Insider Models for Options
The article proposes a solution for optimal stopping problems in pricing perpetual American standard and lookback put and call options, using the Black-Merton-Scholes model and Brownian filtrations.
12 sharesSource ↗
Quant LetterNo. 105
136 items across 9 sections, as sent to readers on 10 July 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
25 items
The article proposes a solution for optimal stopping problems in pricing perpetual American standard and lookback put and call options, using the Black-Merton-Scholes model and Brownian filtrations.
12 sharesSource ↗
The study finds that most gains in the U.S. stock market over the past 30 years have been earned overnight, with intraday returns being negative or flat, largely due to intraday and overnight news.
11 sharesSource ↗
The paper introduces a new learning algorithm for online portfolio optimization that uses the serial dependence of assets' returns to outperform the best constant rebalancing portfolio in a stochastic market.
10 sharesSource ↗
The study investigates a dynamic asset pricing problem, showing that an agent's perceived ambiguity or ambiguity-aversion can lower the risk-free rate and increase the stock price.
9 sharesSource ↗
The study introduces a method for choosing reference instruments in electronic trading, using predictive models and a Composite Liquidity Factor, which aligns closely with market-optimal quoting choices.
7 sharesSource ↗
Research shows that Systematic Investment Plans in India's Nifty 50 index timed on Futures and Options expiry days perform better in the short to medium term than those on the first trading day of each month.
5 sharesSource ↗
A study suggests a quantum stochastic walk optimizer for financial markets, which increases the annualized Sharpe ratio by 15% and reduces turnover by 90% compared to traditional optimization.
5 shares1 citation todaySource ↗
The paper presents a reinforcement learning framework for optimal trade execution, using multivariate logistic-normal distributions, which outperforms traditional benchmark strategies.
3 shares4 citations todaySource ↗
The paper introduces a tree taxonomy framework for categorizing economic policies, aiming to provide a comprehensive list of actions for governing authorities to control an economy.
3 sharesSource ↗
A study found that a location disclosure policy on Sina Weibo, China's largest microblogging platform, decreased users' engagement on non-local issues and increased regional discrimination.
62 shares1 citation todaySource ↗
The introduction of a location disclosure policy on Sina Weibo led to less engagement on non-local issues and more regional discrimination, indicating that authoritarian regimes can use social divisions to suppress opposition.
62 shares1 citation todaySource ↗
A new mathematical model based on the Navier-Stokes equations accurately describes liquidity dynamics and systemic risk in economic systems, providing a strong framework for predicting crises and planning countercyclical policies.
14 shares4 citations todaySource ↗
The article discusses a framework that combines behavioral distortions with rational portfolio optimization, highlighting the importance of return asymmetry and belief distortions in managing portfolio risk and capital allocation in high-risk situations.
11 sharesSource ↗
Research on social media users shows that 20-34% of a platform's value to users is due to local network effects, with the value of connections differing greatly across platforms, genders, races, and ages.
10 sharesSource ↗
The research introduces a job-based measure of economic complexity that is linked to higher wage levels and labor productivity growth, unlike the traditional measure that focuses on economic outputs.
8 sharesSource ↗
The skfolio, a new open-source Python library, has been launched for portfolio construction and risk management, allowing machine learning workflows for portfolio optimization.
22 sharesSource ↗
The article highlights the significance of the population stability index (PSI) and the Kolmogorov-Smirnov statistic (KS) in maintaining model stability, stressing the need to account for scoring indicator errors in binary choice models.
8 sharesSource ↗
The article investigates the effects of varied participation in Economics and Computation (EconCS) community systems, encouraging the community to decrease participation disparity and create mechanisms that offer quality service to everyone.
8 shares3 citations todaySource ↗
A new visual mapping method has been introduced for evaluating strategic alignment in national artificial intelligence policies, identifying unique alignment archetypes across governance models and offering practical advice for policymakers.
6 shares2 citations todaySource ↗
The article presents a new Darwinian Agent-Based Modeling method for macroeconomic forecasting, which uses evolutionary principles and simple rules to create realistic economic patterns efficiently.
