---
title: Quant Letter No. 71: October 2024, Week 4
url: https://www.ml-quant.com/issues/2024-10-23/
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: 2024-10-23
---


# Quant Letter No. 71: October 2024, Week 4

Sent 2024-10-23. 160 items.

## arXiv

### Finance

- __[Superelliptical Market Maker](http://arxiv.org/abs/2410.13265v1)__: The article discusses a new automated market maker model that can handle both negative and positive asset pricing, useful in electricity, energy, and derivatives markets, and compares it to a replicating market maker. (2024-10-17, shares: 5) · https://www.ml-quant.com/papers/arxiv/2410.13265/
- __[Portfolio Management with Default](http://arxiv.org/abs/2410.13103v1)__: The paper explores the optimal portfolio delegation between an investor and a portfolio manager in the event of a random default time, using mathematical methods and a deep-learning algorithm to study investment decisions and compensation structures. (2024-10-17, shares: 3) · https://www.ml-quant.com/papers/arxiv/2410.13103/
- __[Equilibria in Trading](http://arxiv.org/abs/2410.13583v1)__: The third paper in a series on game theory in competitive position-building offers a comprehensive solution for finding equilibrium strategies, examining the importance of trade centralization and demonstrating its strategic benefits. (2024-10-17, shares: 2) · https://www.ml-quant.com/papers/arxiv/2410.13583/

### Crypto & Blockchain

- __[Local Energy Markets for Grid Efficiency](http://arxiv.org/abs/2410.13330v1)__: The study reveals that local energy markets can enhance economic efficiency and grid stability. They can significantly reduce average energy prices and operational peak power levels, particularly in areas with a high concentration of photovoltaic systems and heat pumps. (2024-10-17, shares: 2) · https://www.ml-quant.com/papers/arxiv/2410.13330/

### Historical Trending

- __[Deep RL for Volatility Fitting](http://arxiv.org/abs/2410.11789v1)__: The article discusses the use of Deep Reinforcement Learning in solving volatility issues in equity derivatives, showing its effectiveness and adaptability in handling complex functions and online learning. (2024-10-15, shares: 5) · https://www.ml-quant.com/papers/arxiv/2410.11789/
- __[Modeling Sparse Order Books in Electricity Trading](http://arxiv.org/abs/2410.06839v1)__: The paper presents a new model for simulating sparse limit order books in illiquid markets like the European intraday electricity market, using an inhomogeneous Poisson process for order arrivals and cancellations. (2024-10-09, shares: 5) · https://www.ml-quant.com/papers/arxiv/2410.06839/
- __[GANs for Financial Time Series](http://arxiv.org/abs/2410.09850v1)__: The study examines the capability of Generative Adversarial Networks in learning complex financial time series patterns, highlighting that their performance is greatly influenced by the generator architecture chosen. (2024-10-13, shares: 5) · https://www.ml-quant.com/papers/arxiv/2410.09850/
- __[Cross-Currency Basis Swaps Pricing](http://arxiv.org/abs/2410.08477v1)__: The article discusses the pricing and hedging methods for financial products linked to the SOFR and AONIA, which have replaced LIBOR as the main benchmark rate for borrowing costs. (2024-10-11, shares: 4) · https://www.ml-quant.com/papers/arxiv/2410.08477/
- __[Scalable Regression with Reference Sets](http://arxiv.org/abs/2410.09196v1)__: The paper introduces a new methodology for Distribution Regression on stochastic processes, resolving estimation uncertainties and expanding its use in various learning tasks across different fields. (2024-10-11, shares: 3) · https://www.ml-quant.com/papers/arxiv/2410.09196/
- __[Model Risk and Semi-Static Hedging](http://arxiv.org/abs/2410.06906v1)__: The study expands on previous research on model risk distributionally robust sensitivities, introducing the minimization of the distributionally robust problem in relation to semi-static hedging strategies and outlining the optimal strategies. (2024-10-09, shares: 3) · https://www.ml-quant.com/papers/arxiv/2410.06906/

