket Realism
33 shares