Quant Letter: July 2024, Week-3

Weekly (54th Edition)

SSRN

Recently Published

Quantitative

Missing Data Bias in Fund Portfolio Data: The paper warns of bias in commercial databases due to nonrandom portfolio reporting, which can lead to skewed conclusions in fund literature. (2024-07-17, shares: 2.0)

Market Liquidity Determinants: The study applies machine learning to identify factors affecting equity market liquidity, uncovering complex relationships between market liquidity and placement characteristics. (2024-07-15, shares: 3.0)

Statistically Valid Backtesting Framework: The article emphasizes the need for a more accurate backtesting framework for financial institutions, pointing out flaws in current methods. (2024-07-13, shares: 5.0)

Decentralised Finance and Market Making: The study develops optimal strategies for large order traders and statistical arbitrages in automated market makers with concentrated liquidity. (2024-07-12, shares: 2.0)

Python Trading Strategies: The author appreciates Kakushadze and Serur for their 151 trading strategies and shares a Python version of these strategies on Github. (2024-07-13, shares: 8.0)

Financial

Estimating Mean Reversions in Interest Rates: The article introduces a new method for calculating the rate at which interest rates return to their average in multifactor HJM models, important for pricing derivatives. (2024-07-17, shares: 6.0)

Impact of SEC Regulations on Cryptocurrency: The research examines the negative market effects and informed trading prior to the announcement of the U.S. SEC's classification of cryptocurrencies as securities. (2024-07-17, shares: 5.0)

Geometric Insights on Portfolio Construction: The article argues that the equally weighted portfolio is usually less preferable than the mean-variance portfolio, based on the influence of the covariance matrix's condition number on the αweight angle in portfolio optimizations. (2024-07-15, shares: 3.0)

Semivolatility portfolios: The article proposes the use of semi-volatility-managed portfolios to enhance the performance of momentum portfolios by controlling skewness and downside volatility. (2024-07-11, shares: 2.0)

Dual Dominance: The article explores the relationship between the Markowitz mean-variance model and the Ziemba capital growth model, offering insights into model-based portfolio construction. (2024-07-14, shares: 2.0)

CNN2D-MV Stock Model: The article introduces a hybrid model that combines a 2D convolutional neural network with the mean-variance model to improve asset selection and portfolio performance. (2024-07-15, shares: 2.0)

Smarter Beta Investing: The article suggests integrating sustainable factors into traditional investing methods without affecting financial performance or diversification, and offers ways to correct sustainable bias in traditional long-short MSCI style factor portfolios. (2024-07-14, shares: 2.0)

Recently Updated

Quantitative

APT and Arbitrage: The Arbitrage Pricing Theory (APT) enables potential arbitrage opportunities due to the absence of a positive pricing function requirement. (2024-07-08, shares: 3.0)

Multi-Agent Stock Simulation: A new multi-agent distributed stock exchange simulation environment (DSXE) has been developed to model global financial markets, enabling large-scale simulations and successful fragmented market modeling. (2024-05-09, shares: 2.0)

Humanising Portfolio Selection: The paper proposes a unified approach to active portfolio selection, demonstrating how investor subjectivity can improve portfolio performance. (2024-07-08, shares: 2.0)

Insider Ownership in Japan: A study reveals that insider ownership significantly increases default risk in Japanese firms, based on data from 2004-2019. (2024-07-01, shares: 2.0)

Debt and Trade: Global View: The study reveals that multinational corporations often raise debt capital outside their home country to hedge against exchange rate fluctuations and align with their supply chain markets, in addition to accessing deeper financial markets. (2024-07-07, shares: 2.0)

ArXiv

Finance

Nash Equilibrium in Broker-Trader Interactions: The research investigates the trading strategies equilibrium between a broker and her clients using a system of stochastic differential equations. (2024-07-15, shares: 6)

Financial Network Shock Propagation: The study introduces a new way to predict the impact of shocks on a network node, using a vector autoregressive model in the context of the electronic Interbank Deposit Market. (2024-07-12, shares: 5)

