Quant Letter: February 2024, Week-2
Quant Letter: February 2024, Week-2
Weekly (34th Edition)
ArXiv
Finance
Autoencoder Trading Strategies: The research shows that using Autoencoder architectures in Statistical Arbitrage simplifies strategy development and improves returns compared to traditional methods. (2024-02-13, shares: 4)
Closed-Form AMM Arbitrage Solutions: The article introduces a new mechanism for identifying arbitrage trades on automated markets, providing better opportunities and quicker capitalization than previous methods, and enabling on-chain arbitrage bots for multi-asset pools. (2024-02-09, shares: 4)
Causal Network Contagion VaR for Risk Management: The paper presents the Causal-NECOVaR, a new method for financial risk analysis that provides reliable risk predictions regardless of market shocks and systemic changes. (2024-02-08, shares: 4)
Monotone Control Integration for Option Pricing: The study introduces a new solution to the Hamilton-Jacobi-Bellman equation in option pricing, proving its stability, consistency, and effectiveness against traditional methods. (2024-02-09, shares: 2)
Statistical Arbitrages: A Optimization Approach: A new technique is suggested for identifying statistical arbitrages, not limited to traditional pairs, through a portfolio optimization problem solvable by the convex-concave procedure. (2024-02-12, shares: 4)
Portfolio Optimization with Costs and Preferences: The Merton investment-consumption problem is expanded to incorporate transaction costs and stochastic differential utility, using new math techniques to understand all parameter combinations and previously difficult aspects. (2024-02-13, shares: 4)
Multivariate CRPS Learning: A new method for merging multivariate probabilistic forecasts, considering dependencies between quantiles and marginals, has shown significant improvements in predicting day-ahead electricity prices. (2023-03-17, shares: 17)
Crypto & Blockchain
Liquidity Provision in Crypto Markets: A study reveals that the liquidity provision premium in cryptocurrency markets can be predicted using factors like the VIX index and Tether liquidity, and is influenced by stock market premiums globally. (2022-03-21, shares: 394.0)
Bundling Broadband for K-12 Schools: Cost Savings & Improved Speed: A study revealed that New Jersey K-12 schools experienced a decrease in broadband internet prices by a third and a sixfold increase in speed when they switched to a bundled procurement system in 2014. The schools also saved an amount equivalent to their total federal E-rate subsidy, resulting in significant welfare gains. (2024-02-11, shares: 2)
Fragmentation & Liquidity on DEX: Research indicates that high-fee trading pools on Uniswap attract more liquidity providers but have lower trading volumes, suggesting that fragmented liquidity boosts market participation and competition. (2022-11-17, shares: 648.0)
Emoji Sentiments in Crypto Markets: Research using GPT4 and a BERT model shows that Twitter emoji sentiment can predict cryptocurrency market trends and help avoid major downturns. (2024-02-11, shares: 4.0)
Salience Theory and Crypto Returns: The Salience theory, based on returns and trading volume, has a negative predictive power for forecasting return trends in the cryptocurrency market, with trading volume being a key factor. (2024-02-09, shares: 3.0)
ArXiv ML
Recently Published
Scaling Laws for Mixture of Experts: The research introduces a new hyperparameter, granularity, to Mixture of Experts models, improving training optimization and outperforming dense Transformers. (2024-02-12, shares: 120)
WebLINX: Website Navigation: The study presents WEBLINX, a benchmark for conversational web navigation, and a model that ranks relevant HTML elements, emphasizing the need for large multimodal models. (2024-02-08, shares: 71)
SSRN
Recently Published
Quantitative
Asset Embeddings: The paper suggests that investors' holdings data, when analyzed with artificial intelligence and machine learning, can reveal significant company traits. (2023-07-20, shares: 2.0)
WTI Futures Market View-Taking: Commercial positions in WTI futures often fail, with financial commercials outperforming supply chain ones. (2024-02-13, shares: 6.0)
Low Turnover Portfolio vs. 50/50 Strategy: A low turnover portfolio, slowly readjusted to fixed weights, performs better than the standard equities/bonds portfolio and is a viable alternative to a simple momentum or value portfolio. (2024-02-12, shares: 2.0)
Financial
