Multi-Curve Interest Rate Models
The research investigates the stability and existence of finite-dimensional realizations in multi-curve interest rate models, using a three-curve Hull-White model for analysis.
6 shares5 citations todaySource ↗
Quant LetterNo. 34
January 2024, Week 4
92 items across 9 sections, as sent to readers on 23 January 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 92
- Papers
- 69
- Sections
- 9
- Issue
- No. 34
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
22 items
Finance9
Generative Modeling for Financial Time Series
The paper introduces new methods for conditional time series generation in financial risk modeling using deep generative methods, and presents a framework to assess the quality of the generated series.
6 shares11 citations todaySource ↗
Stylized Facts and Microstructure
The study analyzes the characteristics of German bond futures, identifying common and unique features across different futures and introducing metrics for evaluating market simulators.
5 shares1 citation todaySource ↗
Default Probability Projections in Stress Testing
The paper highlights the complexities of credit risk stress testing, warning of potential inaccuracies in projected default rates due to inconsistent model parameterization.
4 sharesSource ↗
Continuity of Utilities
The research confirms that a state-dependent function inherits pointwise continuity from the preference ordering, providing a solution to a conjecture and deriving an explicit representation of conditional Chisini means.
4 shares1 citation todaySource ↗
ES Contribution Forecasting
The study introduces a new semiparametric model for predicting dynamic Expected Shortfall contributions, which has shown excellent results in analyzing stock returns.
3 sharesSource ↗
Data-driven Option Prices
A new data-driven option pricing method is suggested, using historical asset prices and deep learning to solve optimization problems, proving effective in numerical tests.
3 shares1 citation todaySource ↗
BioFinBERT: LLMs for Financial Sentiment Analysis
LLMs for Financial Sentiment Analysis: BioFinBERT, a finetuned Large Language Model, is introduced for financial sentiment analysis of biotech press releases and financial texts, which greatly impact biotech stock prices.
3 shares2 citations todaySource ↗
Asset Modelling with Random Coefficients and Switches
A stochastic model is examined that incorporates external influences and uncertainty in the parametrization of stochastic dynamics, using a Markov-modulated approach for regime switching, applied to option pricing in a numerical experiment.
3 shares3 citations todaySource ↗
Economics4
DP: Applications in Econ & Finance
Applications in Econ & Finance: The book is a detailed guide on dynamic programming and its use in economics and finance, aimed at graduate students and researchers.
14 shares3 citations todaySource ↗
Measuring the Capital Network of US Economy
The article examines the US business network structure, proposing a new metric for capital flow concentration based on link distribution.
6 sharesSource ↗
Resolving the Puzzle of Equity Premium in Efficient Markets
The study offers a new solution to the equity premium puzzle, arguing that risk aversion is context-specific, resolving the puzzle in efficient markets.
6 sharesSource ↗
Ranking Emerging Powers for AI Investment in LatAm
The paper ranks Latin American countries on their potential to emerge as AI powers, with Argentina, Colombia, Uruguay, Costa Rica, and Ecuador leading.
5 shares3 citations todaySource ↗
Crypto & Blockchain3
Neural Hawkes: High Dimension Non-Parametric Estimation
High Dimension Non-Parametric Estimation: A new method called the moment-based neural Hawkes estimation method has been developed to analyze the microstructure of cryptocurrency markets, using neural networks to solve partial differential equations.
5 shares6 citations todaySource ↗
Decentralized Matching: Experimental Study Insights
Experimental Study Insights: A study on decentralized two-sided matching markets shows that stable outcomes are common, median stable matchings are most prevalent, and participants' preferences affect their stable partners, with strategic avoidance of blocking pair cycles.
4 sharesSource ↗
Market Responses: Genuine vs Strategic Generosity
Genuine vs Strategic Generosity: Research on NFT charity fundraisers shows that donors who quickly resell their NFTs or have high social exposure face significant market penalties, emphasizing the role of digital visibility and traceability in online philanthropy.
4 shares2 citations todaySource ↗
Historical Trending6
Class Rank's Impact on Academic Performance
Research on Italian students shows that visible class rankings based on exam grades significantly affect students' perceptions and academic performance, regardless of their peers' achievements.