8 sharesSource ↗
The article discusses a new Darwinian Agent-Based Modeling approach for macroeconomic forecasting, highlighting its ability to generate realistic economic patterns and maintain computational efficiency using evolutionary principles and simple rules.
8 sharesSource ↗
The article investigates the use of modern fintech tools such as asset tokenization, smart contracts, and decentralized autonomous organizations for structuring mortgage-backed security contracts, which could enable real-time ratings systems and enhance market efficiency.
7 shares2 citations todaySource ↗
The article presents a new algorithm that uses unemployment and vacancy data to detect US recessions in real time, achieving a 71% accuracy rate for May 2025 data.
31 shares3 citations todaySource ↗
The article argues that AI systems are incapable of performing key functions of economic coordination or creating norms, interpreting institutions, or taking responsibility, challenging the belief in AI's ability to maintain economic and epistemic order.
21 shares2 citations todaySource ↗
The article introduces a new framework that reinterprets the CAP theorem as a constraint optimization problem, showing that availability and consistency can be maintained simultaneously within certain limits through formal economic control.
13 sharesSource ↗
Working papers in finance and economics from SSRN.
30 items
The study uses machine learning to predict the exercise of American call options, outperforming traditional assumptions of options expiring out of money.
61 sharesSource ↗
The paper finds that traditional volatility models forecast best when they match the data-generating process.
42 sharesSource ↗
The article introduces a technical analysis method that uses dividends to predict a share's lifetime maximum and minimum prices.
35 sharesSource ↗
The paper presents a new inflation model that shows inflation reacts more to larger shocks due to nonlinear shock transmission.
64 shares4 citations todaySource ↗
The study establishes a link between operational flexibility and firms' equity risk-return characteristics, showing lower volatility and equity cost with more flexibility.
32 sharesSource ↗
The study investigates the use of quantum machine learning for optimizing high-frequency trading strategies in US treasuries and forex markets.
3 sharesSource ↗
The research shows that deficit financing dividend taxation impacts macroeconomic asset pricing and public debt, affecting investment and debt-to-output fluctuations.
32 sharesSource ↗
The study examines the challenges and opportunities in using Machine Learning for processing Classical Tamil language and its dialects, with a focus on linguistic and cultural aspects.
13 sharesSource ↗
The research uses a simulation model and machine learning to analyze import container flows at the Port of New York-New Jersey, improving accuracy in commodity classification and container dwell times.
27 sharesSource ↗
Kerala Study: The study introduces the SMART AI-Driven Tourism Marketing Framework to boost tourist engagement in Kerala, emphasizing the role of AI and ML in transforming the global tourism market.
14 sharesSource ↗
The article claims that creating ethical and racially-just machine learning is currently unachievable due to reasons like racially biased training data and unclear algorithm design.
16 sharesSource ↗
The research proposes a framework for building supply chain resilience during large-scale disruptions, based on an analysis of successful global brands and their supply chains.
42 sharesSource ↗
The study explores the effect of global supply chain pressures on U.S. stock market returns, providing insights for corporate managers on risk management and supply chain strategy.
20 sharesSource ↗
The article talks about the fast transformation and growth of econometrics, highlighting major advances in the analysis of cross-sectional data, policy analysis, and time series econometric techniques.
23 sharesSource ↗
The research studies the interaction between banks' use of AI in credit scoring and relationship lending, concluding that AI investments help lessen the countercyclical effects of relationship lending on firms' credit supply and decisions.
33 shares3 citations todaySource ↗
Anomalies Explained: Pharmaceutical stocks offer higher returns when writing options due to their high growth potential and unpredictable nature of drug trials.
431 sharesSource ↗
The Common Task Framework can enhance innovation and honesty in research, and could be used in financial economics to assess asset pricing models.
246 sharesSource ↗
Economic Indicators: A new intraday trading strategy for the USTEC CFD, using a language model to filter trading signals based on news sentiment, boosts profitability.
63 sharesSource ↗
Tax Outcomes: IRS officials' personal stock trades yield positive abnormal returns and are linked to future tax enforcement outcomes for the companies they invest in.
