---
title: Quant Letter No. 15: September 2023, Week 2
url: https://www.ml-quant.com/issues/2023-09-14/
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: 2023-09-14
---


# Quant Letter No. 15: September 2023, Week 2

Sent 2023-09-14. 119 items.

## arXiv

### Finance

- __[Realistic financial price path generation](https://arxiv.org/abs/2309.04507)__: A novel machine learning method for simulating financial price data sequences with drawdowns is discussed, using a non-parametric Monte Carlo approach. (2023-09-08, shares: 6) · https://www.ml-quant.com/papers/arxiv/2309.04507/
- __[Financial market aggregation](https://arxiv.org/abs/2309.04116)__: The article proposes a new framework for aggregating financial markets through arbitrage, introducing the concept of market-dynamical entropy. (2023-09-08, shares: 5) · https://www.ml-quant.com/papers/arxiv/2309.04116/
- __[Corporate bond market liquidity modeling](https://arxiv.org/abs/2309.04216)__: The article introduces a Fair Transfer Price concept for valuing illiquid corporate bonds using Markov-modulated Poisson processes and micro-price concepts. (2023-09-08, shares: 6) · https://www.ml-quant.com/papers/arxiv/2309.04216/
- __[Estimating NBA player contract ROI with a new framework](https://arxiv.org/abs/2309.05783)__: The article introduces a new method for estimating the return on investment for NBA player contracts, using a game contribution percentage measure and a standard currency conversion calculation. (2023-09-11, shares: 5) · https://www.ml-quant.com/papers/arxiv/2309.05783/
- __[Gamma Hedging & Rough Paths](https://arxiv.org/abs/2309.05054)__: The study uses rough path theory to show that a specific hedging strategy can replicate other European options, even without a specific pricing model. (2023-09-10, shares: 4) · https://www.ml-quant.com/papers/arxiv/2309.05054/
- __[Kelvin Waves & Financial Engineering](https://arxiv.org/abs/2309.04547)__: The research finds unexpected links between financial engineering, hydrodynamics, and molecular physics, showing that solutions can be found through affine differential equations. (2023-09-08, shares: 4) · https://www.ml-quant.com/papers/arxiv/2309.04547/
- __[News-driven Expectations & Volatility Clustering](http://dx.doi.org/10.3390/jrfm13010017)__: The paper attributes the regularities of financial volatility to traders' reactions to news, influenced by the behaviors of long-term investors and short-term speculators. (2023-09-09, shares: 3) · https://www.ml-quant.com/papers/doi/10-3390-jrfm13010017/
- __[Monte Carlo Simulation for Lévy-Driven Pairs Trading](https://arxiv.org/abs/2309.05512)__: The study uses a Monte Carlo framework to explore optimal trading strategies in pairs trading on mean-reverting spreads, influenced by the parameters of the model. (2023-09-11, shares: 3) · https://www.ml-quant.com/papers/arxiv/2309.05512/
- __[Monotone Numerical Integration for Mean-Variance Portfolio Optimization](https://arxiv.org/abs/2309.05977)__: The research introduces an efficient numerical integration method for portfolio optimization, demonstrating its computational efficiency and accuracy, and its convergence to the unique solution of the optimization problem. (2023-09-12, shares: 3) · https://www.ml-quant.com/papers/arxiv/2309.05977/

### Miscellaneous

- __[C+ Design Patterns for Low-latency Applications: C++ Design Patterns for Low-latency](https://arxiv.org/abs/2309.04259)__: C++ Design Patterns for Low-latency: The study concentrates on enhancing latency-critical code in high-frequency trading systems, leading to a Low-Latency Programming Repository, an optimized trading strategy, and the application of the Disruptor pattern in C++, all to boost performance in latency-sensitive applications. (2023-09-08, shares: 7) · https://www.ml-quant.com/papers/arxiv/2309.04259/
- __[Data Sources for Data Science and Machine Learning: Data Sources for ML](https://arxiv.org/abs/2309.05682)__: Data Sources for ML: The article provides a detailed list of data sources for multiple sectors like finance and life sciences, catering to the growing need for data in data science, machine learning, and AI. (2023-09-10, shares: 8) · https://www.ml-quant.com/papers/arxiv/2309.05682/

### Crypto & Blockchain

- __[Crypto Derivatives' Real-time VaR Calculations](https://arxiv.org/abs/2309.06393?utm_source=dlvr.it&utm_medium=twitter)__: The thesis focuses on creating a real-time calculation process to estimate the Value at Risk (VaR) for cryptocurrency derivatives portfolios, using three time-series models and high-frequency market data. (2023-09-11, shares: 6) · https://www.ml-quant.com/papers/arxiv/2309.06393/
- __[Epps Effect & Short-Term Momentum Traders](https://arxiv.org/abs/2309.06711?utm_source=dlvr.it&utm_medium=twitter)__: The study investigates a variation in the Epps effect in the foreign exchange and cryptocurrency markets, indicating that the irregularity in the cross-correlation of returns on Euro and Bitcoin pairs is due to the actions of short-term momentum traders. (2023-09-13, shares: 2) · https://www.ml-quant.com/papers/arxiv/2309.06711/

