---
title: Quant Letter No. 9: July 2023, Week 4
url: https://www.ml-quant.com/issues/2023-07-26/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
issue_date: 2023-07-26
---


# Quant Letter No. 9: July 2023, Week 4

Sent 2023-07-26. 96 items.

## arXiv

### Finance

- __[Dynamic Market Maker for Automated Trading](https://arxiv.org/abs/2307.13624)__: The article introduces a Dynamic Function Market Maker protocol for decentralized automated market makers, providing a fully automated and robust solution. (2023-07-25, shares: 4) · https://www.ml-quant.com/papers/arxiv/2307.13624/
- __[Carbon Tax Propagation in Credit Portfolio](https://arxiv.org/abs/2307.12695)__: The study examines the impact of carbon taxes on firm value and credit risk measures in a closed economy, offering a method to calculate risk measures evolution based on a climate transition scenario. (2023-07-24, shares: 4) · https://www.ml-quant.com/papers/arxiv/2307.12695/
- __[Market Correlation Memory Effects](https://arxiv.org/abs/2307.12744)__: The study highlights the importance of considering the memory effect in market correlations for improving the accuracy of forecasting models and aiding in portfolio selection. (2023-07-24, shares: 3) · https://www.ml-quant.com/papers/arxiv/2307.12744/
- __[Adaptive RL for VWAP Tracking](https://arxiv.org/abs/2307.10649)__: The research introduces a reinforcement learning strategy that accurately tracks the daily volume-weighted average price of stocks, using a dual-level architecture for better results. (2023-07-20, shares: 3) · https://www.ml-quant.com/papers/arxiv/2307.10649/
- __[Mean Field Games for Portfolio Optimization](https://arxiv.org/abs/2307.10540)__: The paper discusses the use of the Mean Field Game framework for portfolio optimization, outlining optimal investment and consumption strategies. (2023-07-20, shares: 3) · https://www.ml-quant.com/papers/arxiv/2307.10540/
- __[Transfer Learning for Portfolio Optimization](https://arxiv.org/abs/2307.13546)__: The study presents the concept of transfer risk in transfer learning techniques for financial portfolio optimization, showing its potential to improve the efficiency of the transfer learning approach. (2023-07-25, shares: 3) · https://www.ml-quant.com/papers/arxiv/2307.13546/
- __[Deep RL for Wealth Management](http://dx.doi.org/10.1007/978-3-031-34111-3_7)__: The paper suggests a new approach for goal-based wealth management using deep reinforcement learning, proving its effectiveness over several benchmarks on both simulated and historical market data. (2023-07-25, shares: 3) · https://www.ml-quant.com/papers/doi/10-1007-978-3-031-34111-3-7/

### Risk Engineering

- __[Optimal Bubble Riding with Price-dependent Entry](https://arxiv.org/abs/2307.11340)__: The paper improves the optimal bubble riding model by allowing price-dependent entry times, resulting in a mean field game of controls with common noise and random entry time. (2023-07-21, shares: 4) · https://www.ml-quant.com/papers/arxiv/2307.11340/
- __[Volatility Trading System for Stock Forecasting](https://arxiv.org/abs/2307.13422)__: The article presents a new stock market trading strategy using machine learning and statistical analysis to predict trends, proven effective through backtesting. (2023-07-25, shares: 8) · https://www.ml-quant.com/papers/arxiv/2307.13422/
- __[Adversarial Deep Hedging for Derivatives](https://arxiv.org/abs/2307.13217)__: The study introduces adversarial deep hedging, a new method for derivative hedging in incomplete markets, performing well across various real market data without explicit modeling. (2023-07-25, shares: 8) · https://www.ml-quant.com/papers/arxiv/2307.13217/