## SSRN

### Quantitative

- __[Role of Foreign Exchange Reserves in Dollarization](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993137)__: The research indicates that active intervention in foreign exchange can stabilize economic volatility in economies heavily reliant on the US dollar. (2024-10-19, shares: 7) · https://www.ml-quant.com/papers/ssrn/4993137/
- __[Machine Learning for Engineering Constants Prediction](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991455)__: The study uses machine learning and the finite element method to determine the mechanical properties of certain composites, offering a more efficient alternative to traditional methods. (2024-10-18, shares: 3) · https://www.ml-quant.com/papers/ssrn/4991455/
- __[IPO Pricing Prediction with Lasso-Neural Networks](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990940)__: A new model using Lasso neural networks has been developed to predict IPO pricing for Chinese companies, with retained earnings per share being a key factor. (2024-10-17, shares: 5) · https://www.ml-quant.com/papers/ssrn/4990940/
- __[Bayesian GEVMAR Model for Actuarial Data](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993360)__: The study uses a new model to analyze nonstandard actuarial data in general insurance, showing better results than the previous Gaussian model. (2024-10-19, shares: 4) · https://www.ml-quant.com/papers/ssrn/4993360/
- __[Fedmse: Semi-Supervised Federated Learning for IoT Detection](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990105)__: Semi-Supervised Federated Learning for IoT Detection: A new federated learning approach has been proposed to enhance IoT network intrusion detection, integrating the Shrink Autoencoder and Centroid one-class classifier with a new aggregation algorithm. (2024-10-17, shares: 5) · https://www.ml-quant.com/papers/ssrn/4990105/
- __[Composite Laminate Design](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991453)__: The paper discusses a machine learning method for designing composite laminates efficiently, using a generator and discriminator to predict mechanical properties with limited data. (2024-10-18, shares: 3) · https://www.ml-quant.com/papers/ssrn/4991453/
- __[Generative AI Training](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993782)__: The article suggests that using copyrighted data to train generative AI models without licenses is a copyright infringement, as the DSM Directive's exceptions for text and data mining do not apply. (2024-10-19, shares: 4) · https://www.ml-quant.com/papers/ssrn/4993782/
- __[Technology Value Prediction](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4992440)__: The study introduces a deep-learning model that predicts the economic value of technology using patent and firm data, showing better prediction performance than other models. (2024-10-19, shares: 3) · https://www.ml-quant.com/papers/ssrn/4992440/
- __[Accounting Comparability](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993512)__: The research indicates that firms with higher accounting comparability have lower ESG reputational risk, reduced capital costs, and increased investment activity, emphasizing the role of comparability in financial decision-making and risk management. (2024-10-20, shares: 3) · https://www.ml-quant.com/papers/ssrn/4993512/
- __[Reinforcement Learning in Market-Making](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991392)__: The paper presents a deep reinforcement learning framework for optimal market-making trading, using the Soft Actor-Critic algorithm to manage complex, high-dimensional problems with continuous state and action spaces. (2024-10-17, shares: 3) · https://www.ml-quant.com/papers/ssrn/4991392/
- __[Mutual Funds & Low-Risk Anomaly](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993876)__: Mutual funds' demand pressure on high-beta assets following market changes leads to overpricing and lower expected returns, causing the low-risk anomaly in stock returns. (2024-10-15, shares: 3) · https://www.ml-quant.com/papers/ssrn/4993876/
- __[AI in Working Capital Management](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4992621)__: AI enhances working capital management in the auto industry by improving demand forecasting, streamlining accounts, managing inventory, and spotting financial anomalies. (2024-08-23, shares: 2) · https://www.ml-quant.com/papers/ssrn/4992621/
- __[AIPowered Data Warehouse Solutions](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993596)__: AI integration into data warehousing boosts data processing efficiency, accuracy, and scalability, enabling automated data extraction, real-time analytics, and improved data quality. (2024-07-28, shares: 2) · https://www.ml-quant.com/papers/ssrn/4993596/
- __[Machine Learning for Fake News Classification](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990295)__: ML algorithms combined with IoT frameworks can enhance news classification and detect fake news in real-time, helping to fight misinformation. (2022-12-14, shares: 2) · https://www.ml-quant.com/papers/ssrn/4990295/
- __[Evolution of AI & Machine Learning](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4988863)__: The growth of big data analytics has advanced AI and ML, with increased data availability leading to more accurate, efficient, and versatile models. (2021-12-02, shares: 2) · https://www.ml-quant.com/papers/ssrn/4988863/
- __[Credit Spread and Business Cycle](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4988908)__: The study suggests that inaccuracies in credit spread predictions, indicative of heightened market optimism, can strongly forecast future economic downturns, with a significant increase in prediction errors leading to a 1.47% decrease in GDP growth. (2024-06-26, shares: 3) · https://www.ml-quant.com/papers/ssrn/4988908/
- __[Telecom Network Spectrum Optimization](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4989103)__: The research investigates the application of Artificial Intelligence and Machine Learning, particularly Artificial Neural Networks, in telecommunications for optimizing spectrum management and addressing industry issues like predictive maintenance, virtual assistance, network optimization, fraud prevention, and revenue growth. (2024-10-12, shares: 2) · https://www.ml-quant.com/papers/ssrn/4989103/
- __[Mathematical Statistics in Engineering](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4989144)__: The paper presents a cascaded machine learning algorithm for resource allocation and power usage in cognitive radio networks, emphasizing on energy efficiency, fairness, and spectrum utilization. (2022-08-19, shares: 2) · https://www.ml-quant.com/papers/ssrn/4989144/
- __[Predictive Maintenance Optimization with ML and IoT](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4994457)__: The study presents a predictive maintenance framework that employs IoT sensors and advanced Machine Learning algorithms to anticipate equipment failures and carry out proactive maintenance, leading to a 30-40% decrease in unexpected downtime and 20-30% in maintenance costs. (2024-10-07, shares: 3) · https://www.ml-quant.com/papers/ssrn/4994457/
- __[Unsupervised ML in Telecom Retail Optimization](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4994164)__: The document lacks sufficient information for a summary. (2024-10-02, shares: 2) · https://www.ml-quant.com/papers/ssrn/4994164/

### Financial

- __[Bank Securities Management](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991701)__: A study reveals that US banks increased their interest rate risk in 2022-23 due to rapid rate changes and reluctance to sell bonds at a discount. (2024-10-18, shares: 6) · https://www.ml-quant.com/papers/ssrn/4991701/
- __[FX Volatility](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993938)__: High foreign exchange volatility results in higher currency carry returns during high ambiguity, as investors avoid trading, a study shows. (2024-10-21, shares: 7) · https://www.ml-quant.com/papers/ssrn/4993938/
- __[MGARCH Model](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990401)__: A new study using a multivariate GARCH model identifies shocks and volatility spillovers in speculative return systems, using SP 500 returns, Treasury yields, and the U.S. Dollar Index. (2024-10-17, shares: 7) · https://www.ml-quant.com/papers/ssrn/4990401/
- __[Asset Allocation](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993934)__: An article suggests that dynamic asset allocation, which adjusts based on expected returns and risk, may be more beneficial than static allocation, as supported by academic research. (2024-10-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4993934/
- __[Firm Leverage](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4994384)__: A study finds that low-leverage firms reduce investment more than high-leverage firms when government debt increases, due to higher taxation weakening their cash flows. (2024-10-21, shares: 3) · https://www.ml-quant.com/papers/ssrn/4994384/
- __[EuroArea Bond Market Liquidity During COVID-19](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991885)__: The euroarea sovereign bond market's liquidity was significantly affected during the March 2020 cash rush, but it recovered quickly and was not as severely impacted as during the euroarea sovereign debt crisis. (2024-10-19, shares: 5) · https://www.ml-quant.com/papers/ssrn/4991885/
- __[Female Financial Portfolio Choices and Marital Laws](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4994123)__: In Spain, married couples with separate property tend to have riskier financial portfolios than those with community property, particularly when the wife manages the finances, due to high divorce costs. (2024-10-21, shares: 4) · https://www.ml-quant.com/papers/ssrn/4994123/
- __[FX Interventions and USD/MXN Exchange Rate](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4992672)__: The Bank of Mexico's 2017 domestic nondeliverable forwards (DNDF) policy successfully reduced depreciation pressure and volatility of the USDMXN exchange rate, strengthening the Mexican Peso. (2024-10-18, shares: 3) · https://www.ml-quant.com/papers/ssrn/4992672/
- __[Euler Equation Testing with Stock Market Data](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4992945)__: A study using stock market data found a pattern of failure among different groups of listed firms, significantly linked to firm characteristics associated with well-known stock anomalies. (2024-10-19, shares: 2) · https://www.ml-quant.com/papers/ssrn/4992945/
- __[Leverage Corrections in ETF Price Discovery](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4993940)__: New measures introduced in a study show that regular ETFs dominate the price discovery process for the SP 500 index, correcting the leverage bias. (2024-10-18, shares: 2) · https://www.ml-quant.com/papers/ssrn/4993940/
- __[Beta Replication Challenges](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990063)__: The article discusses the challenges of trendfollowing investment strategies, suggesting replication of a broad index of funds as a solution, but warns of risks from regression-based replication. (2024-10-15, shares: 205) · https://www.ml-quant.com/papers/ssrn/4990063/
- __[Intelligent Forecasts in Portfolio Optimization](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4994190)__: The study proposes an optimization framework for the top 500 U.S. stocks, emphasizing the use of characteristic information for stable weights and consistent outperformance. (2023-03-21, shares: 2) · https://www.ml-quant.com/papers/ssrn/4994190/
- __[Hidden Liquidity on U.S. Exchanges](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4988855)__: The paper investigates hidden liquidity on U.S. equity exchanges, showing that interaction leads to price improvement and suggests an AI model to predict where these orders may appear. (2024-10-15, shares: 4) · https://www.ml-quant.com/papers/ssrn/4988855/
- __[Futures Market Information in Forecasting](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4989500)__: The study uses Chinese futures market data to predict macroeconomic variables, finding that financial futures data slightly improve GDP forecasts, while commodity futures significantly enhance PPI forecasts. (2024-10-01, shares: 3) · https://www.ml-quant.com/papers/ssrn/4989500/
- __[Fallacies in CAPM Intuition](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990174)__: The article argues that firm-specific risk significantly impacts beta and the Market Risk Premium (MRP), contradicting the standard intuition for the CAPM. (2024-10-12, shares: 2) · https://www.ml-quant.com/papers/ssrn/4990174/
- __[Hedging Strategy with Transaction Costs](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990913)__: The traditional binomial model for derivative security pricing is enhanced to include transaction costs, portfolio constraints, and dividend-paying assets, aiming to identify the best hedging strategy. (2024-04-01, shares: 2) · https://www.ml-quant.com/papers/ssrn/4990913/
- __[Sustainable Fund Flows Comparison](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4989575)__: An analysis of over 23,000 equity mutual funds and ETFs reveals that self-declared sustainability statements in fund prospectuses drive retail and institutional fund flows more than external sustainability ratings. (2024-06-04, shares: 22) · https://www.ml-quant.com/papers/ssrn/4989575/
- __[Activist Investing: Credit Effects](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4991711)__: Credit Effects: Hedge fund activism increases firm value but negatively impacts existing bondholders, with those selling target firm debt post-intervention experiencing higher losses. (2024-10-14, shares: 2) · https://www.ml-quant.com/papers/ssrn/4991711/
- __[Retail Investor Attention and Fund Performance](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4992233)__: A metric called Total Views, which measures retail investor attention to mutual funds, can predict retail fund flows and performance, with high-performing funds attracting more inflows. (2024-09-20, shares: 2) · https://www.ml-quant.com/papers/ssrn/4992233/
- __[Investment Capital for Green Firms](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4990603)__: Firms that highlight environmental issues in their prospectus have a lower implied cost of capital at IPOs, as per a study of stock listings at Euronext Oslo, with no correlation found between underpricing and environmental issues. (2024-10-14, shares: 3) · https://www.ml-quant.com/papers/ssrn/4990603/