MeanVariance Optimization for Life Insurance Contracts: The study provides formulas for optimal wealth and strategy for equity holders in life insurance contracts, suggesting increased risky investments during poor economic conditions. (2024-07-16, shares: 4)

SelfOrganized Criticality in Economics & Finance: The article proposes Self-Organised Criticality as a reason for extreme volatility in financial markets and large business cycle fluctuations, calling for specific policy considerations. (2024-07-14, shares: 3)

Telecom Breakups: Market Capitalization Impact: The study measures market power by analyzing the decrease in market capitalization after a monopoly breakup, highlighting significant value drops for AT&T and AMX. (2024-07-12, shares: 3)

Crypto & Blockchain

Stablecoin Transparency and Market Impact: The study shows that in times of market instability, the transparency of the USDC cryptocurrency leads to quick market responses, while the lack of transparency of USDT acts as a buffer against immediate effects. This suggests that investors may seek safety in less transparent cryptocurrencies during turbulent times. (2024-07-16, shares: 4)

ArXiv ML

Recently Published

Anomaly Detection with LLMs: The paper introduces a two-stage reasoning framework for identifying and mitigating out-of-distribution failure modes in robotic systems using large language models, comprising a quick binary anomaly classifier and a slower fallback selection stage. (2024-07-11, shares: 17)

Topological Bounds for Algorithms: The research proposes a new set of topology-based complexity notions that correlate with the generalization gap in deep neural networks, offering a computationally efficient way to predict generalization without test data, and surpassing existing topological bounds across various datasets and models. (2024-07-11, shares: 15)

Spider2-V: Data Science Automation: Spider2-V is a benchmark introduced to assess the performance of multimodal agents in automating data science and engineering workflows, showing that current models have difficulties in fully automating these workflows. (2024-07-15, shares: 11)

RePec

Finance

Financial Disinformation Detection: A machine learning system has been created to identify financial misinformation on social media, offering significant theoretical and practical benefits. (2022-03-18, shares: 32.0)

Transnational Bid-Rigging Detection: Machine learning and statistical screening can accurately detect bid-rigging cartels, but their effectiveness decreases when used on data from different countries due to institutional variations. (2022-12-01, shares: 24.0)

Anomalies and Return Predictability: The study shows that portfolio returns based on long-short anomaly can predict overall market returns, due to asymmetric limits of arbitrage and overpricing correction persistence. (2022-08-09, shares: 116.0)

Factor Timing in China: The paper proposes a deep learning strategy using 146 factors, which is effective and robust in the unique structure of the Chinese stock market. (2023-01-27, shares: 52.0)

Forecasting Chinese Macroeconomy: The research finds that mixed-frequency factor models are better at forecasting the Chinese macroeconomy than traditional models, except during the Global Financial Crisis. (2023-02-10, shares: 10.0)

GitHub

Finance

Online Machine Learning Python: The piece provides a tutorial on implementing online machine learning using the Python programming language. (2019-01-24, shares: 4884.0)

Investment Research: The article discusses how to make investment research available to everyone, irrespective of their geographical location. (2020-12-20, shares: 26626.0)

Rust Machine Learning: The article introduces a new machine learning framework developed using the Rust programming language. (2018-04-05, shares: 3552.0)

HighPerformance Trading: The piece showcases a high-performance trading library, developed in Mojo and C, designed to simplify quantitative trading. (2023-12-07, shares: 33.0)

Trending

CrewAI: Collaborative AI for Autonomous Agents: CrewAI offers a system for AI agents to work together autonomously in role-playing situations. (2023-10-27, shares: 17180.0)

PyroPPL: Deep Probabilistic Programming: The article explores the combination of Python and PyTorch in advanced probabilistic programming. (2017-06-16, shares: 8440.0)

ModelScope: Model as a Service: ModelScope is working towards realizing the idea of ModelasaService. (2022-07-25, shares: 6510.0)

LinkedIn

Trending

DataDriven Options Pricing: The article reviews a research paper by Oxford University scholars on data-driven option pricing. (2024-07-11, shares: 4.0)

Schrodinger Bridges Plenary Talk: The author shares their experience of presenting a talk on Schrodinger Bridges and Random Matrices at the 12th Bachelier World Congress. (2024-07-13, shares: 6.0)