### Historical Trending

- __[Deep RL for Gas Trading: Enhanced Performance](https://arxiv.org/abs/2301.08359)__: Enhanced Performance: Deep Reinforcement Learning (Deep RL) can enhance trading of natural gas futures contracts, outperforming traditional strategies through ensemble learning. (2023-01-19, shares: 40) · https://www.ml-quant.com/papers/arxiv/2301.08359/
- __[Market States and Risk Assessment: Dynamic Approach](https://arxiv.org/abs/2011.05984)__: Dynamic Approach: Modifying market state selection criteria based on correlation structures can enhance risk assessment and market dynamics, as shown in the SP 500 and Nikkei 225 markets. (2020-11-10, shares: 32) · https://www.ml-quant.com/papers/arxiv/2011.05984/
- __[DRL for Power Arbitrage: Leveraging Expertise](https://arxiv.org/abs/2301.08360)__: Leveraging Expertise: A dual-agent reinforcement learning approach can optimize European power arbitrage trading, improving training convergence and performance, and tripling profit and loss. (2023-01-19, shares: 28) · https://www.ml-quant.com/papers/arxiv/2301.08360/
- __[Credit Info from Earnings Calls](https://arxiv.org/abs/2209.11914)__: A new method has been developed to predict credit spread changes and company profitability using information from quarterly earnings calls, indicating that investors may not be fully exploiting this data. (2022-09-24, shares: 27) · https://www.ml-quant.com/papers/arxiv/2209.11914/
- __[Robust Deep Learning for Financial Temporal Data](https://arxiv.org/abs/2303.07925v1)__: A new deep learning framework for financial data uses XGBoost models to adapt to market changes and provide accurate predictions under various market conditions. (2023-03-14, shares: 23) · https://www.ml-quant.com/papers/arxiv/2303.07925/
- __[Long-Term Effects of Early-Life Pollution](http://arxiv.org/abs/2202.11785)__: A UK study found that exposure to the 1952 London smog in early life led to lower fluid intelligence, poorer respiratory health, and potentially fewer years of education in later life. (2022-02-23, shares: 19) · https://www.ml-quant.com/papers/arxiv/2202.11785/

## SSRN

### Quantitative

- __[Low-latency Application Design Patterns](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4565813)__: The research focuses on improving high-frequency trading systems by optimizing latency-critical code, resulting in a Low Latency Programming Repository and an optimized trading strategy. (2023-09-08, shares: 8) · https://www.ml-quant.com/papers/ssrn/4565813/
- __[Asset Pricing Models: CAPM, APT, and PAPM](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566414)__: CAPM, APT, and PAPM: The Popularity Asset Pricing Model (PAPM) improves on the Capital Asset Pricing Model (CAPM) by considering investor preferences and beliefs, addressing CAPM's empirical limitations. (2023-09-08, shares: 3) · https://www.ml-quant.com/papers/ssrn/4566414/
- __[Loss of Liquidity in Financial Market Aggregation](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4569993)__: A new framework for understanding financial markets using utility functions and limit order book states is introduced, suggesting a measure of liquidity loss due to arbitrage. (2023-09-13, shares: 4) · https://www.ml-quant.com/papers/ssrn/4569993/
- __[Geopolitical Risk in Green and Conventional Bonds](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566554)__: Green bonds are significantly influenced by geopolitical risk and are also affected by sovereign and corporate bonds, indicating they behave differently from conventional bonds, especially during high volatility periods. (2023-09-09, shares: 3) · https://www.ml-quant.com/papers/ssrn/4566554/
- __[Global Common Volatility Hedge: Bitcoin and Gold](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566562)__: Bitcoin and Gold: The study reveals that gold is a reliable hedge and safe-haven asset against global volatility, while Bitcoin shows weaker hedging abilities but strong safe-haven potential during extreme situations. (2023-09-09, shares: 2) · https://www.ml-quant.com/papers/ssrn/4566562/
- __[Stock Market Volatility in China: Geopolitical Risks](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566710)__: Geopolitical Risks: The study explores how investor sentiment and geopolitical risks affect Chinese stock market volatility, showing these factors increase industry stock market volatility in both positive and negative markets. (2023-09-09, shares: 2) · https://www.ml-quant.com/papers/ssrn/4566710/
- __[Radiological Consequences Assessment: Comparative Analysis](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4570883)__: Comparative Analysis: The Benchmarking on Assessment of Radiological Consequences (BARCO) project compares real-time forecasts of radiological impact in emergencies, offering recommendations for code users. (2023-09-13, shares: 5) · https://www.ml-quant.com/papers/ssrn/4570883/
- __[Risk Hedging in Fixed-Income Securities by Banks](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4567780)__: Unlike Silicon Valley Bank, other banks use discretionary hedging against losses in fixed-income securities and funding risks, adjusting their hedging activity based on losses or gains and using forward interest rate guidance in risk management. (2023-09-11, shares: 2) · https://www.ml-quant.com/papers/ssrn/4567780/
- __[Detecting Accounting Frauds with Machine Learning](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4568957)__: The article introduces Logit-Boost, a new machine learning model for detecting fraud in accounting, which performs better and uses fewer predictors than other methods. (2022-06-02, shares: 281) · https://www.ml-quant.com/papers/ssrn/4568957/
- __[ESG Risk Management's Impact on Shareholder Value](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4565374)__: The study reveals that companies with fewer supply chain ESG incidents yield higher future stock returns and accounting performance, emphasizing the importance of ESG risk management. (2023-07-12, shares: 2) · https://www.ml-quant.com/papers/ssrn/4565374/
- __[Passive Investing's Influence on Market Volatility](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4567120)__: The paper disproves the ETF bubble hypothesis, stating that the growth of passive investing did not inflate prices but did increase asset price volatility. (2023-08-28, shares: 2) · https://www.ml-quant.com/papers/ssrn/4567120/
- __[Financial Data Extraction from Unstructured Sources](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4567607)__: A study has developed a new framework that can accurately automate the extraction of financial data from PDF files using large language models. (2023-09-06, shares: 3) · https://www.ml-quant.com/papers/ssrn/4567607/

