Deep Learning for Option Hedging
This article discusses a method using deep learning to price and hedge European options in incomplete markets, optimizing risk distribution while handling tricky payoffs.
3 shares1 citation todaySource ↗
Quant LetterNo. 121
128 items across 10 sections, as sent to readers on 1 December 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
27 items
This article discusses a method using deep learning to price and hedge European options in incomplete markets, optimizing risk distribution while handling tricky payoffs.
3 shares1 citation todaySource ↗
The QNA framework applies quantum techniques to examine interdependencies in financial markets, offering new metrics for understanding entanglements and hidden information that classical methods miss.
1 sharesSource ↗
A portfolio strategy leveraging transfer learning improves investment results by filtering useful information from noise, leading to better performance as indicated by a higher Sharpe ratio.
1 sharesSource ↗
This innovative approach simplifies the pricing and hedging of path-dependent options, improving strategies in markets with friction through numerical analysis.
0 shares8 citations todaySource ↗
The study connects individual option hedging to broader market volatility, revealing how market-maker actions during volatility spikes can increase fluctuations, especially in low-beta stocks.
0 sharesSource ↗
A new approach to representing risk in portfolios improves loss analysis for regulatory and managerial purposes beyond traditional methods.
0 sharesSource ↗
The survey explains how extreme modeling techniques can be applied in insurance, using real-world data examples.
0 sharesSource ↗
This paper introduces new bounds for the Fréchet problem and examines effective methods for risk aggregation and sharing in risk management.
0 sharesSource ↗
A combined A3T-GCN model enhances the accuracy of FTSE100 stock price forecasts by using technical indicators and optimized sequences.
0 sharesSource ↗
A unique portfolio optimization method that incorporates ESG scores into the Black-Litterman framework shows significant returns with daily updates.
0 sharesSource ↗
The article studies the decline of profit rates in Spain since 1960, linking it to capital composition and surplus value.
0 sharesSource ↗
The study shows that while HIV stigma reduces testing rates, it may also discourage risky behaviors, suggesting some stigma might benefit society.
0 sharesSource ↗
The research on the Phillips Curve from 1980 to 2016 reveals strong forward-looking inflation expectations in developed countries, while others face challenges in its application due to past volatility.
0 shares5 citations todaySource ↗
This paper examines the Phillips relationship, noting it works in developed nations but fails during recessions, emphasizing the need for economic stability for the theory to be valid.
0 shares8 citations todaySource ↗
A study found that Black men drafted in the Vietnam War faced higher long-term death rates due to combat than those drafted later.
0 sharesSource ↗
Research indicates that cross-modal decisions increase patience globally, but Japanese participants are generally more patient than Americans.
0 sharesSource ↗
An analysis shows that complex reporting in assignment systems causes misreporting, with sequential choice methods being the most accurate and efficient.
0 shares1 citation todaySource ↗
A study on electricity markets found that many firms altered bids to dodge penalties, but the measures' overall effectiveness remains questionable, suggesting the need for stricter regulations.
0 shares1 citation todaySource ↗
Organizations using AI face challenges in traditional ROI calculations due to risks, leading to a new framework that includes risk assessments.
2 sharesSource ↗
A project successfully developed a natural language processing model that classifies job ads with 72% accuracy by using an ensemble approach.
0 sharesSource ↗
The use of AI in regulated industries exposes gaps between technical risk assessments and compliance, prompting a new taxonomy for AI risk evaluation and financial impacts.
0 shares2 citations todaySource ↗
Research shows that large language models can indirectly collaborate in Dutch auctions to increase prices, influenced by market structure.
0 sharesSource ↗
Credit Exposure Dataset: The DeXposure dataset offers a comprehensive resource for analyzing credit exposure in decentralized finance, featuring 43.7 million entries for financial machine learning research.
1 shares6 citations todaySource ↗
The study examines the price factors influencing five major cryptocurrencies from 2010-2018, highlighting the roles of market conditions, long-term appeal, and the SP500 index.
1 shares225 citations todaySource ↗
The report enhances a deep reinforcement learning model for liquidity provision in Uniswap V3, showing better performance and theoretical backing compared to the original.
0 sharesSource ↗
A model assesses decentralized versus centralized monitoring in public services, identifying key thresholds for effective regulatory oversight, especially in U.S. nursing homes.
0 shares3 citations todaySource ↗
The article introduces a new Lévy model that uses a time change to better model both SPX and VIX options together, aiming to solve the problems related to consistent volatility modeling.
1 sharesSource ↗
Working papers in finance and economics from SSRN.
31 items
The article suggests using open-source satellite data to map residential buildings worldwide, aiming to evaluate their vulnerability to climate risks and their environmental effects.