660 sharesSource ↗
Currency risk premia fluctuate on U.S. FOMC announcement days, with currencies expecting a larger reduction in implied variance earning higher returns.
213 sharesSource ↗
Ambiguity preference variables can forecast credit asset comovements, with lower-rated US credit assets being more affected by ambiguity aversion.
44 sharesSource ↗
Despite a strong desire to learn about financial preparedness, college students lack financial literacy and understanding of investing and debt.
43 sharesSource ↗
Mutual funds in the Euroarea with a diverse geographic investor base have more fluctuating flows, but it doesn't impact overall performance.
33 sharesSource ↗
The U.S.'s solo approach to digital asset regulation could isolate its markets and weaken its monetary power, indicating a need for global collaboration.
62 sharesSource ↗
Bonds issued in varying interest rate climates offer different coupons and market prices, with higher priced bonds suggesting a greater default loss.
59 sharesSource ↗
During the pandemic, government-backed loans were more likely given to safer borrowers with liquidity constraints, who had fewer repayment issues.
25 shares1 citation todaySource ↗
Capital-loss carryforwards can be assessed using an option-pricing perspective, providing a market-based method for determining when these strategies are economically beneficial.
67 sharesSource ↗
Fund managers can mitigate the adverse effects of competition on fund alpha by adjusting active management levels, particularly in response to competition from passive funds.
29 sharesSource ↗
A study of 43 macroeconomic variables across G7 economies over two centuries shows mean reversion in the U.S., but more persistent dynamics in Italy and Japan.
37 sharesSource ↗
Companies with high fixed costs have negative exposure to inflation surprises, primarily due to variable costs, which are positively linked with inflation beta.
35 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The rise of algorithmic trading and passive investing has caused issues during market downturns, but a new Automated Adaptive Trading System could help stabilize emerging markets during such times.
27 sharesSource ↗
Machine learning has been used to pinpoint assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization plan for efficient asset allocation.
25 sharesSource ↗
Using expected shortfall as the risk measure in risk parity portfolio optimization reduces sensitivity to volatility shocks, decreases portfolio turnover during market turmoil, and enhances risk-adjusted returns considering fat-tailed returns.
16 sharesSource ↗
The research finds that trading strategies based on Sharpe Ratio consistently yield better results than the buy-and-hold strategy in global markets, supporting the Adaptive Market Hypothesis.
15 sharesSource ↗
The study introduces a new method for assessing decision-making units' efficiency over time, using the Whale Optimization Algorithm to identify stable trading strategies and firms.
11 sharesSource ↗
The paper uses a new data augmentation technique to analyze poverty in the Middle East and North Africa, highlighting the significance of using alternative data sources for poverty analysis.
10 sharesSource ↗
The BRM method is introduced for analyzing incomplete data, improving speed and reducing data imputation by pretraining models over subsets of missing data.
20 sharesSource ↗
A new machine learning strategy, N-MDIS, is proposed for improving equity premium prediction, outperforming existing strategies.
19 sharesSource ↗
The research shows that firms are more likely to adopt zero-leverage policies as product market competition increases, especially those with higher earnings volatility.
18 sharesSource ↗
The study reassesses the impact of news sentiment on stock return volatility, demonstrating that accurately measured news sentiment significantly influences intraday stock return volatility.
16 sharesSource ↗
A modified version of Stochastic Gradient Boosting is proposed for estimating production possibility sets in DEA, reducing overfitting and meeting shape constraints, proving competitive against existing methods.
16 sharesSource ↗
A study reveals that machine learning models are more efficient in predicting Chinese corporate merger and acquisition activities than traditional methods.
28 sharesSource ↗
New probabilistic deep learning frameworks have been proposed for better risk management in financial institutions, surpassing previous methods in backtesting.
27 sharesSource ↗
Machine learning methods have been found to accurately predict Chinese stock market volatility using the volatility of long-term treasury bond contracts.
24 sharesSource ↗
The article proposes a new algorithm and machine learning model for the Lot Streaming and Scheduling Problem (LSSP) with unpredictable product arrival times, aiming to increase efficiency and accuracy.