Credit Options and Economic Fluctuations: Options on the CDX index can predict short-term economic downturns by indicating changes in credit risk premia and shifts in credit market conditions. (2024-02-09, shares: 3.0)
Interest Rate Differential and Currency Returns: The study reveals that the prospective interest rate differential is a better predictor of currency excess returns than carry, explaining returns of various currency portfolios. (2024-02-09, shares: 3.0)
Treasury Market Depth Measurement: The study indicates that the market depth of U.S. Treasury securities, a key liquidity measure, remains largely consistent despite different measurement decisions in depth calculations. (2024-02-12, shares: 2.0)
Factor and Stock Return Optimization: A new asset pricing factor, created using optimal portfolio weights to maximize the Sharpe ratio, can explain the cross-section of stock and bond returns, even when accounting for popular factors. (2024-02-09, shares: 2.0)
Recently Updated
Quantitative
Forecasting US Single Family House Prices with GMDH: The article discusses the use of a machine learning technique, the group method of data handling (GMDH), for predicting house price index (HPI), leading to more accurate housing market forecasts. (2023-06-14, shares: 2.0)
Polynomial Factor Models: Nonlinear Relationships: Polynomial Factor Models (PFM) provide a novel method for handling high-dimensional panel data, allowing for the consistent estimation of factor interactions and loadings by capturing nonlinear relationships. (2023-01-31, shares: 2.0)
Reinforcement Learning for Optimal Execution: A new actor-critic reinforcement learning algorithm is introduced for optimal execution problem, featuring a recalibration step for convergence and showing linear convergence under appropriate conditions. (2023-03-10, shares: 372.0)
Market Model Calibration with Neural Network: Faster Efficiency: Machine learning can streamline the calibration of market models, reducing computational time and increasing practicality, with a new approach allowing model parameters to evolve as a stochastic process for a robust training set. (2024-01-05, shares: 2.0)
Inflation and Directional Volatility Ratio: The article presents a new method called the directional volatility ratio for predicting inflation trends, which is more effective than traditional methods. (2023-10-14, shares: 2.0)
Testing q-theory under Endogenous Truncation: Bias Correction: A new methodology corrects bias in empirical investment studies that rely on truncated samples of publicly listed firms, supporting the q-theory and showing that investment-cash flow sensitivity disappears and the relation between investment and q increases fourfold. (2022-07-26, shares: 2.0)
Financial
Assaying Anomalies in Equity Returns: A new protocol and web application are proposed for testing potential predictors of equity returns, providing thorough analysis and identifying common problems in testing equity strategies. (2023-01-26, shares: 970.0)
HFT & Option Market Liquidity: A study finds that increased aggressive high-frequency trading in equity markets results in wider bid-ask spreads in the options market due to sniping risk and informed trading. (2021-02-18, shares: 2.0)
Algorithmic Trading & CEO Turnover: Algorithmic trading leads to directors relying less on stock returns for CEO turnover decisions, instead focusing more on nonmarket measures. (2022-09-13, shares: 2.0)
Behavioral Influences on Contrarian Retail Trading: Retail investors' selling behavior, influenced by unrealized capital gains, impacts short-term return reversals and volatility among certain stocks. (2022-07-25, shares: 2.0)
Institutional Investors & Tiny Retail Trades: Institutional investors delay sales and accumulate stakes in response to expected small retail trades, leading to delayed price discovery. (2024-01-15, shares: 3.0)
RePec
Finance
Trading Behavior of Individual Investors in Mutual Funds: A study found that individual investors in mutual funds are momentum buyers and contrarian sellers, with older and larger transaction size investors more likely to be momentum buyers. (2024-02-14, shares: 14.0)
Trading Responses to Credit Rating Announcements: Investors respond differently to changes in credit ratings, selling during downgrades by investor-paid agencies and buying during upgrades by issuer-paid agencies. (2024-02-14, shares: 11.0)
Opening Price Gaps and Information Adjustments in Stocks: AI and big data research shows negative gap openings are more frequent than positive ones, and price adjustments for bad news are faster than for good news. (2024-02-14, shares: 11.0)
Machine Learning