### Economics

- __[AI Predicting Human Decision-Making](https://arxiv.org/abs/2307.12776)__: A study reveals that only the GPT-4 chatbot could predict human decisions in a game, but it overestimated altruistic actions, impacting AI development. (2023-07-21, shares: 2) · https://www.ml-quant.com/papers/arxiv/2307.12776/
- __[Social Media's Impact on ESG Reputation Risk](https://arxiv.org/abs/2307.11571)__: The paper examines the influence of social media on shareholders' reactions to Environmental, Social, and Governance-related reputational risks, revealing a significant decrease in abnormal returns after an ESG-risk event. (2023-07-21, shares: 2) · https://www.ml-quant.com/papers/arxiv/2307.11571/
- __[Document Analytics for Banking Efficiency](https://arxiv.org/abs/2307.11845)__: The research investigates the use of advanced document analytics, such as LayoutXLM, in banking to analyze diverse documents efficiently and accurately, enhancing operational efficiency. (2023-07-21, shares: 3) · https://www.ml-quant.com/papers/arxiv/2307.11845/

### Historical Trending

- __[Price Discovery of Derivatives](https://arxiv.org/abs/2302.13426)__: The research proposes a theory on price discovery in derivative markets, focusing on insider trading and suggesting option strategies for trading. (2023-02-26, shares: 36) · https://www.ml-quant.com/papers/arxiv/2302.13426/
- __[Free Boundary Problem for Defaultable Bonds](https://arxiv.org/abs/2301.10898)__: The paper presents a pricing model for a corporate bond with credit rating migration risk, proving the solution's existence, uniqueness, and regularity. (2023-01-26, shares: 13) · https://www.ml-quant.com/papers/arxiv/2301.10898/
- __[Nonparametric Estimator of Tail Dependence](https://arxiv.org/abs/2111.11128)__: The study provides a theoretical expression for the mean squared error of a nonparametric estimator of the tail dependence coefficient and suggests a new method for optimal threshold selection. (2021-11-22, shares: 13) · https://www.ml-quant.com/papers/arxiv/2111.11128/
- __[Optimal Consumption-Investment Problems with Alternative Data](https://arxiv.org/abs/2210.08422)__: The research presents a new duality theory for optimal consumption-investment problem, incorporating alternative data like social media commentary and COVID-19 data, and suggests a consumption-investment strategy using these data. (2022-10-16, shares: 9) · https://www.ml-quant.com/papers/arxiv/2210.08422/
- __[FinGPT: Democratizing Internet-scale Data for Financial Large](https://arxiv.org/abs/2307.10485)__: Democratizing Internet-scale Data for Financial Large: The paper presents FinGPT, an open-source, data-centric framework that automates the gathering and curation of real-time financial data from various online sources, aiming to democratize financial data for large language models. (2023-07-19, shares: 8) · https://www.ml-quant.com/papers/arxiv/2307.10485/

## SSRN

### Financial

- __[Asset Pricing Outliers](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517498)__: The article discusses how using a Minimum Covariance Determinant estimator improves the performance of stochastic discount factor models by handling multivariate outliers effectively. (2023-07-21, shares: 5) · https://www.ml-quant.com/papers/ssrn/4517498/
- __[Ambiguity Attitude and Risk-Return Tradeoff](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516515)__: The research shows that the link between the conditional equity premium and market volatility is influenced by the agent's ambiguity attitude, and market volatility doesn't significantly forecast returns. (2023-07-20, shares: 4) · https://www.ml-quant.com/papers/ssrn/4516515/
- __[CDS Volatility as Economic Uncertainty Indicator](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4515924)__: The article suggests that the fluctuation of sovereign credit default swaps can indicate economic uncertainty, aligning with economic policy uncertainty indices. (2023-07-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4515924/
- __[Retail vs Secondary Market Arbitrage](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4521147)__: The study explores the link between product features and arbitrage returns in retail and secondary markets, creating a model to predict arbitrage return at product launch. (2023-07-26, shares: 2) · https://www.ml-quant.com/papers/ssrn/4521147/
- __[Anomaly Predictability in Portfolios](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516438)__: Discussed above - the study suggests that past pricing errors can predict future anomaly returns, indicating that cross-sectional models should include price information to track return dynamics over time. (2023-07-20, shares: 7) · https://www.ml-quant.com/papers/ssrn/4516438/
- __[ETF Pricing Dynamics](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517382)__: Policymakers are exploring swing pricing, a method that adjusts a mutual fund's value based on investor activity, to mitigate financial risks from open-end mutual funds. (2022-01-31, shares: 88) · https://www.ml-quant.com/papers/ssrn/4517382/
- __[Market Fragmentation](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517362)__: A rise in market fragmentation, the spread of market trading across various platforms, results in a greater price impact of equity trading, especially for smaller stocks. (2023-02-27, shares: 108) · https://www.ml-quant.com/papers/ssrn/4517362/
- __[Bond Fund Herding](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517569)__: The study reveals that collective behavior of mutual funds, known as fund herding, can sway a company's decision to issue new bonds, particularly in uncertain times. (2022-10-18, shares: 69) · https://www.ml-quant.com/papers/ssrn/4517569/
- __[Hedge Fund Evaluation with Machine Learning](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4519123)__: Bayesian Additive Regression Trees (BART), a Bayesian machine learning method, is more effective in assessing hedge fund performance than traditional models. (2022-09-28, shares: 2) · https://www.ml-quant.com/papers/ssrn/4519123/
- __[Fractional Trading's Impact on Order Book Dynamics](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4518690)__: The implementation of fractional trading in stock markets has significantly affected price levels and order book dynamics, potentially changing the investment habits of nonprofessional investors. (2022-10-31, shares: 2) · https://www.ml-quant.com/papers/ssrn/4518690/