90 sharesSource ↗
MAD Risk Parity Portfolios: Features & Performance
Features & Performance: A study using the Mean Absolute Deviation (MAD) to measure risk in the Risk Parity (RP) model found that RP strategies typically perform between minimum risk and equally weighted strategies.
34 shares23 citations todaySource ↗
Faster xVA Sensitivity Computations
The article highlights the effectiveness of polynomial approximations in reducing computational costs in portfolio valuations, especially in calculating interest rate sensitivities.
29 shares2 citations todaySource ↗
Quantum Groups in Finance
The paper discusses the concept of quantum economics, differentiating it from classical economics, and suggests the potential use of noncommutativity in pricing derivative securities.
29 shares2 citations todaySource ↗
Happiness Econometrics: Value Rounding Behavior
Value Rounding Behavior: The study addresses the issue of response scale simplification in surveys, particularly by less educated respondents, and introduces a model to estimate latent subjective wellbeing.
27 shares27 citations todaySource ↗
Positive News and Motivated Reasoning
The research explores the impact of news valence on belief updating, concluding that people do not overly trust good news over bad news, challenging the idea that beliefs are distorted based on utility.
24 shares2 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
23 items
Quantitative11
Advanced Portfolio Allocation and Asset Management Course
The University of Paris-Saclay offers an advanced asset management course covering portfolio optimization, smart beta factor investing, and the use of machine learning in asset management.
3 sharesSource ↗
Machine Beta: A Fresh Smart Beta Approach
A Fresh Smart Beta Approach: The article presents Machine Beta, a method that uses statistical factors to reduce biases in market capitalization-weighted benchmarks, aiming for lower tracking errors and better performance.
3 sharesSource ↗
Higher-Order Financial Networks in Portfolio Optimization
The study explores the role of high-order financial network structures in shaping financial market conditions and improving portfolio performance, demonstrating their ability to enhance market timing and asset allocation.
2 sharesSource ↗
Guidelines for Double/Debiased ML in Economics
The article discusses the integration of machine learning in economics, focusing on the DoubleDebiased Machine Learning framework and the importance of model generalizability.
4 sharesSource ↗
Non-Affine Stochastic Volatility Models for Index Option Smirk
A new multifactor stochastic volatility model for the Chinese options market surpasses the double Heston model in option pricing performance and correlation structure.
4 sharesSource ↗
Forecasting Bid-Ask Spreads in Foreign Exchange with ML
Machine learning algorithms can effectively predict transaction costs in the foreign exchange market, which can greatly vary based on factors like time of day or week.
3 shares1 citation todaySource ↗
Expected Returns of ML Strategies
Despite high turnover rates and the selection of hard-to-arbitrage stocks, machine learning strategies can predict profitable returns that common risk factors cannot explain, according to a study.
4 shares2 citations todaySource ↗
Overnight Bias in VIX1D Index
A study finds an overnight bias in the VIX1D index, suggesting data filtering and revising the calculation method to improve its reliability for risk assessment in financial markets.
166 sharesSource ↗
Fourier Spot Volatility Estimator
The paper demonstrates the reliability and efficiency of the Fourier spot volatility estimator in handling microstructure noise without data manipulation or bias correction.
2 sharesSource ↗
Pricing & Hedging of Temperature Derivatives with Memory
A new temperature model based on generalized Langevin equations can predict the risk-neutral price dynamics of temperature derivatives, making it useful for hedging against unfavorable weather conditions, a paper suggests.
3 sharesSource ↗
Analytical Approximations for Basket Skew
A paper introduces analytical approximations for the skew and convexity of an option on a basket of assets, which can be used to estimate the basket implied volatility at strikes around the ATM point and sufficiently small volatility or maturity.
2 shares2 citations todaySource ↗
Financial12
Monetary Policy's Impact on Household Portfolios
Research shows that American households invest more in equities and risky assets when interest rates increase, likely to protect against inflation.
153 sharesSource ↗
Short Selling Pressure & Share Repurchases in China
The research analyzes the effect of short selling on share repurchase strategies in China's Ashare market, revealing that short selling pressure influences the repurchase strategy.