16 sharesSource ↗
The paper introduces a new machine learning technique for decomposing and analyzing complex time series, providing a potential alternative to the Box-Jenkins method for financial modeling.
13 sharesSource ↗
The study uses machine learning to create a monetary policy frictions index from financial news, finding that these frictions significantly impact the nonperforming loans of Chinese commercial banks.
12 sharesSource ↗
The research uses machine learning to study the global housing market, discovering that the US market is the main source of systematic shocks and its interest rate is a key factor in predicting spillover intensities.
10 sharesSource ↗
Machine Learning vs. Deep Learning: Deep learning methods have been found to be more effective than traditional machine learning in predicting oil prices, especially during crises.
31 sharesSource ↗
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 ↗
The study uses machine learning to predict the CBOE Volatility Index, highlighting weekly jobless claim data as a significant factor.
23 sharesSource ↗
Traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices, according to the study.
13 sharesSource ↗
The research indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
The study emphasizes the need for communication and a comprehensive approach to address climate change, using machine learning to analyze social media discussions on the subject.
4 sharesSource ↗
The research investigates the use of dark patterns in retail investment, suggesting the use of behavioral sciences and AI for improved regulation and investor protection.
2 sharesSource ↗
The research profiles young informal workers in the EU27, aiming to understand how Covid-19 has impacted youth employment informality.
2 sharesSource ↗
The article discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
The review investigates the link between e-governance initiatives and citizen participation, emphasizing the need for interdisciplinary research for better understanding and evaluation.
2 sharesSource ↗
The paper analyzes literature on factors affecting banks' performance, proposing new research areas in digital transformation, artificial intelligence, and the impact of COVID-19.
1 sharesSource ↗
The study tests the applicability of the Work Need Satisfaction Scale (WNSS) to online gig workers, suggesting modifications to the scale to better reflect the specifics of online platform work.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
QLASS is a new method for training language agents that improves performance and efficiency through step-by-step guidance, even with limited supervision.
188 shares19 citations todaySource ↗
Researchers suggest using platinum benchmarks, which are designed to reduce label errors, to more accurately assess the reliability of large language models.
55 shares54 citations todaySource ↗
The MAETok autoencoder enhances image synthesis by learning a semantically rich latent space, achieving top performance on ImageNet generation with only 128 tokens.
38 shares94 citations todaySource ↗
NutWorld is a new framework that converts monocular videos into dynamic 3D Gaussian representations in one go, allowing for high-quality video reconstruction and real-time applications.
29 shares8 citations todaySource ↗
The Risk-Averse Calibration (RAC) algorithm improves decision-making by considering prediction uncertainty, striking a balance between safety and utility in risk-sensitive areas like medicine.
20 shares46 citations todaySource ↗
ML Humanoid Platform: ToddlerBot is an affordable, open-source robot designed for AI research, featuring a user-friendly interface and a digital twin for easy data collection and policy implementation.
19 shares21 citations todaySource ↗
Browser Agent Learning: NNetNav is an unsupervised method that creates synthetic demonstrations for training browser agents, making website interaction more manageable by using language instruction hierarchy.
15 shares57 citations todaySource ↗
Cross-Model Adaptation: LoRA-X is a new adapter that enables the transfer of LoRA parameters between models without the need for original or synthetic training data.
13 shares11 citations todaySource ↗
PoLAr-MAE is a self-supervised learning method that efficiently analyzes Liquid Argon Time Projection Chambers images by learning trajectory representations directly from data.
13 shares9 citations todaySource ↗
Position Encodings with STRING: STRING is a position encoding method that provides exact translation invariance and low computational footprint, useful in robotics for efficient 3D token representation.
13 shares20 citations todaySource ↗
Repositories the letter featured.
10 items
The article introduces a new library for efficient and flexible statistical data testing.
3,895 shares
The article outlines the fastest way to move from backtesting to live trading.
37 shares
The article shares the source code for Deep Fundamental Factor Models.
64 shares
The article provides 60 deep learning paper implementations and tutorials with accompanying notes.
61,624 shares
The article explores an unofficial implementation of a trend labeling method for financial time series prediction.