### Governance

- __[Accounting Quality and Fund Fire Sales](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4520446)__: The study indicates that high accounting quality is linked to smaller fire-sale discounts, implying that good accounting practices can reduce undervaluation caused by mutual fund fire sales. (2023-07-25, shares: 4) · https://www.ml-quant.com/papers/ssrn/4520446/
- __[Corporate Policy Extraction using ChatGPT](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4521096)__: The research uses ChatGPT to interpret managerial expectations from corporate disclosures, predicting future capital expenditure and intangible and R&D investments. (2023-07-25, shares: 3) · https://www.ml-quant.com/papers/ssrn/4521096/
- __[Generative AI and Investment Advisory via ChatGPT](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4519182)__: The article shows that AI like ChatGPT can generate portfolio recommendations based on policy announcements, potentially outperforming markets unlike traditional textual analysis. (2023-07-24, shares: 3) · https://www.ml-quant.com/papers/ssrn/4519182/
- __[Machine Learning for Monitoring Review and Testing at Financial Institutions](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4519923)__: The article investigates the use of machine learning for automating Volcker Rule compliance testing, a neglected area in risk management. (2022-10-03, shares: 3) · https://www.ml-quant.com/papers/ssrn/4519923/
- __[Trade Credit Provision and Finance Subsidiaries](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517691)__: The research shows that larger, more active captive finance subsidiaries positively impact the parent company's trade credit provision and lower default rates. (2022-12-01, shares: 5) · https://www.ml-quant.com/papers/ssrn/4517691/
- __[PE and Corporate Borrowing Constraints](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517765)__: Private equity buyouts help firms increase their leverage by borrowing against cash flows, with PE sponsors providing equity and stability during distress. (2022-12-12, shares: 2) · https://www.ml-quant.com/papers/ssrn/4517765/
- __[Machine Learning in Mortality Forecasting](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4521377)__: The article introduces a new machine learning approach for long-term mortality forecasting, enhancing prediction accuracy and addressing the issue of diminishing patterns in long-term forecasts. (2023-06-16, shares: 2) · https://www.ml-quant.com/papers/ssrn/4521377/

### Derivatives

- __[Quantifying Volatility Smile](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4519663)__: The article examines the impact of maximal trading speed at the start and end of equity markets on backtesting quantitative strategies. (2023-07-24, shares: 4) · https://www.ml-quant.com/papers/ssrn/4519663/
- __[Option Pricing with Costs and Volatility](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4520949)__: The research uses a specific model to solve a complex equation related to option pricing, but finds discrepancies suggesting potential risks in the model. (2023-07-25, shares: 4) · https://www.ml-quant.com/papers/ssrn/4520949/
- __[Pricing Pseudo-Swaps with Pseudo-Statistics](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4517749)__: The article introduces a method for pricing different types of swaps using pseudostatistics, and compares it to an existing model. (2023-07-21, shares: 2) · https://www.ml-quant.com/papers/ssrn/4517749/
- __[Volatility Curve Stationarity Testing](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516345)__: The paper introduces a test for stability of hidden volatility curves over time using high-frequency financial data, revealing nonstationary variation in intraday volatility pattern over time in SP 500 futures data. (2023-07-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4516345/