Optimal Trading Strategies: The article explores Grinold and Khan's continuous-time model for determining the optimal fractional holding of a stock. (2024-07-15, shares: 2.0)

Reducing Hallucination in Financial Reports: The author's research on minimizing hallucination in financial report information extraction using Large Language Models is highlighted in the ACM Kudos bulletin. (2024-07-13, shares: 4.0)

Informative

Growth vs Value Stocks: Avoid Short-Term Narratives: Recent data contradicts the belief that lower rates favor growth stocks and higher rates favor value stocks, suggesting investors should not solely rely on this theory. (2024-07-12, shares: 3.0)

High Frequency Trading Research on eFinancialCareers: A study on high-frequency trading by an Imperial College London alumnus and his professor has been highlighted in an eFinancialCareers article. (2024-07-11, shares: 3.0)

Option Trading Strategy with Implied Skew: Lorenzo Ravagli from J.P. Morgan shares his research on developing an option trading strategy based on implied skew in a Quantcast episode. (2024-07-12, shares: 4.0)

Time Series Transformers for Prediction: The Bank of America Quant Speaker Series will discuss Time Series Transformers and LLM agents for enhancing financial time series prediction. (2024-07-13, shares: 3.0)

News

Quantitative

AI Fund Launch: Astant Global Management, a London-based investment manager, is set to launch a new AI-based quantitative hedge fund strategy later this year. (2024-07-15, shares: 6)

Quant Funds: FinTech: Don Silva's article on Medium explores the convergence of finance and technology in Quant Funds. (2024-07-12, shares: 4)

Quant Finance Compensation: Quantitative roles can provide similar salaries to those in quantitative research. (2024-07-16, shares: 4)

DTCC FICC VaR Calculator: The Depository Trust & Clearing Corporation has launched a public Value at Risk calculator to assist market participants in evaluating potential margin and clearing fund obligations. (2024-07-12, shares: 2)

Twitter

Quantitative

Practical Uses of Derivatives: Fabozzi's research illustrates the practical applications of derivatives in areas like asset allocation and liquidity management. (2024-07-17, shares: 7)

Valuation and Hedging Cryptocurrency Options: Lucic's paper delves into the practical aspects of valuation hedging and systematic deltahedged strategies in cryptocurrency options. (2024-07-12, shares: 7)

Statistical Arbitrage with Oil Futures: Fanelli's research presents a statistical arbitrage portfolio involving different oil futures, demonstrating significant performance after costs. (2024-07-13, shares: 5)

Quantile Regression for Factor Modeling: A study on Quantile Regression and Equity Factor Modeling explores the application of the 3 and 5 Factor model in Taiwan's stock market. (2024-07-13, shares: 3)

Liquid Alternative Strategies: ManGroup's report suggests that liquid alternative strategies, such as trend-following and long-short quality stocks, could potentially replace bonds. (2024-07-17, shares: 1)

Miscellaneous

Generative AI Impact on Quant Research: The article explores the effects, difficulties, and potential advancements of using generative AI in quantitative research. (2024-07-11, shares: 1)

Firm Profitability Decomposition: The article reviews a study by Han et al., suggesting that investors frequently undervalue the impact of firm-specific factors on profitability, leading to substantial returns. (2024-07-15, shares: 0)

Investors' Beliefs on Efficient Markets Survey: The article discloses a survey indicating that most investors think a company's future returns are affected by outdated news about its future profits. (2024-07-15, shares: 0)

Market Timing Strategy Outperforms Markov-Switching Models: Article 2: Research by Shu and team shows that a market timing strategy using a statistical jump model is more effective than Markov-switching models, leading to better Sharpe ratios and reduced turnover. (2024-07-14, shares: 0)

Incorporating Text Sentiment into Backtesting: Article 3: QuantRocket discusses how to integrate text sentiment into your backtesting process in a recent article. (2024-07-11, shares: 0)

Exotic Markets: Russell Korgaonkar discusses Man AHL's investment in unusual markets, highlighting potential benefits for investors and predicting future trends. (2024-07-11, shares: 2)