## RePEc

### Finance

- __[Metaalgorithm for Portfolio Selection](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F01605682.2023.2295975%3Bh%3Drepec%3Ataf%3Atjorxx%3Av%3A75%3Ay%3A2024%3Ai%3A10%3Ap%3A2032-2051)__: The article discusses the use of Online Gradient Update and Online Newton Update meta-algorithms in online portfolio selection, showing they can reduce risk and improve price prediction. (2024-10-23, shares: 19) · https://www.ml-quant.com/papers/repec/taf-tjorxx-v-75-y-2024-i-10-p-2032-2051/
- __[Sustainable Investments Optimization](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10479-024-06189-w%3Bh%3Drepec%3Aspr%3Aannopr%3Av%3A341%3Ay%3A2024%3Ai%3A2%3Ad%3A10.1007_s10479-024-06189-w)__: A new portfolio optimization approach is developed, incorporating environmental, social responsibility, and corporate governance aspects, providing an efficient alternative to large-scale covariance matrix estimation. (2024-10-23, shares: 18) · https://www.ml-quant.com/papers/repec/spr-annopr-v-341-y-2024-i-2-d-10-1007-s10479-024-06189-w/
- __[Evolution of Chinese Futures](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Fecpo.12296%3Bh%3Drepec%3Abla%3Aecopol%3Av%3A36%3Ay%3A2024%3Ai%3A3%3Ap%3A1416-1449)__: The impact of high-frequency and algorithmic trading on China's market quality is studied, showing improvements in contract continuity, liquidity diversification, and reduced costs for investors. (2024-10-23, shares: 17) · https://www.ml-quant.com/papers/repec/bla-ecopol-v-36-y-2024-i-3-p-1416-1449/
- __[Linear Factor Models in U.K. Stocks](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11156-024-01286-0%3Bh%3Drepec%3Akap%3Arqfnac%3Av%3A63%3Ay%3A2024%3Ai%3A3%3Ad%3A10.1007_s11156-024-01286-0)__: The efficiency of ten linear factor models in U.K. stock returns is examined, with the eight-factor model performing best when dynamic trading and conditioning information are considered. (2024-10-23, shares: 12) · https://www.ml-quant.com/papers/repec/kap-rqfnac-v-63-y-2024-i-3-d-10-1007-s11156-024-01286-0/
- __[FourFactor Model with Factor Momentum](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0927538X24002634%3Bh%3Drepec%3Aeee%3Apacfin%3Av%3A87%3Ay%3A2024%3Ai%3Ac%3As0927538x24002634)__: A new four-factor model focusing on the momentum effect in China is introduced, proving to be superior over traditional models in explaining stock, industry, and regional momentum. (2024-10-23, shares: 11) · https://www.ml-quant.com/papers/repec/eee-pacfin-v-87-y-2024-i-c-s0927538x24002634/