### Financial

- __[Fund Diversification Measures](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4570736)__: The research introduces a new method for assessing risk diversification in mutual fund families, revealing significant variations unrelated to the number of funds or objectives. (2023-09-11, shares: 3) · https://www.ml-quant.com/papers/ssrn/4570736/
- __[Retail Option Trading's Impact on Stock Liquidity](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4567604)__: The study reveals that retail trading in the options market affects the liquidity of underlying stocks, especially when liquidity supply is anticipated to be limited. (2023-09-11, shares: 3) · https://www.ml-quant.com/papers/ssrn/4567604/
- __[Reinforcement Learning for Option Hedging](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566384)__: The research indicates that reinforcement learning can be an effective alternative to traditional hedging methods for barrier options, potentially reducing transaction costs due to fewer trades. (2023-09-08, shares: 3) · https://www.ml-quant.com/papers/ssrn/4566384/
- __[High-Frequency Trading and Price Deviations](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4568645)__: The study shows that high-frequency trading can lead to larger deviations in stock prices from firms' intrinsic values, providing insights into the long-term valuation effects of high-frequency trading. (2023-09-11, shares: 3) · https://www.ml-quant.com/papers/ssrn/4568645/
- __[Term SOFR Fixing with Futures](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566882)__: The paper outlines a strategy using a Time Weighted Average Price algorithm to manage the discrepancy between Term SOFR and overnight SOFR fixings. (2023-09-09, shares: 4) · https://www.ml-quant.com/papers/ssrn/4566882/
- __[Rational Hedging with Implied Volatilities](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4570758)__: The article presents new implied volatility models, exploring their application in delta hedging, some of which require advanced techniques and neural nets. (2023-09-13, shares: 2) · https://www.ml-quant.com/papers/ssrn/4570758/
- __[Optimal Planning for Wealth Management](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566372)__: The paper suggests a semi-analytical method for optimizing financial contributions towards a goal like retirement, using a controlled backward Kolmogorov equation. (2023-09-08, shares: 9) · https://www.ml-quant.com/papers/ssrn/4566372/
- __[Dark Trading's Effect on Firm Overinvestment](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4565806)__: The study indicates that dark trading availability for a stock encourages traders to gather valuable information, preventing managerial overinvestment. (2023-09-08, shares: 2) · https://www.ml-quant.com/papers/ssrn/4565806/
- __[Analysis of Trends and Drivers in Retail Trading](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4567018)__: The survey shows varying retail participation in global exchanges, with the COVID-19 pandemic increasing retail activity and exchanges using different methods to attract retail investors. (2023-09-08, shares: 2) · https://www.ml-quant.com/papers/ssrn/4567018/
- __[ETF Measure of Stock Fragility](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4571071)__: Using exchange-traded funds data in an alternative estimation procedure enhances the prediction of stock price fragility, highlighting the impact of ETF activity and institutional investors' demand on price volatility. (2023-07-25, shares: 98) · https://www.ml-quant.com/papers/ssrn/4571071/
- __[Circuit Breakers & Market Quality](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4569362)__: Contrary to the belief that circuit breakers cause panic trading, marketwide trading halts during the COVID-19 pandemic stabilized stock returns, reduced trading costs, and resulted in more informative prices. (2022-06-20, shares: 24) · https://www.ml-quant.com/papers/ssrn/4569362/
- __[Dynamic Inflation Hedging with Online Prices](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4566242)__: Online retail inflation indices from 21 countries can predict changes in US Treasury bond yields, offering a potential investment strategy. (2022-09-21, shares: 2) · https://www.ml-quant.com/papers/ssrn/4566242/
- __[Value-weighted Approach to Duration Dependent Volatility Models](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4570144)__: Using different duration values in a Markov-switching model can improve the prediction of bitcoin returns, outperforming GARCH-type models. (2022-01-01, shares: 4) · https://www.ml-quant.com/papers/ssrn/4570144/
- __[Theory and Empirics of Prospect Capital Asset Pricing Model](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4569590)__: A proposed model suggests investors seek a balance between expected returns, variance, and skewness, significantly affecting stock prices, especially among less experienced investors. (2022-12-27, shares: 2) · https://www.ml-quant.com/papers/ssrn/4569590/
- __[Frequency and Purpose of Complex Options in the Market](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4568445)__: Complex options trades, accounting for over 30% of options trading volume, are often used to adjust the expiration or strike of a simple position. (2023-03-21, shares: 2) · https://www.ml-quant.com/papers/ssrn/4568445/