### Miscellaneous

- __[NLP for SQL Query Generation](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4515801)__: The paper explores the creation of systems for generating SQL queries using natural language processing, discussing challenges, methods, and future research. (2023-07-20, shares: 6) · https://www.ml-quant.com/papers/ssrn/4515801/
- __[Auto ML Technique Analysis](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516309)__: The paper reviews Auto Machine Learning (AutoML), its pros and cons, and potential future research, highlighting its role in enhancing model accuracy and minimizing human intervention. (2023-07-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4516309/
- __[Modeling Shanghai Composite Index Opening Spread](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516288)__: The research uses hybrid models to predict the opening price difference rate of the Shanghai Stock Exchange Composite Index, suggesting implications for stock market forecasting and investment decisions. (2023-07-20, shares: 3) · https://www.ml-quant.com/papers/ssrn/4516288/

### Quantitative

- __[Dynamic Function Market Maker](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4520753)__: The article suggests a new protocol for efficient asset pricing and risk management in decentralized automated market makers, combining a data aggregator and order routing. (2023-02-25, shares: 9) · https://www.ml-quant.com/papers/ssrn/4520753/
- __[Optimization of Trading Strategies with MACD Indicator](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516905)__: The article explores the use of the Moving Average Convergence Divergence indicator for optimizing trading strategies, enabled by increased computational power and data availability. (2023-04-11, shares: 2) · https://www.ml-quant.com/papers/ssrn/4516905/
- __[Augmented HAR for Volatility Forecasting](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4516177)__: The Augmented HAR algorithm, combined with artificial neural networks, enhances forecast accuracy for stocks with less than seven years of data. (2023-06-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4516177/

### Risk Engineering

- __[Decomposing Downside Investment Risk: CES](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4519406)__: CES: The paper suggests using Centred Expected Shortfall (CES) instead of Expected Shortfall (ES) for a more precise evaluation of portfolio risk. (2023-02-16, shares: 2) · https://www.ml-quant.com/papers/ssrn/4519406/
- __[Liquidity Premium for Crypto Assets](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4521131)__: The research introduces new liquidity premium Beta measures for crypto assets and portfolios, enhancing predictability and performance in situations of high liquidity. (2023-06-28, shares: 2) · https://www.ml-quant.com/papers/ssrn/4521131/
- __[Political Uncertainty and VIX Futures](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4518944)__: The research identifies a link between the 2020 U.S. presidential election and the VIX futures term structure, with political uncertainty heightening investors' worries about anticipated market uncertainty. (2022-06-07, shares: 49) · https://www.ml-quant.com/papers/ssrn/4518944/
- __[Zero-Day Options Trading and Asset Volatility](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4520410)__: The surge in ZeroDaytoExpiry (0DTE) options trading from 2011 to 2022 has led to increased volatility in the underlying asset. (2023-04-26, shares: 2) · https://www.ml-quant.com/papers/ssrn/4520410/