### Statistical

- __[Economic Growth Forecasting in Sverdlovsk](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournalaer.ru%2F%2Ffileadmin%2Fuser_upload%2Fsite_15934%2F2024%2F05_Balungu_Kumar.pdf%3Bh%3Drepec%3Aaiy%3Ajnjaer%3Av%3A23%3Ay%3A2024%3Ai%3A3%3Ap%3A674-695)__: A study reveals that machine learning models, particularly the random forest model, are more effective than traditional models in predicting economic growth in Russia's Sverdlovsk region. (2024-10-23, shares: 28) · https://www.ml-quant.com/papers/repec/aiy-jnjaer-v-23-y-2024-i-3-p-674-695/
- __[Online Investor Sentiment and Market Risk](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.mdpi.com%2F2227-7390%2F12%2F20%2F3192%2Fpdf%3Bh%3Drepec%3Agam%3Ajmathe%3Av%3A12%3Ay%3A2024%3Ai%3A20%3Ap%3A3192-%3Ad%3A1497063)__: Machine learning techniques like extreme gradient boosting and random forest significantly improve the prediction of aggregated stock market risk premium based on online investor sentiment, enhancing portfolio performance. (2024-10-23, shares: 22) · https://www.ml-quant.com/papers/repec/gam-jmathe-v-12-y-2024-i-20-p-3192-d-1497063/
- __[Firm Performance Prediction with Nonfinancial Disclosures](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.emerald.com%2Finsight%2Fcontent%2Fdoi%2F10.1108%2FJAEE-07-2023-0205%2Ffull%2Fhtml%3Futm_source%3Drepec%26utm_medium%3Dfeed%26utm_campaign%3Drepec%3Bh%3Drepec%3Aeme%3Ajaeepp%3Ajaee-07-2023-0205)__: A study in Pakistan shows that including nonfinancial disclosures such as narrative disclosure tone and corporate governance indicators in financial predictive models greatly improves firm performance prediction. (2024-10-23, shares: 18) · https://www.ml-quant.com/papers/repec/eme-jaeepp-jaee-07-2023-0205/
- __[AI and Big Data Tokens: Herding and Cognition](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS027553192400299X%3Bh%3Drepec%3Aeee%3Ariibaf%3Av%3A72%3Ay%3A2024%3Ai%3Apa%3As027553192400299x)__: Herding and Cognition: Research indicates that investors in AI and big data token markets tend to follow the crowd in stable markets and low volume days, but act independently in volatile markets and high volume days. (2024-10-23, shares: 17) · https://www.ml-quant.com/papers/repec/eee-riibaf-v-72-y-2024-i-pa-s027553192400299x/
- __[ERM Impact on XBANK Companies](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1057%2Fs41599-024-03871-z%3Bh%3Drepec%3Apal%3Apalcom%3Av%3A11%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1057_s41599-024-03871-z)__: The research investigates the link between enterprise risk management adaptation and the performance, value, and risks of ten banking firms listed on the Borsa Istanbul Banks index from 2019 to 2022. (2024-10-23, shares: 12) · https://www.ml-quant.com/papers/repec/pal-palcom-v-11-y-2024-i-1-d-10-1057-s41599-024-03871-z/
- __[Graduate Employability Model in Croatia](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.2478%2Fbsrj-2024-0006%3Bh%3Drepec%3Abit%3Absrysr%3Av%3A15%3Ay%3A2024%3Ai%3A1%3Ap%3A110-130%3An%3A1006)__: The study uses a model to analyze the transition from study to work for Croatian graduates, finding that cultural, human, and bridging social capital increase the chances of quickly finding suitable employment post-graduation. (2024-10-23, shares: 11) · https://www.ml-quant.com/papers/repec/bit-bsrysr-v-15-y-2024-i-1-p-110-130-n-1006/
- __[Green Bond Cost Optimization](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Ffor.3142%3Bh%3Drepec%3Awly%3Ajforec%3Av%3A43%3Ay%3A2024%3Ai%3A7%3Ap%3A2607-2634)__: The research creates a multi-stage stochastic model to predict the issuance of green bonds, determining that the model effectively identifies the most cost-effective conditions for issuing these bonds considering various risk factors. (2024-10-23, shares: 10) · https://www.ml-quant.com/papers/repec/wly-jforec-v-43-y-2024-i-7-p-2607-2634/
- __[Microsoft Copilot and Finance Workforce](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.carijournals.org%2Fjournals%2Findex.php%2FIJF%2Farticle%2Fview%2F1918%2F2296%3Bh%3Drepec%3Abhx%3Aojtijf%3Av%3A9%3Ay%3A2024%3Ai%3A3%3Ap%3A32-41%3Aid%3A1918)__: The paper explores the potential impact of the AI tool, Microsoft Copilot, on the finance workforce, suggesting a future balance between automation, skill evolution, and ethical considerations. (2024-10-23, shares: 10) · https://www.ml-quant.com/papers/repec/bhx-ojtijf-v-9-y-2024-i-3-p-32-41-id-1918/

### Machine Learning

- __[Machine Learning for CPI Forecasting](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Frjmf.econs.online%2Fupload%2Fiblock%2F595%2Fnf16exkayd8naa2h0ycp85tb11rrzryv%2FBottom-up-Inflation-Forecasting-Using-Machine-Learning-Methods.pdf%3Bh%3Drepec%3Abkr%3Ajournl%3Av%3A83%3Ay%3A2024%3Ai%3A3%3Ap%3A23-44)__: Machine learning models like gradient boosting and regularised regression offer more precise inflation predictions than traditional methods, especially when applied to large data sets in a component-aggregated manner. (2024-10-23, shares: 27) · https://www.ml-quant.com/papers/repec/bkr-journl-v-83-y-2024-i-3-p-23-44/
- __[Forecasting German Recessions with ML](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.econstor.eu%2Fbitstream%2F10419%2F303050%2F1%2F1903197465.pdf%3Bh%3Drepec%3Azbw%3Adicedp%3A303050)__: Machine learning models, using a limited number of indicators and Sequential Floating Forward Selection, are successful in predicting German business cycles, especially during times of quantitative easing. (2024-10-23, shares: 23) · https://www.ml-quant.com/papers/repec/zbw-dicedp-303050/
- __[Importance of Hyperparameters in ML](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.cambridge.org%2Fcore%2Fproduct%2Fidentifier%2FS2049847023000614%2Ftype%2Fjournal_article%3Bh%3Drepec%3Acup%3Apscirm%3Av%3A12%3Ay%3A2024%3Ai%3A4%3Ap%3A841-848_9)__: A study shows that only 20.31% of machine learning-related political science papers published from 2016 to 2021 disclose their hyperparameters and tuning methods, indicating a need for more transparency and robustness in machine learning models. (2024-10-23, shares: 21) · https://www.ml-quant.com/papers/repec/cup-pscirm-v-12-y-2024-i-4-p-841-848-9/
- __[Collusion Detection in Public Procurement](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs42001-024-00293-4%3Bh%3Drepec%3Aspr%3Ajcsosc%3Av%3A7%3Ay%3A2024%3Ai%3A2%3Ad%3A10.1007_s42001-024-00293-4)__: A new algorithm has been developed to identify collusion in public procurement auctions, revealing a high probability of such practices in Turkey and Europe, leading to increased procurement costs. (2024-10-23, shares: 18) · https://www.ml-quant.com/papers/repec/spr-jcsosc-v-7-y-2024-i-2-d-10-1007-s42001-024-00293-4/
- __[Fake News Detection Methods](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fabs%2F10.1142%2FS0219649224500758%3Bh%3Drepec%3Awsi%3Ajikmxx%3Av%3A23%3Ay%3A2024%3Ai%3A05%3An%3As0219649224500758)__: A predictive model using linguistic features has been created to detect fake news articles, with the most accurate model being generated through logistic regression and feature hashing vectorisation. (2024-10-23, shares: 16) · https://www.ml-quant.com/papers/repec/wsi-jikmxx-v-23-y-2024-i-05-n-s0219649224500758/
- __[Crude Oil Futures Volatility Forecasting with Machine Learning](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Ffor.3077%3Bh%3Drepec%3Awly%3Ajforec%3Av%3A43%3Ay%3A2024%3Ai%3A5%3Ap%3A1422-1446)__: Machine learning forecasts have been found to provide superior predictions for the volatility of WTI futures prices, leading to economic gains when used in portfolio construction. (2024-10-23, shares: 14) · https://www.ml-quant.com/papers/repec/wly-jforec-v-43-y-2024-i-5-p-1422-1446/
- __[Improved NHL Draft Predictions with Scouting Reports](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1515%2Fjqas-2024-0047%3Bh%3Drepec%3Abpj%3Ajqsprt%3Av%3A20%3Ay%3A2024%3Ai%3A4%3Ap%3A331-349%3An%3A1006)__: Large Language Models (LLMs) are being used to enhance predictions of NHL draft outcomes by extracting information from scouting report texts and combining it with on-ice statistics. (2024-10-23, shares: 11) · https://www.ml-quant.com/papers/repec/bpj-jqsprt-v-20-y-2024-i-4-p-331-349-n-1006/