30 sharesSource ↗
The article recommends using open-source satellite data to create a worldwide census of homes. This would aid in evaluating climate risks and their effects on housing policies.
30 sharesSource ↗
The article proposes using open-source satellite data to map residential buildings worldwide, which would help evaluate their risks from climate change and their contributions to it.
30 sharesSource ↗
The paper introduces a method using clustering techniques and high-frequency data to find similar financial assets, aimed at improving statistical arbitrage strategies.
1,135 sharesSource ↗
This study outlines a framework for estimating alpha in private capital, showing notable annual returns for buyouts but unreliable data for venture capital and real estate.
1,318 shares2 citations todaySource ↗
The research presents FINDALL, a search engine that effectively identifies relevant stocks for direct indexing, outperforming traditional ETFs with lower costs.
264 sharesSource ↗
An analysis of COVID-19 short selling bans in Europe reveals they harmed liquidity and trading volumes without affecting prices, with ongoing effects after the bans were lifted.
90 sharesSource ↗
The study shows that delta-hedged credit index options have large negative Sharpe ratios and are more affected by credit-specific factors than by equity index returns.
254 sharesSource ↗
Analysis indicates that payment for order flow in crypto markets increases trading costs and reduces volumes, especially for assets beyond Bitcoin and Ethereum, after new tokens are introduced.
332 sharesSource ↗
Poor credit risk management in Indian banks has led to rising Non-Performing Assets, highlighting the need for modern risk tools, such as credit derivatives, to improve future performance.
76 sharesSource ↗
This study shows that different European real estate markets have varying volatility and suggests using tactical asset allocation to improve investment performance.
190 sharesSource ↗
The paper examines India's growing asset securitization trend and the confusing tax issues that come with it.
159 sharesSource ↗
This research highlights the rise of collective investment trusts in 401k plans due to their lower costs and tailored options for investors.
154 sharesSource ↗
The study looks at how mutual fund performance is influenced by internal biases when large amounts of capital are invested.
128 sharesSource ↗
This research details how falling coal production negatively impacts municipal finances, leading to higher debt and bond yields in less diverse counties.
123 sharesSource ↗
The study investigates Malaysian government bond yield changes during COVID-19, finding they began to resemble stocks as investor risk tolerance increased.
64 sharesSource ↗
This research indicates that having more women in a company's leadership improves risk management, especially in uncertain times.
61 sharesSource ↗
This paper explores using spectral clustering to find similar assets for statistical arbitrage across various financial markets.
1,135 sharesSource ↗
A new framework shows that buyout funds have generated an impressive annual alpha of 2.5% in private capital asset classes.
1,318 shares2 citations todaySource ↗
The FINDALL search engine outperforms traditional ETFs by creating thematic indices, significantly reducing expense ratios.
264 sharesSource ↗
Short selling bans during COVID-19 worsened liquidity and trading volumes, causing long-term negative impacts even after the bans ended.
90 sharesSource ↗
Delta-hedged credit index options have worse Sharpe ratios than equity options, influenced by credit option order flow.
254 sharesSource ↗
Payment for order flow in crypto markets raises trading costs and reduces overall volume, indicating poor market quality compared to equities.
332 sharesSource ↗
Poor credit risk management in Indian banks leads to non-performing assets, highlighting the need for modern tools like credit derivatives.
76 sharesSource ↗
The paper reveals tactical asset allocation strategies for European real estate returns that vary by sector and country during financial crises.
190 sharesSource ↗
The article highlights challenges in India's asset securitization practice due to unclear taxation regulations.
159 sharesSource ↗
The study shows that collective investment trusts in 401k plans are favored over mutual funds for their lower fees and cost sensitivity.
154 sharesSource ↗
The paper explores how mutual fund managers' psychological factors and perceptions influence their investment strategies in response to capital flows.
128 sharesSource ↗
The research finds that coal-dependent municipalities face rising debt and yields due to the hydraulic fracturing boom and declining coal production.
123 sharesSource ↗
The study illustrates how the COVID-19 pandemic changed investor behavior in Malaysian government bonds, linking them more closely with gold prices.
64 sharesSource ↗
The paper concludes that greater gender diversity in firms enhances risk management, leading to better handling of uncertainties and costs.
61 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
A machine learning model evaluates how different assets affect declines in the Pakistan Stock Exchange and suggests a smart investment strategy.
10 sharesSource ↗
The growth of algorithmic trading and passive investing makes it harder for emerging market investors during tough times, leading to the creation of a new Automated Adaptive Trading System for better portfolio protection.
9 sharesSource ↗
A risk parity approach enhances portfolio performance and lowers losses during market volatility by effectively managing extreme returns and changing correlations, without complex simulations.