## RePEc

### Finance

- __[Forecasting GCC Financial Stress with CNNs](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10690-022-09387-3%3Bh%3Drepec%3Akap%3Aapfinm%3Av%3A30%3Ay%3A2023%3Ai%3A3%3Ad%3A10.1007_s10690-022-09387-3)__: The study uses a One-Dimensional Convolutional Neural Network to predict financial stress in the GCC's oil, stock, and bond markets, finding that financial stress indices enhance forecasting performance and oil can hedge stock market risks. (2023-09-14, shares: 17) · https://www.ml-quant.com/papers/repec/kap-apfinm-v-30-y-2023-i-3-d-10-1007-s10690-022-09387-3/
- __[Ex Post Analysis](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811273827_0006%3Bh%3Drepec%3Awsi%3Awschap%3A9789811273827_0006)__: The paper explores the importance of counterfactuals and optimal trading oracles in theory and practice, concluding with an end note. (2023-09-14, shares: 17) · https://www.ml-quant.com/papers/repec/wsi-wschap-9789811273827-0006/
- __[Trading Solutions](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811273827_0004%3Bh%3Drepec%3Awsi%3Awschap%3A9789811273827_0004)__: The research confirms Campbell et al.'s findings on overall idiosyncratic volatility, suggesting their results are specific to their sample and further exploring volatility trends and their connection to company traits. (2023-09-14, shares: 16) · https://www.ml-quant.com/papers/repec/wsi-wschap-9789811273827-0004/
- __[Finance Data Frequency](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS105752192300306X%3Bh%3Drepec%3Aeee%3Afinana%3Av%3A89%3Ay%3A2023%3Ai%3Ac%3As105752192300306x)__: The research discusses Peter Muller’s Rule, the Holding Function, Information Sets and Alphas, Performance Statistics, and the Hierarchy of Optimization Strategies. (2023-09-14, shares: 16) · https://www.ml-quant.com/papers/repec/eee-finana-v-89-y-2023-i-c-s105752192300306x/
- __[Volatility & Expected Returns: Past & Present](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1561%2F104.00000125%3Bh%3Drepec%3Anow%3Ajnlcfr%3A104.00000125)__: Past & Present: The study confirms previous findings that stock returns are influenced by aggregate-volatility risk and idiosyncratic volatility, and suggests that recent asset-pricing models fail to consistently account for this, except for the models by Stambaugh and Yuan, and Barillas and Shanken. (2023-09-14, shares: 22) · https://www.ml-quant.com/papers/repec/now-jnlcfr-104-00000125/
- __[NPS Strategies Comparison](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.emerald.com%2Finsight%2Fcontent%2Fdoi%2F10.1108%2FJDQS-12-2022-0027%2Ffull%2Fhtml%3Futm_source%3Drepec%26utm_medium%3Dfeed%26utm_campaign%3Drepec%3Bh%3Drepec%3Aeme%3Ajdqspp%3Ajdqs-12-2022-0027)__: The research investigates counterfactuals and ergodicity, traders' decision-making processes, lattice methods, partial autocorrelation, and the contrast between static and stochastic optimization. (2023-09-14, shares: 14) · https://www.ml-quant.com/papers/repec/eme-jdqspp-jdqs-12-2022-0027/
- __[Mean-Variance Optimization & Sharpe Ratio](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811273827_0001%3Bh%3Drepec%3Awsi%3Awschap%3A9789811273827_0001)__: The author recognizes Harry Markowitz's 1952 paper on Portfolio Selection as the basis for the field of quantitative investment strategy. (2023-09-14, shares: 19) · https://www.ml-quant.com/papers/repec/wsi-wschap-9789811273827-0001/
- __[Volatility Patterns](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1561%2F104.00000127%3Bh%3Drepec%3Anow%3Ajnlcfr%3A104.00000127)__: The research offers a bibliometric review of the use of high-frequency data in finance, tracing the development of the field and highlighting key sources, authors, and topics. (2023-09-14, shares: 16) · https://www.ml-quant.com/papers/repec/now-jnlcfr-104-00000127/
- __[Framework Overview](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811273827_0002%3Bh%3Drepec%3Awsi%3Awschap%3A9789811273827_0002)__: The study analyzes the National Pension Service of Korea's trading strategies and their market impact, highlighting the differences between internal and external management and their effects on volatility and liquidity. (2023-09-14, shares: 15) · https://www.ml-quant.com/papers/repec/wsi-wschap-9789811273827-0002/

### Statistical

- __[Football Prediction with Machine Learning](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D133178%3Bh%3Drepec%3Aids%3Aijbsre%3Av%3A17%3Ay%3A2023%3Ai%3A5%3Ap%3A565-586)__: The project uses machine learning models to predict English Premier League football matches outcomes with a 52.3% accuracy for the 2020-2021 season, using expected goals metric instead of traditional goals scored. (2023-09-14, shares: 20) · https://www.ml-quant.com/papers/repec/ids-ijbsre-v-17-y-2023-i-5-p-565-586/
- __[Predictive Analytics for Decision-Making](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F09638180.2022.2138934%3Bh%3Drepec%3Ataf%3Aeuract%3Av%3A32%3Ay%3A2023%3Ai%3A3%3Ap%3A637-662)__: Research indicates that managers' operational decisions are influenced by the type of data used in predictive analytics tools and trend consistency, with a tendency to disregard predictions from social media data revealing unexpected negative trends. (2023-09-14, shares: 14) · https://www.ml-quant.com/papers/repec/taf-euract-v-32-y-2023-i-3-p-637-662/