3 sharesSource ↗
Volatility Indices for Market Tail Risk Hedging
The Cboe Volatility Index (VIX) and its derivatives are examined as potential market risk indicators and hedging tools, but their correlation with the U.S. stock market has limitations.
2 sharesSource ↗
Risk Factors in Stocks, Bonds, and Options
The research identifies a shared risk factor structure across all major corporate securities, which significantly influences individual asset returns.
2 shares4 citations todaySource ↗
ECB's PEPP Program and Corporate Bond Market Crisis
The study evaluates the effectiveness of the ECB's QE program in mitigating the financial crisis in the European corporate bond market post-COVID-19, finding it reduced credit spreads but didn't improve liquidity.
2 sharesSource ↗
Decoding Ethereum's Volatility Dynamics
The research focuses on cryptocurrency volatility, particularly Ethereum, revealing that scalability factors and wealth distribution significantly affect volatility persistence and the stability-enhancing impact of Ethereum’s Merge upgrade.
2 sharesSource ↗
Credit Factor Investing Challenges
The article suggests that factor investing in corporate bonds can be successful despite challenges like nontradable assets and high transaction costs, with realistic expectations and avoidance of common mistakes.
828 sharesSource ↗
Volatility Estimation and Leverage Effect
The paper introduces nonparametric estimators for volatility and leverage effect, using high-frequency observations of short-dated options, with the rate of convergence depending on the latent volatility process and observation error.
2 sharesSource ↗
USD Bonds: Exchange Rate Risk and Foreign Discount
Exchange Rate Risk and Foreign Discount: The research explores the impact of differential exchange rate risk on pricing disparities in U.S. dollar bonds, emphasizing the significant role of exchange rate risk in bond pricing and its transmission mechanisms.
195 sharesSource ↗
Currency Hedging's Impact on Equity Fund Performance
The study examines the effect of currency hedging on the alphas and fund flows of currency-hedged equity funds, introducing a currency hedging return factor to account for hedging activities in factor models.
2 sharesSource ↗
Enhancing Fund Performance with Common Holdings
The article states that equities mutual funds investing in common stocks and following past peer trades can match the performance of their same-benchmark peers, generating higher average returns and lower volatility.
2 sharesSource ↗
Credit Rating Agencies & Options Market
A study reveals that credit rating agencies' predictive abilities improve with increased options trading volume, leading to more accurate credit risk assessments.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
19 items
Finance4
Comparing Factor Models for Portfolio Allocation
The article compares the performance of the Hou-Xue-Zhang four-factor model and the Fama-French five-factor model in investment scenarios, with the former slightly outperforming unless certain factors are considered.
12 sharesSource ↗
Macroeconomic Factors and Financing Strategies in Working Capital
A study reveals a complex relationship between working capital finance and firm performance, influenced by macroeconomic indicators, which became linear and negative during the 2008-2010 financial crisis.
11 sharesSource ↗
Mean-Variance Optimization with Affine GARCH
The article discusses the expanded use of Affine GARCH models in portfolio optimization to accommodate various objective functions, with a GARCH model performing better than a homoscedastic variant in terms of the efficient frontier.
11 sharesSource ↗
Estimating Dynamic Covariance Matrices
The piece explores recent advancements in estimating large dynamic covariance matrices that evolve over time, with a focus on non- and semi-parametric models and estimation methods.
12 sharesSource ↗
Statistical4
Pseudo-Out-of-Sample Information for Forecasting Stock Volatility
A new method using technical indicators for predicting volatility in the Chinese stock market outperforms existing models.
14 sharesSource ↗
Implied Volatility and Return Relationship
The research applies the VIX method to individual equity options data, discovering a negative correlation between equity return and volatility, indicating behavioral biases over leverage and volatility-feedback effects.
29 sharesSource ↗
Calibration of Stochastic Volatility Model
The research calibrates a partially specified stochastic volatility model using the Heston model's priors, and uses this model to predict future trends for synthetic and S&P500 data.
15 sharesSource ↗
Tech Indicators & Implied Volatility Index
The article discusses how technical indicators based on underlying assets can enhance the accuracy of forecasting errors in implied volatility indexes, improving Value at Risks estimation.