### Historical Trending

- __[Asset Pricing from News](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frfs%2Fhhad042%3Bh%3Drepec%3Aoup%3Arfinst%3Av%3A36%3Ay%3A2023%3Ai%3A12%3Ap%3A4759-4787.)__: A pricing model using news text from The Wall Street Journal predicts future investment opportunities better than standard models, aligning with the ICAPM. (2023-09-19, shares: 6) · https://www.ml-quant.com/papers/repec/oup-rfinst-v-36-y-2023-i-12-p-4759-4787/
- __[Partisanship in Finance](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frfs%2Fhhad029%3Bh%3Drepec%3Aoup%3Arfinst%3Av%3A36%3Ay%3A2023%3Ai%3A11%3Ap%3A4373-4416.)__: SEC Commissioners showed increased partisanship from 2010-2019, as seen in SEC rules language and voting behavior, while the Federal Reserve Board remained nonpartisan. (2023-07-22, shares: 4) · https://www.ml-quant.com/papers/repec/oup-rfinst-v-36-y-2023-i-11-p-4373-4416/
- __[Regulatory Intensity and Exposure](https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frfs%2Fhhad001%3Bh%3Drepec%3Aoup%3Arfinst%3Av%3A36%3Ay%3A2023%3Ai%3A8%3Ap%3A3311-3347.)__: Increased regulatory intensity raises costs and prompts companies, especially financially constrained ones, to cut capital investment, hire less, and lobby more. (2023-12-21, shares: 4) · https://www.ml-quant.com/papers/repec/oup-rfinst-v-36-y-2023-i-8-p-3311-3347/
- __[EU News Engagement on Facebook](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.cogitatiopress.com%2Fpoliticsandgovernance%2Farticle%2Fview%2F4775%3Bh%3Drepec%3Acog%3Apoango%3Av10%3Ay%3A2022%3Ai%3A1%3Ap%3A121-132)__: Study of social media engagement with EU news shows negativity increases reactions and shares but decreases comments, while emotionality decreases reactions and shares but increases comments. (2022-02-24, shares: 4) · https://www.ml-quant.com/papers/repec/cog-poango-v10-y-2022-i-1-p-121-132/
- __[Collusion Regulation](https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1146%2Fannurev-economics-051520-021936%3Bh%3Drepec%3Aanr%3Areveco%3Av%3A15%3Ay%3A2023%3Ap%3A177-204)__: The regulation of collusion, including detection, prosecution, and firm-regulator bargaining, is explored, highlighting the need for accurate legal system modeling. (2023-04-26, shares: 1) · https://www.ml-quant.com/papers/repec/anr-reveco-v-15-y-2023-p-177-204/

## Machine learning

### Recently Published

- __[Scaling Autoregressive Text-to-image Generative Models](https://arxiv.org/abs/2410.13863)__: The study explores text-to-image generation, finding continuous token-based models offer superior visual quality and random-order models score higher on the GenEval benchmark, leading to a new model, Fluid. (2024-10-17, shares: 194) · https://www.ml-quant.com/papers/arxiv/2410.13863/
- __[Decoupling Visual Encoding for Multimodal Understanding](https://arxiv.org/abs/2410.13848)__: The paper presents Janus, a framework that separates visual encoding into different pathways for multimodal understanding and generation, offering improved performance and flexibility. (2024-10-17, shares: 85) · https://www.ml-quant.com/papers/arxiv/2410.13848/
- __[Bridging Training-Inference Gap in LLMs with Self-Generated Tokens](https://arxiv.org/abs/2410.14655)__: The paper suggests two methods to address the discrepancy between training and inference time in language models, resulting in enhanced performance in tasks like summarization and question-answering. (2024-10-18, shares: 43) · https://www.ml-quant.com/papers/arxiv/2410.14655/
- __[Connecting Gaussian Splatting and Depth](https://arxiv.org/pdf/2410.13862)__: The study introduces DepthSplat, a model that combines Gaussian splatting and depth estimation, leading to improved performance in depth estimation and novel view synthesis. (2024-10-17, shares: 39) · https://www.ml-quant.com/papers/arxiv/2410.13862/
- __[Differentiable Robot Rendering](https://arxiv.org/abs/2410.13851)__: The paper presents a method for differentiable robot rendering, enabling the visual appearance of a robot to be directly differentiable with respect to its control parameters, useful for reconstructing robot poses from images and controlling robots through vision language models. (2024-10-17, shares: 16) · https://www.ml-quant.com/papers/arxiv/2410.13851/
- __[Deep Ensembles and Fairness](https://arxiv.org/pdf/2410.13831)__: Deep Ensembles, a type of AI, can unintentionally favor certain groups, leading to unfair benefits; this can be reduced through post-processing without affecting performance. (2024-10-17, shares: 15) · https://www.ml-quant.com/papers/arxiv/2410.13831/
- __[Efficient Video Representation](https://arxiv.org/abs/2410.16267)__: XGen-MM-Vid (BLIP-3-Video) is a language model for videos that captures temporal information efficiently, offering accuracy similar to larger models but with greater efficiency. (2024-10-21, shares: 13) · https://www.ml-quant.com/papers/arxiv/2410.16267/
- __[Safe RL for Autonomous Driving](https://arxiv.org/abs/2410.14468)__: The Simple to Complex Collaborative Decision framework uses reinforcement learning to enhance safety and efficiency in autonomous vehicle decision-making, guided by a teacher model to avoid danger. (2024-10-18, shares: 10) · https://www.ml-quant.com/papers/arxiv/2410.14468/
- __[Agent-to-Sim Behavior Models](https://arxiv.org/abs/2410.16259)__: Agent-to-Sim (ATS) is a system that learns interactive behavior models of 3D agents from video collections, allowing transfer from real-life videos to a behavior simulator. (2024-10-21, shares: 10) · https://www.ml-quant.com/papers/arxiv/2410.16259/
- __[SimLayerKV Cache Reduction](https://arxiv.org/abs/2410.13846)__: SimLayerKV is a technique that minimizes memory usage in large language models by identifying and reducing cache in lazy layers, achieving significant cache compression with minimal performance loss. (2024-10-17, shares: 8) · https://www.ml-quant.com/papers/arxiv/2410.13846/