44 shares
The article provides a method to simplify a codebase on GitHub by replacing 'hub' with 'ingest' in the URL.
10,798 shares
The article discusses a system for tracking Claude Code usage with predictive analytics and warning alerts.
2,359 shares
The article announces the availability of the official Python client library for the Polygon REST and WebSocket API.
1,053 shares
The article reviews a self-hosted ROM manager and player that is aesthetically pleasing and highly functional.
5,408 shares
Industry news: funds, hiring, markets and regulation.
15 items
Teaghan Price has been hired by Peregrine Capital South Africa to enhance adviser relationships in KwaZuluNatal.
5 shares
Eric Ho has been appointed as the new Senior Investment Counsel at London's Shiprock Capital Management.
5 shares
Olivier Nobile from Arkea Asset Management recommends active equity managers adopt hedge fund strategies to remain competitive amid a shift towards low-cost passive investments.
4 shares
Mazi Asset Management is working to expand its successful NCIS Qualified Long Short Hedge Fund in South Africa.
4 shares
The Children’s Investment Fund, led by Chris Hohn, has seen a 21% return this year, surpassing the S&P 500.
3 shares
Steve Mandel’s Lone Pine Capital, a Tiger Cub hedge fund, has outperformed several multistrategy giants in the first half of the year.
3 shares
Parataxis, a US-based company, is launching South Korea's first bitcoin treasury platform through its new entity, Parataxis Korea.
3 shares
The article explores the alleged decline of a once top-rated finance company.
2 shares
The article highlights the major issues that banks are currently struggling with.
1 shares
The article predicts a rise in activist hedge funds' public campaigns due to a boost in global M&A activity in late 2025.
1 shares
The article explores the complex concept of something being both present and absent at the same time.
0 shares
The article covers the incident of Alex Gerko blocking the author or a certain organization.
0 shares
The article tells the story of a person's career transition from being a spy to becoming a Senior Vice President.
0 shares
The article emphasizes on JPMorgan's growing use of artificial intelligence in its business operations.
0 shares
Episodes on markets, quant methods and economics.
10 items
In a podcast, Dan Rasmussen and D.A. Wallach discuss the influence of AI on healthcare, the current state of biotech, and the transformative power of innovative treatments.
11 shares
A podcast episode provides a midyear global outlook, discussing tariff-related volatility, policy uncertainty, and the future of private market assets.
10 shares
Zimbabwean master’s student Edson Bope shares his experiences and challenges in the U.S. job market for quantitative finance roles in a podcast episode.
9 shares
A podcast episode explores the potential repercussions of replacing programmers with AI, based on a viral article warning against such a move.
8 shares
The eighth season of Talking Tuesdays with Fancy Quant will feature guest speakers from the quantitative finance community discussing various topics and sharing their life stories.
7 shares
Emerging markets like Taiwan, South Korea, and China are becoming attractive investment destinations, especially in the tech sector.
6 shares
Seth Cogswell believes the current investment climate resembles the 2000 bubble, and suggests mid-cap companies as stable investment opportunities with growth potential.
5 shares
Dmitry Pargamanik advises traders to use historical options data to predict and manage volatility during earnings announcements.
4 shares
Henry Yoshida's Rocket Dollar platform enables investors to diversify their retirement accounts with alternative investments like private equity, real estate, and cryptocurrency.
3 shares
Riddler Road Rally is a citywide car-based scavenger hunt happening in eleven cities across Utah and Idaho, providing a unique and entertaining experience.
2 shares
Posts from quant researchers on X.
4 items
AQR maintains its top position in managed futures funds for the year, with LoCorr coming in second.
1 shares
Commodity Returns, Crypto Microstructure, Mispriced Stocks, Factor Momentum, and More: Article 2: Recent investment research explores topics including forecasting commodity returns, crypto market microstructure, spotting mispriced stocks, and factor momentum.
0 shares
The article examines Nagel's new paper that questions the efficiency of intricate models in predicting returns, suggesting they are essentially volatility-timed momentum.
0 shares
Threads from r/quant, r/algotrading and friends.
2 items
5 shares
5 shares