9 sharesSource ↗
Research indicates that trading strategies based on the Sharpe Ratio outperform a simple buy-and-hold method globally, reinforcing the Adaptive Market Hypothesis by revealing market inefficiencies.
8 sharesSource ↗
Disagreement in macroeconomic expectations affects financial risk and stock market returns, especially for small-cap and low-profit stocks.
5 sharesSource ↗
The study presents optimal strategies for managing pension plans using stochastic control for investment and benefit distribution over different timeframes.
5 sharesSource ↗
A new method, Window Data Envelopment Analysis, evaluates efficiency over time, improving assessments of trading strategies and utility companies.
5 sharesSource ↗
American puts generally have less negative raw returns but worse delta-hedged returns than European puts, with early exercise impacting option profitability.
4 sharesSource ↗
The paper highlights the need for sustainable return measures in long-term investments, noting how return sequence risk and cash flow reinvestment influence outcomes.
4 sharesSource ↗
A study shows that GPT-4 is better than RavenPack at predicting stock return volatility based on news sentiment from 2019 to 2023.
6 sharesSource ↗
JPlus is a gamified app that helps collect emotional speech data, and users find it motivates them and values social interactions.
4 sharesSource ↗
Research indicates that companies facing more competition are likely to use zero-leverage strategies, especially when their earnings are more volatile.
4 sharesSource ↗
A new machine learning method for unsupervised classification effectively models complex time series data using financial data from the COVID-19 pandemic.
6 sharesSource ↗
Two innovative deep learning frameworks are proposed to enhance the accuracy of Value at Risk (VaR) and Expected Shortfall (ES) estimates for better financial risk management.
6 sharesSource ↗
The study finds that US house prices significantly impact global housing markets, suggesting the need for careful observation of related economic policies.
5 sharesSource ↗
Research shows that longer maturity treasury bond futures in China better predict stock market volatility, with machine learning outperforming traditional approaches.
5 sharesSource ↗
Classical vs. Transformer Models: The evaluation of models for classifying journal articles indicates that BERT models excel compared to traditional methods, particularly in large datasets, while GPT-3.5-turbo's performance varies by discipline.
4 sharesSource ↗
The study analyzes anti-abortion Twitter communities in Spanish-speaking areas, noting their use of hate speech and structured activism against changing abortion laws.
4 sharesSource ↗
The paper critiques methods for predicting demand for new fashion items, suggesting machine learning can enhance accuracy amid evolving consumer tastes.
4 sharesSource ↗
The study finds that deep learning methods are more effective than traditional approaches for predicting oil prices during crises by better capturing price trends.
4 sharesSource ↗
Machine learning can more accurately predict the VIX, emphasizing the role of jobless claims in market volatility.
12 sharesSource ↗
Traditional machine learning models are more effective than advanced deep learning in predicting stock prices for major Eurozone banks due to data constraints.
7 sharesSource ↗
The Work Need Satisfaction Scale (WNSS) does not fit online gig workers well, indicating a need for modifications to reflect their unique needs.
2 sharesSource ↗
AI techniques can improve resource management in cloud computing, enhancing efficiency and performance in DevOps with predictive analytics.
2 sharesSource ↗
The study examines young informal workers in the EU before the pandemic to understand Covid-19's effects on youth labor market informality.
2 sharesSource ↗
Egovernance boosts citizen participation but faces challenges like technology issues and lack of trust in government.
2 sharesSource ↗
Dark patterns in digital investment platforms take advantage of consumer biases, and the study suggests regulatory measures to reduce these effects.
1 sharesSource ↗
A review of bank performance literature discusses factors affecting it, especially amid ongoing digital transformation since COVID-19.
1 sharesSource ↗
The study finds that AI capabilities improve firm performance and highlights the importance of a data-driven culture for sustainable growth.
1 sharesSource ↗
Analysis of social media shows the need for collaborative communication strategies to tackle climate change and reach net-zero goals.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
10 items
The article introduces equalized odds in survival analysis, using Conditional Mutual Information Augmentation to improve fairness and prediction accuracy in various fields.
5 shares2 citations todaySource ↗
The study compares DeepL and Supertext machine translation systems, finding Supertext excels at translating longer texts while emphasizing the need for context-sensitive evaluations.
4 sharesSource ↗
The paper presents Expected Possession Value (EPV) for football, improving pass value assessments and accurately identifying goal-scoring possibilities.
4 shares2 citations todaySource ↗
The Articulate Anymesh framework converts rigid 3D meshes into articulated objects with Vision-Language Models, enhancing object modeling and robotic manipulation.