## RePEc

### Finance

- __[Factor portfolio optimization](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0165176523001623%3Bh%3Drepec%3Aeee%3Aecolet%3Av%3A228%3Ay%3A2023%3Ai%3Ac%3As0165176523001623)__: The article discusses a model that uses machine learning and market predictors to reduce noise in historical data, enhancing portfolio optimization. (2023-07-26, shares: 23) · https://www.ml-quant.com/papers/repec/eee-ecolet-v-228-y-2023-i-c-s0165176523001623/
- __[Fama-French Model vs. Machine Learning](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2227-7390%2F11%2F13%2F2988%2Fpdf%3Bh%3Drepec%3Agam%3Ajmathe%3Av%3A11%3Ay%3A2023%3Ai%3A13%3Ap%3A2988-%3Ad%3A1186815)__: The piece highlights a seven-factor model that improves the average R-squared by 7% in the A-share market, with SVM and random forests being the most effective machine learning algorithms. (2023-07-26, shares: 20) · https://www.ml-quant.com/papers/repec/gam-jmathe-v-11-y-2023-i-13-p-2988-d-1186815/
- __[Forecasting VaR and ES in portfolios](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2452306221000563%3Bh%3Drepec%3Aeee%3Aecosta%3Av%3A27%3Ay%3A2023%3Ai%3Ac%3Ap%3A1-15)__: The article presents two new procedures for estimating Value-at-Risk and Expected Shortfall in large portfolios, which outperform existing methods based on backtesting and scoring results. (2023-07-26, shares: 19) · https://www.ml-quant.com/papers/repec/eee-ecosta-v-27-y-2023-i-c-p-1-15/
- __[Algorithmic Trading & Block Ownership: Investor Impact](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0890838922000828%3Bh%3Drepec%3Aeee%3Abracre%3Av%3A55%3Ay%3A2023%3Ai%3A4%3As0890838922000828)__: Investor Impact: Algorithmic trading discourages sophisticated investors from gathering information, thus reducing the chances of block ownership initiation in U.S. public companies. (2023-07-26, shares: 17) · https://www.ml-quant.com/papers/repec/eee-bracre-v-55-y-2023-i-4-s0890838922000828/
- __[Factor Models for Incomplete Data: Unknown Group Structure](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207022000723%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A39%3Ay%3A2023%3Ai%3A3%3Ap%3A1205-1220)__: Unknown Group Structure: A new method that combines two algorithms accurately estimates missing data and identifies group structures in large economic databases. (2023-07-26, shares: 14) · https://www.ml-quant.com/papers/repec/eee-intfor-v-39-y-2023-i-3-p-1205-1220/
- __[External Debt & Exchange Rate Volatility in South Asia](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.1177%2F22779787221107711%3Bh%3Drepec%3Asae%3Asmppub%3Av%3A12%3Ay%3A2023%3Ai%3A1%3Ap%3A83-110)__: External debt significantly increases exchange rate volatility in South Asian Countries, as per data from the World Development Indicators from 1980-2020. (2023-07-26, shares: 13) · https://www.ml-quant.com/papers/repec/sae-smppub-v-12-y-2023-i-1-p-83-110/

### Statistical

- __[Machine Learning for Inflation Forecasting](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2666143823000042%3Bh%3Drepec%3Aeee%3Alajcba%3Av%3A4%3Ay%3A2023%3Ai%3A2%3As2666143823000042)__: The article discusses the use of machine learning to enhance inflation prediction in Brazil, emphasizing the role of non-linear factors in inflation trends. (2023-07-26, shares: 13) · https://www.ml-quant.com/papers/repec/eee-lajcba-v-4-y-2023-i-2-s2666143823000042/
- __[Robust Monitoring Machine for R2-Hacking](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1186%2Fs40854-023-00497-z%3Bh%3Drepec%3Aspr%3Afininn%3Av%3A9%3Ay%3A2023%3Ai%3A1%3Ad%3A10.1186_s40854-023-00497-z)__: The research introduces a method using collective machine learning to prevent data manipulation in test samples, enhancing the accuracy and consistency of stock return predictions and preventing R^2-hacking issues. (2023-07-26, shares: 12) · https://www.ml-quant.com/papers/repec/spr-fininn-v-9-y-2023-i-1-d-10-1186-s40854-023-00497-z/

### Machine Learning

- __[Herding Effect & Market Volatility in Chinese Stock Market](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Ffor.2968%3Bh%3Drepec%3Awly%3Ajforec%3Av%3A42%3Ay%3A2023%3Ai%3A5%3Ap%3A1275-1290)__: The research investigates the predictive power of market herding effect on Chinese stock market volatility, revealing improved prediction accuracy with machine learning algorithms. (2023-07-26, shares: 15) · https://www.ml-quant.com/papers/repec/wly-jforec-v-42-y-2023-i-5-p-1275-1290/
- __[Facial Characteristics & Returns in Economics](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.1177%2F15270025231160769%3Bh%3Drepec%3Asae%3Ajospec%3Av%3A24%3Ay%3A2023%3Ai%3A6%3Ap%3A737-758)__: The paper applies computer vision and machine learning to identify facial traits of college football coaches, suggesting a salary bias against attractiveness and favoring aggressiveness. (2023-07-26, shares: 13) · https://www.ml-quant.com/papers/repec/sae-jospec-v-24-y-2023-i-6-p-737-758/
- __[Explainable ML Methods for Actuarial Problems](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2227-7390%2F11%2F14%2F3088%2Fpdf%3Bh%3Drepec%3Agam%3Ajmathe%3Av%3A11%3Ay%3A2023%3Ai%3A14%3Ap%3A3088-%3Ad%3A1193020)__: The article discusses the use of explainable artificial intelligence in solving insurance problems, highlighting the need for accurate and understandable machine learning models. (2023-07-26, shares: 24) · https://www.ml-quant.com/papers/repec/gam-jmathe-v-11-y-2023-i-14-p-3088-d-1193020/