### Historical Trending

- __[Multitask Sparse Parity Problem](https://arxiv.org/abs/2404.17563)__: The research provides a framework for understanding how new skills develop in deep learning models, including formulas for skill emergence and the relationship between loss, training time, data size, model size, and optimal compute. (2024-04-26, shares: 49) · https://www.ml-quant.com/papers/arxiv/2404.17563/
- __[ML Input Data Pipelines with cedar](http://arxiv.org/abs/2401.08895)__: The article presents cedar, a programming framework for machine learning data pipelines, which enhances performance by applying complex optimizations, resulting in up to 10.65x improvement compared to existing systems. (2024-01-17, shares: 23) · https://www.ml-quant.com/papers/arxiv/2401.08895/
- __[Scalable Machine Unlearning with S3T](https://arxiv.org/pdf/2406.16257v1)__: The research introduces S3T, a framework that can efficiently remove the impact of a specific training data instance from a trained machine learning model without the need for complete retraining. (2024-06-24, shares: 16) · https://www.ml-quant.com/papers/arxiv/2406.16257/
- __[EasyRec: Recommendation Language Models](http://arxiv.org/abs/2408.08821v1)__: Recommendation Language Models: The study presents EasyRec, a method that combines text-based semantic understanding with collaborative signals for recommender systems, showing improved performance in text-based zero-shot recommendation situations. (2024-08-16, shares: 15) · https://www.ml-quant.com/papers/arxiv/2408.08821/
- __[D Gaussian Reconstruction Model](https://arxiv.org/pdf/2410.12781)__: The paper introduces Long-LRM, a 3D Gaussian reconstruction model that can reconstruct large scenes from a long sequence of images, offering performance similar to optimization-based methods but with greater efficiency. (2024-10-16, shares: 13) · https://www.ml-quant.com/papers/arxiv/2410.12781/

## Papers with code

### Trending

- __[SegFormer: Semantic Segmentation with Transformers](https://github.com/VikParuchuri/surya)__: Semantic Segmentation with Transformers: SegFormer is a novel framework for semantic segmentation, merging Transformers with multilayer perception decoders. (2024-10-17, shares: 11920)
- __[ArenaHard: Crowdsourced Data Benchmarks](https://github.com/lmarena/arena-hard-auto)__: Crowdsourced Data Benchmarks: The expansion of Large Language Models (LLMs) requires the ongoing creation of advanced benchmarks for assessing these models. (2024-10-19, shares: 582)
- __[Janus: Multimodal Understanding and Generation](https://github.com/deepseek-ai/janus)__: Multimodal Understanding and Generation: Janus is an innovative autoregressive framework that combines multimodal understanding and generation. (2024-10-21, shares: 573)
- __[TaskGen: Memory-Infused Agentic Framework](https://github.com/simbianai/taskgen)__: Memory-Infused Agentic Framework: TaskGen is a freely available framework that employs an agent to dissect and resolve intricate tasks. (2024-10-21, shares: 428)
- __[ASFT Supervised Fine-Tuning with Absolute Likelihood](https://github.com/turbo-llm/turbo-alignment)__: The study contrasts ASFT with DPO and its versions, utilizing the latest instruction-tuned model Llama3, fine-tuned on UltraFeedback and HHRLHF. (2024-10-19, shares: 249)

### Rising

- __[Global Singing Corpus](https://github.com/gtsinger/gtsinger)__: The progress of personalized singing tasks is hindered by the lack of high-quality, diverse singing datasets, which often suffer from poor quality, limited language and singer diversity, and unsuitable task suitability. (2024-10-19, shares: 195)
- __[Efficient LLM Inference](https://github.com/mit-han-lab/duo-attention)__: The DuoAttention framework, which utilizes a full KV cache for retrieval heads and a lightweight constant-length KV cache for streaming heads, is introduced, offering reduced memory and latency without compromising long-context abilities. (2024-10-17, shares: 183)
- __[DepthSplat Connection](https://github.com/cvg/depthsplat)__: Gaussian splatting and single-multiview depth estimation, two separate fields of study, are discussed. (2024-10-19, shares: 131)
- __[SelfSupervised Speaker Diarization](https://github.com/butspeechfit/diarizen)__: The article discusses the application of WavLM in tackling the problem of insufficient data in neural diarization training. (2024-10-21, shares: 113)
- __[Shortcut Diffusion Models](https://github.com/kvfrans/shortcut-models)__: The article presents shortcut models, a type of generative models that utilize a single network and training phase to generate high-quality samples. (2024-10-21, shares: 100)
- __[MixtureofHead Attention](https://github.com/skyworkai/moh)__: The article shows that multihead attention can be represented in a form of summation. (2024-10-17, shares: 63)

## GitHub

### Finance

- __[DQL for Algorithmic Trading](https://github.com/adamd1985/Deep-Q-Learning-Applied-to-Algorithmic-Trading)__: The article explores the use of Deep QLearning for algorithmic trading strategies. (2024-03-06, shares: 12)
- __[RL for Finance Code](https://github.com/yhilpisch/rl4f)__: The article offers the coding resources for a book on reinforcement learning in financial applications. (2024-10-17, shares: 5)
- __[Pyramidal Flow Matching for Video](https://github.com/jy0205/Pyramid-Flow)__: The article provides the coding for Pyramidal Flow Matching, a technique for efficient video generation modeling. (2024-10-06, shares: 1858)
- __[Fast Data Pipeline Building with Ploomber](https://github.com/ploomber/ploomber)__: The article introduces a quick method for creating versatile data pipelines that can be developed and deployed flexibly. (2020-01-20, shares: 3503)

### Trending

- __[PPS in Python](https://github.com/8080labs/ppscore)__: The article Predictive Power Score PPS in Python explains how Python can be used to apply the Predictive Power Score, a tool for data analysis. (2020-04-17, shares: 1112)
- __[Official Inference Framework](https://github.com/microsoft/BitNet)__: Official inference framework for 1bit LLMs introduces a formal framework for making predictions using 1bit Long-Short Term Memory models. (2024-08-05, shares: 761)
- __[LightRAG RetrievalAugmented Generation](https://github.com/HKUDS/LightRAG)__: LightRAG Simple and Fast RetrievalAugmented Generation presents LightRAG, an efficient technique for retrieval-augmented generation in machine learning. (2024-10-02, shares: 3908)
- __[Agent in Terminal](https://github.com/ErikBjare/gptme)__: Your agent in your terminal equipped with local tools writes code uses the terminal browses the web vision discusses a virtual assistant capable of coding, using the terminal, and web browsing with local tools. (2023-03-24, shares: 2098)
- __[Sandboxie](https://github.com/sandboxie/sandboxie)__: The Sandboxie application reviews Sandboxie, a software that creates a safe virtual environment for testing and running programs. (2020-04-14, shares: 3570)