13 sharesSource ↗
Machine Learning6
Media Hype and Fake News Impact on Commodity Prices
The study shows that media hype and fake news greatly influence commodity prices, especially during COVID-19. It also found that bi-directional long-short-term memory is useful in predicting these impacts.
10 sharesSource ↗
ML Models' Predictability of Commodity Futures Returns
Light gradient-boosting machine learning models outperform linear models in predicting future returns in 22 commodities.
15 sharesSource ↗
Cryptocurrency Market Analysis with ML
A study successfully used machine learning to predict Bitcoin to US dollar exchange rates with 78% accuracy.
25 sharesSource ↗
Incorporating ESG Ratings for Profitable Investments
Companies with high environmental, social, and corporate governance scores are financially more successful, with machine learning predicting a 14% higher return on equity.
17 sharesSource ↗
ML for Identifying Politically Connected Firms
Machine learning can identify over 85% of politically connected firms using public financial and industry data, aiding in conflict of interest detection.
14 sharesSource ↗
PP Lending Platform Failure Prediction in China
Machine learning is used in a study to accurately predict the failure of P2P lending platforms in China by identifying key variables.
13 sharesSource ↗
Historical Trending5
ML for Financial Risk Measurement
A new sequential learning algorithm based on Kalman filtering has proven to be more effective than traditional methods in measuring financial market risk.
31 sharesSource ↗
Credit Growth and Yield Curve Predict Crises
Machine learning models using historical macrofinancial data have been more successful than logistic regression in predicting financial crises.
25 sharesSource ↗
Fractal Analysis for Portfolio Optimization
The use of a Hurst exponent index in portfolio optimization at the Damascus Securities Exchange led to portfolios that exceeded market performance.
23 sharesSource ↗
New ESG Rating Drivers in European Stocks
Short-term ESG momentum significantly affects stock returns and reduces anticipated capital costs, suggesting it could be a new systematic risk factor.
17 sharesSource ↗
Chaos Theory in Economics
The article discusses the growth of chaos mathematics, its applications in fields like topology and Catastrophe Theory, and the potential of Quantum Algorithms and AI to improve predictions in chaotic systems, especially in economics.
15 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
5 items
Recently Published5
Streamlining Large Language Models
The article presents 26 principles to enhance querying and prompting in large language models, backed by experimental results.
1,480 shares145 citations todaySource ↗
Ensemble Learning with Hui-Walter Paradigm
The research applies the Hui-Walter paradigm from epidemiology to machine learning, enabling accurate model evaluation under dynamic and uncertain data conditions without requiring labeled data.
20 sharesSource ↗
LLMs for Document Summary Evaluation
The paper presents Extract-then-Evaluate, a method that selects key sentences from lengthy documents for evaluation in Large Language Models, enhancing efficiency and alignment with human assessments.
29 shares51 citations todaySource ↗
Simplifying Topology Extension in Federated Learning
Flame is a novel system for distributed machine learning that provides flexibility in setting up federated learning applications, separates application logic from deployment specifics, and supports various topologies and mechanisms.
19 shares13 citations todaySource ↗
DiarizationLM: Speaker Diarization Post-Processing
Speaker Diarization Post-Processing: DiarizationLM is a framework that employs large language models to refine speaker diarization system outputs, enhancing transcript readability and reducing word diarization error rate without the need for retraining.
19 shares34 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
3 items
InfoBatch: Dynamic Data Pruning for Faster Training
Dynamic Data Pruning for Faster Training: The article introduces textbfInfoBatch, a new framework designed to speed up training without data loss through dynamic data pruning.
185 shares
Efficient Programming w/ SGLang
The article presents SGLang, a new programming language tailored for efficient programming of LLMs, integrating common LLM programming patterns.
708 shares
Bag of Tricks for LongTailed Visual Recog
The article emphasizes recent advancements in visual recognition dealing with long-tailed distributions with imbalanced frequencies, primarily using intricate paradigms such as meta-learning.
329 shares
GitHub
Repositories the letter featured.
5 items
Finance5
Systematic Trading Resources
The article compiles a variety of resources for systematic trading, including libraries, strategies, and tutorials.