### Historical Trending

- __[Asset Volatility & Capital Structure in Corporate Mergers](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fmnsc.2020.3607%3Bh%3Drepec%3Ainm%3Aormnsc%3Av%3A67%3Ay%3A2021%3Ai%3A5%3Ap%3A2773-2798)__: The research indicates that changes in asset volatility after corporate acquisitions can predict changes in leverage and cash holdings, highlighting the role of firm risk. (2021-11-20, shares: 20) · https://www.ml-quant.com/papers/repec/inm-ormnsc-v-67-y-2021-i-5-p-2773-2798/
- __[Default Risk Prediction of Enterprises using CNN](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdownloads.hindawi.com%2Fjournals%2Fcomplexity%2F2022%2F5139562.pdf%3Bh%3Drepec%3Ahin%3Acomplx%3A5139562)__: The study introduces a metric model based on machine learning to choose the best balance ratio and feature selection, enhancing the performance of neural networks in predicting default risk. (2022-05-22, shares: 17) · https://www.ml-quant.com/papers/repec/hin-complx-5139562/
- __[Mean Expected-Shortfall Strategies: 'Cut Losses, Ride Gains'](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F1350486X.2023.2224354%3Bh%3Drepec%3Ataf%3Aapmtfi%3Av%3A29%3Ay%3A2022%3Ai%3A5%3Ap%3A402-438)__: 'Cut Losses, Ride Gains': A new trading strategy is suggested that focuses on left tail risk, yielding an annualized alpha of 180 bps over five years, unlike the traditional contrarian mean-variance strategy. (2022-01-21, shares: 15) · https://www.ml-quant.com/papers/repec/taf-apmtfi-v-29-y-2022-i-5-p-402-438/
- __[Adaptive Data Clustering Method Based on Density Peaks](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdownloads.hindawi.com%2Fjournals%2Fcomplexity%2F2022%2F6742120.pdf%3Bh%3Drepec%3Ahin%3Acomplx%3A6742120)__: A new data clustering method, AMDPC, based on density peaks, improves clustering accuracy by 22.58% to 28.03% across various datasets compared to traditional algorithms. (2022-11-23, shares: 14) · https://www.ml-quant.com/papers/repec/hin-complx-6742120/

## Papers with code

### Trending

- __[MetaTransformer: Unified Multimodal Learning](https://github.com/invictus717/MetaTransformer)__: Unified Multimodal Learning: The piece explores multimodal learning, a method that develops models capable of processing and connecting information from different sources. (2023-07-23, shares: 155)
- __[TOAST: Transfer Learning with Attention Steering](https://github.com/bfshi/toast)__: Transfer Learning with Attention Steering: The article presents TOAST, a novel transfer learning algorithm that focuses on task-relevant features to enhance attention to task-specific features. (2023-07-21, shares: 124)
- __[AI for Science in Quantum Systems](https://github.com/divelab/AIRS)__: The article underscores the impact of artificial intelligence advancements on new discoveries in the field of natural sciences. (2023-07-23, shares: 146)

### Rising

- __[ChatGPTs' Changing Behavior](https://github.com/lchen001/llmdrift)__: The performance and behavior of AI models GPT3.5 and GPT4 can vary greatly over time. (2023-07-20, shares: 89)
- __[Evaluation for Long Context Language Models](https://github.com/openlmlab/leval)__: The article explores the growing trend of enhancing instruction-following models to handle longer single-turn inputs such as detailed conversations and paper summaries. (2023-07-22, shares: 53)