Accounting for Spatial Autocorrelation in Hedonic Models: The study proposes a spatial cross-validation strategy to correct bias in tree-based algorithms caused by spatial autocorrelation in real estate data, improving accuracy in mass appraisal and investment decisions. (2024-02-14, shares: 23.0)
Improved Prediction of Global Gold Prices with Hurst-Reconfiguration: The paper introduces a hybrid forecasting model for gold prices, combining Hurst-oriented reconfiguration and machine learning, outperforming traditional models in prediction errors and accuracy. (2024-02-14, shares: 16.0)
Active Learning for Stacking and AdaBoost Models: The research shows that active learning within ensemble learning can achieve similar predictive performance with fewer selected instances compared to using full data. (2024-02-14, shares: 11.0)
Machine Learning Simplifies Finance in Real Time: The article introduces a new deep learning algorithm designed to solve complex financial models. This algorithm provides fresh economic insights and lowers computational costs. (2024-02-14, shares: 11.0)
Historical Trending
Uncertainty & Exchange Rate Volatility: The research indicates that exchange rate volatility is increased by economic policy and global financial market uncertainty, but reduced by US monetary policy uncertainty. (2023-07-28, shares: 29.0)
Adaptive Online Portfolio Selection with Transaction Costs: The research proposes a new algorithm for online portfolio selection that improves return prediction accuracy by considering peer impact. (2023-02-06, shares: 23.0)
Decomposing Downside Investment Risk: Centred Expected Shortfall: The article recommends using Centred Expected Shortfall as a risk measure in asset management for a more accurate portfolio risk breakdown. (2023-08-18, shares: 22.0)
Asset Diversification in High Volatility Markets: The article suggests optimizing the risk-return ratio of an investment portfolio by adjusting investment proportions for each asset based on the economic activity cycle. (2023-05-06, shares: 21.0)
GitHub
Finance
Orion: Signal Anomaly Detection: The piece introduces a machine learning library designed to detect anomalies in signals. (2018-07-24, shares: 924.0)
TradingTechnicalIndicators: Trading Indicators Library: The article discusses a Python library used for implementing trading technical indicators. (2020-09-27, shares: 98.0)
Probatus: Classifier and Data Validation: The piece focuses on the validation of data classifiers and the data used in their creation. (2020-11-09, shares: 114.0)
TimeLLM: Large Language Model Forecasting: The article details the official implementation of TimeLLM for time series forecasting, as presented at ICLR 2024. (2024-01-20, shares: 170.0)
Trending
LLMs: Low Latency JSON Generation: The article explains the process of creating JSON with minimal delay using Large Language Models. (2023-11-15, shares: 256.0)
pkl: Config as Code Language with Validation and Tooling: The article presents a new coding language for configuration that provides comprehensive validation and advanced tooling capabilities. (2024-01-19, shares: 6653.0)
tfcausalimpact: Python Causal Impact Implementation: The article showcases a Python version of Causal Impact, inspired by Google's R package, utilizing TensorFlow Probability. (2020-08-17, shares: 534.0)
LinkedIn
Trending
Introducing Mamba-Chat: Advanced language model: Haven has launched Mamba-Chat, a language model that efficiently handles large and complex datasets, accessible via a browser or API. (2024-02-14, shares: 2.0)
Professor Sudheer Chava's Quantitative Finance Accomplishments: The article celebrates Sudheer Chava, a renowned quantitative expert with over 50 research papers, who will be a part of the Fordham Gabelli School of Business MSQF Quant Conference 2024. (2024-02-13, shares: 2.0)
Quant Insights Conference: Portfolio Management Innovations: The Quant Insights Conference on 13th March will discuss new developments in portfolio management, offering attendees CPD credits and networking opportunities with industry professionals. (2024-02-13, shares: 1.0)
Quan Strats 2024: Alpha Generation Overview: Quan Strats 2024, scheduled for March 12 in New York, will center on Alpha generation, featuring debates, panels, and presentations, with over 300 investment industry leaders expected to attend. (2024-02-13, shares: 3.0)
Trust and Transparency in Finance with LLMs and SLMs: The collaboration between large and small language models can improve trust and transparency in finance, despite quantitative application challenges. (2024-02-13, shares: 1.0)