2,447 shares
Easy Data Processing with Datatrove
The article proposes a solution for efficient data processing through customizable, platform-independent pipeline processing blocks.
593 shares
Embeddings for Numerical Features in Deep Learning
The article reports on the NeurIPS 2022 conference's discussion about using embeddings for numerical features in tabular deep learning.
221 shares
Scratch Conformal Predictions
Various Conformal Prediction techniques have been replicated in pure NumPy for educational use.
135 shares
GPTs Leak: Message Limit Bypass
Message Limit Bypass: Leaked GPTs enable users to circumvent the 25 message restriction or utilize GPTs without needing a Plus subscription.
1,038 shares
Blogs
Posts from quant and economics blogs and newsletters.
3 items
Quantitative3
Geopolitics in Election Year
The article credits the success of AI algorithms to dimension expansions, emphasizing the need to consider this factor and use matrix multiplication for dimension expansion.
0 shares
HDF C: Crowded Growth Story
Crowded Growth Story: The article explores the role of dimension expansion in AI algorithms, providing a brief overview of PCA and concluding with the significance of dimension expansion.
0 shares
Matrix Multiplication: AI Algorithms and Dimension Expansion
AI Algorithms and Dimension Expansion: The article offers an in-depth understanding of dimension expansion in AI algorithms, explaining basic algebra through code and citing the rationale behind the necessity of dimension expansion.
0 shares
Videos
Talks, lectures and tutorials.
4 items
Quantitative4
AIFI Winter Bootcamp 2024: AI Models in Finance -> AI Models in Finance Bootcamp 2024
AI Models in Finance -> AI Models in Finance Bootcamp 2024: The bootcamp provides training on using Artificial Intelligence in finance, including theory, practical application, and AI python code.
0 shares
Family Offices: The Downfall of Quant Careers -> Quant Careers: The Downfall of Family Offices
The Downfall of Quant Careers -> Quant Careers: The Downfall of Family Offices: The article explores the advantages and disadvantages of working for a small firm, specifically a family office.
26 shares
RAW Workshop on AI in Finance 4: Screen Recording -> AI in Finance 4 Workshop: Screen Recording
Screen Recording -> AI in Finance 4 Workshop: Screen Recording: The article is a raw, unedited recording from an AI in Finance workshop at Texas State University San Marcos.
4 shares
Annotating OCaml Variables and Returns: Locals with local -> OCaml Variables and Returns: Annotating Locals
Locals with local -> OCaml Variables and Returns: Annotating Locals: The second video in a series on OCamls locals teaches how to annotate variables and return types with local.
4 shares
X / Twitter
Posts from quant researchers on X.
8 items
Quantitative4
Factor Timing with ML: Predictors & Regularization
Predictors & Regularization: The article explores how machine learning can be used in factor timing, focusing on tail risk leverage profitability, momentum, and the impact of economic restrictions.
5 shares
Marvin 2.0: Python Competitor for Langchain
Python Competitor for Langchain: Marvin 2.0, a Python competitor to Langchain, has been launched with features like structured data handling and synthetic data generation.
2 shares
Simple ML Framework for Finance
The piece presents a new machine learning framework tailored for the financial sector.
1 shares
Short-Term Factor Momentum in Commodity Markets
Jiang et al.'s research reveals short-term factor momentum in commodity markets, indicating possibilities for timing commodity factors.
1 shares
Miscellaneous4
Longshort portfolios and political risk premiums
The article highlights the high risk premium associated with portfolios influenced by political risk across different countries and asset types.
1 shares
Generative AI products and investment app stacks
The piece explores the potential for revenue generation from Generative AI products and the chance to reinvent investment app stacks.
1 shares
Introduction to Quantum Computing
The article offers a basic understanding of Quantum Computing, with a focus on Qubits, Superposition, and Entanglement.
0 shares
XAgent: An Autonomous LLM Agent for Complex Task Solving
An Autonomous LLM Agent for Complex Task Solving: The article introduces XAgent, an autonomous LLM agent for solving complex tasks, and mentions that its Python code is accessible on GitHub.
0 shares