## GitHub

### Finance

- __[Codebase Trials: Reinforcement Learning for Pair Trading](https://github.com/chancefocus/trials)__: Reinforcement Learning for Pair Trading: The code presents a new pair trading model using hierarchical reinforcement learning, with code and tests on actual stock data. (2023-04-01, shares: 28)
- __[Sarimadashboard: Time Series Analysis using sARIMA Models](https://github.com/gabri-al/sarima_dashboard)__: Time Series Analysis using sARIMA Models: The code showcases a Dash web app designed to analyze time series datasets using sARIMA models. (2023-05-02, shares: 25)
- __[Binance API in C](https://github.com/niXman/binapi)__: The code explains the process of implementing the Binance API using the C programming language. (2020-01-05, shares: 177)

### Trending

- __[Trex: Intelligent Unstructured Data Transformation](https://github.com/automorphic-ai/trex)__: Intelligent Unstructured Data Transformation: The code outlines techniques for smartly transforming unstructured data into structured data. (2023-07-12, shares: 123)
- __[Pydantic: Data Validation with Python Type Hints](https://github.com/pydantic/pydantic)__: Data Validation with Python Type Hints: The code provides a guide on using Python type hints for data validation. (2017-05-03, shares: 14880)
- __[Apps with LLMs](https://github.com/langchain-ai/langchain)__: The code outlines the method of creating apps using the Low-Level Virtual Machine (LLVM) via composability. (2022-10-17, shares: 55960)
- __[UNIX Find Command: Breadthfirst](https://github.com/tavianator/bfs)__: Breadthfirst: This code introduces a breadth-first version of the UNIX find command, presenting a new search method. (2015-06-14, shares: 791)
- __[Llama2](https://github.com/karpathy/llama2.c)__: The code details the process of implementing Inference Llama 2 using a single C programming language file. (2023-07-23, shares: 3065)

## News

### Quantitative

- __[Man Group Embraces Data Revolution in EM -> Man Group Embraces Data Revolution](https://news.google.com/rss/articles/CBMib2h0dHBzOi8vd3d3LmJsb29tYmVyZy5jb20vbmV3cy9hcnRpY2xlcy8yMDIzLTA3LTIxL21hbi1ncm91cC1xdWFudHMtZW1icmFjZS1kYXRhLXJldm9sdXRpb24taW4tZW1lcmdpbmctbWFya2V0c9IBAA?oc=5)__: Man Group's quantitative division is embracing the data revolution in developing markets. (2023-07-21, shares: 4)
- __[Quantitative Investment Market Growth -> Quantitative Investment Growth](https://news.google.com/rss/articles/CBMiqQFodHRwczovL3d3dy5kaWdpdGFsam91cm5hbC5jb20vcHIvbmV3cy9uZXdzbWFudHJhYS9xdWFudGl0YXRpdmUtaW52ZXN0bWVudC1tYXJrZXQtYnVzaW5lc3MtZ3Jvd3RoLWFuZC1pbmR1c3RyeS1kZXZlbG9wbWVudC1ieS0yMDMwLW1pbGxlbm5pdW0tbWFuYWdlbWVudC1sdGNtLWQtZS1zaGF3LWNv0gEA?oc=5)__: The quantitative investment sector is witnessing substantial business expansion and industry evolution. (2023-07-20, shares: 4)
- __[Wright Research Launches Quantbased Portfolio Management -> Wright Research Launches Portfolio Management](https://news.google.com/rss/articles/CBMieWh0dHBzOi8vd3d3LmJ1c2luZXNzd29ybGQuaW4vYXJ0aWNsZS9XcmlnaHQtUmVzZWFyY2gtTGF1bmNoZXMtUXVhbnQtYmFzZWQtUG9ydGZvbGlvLU1hbmFnZW1lbnQtU2VydmljZXMvMjUtMDctMjAyMy00ODU1MDHSAQA?oc=5)__: Wright Research has launched a new portfolio management system based on quantitative analysis. (2023-07-25, shares: 2)
- __[New Programming Language Rivals C -> New Programming Language Rivals C](https://www.efinancialcareers.com/news/2023/07/rust-vs-c-vs-val)__: The article explores a crucial asset that is advantageous to understand. (2023-07-21, shares: 1)