3 shares53 citations todaySource ↗
This research introduces a hierarchical Bayesian multitask learning model for binary classification, showing improved performance in microbiome analysis and human health predictions.
3 shares1 citation todaySource ↗
The paper introduces the Risk-Averse Calibration (RAC) algorithm, linking prediction uncertainty to risk-averse decision-making for safer medical diagnoses.
3 shares46 citations todaySource ↗
The Calibrated Preference Optimization (CaPO) method improves text-to-image models by using multiple reward systems for optimization without needing human input.
2 shares44 citations todaySource ↗
DCE-MRI Synthesis with Attention: AAD-DCE is a GAN that creates high-quality Dynamic Contrast-Enhanced MRI images from multimodal inputs, highlighting the role of attention mechanisms.
2 shares2 citations todaySource ↗
Self-Supervised Particle Representation: The Point-based Liquid Argon Masked Autoencoder (PoLAr-MAE) uses self-supervised learning to analyze Liquid Argon Time Projection Chamber data effectively with few labeled examples.
2 shares9 citations todaySource ↗
Stepwise Q-Guided Language Improvement: QLASS proposes a stepwise Q-value estimation for language agents, enhancing guidance during tasks and boosting performance with less annotated data.
2 shares19 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
3 items
Reinforcement Learning with Evolving Rubrics (RLER) enhances the affordable training of deep learning models for lengthy tasks and outperforms current methods.
312 shares
GAM is a framework that improves memory efficiency and task performance through JIT compilation, a lightweight memorizer, and reinforcement learning.
87 shares
LatentMAS boosts collaboration among LLM agents by utilizing latent space representations, enhancing reasoning quality while reducing computational expenses.
55 shares
Repositories the letter featured.
8 items
The article reviews different genetic algorithms and optimization techniques used for solving multi-objective challenges.
2,719 shares
A database client that allows developers to quickly and easily access their data.
986 shares
This paper presents a fast graph database that uses GraphBLAS to improve the efficiency of Knowledge Graphs for large language models (LLMs).
2,170 shares
An article outlining strategies to improve the assessment process for applications of large language models (LLMs).
11,539 shares
A focus on tools and techniques for effective data visualization and access.
306 shares
Episodes on markets, quant methods and economics.
10 items
Niels and Andrew Beer explore changes in wealth management, focusing on new investment diversifiers, the growth of liquid alternatives, and insights on managed futures and cryptocurrencies.
8 shares
FX volatility is anticipated to stay low due to steady US growth, but upcoming policy events could test this stability and create hedging opportunities in early 2026.
6 shares
Current declines in equities and cryptocurrencies lead to discussions on price influence and market behavior, highlighting the importance of reflexivity in investment dynamics.
6 shares
David Dredge shares his expertise on volatility investing and his deep experience in risk management within global markets.
5 shares
JP. Morgan strategists present their 2026 outlook for developed markets, analyzing interest rates, curves, swap spreads, and the overall volatility landscape.
5 shares
Economist Mike Bird explains the role of land as a valuable asset and its unique effects on China's economy, introducing the concept of the land trap.
5 shares
Tech & Trade: Michael Gayed interviews Henry Greene on how recent trade changes between the US and China positively impact China's tech sector, particularly in AI and robotics.
4 shares
Experts James Carrick and Joseph England discuss the upcoming UK Budget and its economic implications in light of tight public finances in a podcast.
4 shares
Geopolitics: Jacob Shapiro's podcast delves into various global issues, including geopolitics, finance, and markets, through in-depth discussions.
3 shares
Rosheen McGuckian highlights Europe's ambitious emissions reduction goals and the investment opportunities emerging from the shift to clean energy, despite existing challenges.
3 shares
Posts from quant and economics blogs and newsletters.
6 items
New research indicates that financial market patterns may persist longer than expected, questioning traditional views on market efficiency.
4 shares
The article examines the relationship between bid-ask bounce and volatility to assess their effects on trading prices.
1 shares
Russell Korgaonkar emphasizes the need for innovative trend-following strategies at Man AHL due to advancements in technology and risk management by 2025.
1 shares
The article explores how political shifts between conservative and liberal ideologies influence long-term stock market trends.
0 shares
Discovering Rushdie: A writer shares their impactful childhood experience with literature, beginning with Salman Rushdie's Midnight’s Children.
0 shares
Discovering Rushdie: The author recounts their teenage exploration of literature and cultural insights inspired by Rushdie's writings in England.
0 shares
Posts from quant researchers on X.
1 items
A new study shows that realistic liquidity constraints make most stock trading anomalies unprofitable, even before factoring in trading costs.
2 shares
Threads from r/quant, r/algotrading and friends.
2 items
7 shares
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