CEO Addresses Misunderstandings in the Art and Artifact Industry: NFTrends CEO, Marsha Lipton, discusses the difficulties of digitally tracking art and artifact collections and the misconceptions about blockchain in an interview. (2024-02-13, shares: 3.0)
ChatGPT's Accuracy in Providing Investment Insights from Financial Media: Tommi Johnsen's blog investigates if ChatGPT can analyze financial media information to deliver accurate investment insights. (2024-02-13, shares: 2.0)
Twitter
Quantitative
Low-risk diversification strategies white paper by AQR: Article 1: AQR's white paper indicates that low-risk strategies are less sensitive to macro conditions and volatility than traditional assets and average hedge funds. (2024-02-08, shares: 5)
0 algo trading scripts in GitHub repo: Article 2: A GitHub repository with 150 scripts for quantitative finance, algorithmic trading, and market data analysis is now available. (2024-02-13, shares: 4)
Lasso justification for economic time series data: Article 3: A recent paper explores the appropriate conditions for using Lasso for variable selection in high-dimensional settings in economic time series data. (2024-02-08, shares: 2)
Interesting quant research weekly recap: Article 4: A new weekly summary of notable quantitative research is now published and open for subscription. (2024-02-13, shares: 1)
Retail Option Trading Anatomy: The article delves into the complexities of retail option trading. (2024-02-12, shares: 1)
Longshort Portfolios & Political Risk: The article emphasizes the high risk premium of portfolios based on political risk across different countries and assets. (2024-02-09, shares: 1)
Shelter Inflation Reality Disconnect: The article discusses the discrepancy between current inflation figures and the actual inflation in housing. (2024-02-13, shares: 0)
Forbes' Fintech 50 List 2024: The article introduces the 13 new startups featured in Forbes' Fintech 50 list for 2024. (2024-02-13, shares: 0)
Miscellaneous
Generative AI Impact on Economies and Hiring: Article 1: The Burning Glass Institute studies the economic and job effects of generative AI. (2024-02-13, shares: 0)
Pretrained Open Timeseries Foundation Models (MOMENT): Article 2: The Open Timeseries Foundation has developed and thoroughly tested a group of pretrained models named MOMENT, providing full Python and Jupyter notebook code. (2024-02-13, shares: 0)
Sensitivity Analysis for Unobserved Confounding: Article 3: The article emphasizes the significance of sensitivity analysis in dealing with unobserved confounding. (2024-02-13, shares: 0)
Clients' Share of Profits in Multistrategy Funds: Article 4: Multistrategy funds transferred all their expenses to clients last year, resulting in clients receiving only 41 cents for every dollar earned. (2024-02-12, shares: 0)
Optimal Hash Ode: The article delves into the best hash function for efficient data retrieval. (2024-02-11, shares: 0)
Control Movements' Impact on Bonds: The article investigates the effects of control movements on the value and stability of bonds. (2024-02-10, shares: 0)
Systematic Options Strategies Explained: The article highlights David Sun's transition from a retail investor to a hedge fund manager, with a focus on options strategies and risk management. (2024-02-10, shares: 0)
Resourceful List: The article offers an extensive list of useful resources for various purposes. (2024-02-08, shares: 0)
US Power Trade (2024-02-08, shares: 0)
Financial Data from EDGAR Access (2024-02-08, shares: 0)
Paper with Code
Trending
Time Series Forecasting Models: The second article examines the profound influence of foundation models on machine learning, focusing on their zero-shot and few-shot generalization capabilities. (2024-02-11, shares: 296.0)
Large Language Models & Time Series Analysis: The article highlights the crucial role of time series analysis in comprehending the intricacies of diverse real-world systems and applications. (2024-02-11, shares: 174.0)
Rising
Sim2Real Transfer in 18 Seconds: The new framework enables efficient control of a multirotor using a regular laptop and microcontrollers with minimal training. (2024-02-11, shares: 133.0)
Self-Discovery in Large Language Models: SELFDISCOVER is a novel framework that helps Language Model Learning systems identify task-specific reasoning structures for complex problem-solving. (2024-02-12, shares: 110.0)
Strong Generalization with MetaTree Decision Trees: MetaTree is a system designed to create trees that demonstrate high generalization performance. (2024-02-12, shares: 57.0)