## News

### Quantitative

- __[Hedge Fund Trading Limited](https://www.hedgeweek.com/tougher-risk-parameters-curb-hedge-fund-trading-activity-says-beacon-platform/)__: A Beacon Platform Inc. survey shows hedge funds are cutting back on trading due to tighter risk controls, particularly in credit trading. (2024-10-17, shares: 7)
- __[Hedge Funds Recruit Segantii Alumni](https://www.hedgeweek.com/rival-hedge-funds-snap-up-segantii-alumni-amid-insider-trading-scandal/)__: Bloomberg reports that over half of the employees who left Segantii Capital Management since May have secured jobs at competing hedge funds amidst insider trading allegations. (2024-10-18, shares: 5)
- __[DTCC Enhances Fixed Income Data](https://www.hedgeweek.com/dtcc-enhances-fixed-income-security-master-file-data-offering/)__: The Depository Trust & Clearing Corporation (DTCC) has launched an enhanced fixed income security master file data service, providing more frequent and comprehensive data. (2024-10-21, shares: 5)
- __[Nordea Strategist Starts Hedge Fund](https://www.hedgeweek.com/former-nordea-strategist-teams-with-asgard-am-for-hedge-fund-launch/)__: Andreas Steno Larsen, founder of Steno Research and former Nordea strategist, is starting a new hedge fund, AsgardSteno Global Macro Fund, with Asgard Asset Management. (2024-10-17, shares: 4)
- __[Hazeltree Collaborates with Necto for Bank Access](https://www.hedgeweek.com/hazeltree-partners-with-fintech-necto-to-enhance-global-bank-access/)__: Hazeltree, a cloud-based treasury and liquidity management solutions provider, has teamed up with Necto API, a fintech company that consolidates bank APIs. (2024-10-21, shares: 4)
- __[Brevan Howard's Crypto Move](https://www.hedgeweek.com/sensible-regulations-prompt-brevan-howard-to-conduct-significant-crypto-trading-from-uae/)__: Hedge fund firm Brevan Howard is trading cryptocurrencies from the UAE due to its favorable regulatory environment. (2024-10-22, shares: 3)
- __[Abra Appoints Sales Head](https://www.hedgeweek.com/abra-appoints-electronic-trading-veteran-as-global-head-of-institutional-sales/)__: David Streltsoff has been appointed as the Global Head of Institutional Sales at digital asset platform, Abra. (2024-10-22, shares: 3)
- __[Quants Target Betting](https://www.efinancialcareers.com/news/quants-sports-betting)__: The article discusses the duties and importance of quantitative sports traders. (2024-10-22, shares: 3)
- __[Tribecas Liu Hires CEO](https://www.hedgeweek.com/tribecas-liu-hires-distribution-head-ceo-for-new-hedge-fund/)__: Jun Bei Liu, ex-manager at Tribeca Investment Partners, has appointed Jason Todd as CEO for her new long/short fund launching next year. (2024-10-18, shares: 3)
- __[Hedge Funds Buy Tech Stocks](https://www.hedgeweek.com/hedge-funds-buy-us-tech-stocks-at-fastest-pace-in-five-months/)__: According to Goldman Sachs, global hedge funds are buying US tech stocks at the fastest rate in five months as Q3 earnings season starts. (2024-10-21, shares: 2)

### Miscellaneous

- __[Elliott Acquires Klarna's UK BNPL Loans](https://www.hedgeweek.com/elliott-to-buy-30n-of-klarnas-uk-bnpl-loans/)__: Klarna is said to be selling a majority of its UK buy now pay later loan portfolio to US hedge fund Elliott, potentially freeing up £30bn for new loans. (2024-10-17, shares: 2)
- __[Quant Managers Pursue Gains with AI and Tech](https://news.google.com/rss/articles/CBMimgFBVV95cUxNN0dlNU5fM29aZUg5R3NzUGY2T2RPbGRtdFJ5R0VoRGlBMWdBTWJkYTY5M29TckxJUDd4Qnh5VlJlb0k4OG5tV1FKRnZrcmxSWExGWlZ4MlZTR3Y5bkdoUE1SSEVKdEM2RmZNQk55T0F2YjFUZ0RIYjJWczBiVFMyeUxHWEFYN1lZMkI1YlRKT1pVLXFZMC1xVnF30gGaAUFVX3lxTE03R2U1Tl8zb1plSDlHc3NQZjZPZE9sZG10UnlHRWhEaUExZ0FNYmRhNjkzb1NyTElQN3hCeHlWUmVvSTg4bm1XUUpGdmtybFJYTEZaVngyVlNHdjluR2hQTVJIRUp0QzZGZk1CTnlPQXZiMVRnREhiMlZzMGJUUzJ5TEdYQVg3WVkyQjViVEpPWlUtcVkwLXFWcXc?oc=5)__: Quant managers are utilizing AI and other technologies for potential financial gains. (2024-10-21, shares: 2)
- __[Millennium Sticks with Fundraising Cap](https://www.hedgeweek.com/millennium-to-stick-with-10bn-fundraising-cap-despite-seeing-20bn-in-investor-interest/)__: Despite high interest, Millennium Management is maintaining its original £10bn fundraising goal for new hedge fund capital. (2024-10-23, shares: 2)
- __[Evercore Data Chief Joins Goldman Sachs](https://www.efinancialcareers.com/news/evercore-data-chief-joins-goldman-veterans-investment-firm)__: Former employees of Goldman Sachs have reunited. (2024-10-21, shares: 2)
- __[JPMorgan Reports Surge in Trump Trades](https://www.hedgeweek.com/jpmorgan-sees-surge-in-hedge-fund-trump-trades/)__: Global hedge funds are leaning towards stocks that could profit from a potential Donald Trump victory in the US presidential race. (2024-10-22, shares: 2)
- __[Citadel Hires Equities Engineering Director](https://www.efinancialcareers.com/news/citadel-hires-balyasny-director-to-lead-equities-engineering-william-pan-harold-sultan)__: A hedge fund is growing its team by hiring professionals from the fintech industry. (2024-10-22, shares: 1)
- __[Starboard Acquires Stake in BandAid Owner](https://www.hedgeweek.com/activist-starboard-acquires-stake-in-band-aid-owner-kenvue/)__: Activist hedge fund firm, Starboard Value, has acquired a stake in Kenvue, a company known for brands like BandAid, Listerine, and Tylenol. (2024-10-22, shares: 1)
- __[Nomuras Algo Trading Arm Losing Staff](https://www.efinancialcareers.com/news/nomura-s-zero-bonus-algo-trading-arm-leaking-staff-to-jp-morgan-and-fintechs)__: The company is experiencing a significant employee departure due to various factors. (2024-10-17, shares: 1)
- __[OTC Partners with B2C2](https://www.hedgeweek.com/4otc-partners-with-b2c2-to-provide-low-latency-connectivity-to-digital-assets-exchanges/)__: OTC and B2C2 have teamed up to provide ultra-fast connectivity for digital assets and FX through 1API service to multiple global exchanges. (2024-10-22, shares: 1)
- __[Digital Assets Funds Inflows Spike](https://www.hedgeweek.com/digital-assets-funds-see-largest-weekly-inflows-since-july/)__: According to CoinShares, digital asset inflows hit a record $2.2bn last week, the highest since July, driven by optimism over a potential Republican US election win. (2024-10-22, shares: 1)