### Twitter

- __[LongNet: GPTs for the Entire Internet](https://twitter.com/carlcarrie/status/1683285421692796929)__: GPTs for the Entire Internet: Article 1: Microsoft has created LongNet, a transformer capable of processing the entire Internet as one long sequence. (2023-07-24, shares: 0)
- __[Reducing Risk: Crash Prevention](https://twitter.com/alphaarchitect/status/1682738618543091715)__: Crash Prevention: Article 2: The article explores methods to minimize the impact of sudden downturns in the financial market. (2023-07-22, shares: 0)
- __[Enhancing Equity Strategy Performance with VIX Scaling](https://twitter.com/quantseeker/status/1683575661519155202)__: The article proposes that the VIX can improve equity strategies' performance by accounting for volatility scaling and transaction costs. (2023-07-24, shares: 3)
- __[The Dangers of Overextrapolating Growth in Market Valuations](https://twitter.com/TheIdeaFarm/status/1683439885791707136)__: The article, citing a visualization by @ckaiwu, argues that a successful company doesn't necessarily make a good investment, especially when markets overvalue potential growth in times of euphoria. (2023-07-24, shares: 0)

### Videos

- __[ABFR Webinar](https://www.youtube.com/watch?v=C9tjsnm7m3I)__: The seminar explores the potential impact of Large Language Models on the labor market, with insights from AI and big data experts in economics and finance. (2023-07-24, shares: 1)
- __[Easiest LLAMAv2 Finetuning](https://www.youtube.com/watch?v=3fsn19OI_C8)__: The tutorial video teaches how to fine-tune llamav2 on a personal computer for a custom dataset with autotrainadvanced. (2023-07-20, shares: 30)
- __[Fastest Chat UI](https://www.youtube.com/watch?v=PE0DQlQItro)__: The tutorial video shows a fast way to create a chatbot interface using gradio. (2023-07-22, shares: 32)

### Blogs

- __[LSTM Neural Network Indicators](https://quant.stackexchange.com/questions/76187/technical-analysis-indicators-as-input-of-a-lstm-neural-network-need-advices)__: The first article explores the creation of a trading strategy using a LSTM neural network that is trained with technical analysis metrics. (2023-07-21, shares: 8)
- __[IvyPlus Admissions](https://stockviz.substack.com/p/correlation)__: Shyam Sunder's article explores the idea of correlation. (2023-07-22, shares: 0)
- __[Man Group CEO Luke Ellis on Hedge Funds (podcast)](https://chrt.fm/track/F81DEC/traffic.megaphone.fm/GLD7534141874.mp3?updated=1690226538)__: Under CEO Luke Ellis, Man Group's assets under management have nearly doubled to approximately $145 billion. (2023-07-25, shares: 5)

### Reddit

- __[Software Engineer & Quant Dev Resources](https://www.reddit.com/r/quant/comments/1574tb2/software_engineers_and_quant_devs_resources/)__: A junior engineer in a quant fund is looking for advanced resources on Delta One products to better understand their pricing, trading, and execution. (2023-07-23, shares: 20)
- __[Fixed Income Quant Start](https://www.reddit.com/r/quant/comments/157ymv9/why_do_so_many_quant_start_in_fixed_income/)__: The post discusses how quantitative analysts frequently begin their careers or work in the fixed income sector. (2023-07-24, shares: 29)
- __[HFT Shop Founders' Life Lessons](https://www.reddit.com/r/quant/comments/1563qll/any_folks_have_some_interesting_lessons_after/)__: The author is interested in learning about life lessons from others' experiences. (2023-07-22, shares: 21)
- __[Leveraged ETF Portfolio Drawbacks](https://www.reddit.com/r/algotrading/comments/157vntb/constructing_portfolios_using_leveraged_etfs/)__: The post explores potential disadvantages of portfolio construction using futures and leveraged ETFs, including tax implications and expense ratios. (2023-07-24, shares: 14)
- __[Investment Choices of Quants](https://www.reddit.com/r/quant/comments/157kewy/where_do_quants_invest_their_money/)__: The author is contemplating an unspecified question that they have frequently considered. (2023-07-23, shares: 60)