### Machine Learning

- __[Geopolitical Risks & Stock Market Volatility: ML Insights](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1057521923002545%3Bh%3Drepec%3Aeee%3Afinana%3Av%3A89%3Ay%3A2023%3Ai%3Ac%3As1057521923002545)__: ML Insights: The research uses machine learning to analyze how geopolitical risks, such as military actions, affect US stock market volatility, finding that these models can offer significant financial advantages. (2023-09-14, shares: 36) · https://www.ml-quant.com/papers/repec/eee-finana-v-89-y-2023-i-c-s1057521923002545/
- __[High-Frequency Arbitrage on Cross-Listed Stocks: Info Latency Effects](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1057521923002934%3Bh%3Drepec%3Aeee%3Afinana%3Av%3A89%3Ay%3A2023%3Ai%3Ac%3As1057521923002934)__: Info Latency Effects: The study presents a new method to examine the impact of information delay in high-frequency trading on international cross-listed stocks, suggesting a profitable strategy based on price deviations using Canadian and US stocks. (2023-09-14, shares: 28) · https://www.ml-quant.com/papers/repec/eee-finana-v-89-y-2023-i-c-s1057521923002934/
- __[Improved Dam Break Outflow Prediction with Ensemble ML](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11069-023-06060-4%3Bh%3Drepec%3Aspr%3Anathaz%3Av%3A118%3Ay%3A2023%3Ai%3A3%3Ad%3A10.1007_s11069-023-06060-4)__: The DA-IBK machine learning model excels at predicting dam break peak outflow, significantly outperforming empirical equations, particularly at high outflows. (2023-09-14, shares: 21) · https://www.ml-quant.com/papers/repec/spr-nathaz-v-118-y-2023-i-3-d-10-1007-s11069-023-06060-4/
- __[Leveraging Return Prediction for Improved VaR Estimation](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2306-5729%2F8%2F8%2F133%2Fpdf%3Bh%3Drepec%3Agam%3Ajdataj%3Av%3A8%3Ay%3A2023%3Ai%3A8%3Ap%3A133-%3Ad%3A1219341)__: The article explores the use of Value at Risk (VaR) for predicting potential portfolio losses and managing risk, emphasizing the application of machine learning in stock market predictions and comparing various VaR estimation metrics. (2023-09-14, shares: 25) · https://www.ml-quant.com/papers/repec/gam-jdataj-v-8-y-2023-i-8-p-133-d-1219341/
- __[Limited Predictive Power of ML in Estimating Gold Risk Premium](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2405851322000502%3Bh%3Drepec%3Aeee%3Ajocoma%3Av%3A31%3Ay%3A2023%3Ai%3Ac%3As2405851322000502)__: Machine learning struggles to predict gold risk premium better than historical averages, but performs slightly better when using individual predictors. (2023-09-14, shares: 24) · https://www.ml-quant.com/papers/repec/eee-jocoma-v-31-y-2023-i-c-s2405851322000502/
- __[Bayesian ANN for Efficiency Analysis](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0304407623002075%3Bh%3Drepec%3Aeee%3Aeconom%3Av%3A236%3Ay%3A2023%3Ai%3A2%3As0304407623002075)__: The paper introduces a novel method for frontier estimation in econometrics, merging Data Envelopment Analysis and Stochastic Frontier Analysis using Bayesian artificial neural networks, and validates its efficiency with Monte Carlo experiments and a dataset of large US banks. (2023-09-14, shares: 16) · https://www.ml-quant.com/papers/repec/eee-econom-v-236-y-2023-i-2-s0304407623002075/