## Podcasts

### Quantitative

- __[Portable Alpha](https://resolve-gestalt-university.captivate.fm/episode/diversification-2-0-mastering-the-art-of-portable-alpha)__: The podcast explores Portable Alpha, a financial strategy that combines asset classes with positive expected returns and core assets to enhance market performance, diversification, and client behavior. (2024-10-19, shares: 18)
- __[Credit Trends](https://atanyrate.podbean.com/e/spreadbites-%e2%80%92-asia-credit-conference-vibes-data-center-deliberations-and-credit-derivative-refamiliarization-draft/)__: The Spreadbites podcast by J.P. Morgan experts discusses significant trends in global credit markets. (2024-10-23, shares: 15)
- __[AI in Finance](https://garpcast.libsyn.com/generative-ai-trends-benefits-and-risks)__: Bo Xu from Boston Consulting Group talks about the applications, challenges, and effects of generative AI in financial risk management, including data leakage, intellectual property protection, and third-party risk issues. (2024-10-17, shares: 9)
- __[GeoMacro Insights](https://sites.libsyn.com/244787/marko-papic-geomacro-lens-on-us-election-china-policy-markets)__: Marko Papic from BCA Research discusses the U.S. election, American foreign policy, the consumer-driven economy, and portfolio positioning in a podcast. (2024-10-17, shares: 8)
- __[London Sugar Recap](https://atanyrate.podbean.com/e/global-commodities-london-sugar-week-takeaways-%e2%80%93-weather-and-policy-driving-an-uncertain-outlook/)__: Tracey Allen discusses key insights from London Sugar Week, updates on the state of agricultural markets, and risks post World Food Day in the At Any Rate Podcast's Commodities edition. (2024-10-18, shares: 7)

### Related

- __[Global Dollar Strength](https://atanyrate.podbean.com/e/global-fx-dollar-strength-and-other-highlights-from-the-week/)__: JP. Morgan's podcast discusses the week's financial trends, including the performance of the dollar and various foreign exchange markets. (2024-10-18, shares: 6)
- __[US Rates](https://atanyrate.podbean.com/e/us-rates-strategy-fed-funds-as-a-gauge-of-liquidity/)__: JP. Morgan strategists explore the Federal Reserve's new tool, Reserve Demand Elasticity, which measures the sufficiency of reserves in the banking system. (2024-10-18, shares: 6)
- __[Tech Investing](https://chrt.fm/track/F81DEC/traffic.megaphone.fm/GLD6525783060.mp3?updated=1729114717)__: Chelsea Stoner of Battery Ventures shares her journey to Silicon Valley and her perspective on the venture capital and private equity sectors. (2024-10-22, shares: 5)
- __[PostPandemic Trends](https://pdcn.co/e/www.buzzsprout.com/2034153/episodes/15926986-danielle-dimartino-booth-on-post-pandemic-economic-trends-inflation-metrics-and-investment-strategies.mp3)__: Former Federal Reserve insider, Danielle DiMartino Booth, discusses economic trends, the shortcomings of traditional inflation metrics, and the possibility of further job cuts. (2024-10-19, shares: 4)
- __[Financial History with Dr. Bryan Taylor](https://traffic.megaphone.fm/TIFM6949715724.mp3?updated=1729200320)__: Dr. Bryan Taylor analyzes financial history over the past 800 years to enhance our understanding of future returns on stocks, bonds, and bills. (2024-10-18, shares: 4)

## X / Twitter

### Quantitative

- __[Commodity Factors and Pairs Trading Recap](https://twitter.com/quantseeker/status/1848674418475565423)__: The article explores various financial topics such as commodity factors, pairs trading in option markets, industry momentum, volatility, and suggests relevant blogs, repos, and podcasts. (2024-10-22, shares: 4)
- __[GenAI Synthetic Data Generation](https://twitter.com/carlcarrie/status/1848782756785905781)__: The article highlights the importance of Synthetic Data Generation in training new GenAI models and its various applications. (2024-10-22, shares: 1)
- __[Beta in Trend-Following: Promise and Pitfalls](https://twitter.com/choffstein/status/1846886538954654100)__: Promise and Pitfalls: The article reviews a new paper by sbraun27 and Juliusz Jabłecki on the benefits and challenges of replication in trend-following beta. (2024-10-17, shares: 1)
- __[Stock Return Prediction Signal Automation](https://twitter.com/carlcarrie/status/1848781004690850185)__: The article examines a paper on the use of OpenAI GPT4o for automating stock return prediction signals and its ability to adapt to market changes. (2024-10-22, shares: 0)
- __[Machine Learning Introduction](https://twitter.com/quantseeker/status/1848418239900226051)__: The article offers a basic understanding of Machine Learning. (2024-10-21, shares: 0)

### Miscellaneous

- __[Factor Portfolios & Transaction Costs](https://twitter.com/JOrdonezJr/status/1847657577112293686)__: The article explores a new episode focusing on the endurance of factor portfolios in the face of transaction costs. (2024-10-19, shares: 0)
- __[Useful Python Tips](https://twitter.com/quantseeker/status/1847595891974115779)__: The article offers helpful advice for Python coding. (2024-10-19, shares: 0)
- __[Market Punishment for Diversifiers](https://twitter.com/TheStalwart/status/1847236879986430032)__: The article debates the potential losses from market diversification versus investing in individual stocks. (2024-10-18, shares: 0)
- __[SigKAN Networks for Time Series](https://twitter.com/carlcarrie/status/1846710759985746160)__: The article presents SigKAN SignatureWeighted KolmogorovArnold Networks for Time Series, including Python GitHub and paper references. (2024-10-17, shares: 0)
- __[KolmogorovArnold TimeSeries Notebook](https://twitter.com/carlcarrie/status/1846708812234756431)__: The article showcases a raw KolmogorovArnold TimeSeries notebook. (2024-10-17, shares: 0)

## Reddit

### Quantitative

- __[Mystery](https://www.reddit.com/r/quant/comments/1g7omi3/does_anyone_know_what_happened_to_0xfdf/)__:  (2024-10-20, shares: 40)
- __[Pod](https://www.reddit.com/r/quant/comments/1g7drjn/things_to_consider_while_starting_pod/)__:  (2024-10-19, shares: 38)
- __[Student Struggles](https://www.reddit.com/r/quant/comments/1g7kl34/phd_student_aiming_for_quant_research_and_failing/)__:  (2024-10-19, shares: 67)
- __[Tool Creation](https://www.reddit.com/r/algotrading/comments/1g6xkxm/i_made_a_tool_that_hopefully_some_of_you_will/)__:  (2024-10-19, shares: 119)
- __[Focus Hours](https://www.reddit.com/r/quant/comments/1g672u1/how_much_hours_a_week_are_you_focused/)__:  (2024-10-18, shares: 78)

### Rising

- __[Collaborative Hiring Interviews](https://www.reddit.com/r/quant/comments/1g7pynu/time_for_a_change_pods_vs_collaborative_senior_vs/)__:  (2024-10-20, shares: 38)
- __[Fired After Training](https://www.reddit.com/r/quant/comments/1g7xjbw/fired_after_training_programme/)__:  (2024-10-20, shares: 89)
- __[Open Source Revenue Analysis](https://www.reddit.com/r/algotrading/comments/1g8n88v/revenue_breakdown_by_product_geography_based_on/)__:  (2024-10-21, shares: 33)
- __[Physics Post Doc Search](https://www.reddit.com/r/quant/comments/1g4whiw/physics_post_doc_trying_to_break_in/)__:  (2024-10-16, shares: 72)
- __[Quantitative Analyst Project](https://www.reddit.com/r/quantfinance/comments/1g79vzx/quantitative_analyst_project_group_being_created/)__:  (2024-10-19, shares: 40)