### Historical Trending

- __[Machine Learning for Housing Price Trends](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.emerald.com%2Finsight%2Fcontent%2Fdoi%2F10.1108%2FIJHMA-02-2022-0033%2Ffull%2Fhtml%3Futm_source%3Drepec%26utm_medium%3Dfeed%26utm_campaign%3Drepec%3Bh%3Drepec%3Aeme%3Aijhmap%3Aijhma-02-2022-0033)__: Housing price trends can be accurately predicted by machine learning algorithms considering land use-transportation interactions and socio-economic factors. (2022-11-05, shares: 21) · https://www.ml-quant.com/papers/repec/eme-ijhmap-ijhma-02-2022-0033/
- __[Machine Learning vs. Dictionary Methods for Sentiment Disclosure](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fmnsc.2021.4156%3Bh%3Drepec%3Ainm%3Aormnsc%3Av%3A68%3Ay%3A2022%3Ai%3A7%3Ap%3A5514-5532)__: Machine-learning techniques enhance the accuracy of sentiment analysis in 10-K filings and conference calls, outperforming traditional dictionary-based methods. (2022-03-21, shares: 13) · https://www.ml-quant.com/papers/repec/inm-ormnsc-v-68-y-2022-i-7-p-5514-5532/
- __[Return Predictability with Machine Learning](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fmnsc.2021.4189%3Bh%3Drepec%3Ainm%3Aormnsc%3Av%3A68%3Ay%3A2022%3Ai%3A10%3Ap%3A7701-7741)__: A new prediction model using machine learning can enhance return predictability by reclassifying stocks based on predicted financial performance. (2022-01-11, shares: 19) · https://www.ml-quant.com/papers/repec/inm-ormnsc-v-68-y-2022-i-10-p-7701-7741/
- __[The Leverage Factor: Credit Cycles and Asset Returns](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fmnsc.2022.4508%3Bh%3Drepec%3Ainm%3Aormnsc%3Av%3A68%3Ay%3A2022%3Ai%3A10%3Ap%3A7350-7361)__: Credit Cycles and Asset Returns: Periods of high credit boom followed by low returns to risky equities are predictable, with fixed income serving as a safer option with slightly higher returns. (2022-06-20, shares: 17) · https://www.ml-quant.com/papers/repec/inm-ormnsc-v-68-y-2022-i-10-p-7350-7361/
- __[Determinant Analysis for Housing Price Prediction](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.emerald.com%2Finsight%2Fcontent%2Fdoi%2F10.1108%2FIJHMA-02-2022-0025%2Ffull%2Fhtml%3Futm_source%3Drepec%26utm_medium%3Dfeed%26utm_campaign%3Drepec%3Bh%3Drepec%3Aeme%3Aijhmap%3Aijhma-02-2022-0025)__: A regression-based machine learning model can accurately predict housing prices and identify key influencing factors. (2022-10-12, shares: 8) · https://www.ml-quant.com/papers/repec/eme-ijhmap-ijhma-02-2022-0025/

## Papers with code

### Trending

- __[GPTInvestAR: Enhancing Stock Investment Strategies](https://github.com/UditGupta10/GPT-InvestAR)__: Enhancing Stock Investment Strategies: The article suggests using Large Language Models (LLMs) to streamline the evaluation of companies' Annual Reports. (2023-09-09, shares: 37)
- __[Multimodal Language Models Survey](https://github.com/bradyfu/awesome-multimodal-large-language-models)__: MLLM is a novel research area that utilizes Large Language Models for performing tasks involving multiple modes of communication. (2023-09-10, shares: 4146)
- __[AgentVerse: MultiAgent Collaboration](https://github.com/openbmb/agentverse)__: MultiAgent Collaboration: Autonomous agents have seen substantial advancements through the use of Large Language Models for task generalization. (2023-09-12, shares: 1147)
- __[SharpnessAware Minimization: Weighted Sharpness Regularization](https://github.com/intelligent-machine-learning/dlrover)__: Weighted Sharpness Regularization: The development of Sharpness-Aware Minimization (SAM) aims to achieve better generalization in Deep Neural Networks by seeking flatter minima. (2023-09-12, shares: 276)
- __[Cognitive Architectures for Language Agents](https://github.com/ysymyth/awesome-language-agents)__: Large language models are being integrated with external resources or internal control flows for tasks that require grounding or reasoning. (2023-09-09, shares: 93)

### Rising

- __[Explanation Methods for Time Series Classification](https://github.com/XgenTimeSeries/xgen-timeseries)__: The article stresses the importance of understanding how models learn in classification applications, beyond just the final classification. (2023-09-12, shares: 79)
- __[Kani: Lightweight Framework for Language Models](https://github.com/zhudotexe/kani)__: Lightweight Framework for Language Models: The piece underscores the increasing complexity and popularity of language model applications, such as tools and retrieval enhancements. (2023-09-13, shares: 69)
- __[PyGraft: Generation of Schemas and Knowledge Graphs](https://github.com/nicolas-hbt/pygraft)__: Generation of Schemas and Knowledge Graphs: The article points out the restricted access to public datasets in sensitive areas like education and healthcare. (2023-09-10, shares: 60)
- __[ResFields: Neural Fields for Spatiotemporal Signals](https://github.com/markomih/ResFields)__: Neural Fields for Spatiotemporal Signals: The article discusses the growing use of neural fields, a kind of neural network, for their effectiveness in handling complex 3D data. (2023-09-09, shares: 42)

## GitHub

### Finance

- __[Quant-Invest-Strats: Financial Data Analytics](https://github.com/ArturSepp/QuantInvestStrats)__: Financial Data Analytics: QIS package provides tools for visualizing and analyzing financial data in quantitative investment strategies. (2022-12-30, shares: 33)
- __[Machine Learning Refined: Notes and Demos](https://github.com/jermwatt/machine_learning_refined)__: Notes and Demos: The 2nd edition of Machine Learning Refined, published by Cambridge University Press, includes notes, examples, and Python demos. (2016-08-12, shares: 1384)
- __[btplotting: Backtest and Optimization Plotting](https://github.com/happydasch/btplotting)__: Backtest and Optimization Plotting: btplotting is a tool that enables plotting for backtests, optimization results, and live data from backtrader. (2020-07-16, shares: 263)
- __[plotters: Rust Data Plot Library](https://github.com/plotters-rs/plotters)__: Rust Data Plot Library: A rust drawing library provides high-quality data plotting for both WASM and native, in static and real-time. (2019-04-24, shares: 3132)
- __[acme RL Components](https://github.com/google-deepmind/acme)__: The library features a collection of components and agents for reinforcement learning. (2020-05-01, shares: 3186)

### Trending

- __[MultiJoint dynamics: A Physics Simulator](https://github.com/google-deepmind/mujoco)__: A Physics Simulator: The article explores a universal physics simulator that manages multi-joint dynamics and contact. (2021-08-27, shares: 6077)
- __[DevToys: Developer's Swiss Army Knife](https://github.com/veler/DevToys)__: Developer's Swiss Army Knife: The piece details a multi-functional tool for developers, compared to a Swiss Army knife. (2021-09-29, shares: 17416)
- __[LLaMAAdapter: Finetuning for Quick Instruction Following](https://github.com/OpenGVLab/LLaMA-Adapter)__: Finetuning for Quick Instruction Following: The article discusses the optimization of LLaMA to execute instructions within a set timeframe. (2023-03-19, shares: 4820)
- __[awesomespark: Apache Spark Packages and Resources](https://github.com/awesome-spark/awesome-spark)__: Apache Spark Packages and Resources: The article offers a detailed list of top-notch Apache Spark packages and resources. (2016-02-01, shares: 1525)

## News

### Quantitative

- __[Banks' Data Science Overspending](https://www.efinancialcareers.com/news/2023/09/data-science-jobs-in-banks)__: The article discusses the high costs associated with implementing machine learning technologies. (2023-09-12, shares: 5)
- __[Man Group seeks tech team in Bulgaria](https://www.hedgeweek.com/man-group-launches-recruitment-drive-for-bulgaria-based-tech-team/)__: Man Group, a leading hedge fund firm, has begun a recruitment drive in Bulgaria for engineers and quant developers. (2023-09-13, shares: 2)
- __[Schonfeld introduces longer fee structure](https://www.hedgeweek.com/schonfeld-to-introduce-longer-for-lower-fee-structure/)__: Schonfeld Strategic Advisors is offering a substantial fee discount to clients who commit to longer investment periods in its main equity hedge fund. (2023-09-13, shares: 2)
- __[Aquis Exchange Embraces HFT](https://www.fnlondon.com/articles/aquis-exchange-opens-up-platform-to-high-frequency-trading-20230912)__: Alasdair Haynes predicts a decrease in execution time and a market share increase for Aquis due to an upcoming change. (2023-09-12, shares: 1)

## Podcasts

### Quantitative

- __[Tom Basso: Engineering to Trading Mastery](https://www.buzzsprout.com/2034153/13555599-tom-basso-s-insightful-journey-from-engineering-to-trading-mastery.mp3)__: Engineering to Trading Mastery: Tom Basso, an engineer-turned-trader, emphasizes the importance of understanding both profits and losses in trading and shares his risk management strategies for volatile markets. (2023-09-09, shares: 13)
- __[Navigating Unpredictable Trading with Cheds](https://www.buzzsprout.com/2034153/13586887-navigating-the-unpredictable-seas-of-trading-with-cheds.mp3)__: Experienced trader Cheds likens trading to navigating unpredictable seas, stressing the need for discipline, risk management, continuous learning, and effective follow-ups. (2023-09-13, shares: 9)
- __[James Seyffart on Spot BTC ETF](https://rss.com/podcasts/confessionsmm/1120218)__: James Seyffart, a research analyst, specializes in the broader asset management industry, including cryptocurrencies, and shares his expertise on crypto and Bitcoin-related funds products. (2023-09-13, shares: 7)
- __[Reflexivity of Equity Volatility with Dean Curnutt](https://www.flirtingwithmodels.com/2023/09/11/s6e16-the-reflexivity-of-equity-volatility/)__: Dean Curnutt, founder of Macro Risk Advisors, discusses market risks, the evolving role of the Fed, and his theory on why financial crises seem to occur every 11 years. (2023-09-11, shares: 6)
- __[Understanding Financial Market Turbulence with Gary Shilling](https://www.buzzsprout.com/2034153/13563614-understanding-the-turbulence-of-financial-markets-with-gary-shilling.mp3)__: Economist Gary Shilling talks about his principles for assessing the economy and financial markets, the impact of artificial intelligence on jobs, and the potential effects of a recession on the current economy. (2023-09-10, shares: 6)

### Related

- __[Stock Options View](https://soundcloud.com/patrick-nettlebay/options)__: Professors Zoro and DeSimone explore the Option environment, focusing on OptionMetrics and long-dated options. (2023-09-13, shares: 4)
- __[LGIM AGM Votes](https://audioboom.com/posts/8365277)__: LGIM's Stewardship team shares their voting decisions on key ESG issues during the 2023 AGM season. (2023-09-11, shares: 4)
- __[Overcoming Winograd Schema Challenge](https://dataskeptic.com/blog/episodes/2023/the-defeat-of-the-winograd-schema-challenge)__: Vid Kocijan, a Machine Learning Engineer, presents his research on pretraining common sense reasoning and its influence on societal bias. (2023-09-11, shares: 4)
- __[Sugar Futures: Deadly for Cereal](https://interactive-brokers-podcast.podbean.com/e/sugar-futures-%e2%80%93-talk-about-a-cereal-killer/)__: Deadly for Cereal: McAlinden Research Partners and IBKR experts analyze the global economics of sugar trade, its effect on consumer prices and specific stocks. (2023-09-13, shares: 3)
- __[Global Commodities: Sept. & Dec. Prices](https://atanyrate.podbean.com/e/global-commodities-90-in-september-86-in-december/)__: Sept. & Dec. Prices: Brent crude futures surpassed $90 for the first time this year, though experts forecast a decrease to the mid $80s by the end of 2023. (2023-09-08, shares: 3)

## X / Twitter

### Quantitative

- __[Crypto Volatility & Risk Measures](https://twitter.com/carlcarrie/status/1701581453690028034)__: The article explores the absence of a direct relationship between cryptocurrencies and tech stocks, examining the market structure and volatility of digital assets. (2023-09-12, shares: 3)
- __[Clustering Cryptos by Asset Similarity](https://twitter.com/carlcarrie/status/1702103809709731940)__: The piece proposes that cryptocurrencies can be classified based on their digital asset characteristics, akin to the categorization of stocks and bonds. (2023-09-14, shares: 2)
- __[Corporate Bond Liquidity Model with RFQ Data](https://twitter.com/carlcarrie/status/1702094774864376184)__: The article presents a novel corporate bond liquidity model that uses Request for Quotation (RFQ) data and a Markov-modulated Poisson Process. (2023-09-13, shares: 2)
- __[Crypto Volatility & Risk Measures](https://twitter.com/carlcarrie/status/1701994469032092024)__: The article explores the fluctuating nature and risk factors associated with cryptocurrencies. (2023-09-13, shares: 2)
- __[Data Sources Across Disciplines](https://twitter.com/quantseeker/status/1701884624836690026)__: The paper offers an extensive list of potential data sources from diverse sectors like finance, healthcare, retail, etc. (2023-09-13, shares: 2)
- __[Quant Finance Resources Compilation](https://twitter.com/quantseeker/status/1701518927447171578)__: The article provides a detailed list of useful resources for those involved in quantitative finance. (2023-09-12, shares: 2)
- __[Knight Capital's Trading Disaster](https://twitter.com/carlcarrie/status/1701573392724324538)__: The article recounts how Knight Capital lost more money in minutes than its market value in 2012 due to algorithmic trading software errors. (2023-09-12, shares: 1)

### Miscellaneous

- __[Deep Learning for Stock Market Prediction](https://twitter.com/quantseeker/status/1700878206952231176)__: The article reviews research on using deep learning for predicting stock market trends. (2023-09-10, shares: 1)
- __[Offline RL for Propagator Estimates](https://twitter.com/carlcarrie/status/1699989411184640305)__: The article explores the use of offline reinforcement learning and an optimiser to estimate propagators and cut execution costs amidst uncertainty. (2023-09-08, shares: 1)
- __[TradingGPT Framework](https://twitter.com/carlcarrie/status/1701579674659258658)__: Article: The article delves into the intricacies of the TradingGPT LLM MultiAgent Framework. (2023-09-12, shares: 0)
- __[Llama2.🔥 Launch](https://twitter.com/carlcarrie/status/1701463763843416124)__: Article: A user has successfully converted llama2 from Python to Mojo, enhancing its speed by 20%. (2023-09-12, shares: 0)
- __[Earnings Call Surprise](https://twitter.com/quantseeker/status/1701317851393474910)__: Article: The piece investigates the influence of unexpected information in earnings call text on post-earnings announcement drift. (2023-09-11, shares: 0)
- __[NY FED's GDP Growth Nowcast](https://twitter.com/carlcarrie/status/1700269477232021993)__: Article: The New York Federal Reserve has developed a fresh Nowcast for GDP Growth. (2023-09-08, shares: 0)

## Reddit

### Quantitative

- __[Derivatives for Hedging and Pricing Theory](https://www.reddit.com/r/quant/comments/16eca0a/stirs_derivatives_bookspapers/)__:  (2023-09-09, shares: 9)
- __[Research Tools for Data Storage and Manipulation](https://www.reddit.com/r/quant/comments/16f8w85/whats_your_lob_research_stack/)__:  (2023-09-10, shares: 12)
- __[Curated Reading List for Adversarial Reinforcement Learning](https://www.reddit.com/r/quant/comments/16fqhor/adversarial_reinforcement_learning/)__:  (2023-09-11, shares: 4)
- __[Impact of Exchange Formats on Intraday Momentum Trading](https://www.reddit.com/r/algotrading/comments/16fwqig/do_exchange_formattypes_matter/)__:  (2023-09-11, shares: 0)
- __[Free API for Bond Yields and Prices](https://www.reddit.com/r/quant/comments/16e75as/looking_for_free_api_for_daily_bond_yields_and/)__:  (2023-09-09, shares: 0)
- __[Market Microstructure in Quantitative Trading](https://www.reddit.com/r/quant/comments/16d5904/how_important_is_market_microstructure_for_qt/)__:  (2023-09-08, shares: 17)