Hedge Fund Portfolio Construction
The article explores the use of PolyModel theory and deep learning in creating hedge fund portfolios for high returns and low risks.
8 shares12 citations todaySource ↗
Quant LetterNo. 60
August 2024, Week 1
154 items across 10 sections, as sent to readers on 7 August 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 154
- Papers
- 94
- Sections
- 10
- Issue
- No. 60
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
20 items
Finance10
Correlation in Limit Order Books
The study demonstrates the emergence of an Epps effect in two coupled diffusive limit order books using random walks.
7 shares2 citations todaySource ↗
PDEs for Interest Rate Derivatives Pricing
The paper discusses the use of partial differential equations in pricing interest rate derivatives under the generalized Forward Market Model.
7 shares2 citations todaySource ↗
NeuralFactors for Factor Learning
The research presents NeuralFactors, a machine-learning method for factor analysis that improves performance and efficiency in stock embedding.
6 shares4 citations todaySource ↗
Data Time Travel for Market Making
The article discusses the use of consistent data time travel in offline reinforcement learning for market making in limit order books.
6 sharesSource ↗
Risk Sharing with Lambda VaR
The research investigates risk distribution among multiple parties using Lambda value at risk, offering formulas for optimal allocations under differing beliefs.
5 shares5 citations todaySource ↗
Quadratic and Linear Mean-Variance Equilibria
The article reexamines quadratic and linear mean-variance equilibria, providing conditions for the existence and uniqueness of these equilibria in both discrete and continuous time.
5 sharesSource ↗
NeuralBeta: Estimating Beta
Estimating Beta: A new method, NeuralBeta, uses neural networks to estimate beta in finance, capable of handling both single and multiple variable scenarios and tracking beta's dynamic behavior.
5 shares4 citations todaySource ↗
Existence, Uniqueness, and Positivity of Volatility Solutions
The study confirms the existence and uniqueness of a solution to a path-dependent volatility model used to predict the price of an equity index and its spot volatility.
5 shares3 citations todaySource ↗
Machine Learning Relative Valuation of Municipal Bonds
A data-driven model using the CatBoost algorithm is introduced to create a supervised similarity framework for the muni bond market, outperforming both rule-based and heuristic-based methods.
5 shares3 citations todaySource ↗
Economics3
Voter Turnout in Two-Tier Elections
Research indicates that voter turnout is lower among minorities and higher among majorities in two-tier elections, with the proportional rule exacerbating this inequality more than the winner-takes-all rule.
3 sharesSource ↗
Human Space Usage during COVID-19
Analysis of cell phone data from over 60,000 people in England and Wales during the pandemic shows increased home and amenity visits, decreased workplace visits, and improved equality in amenity usage due to remote work.
2 sharesSource ↗
Efficient Asymmetric Causality Testing
A study discusses the importance of significant differences between positive and negative components in asymmetric causality tests, applying this theory to the interaction between the world's two largest financial markets.
2 sharesSource ↗
Miscellaneous3
Token Incentives for Secure Restaking
The research suggests that restaking protocols can be secured against limited attacks with proper incentive management, enhancing the model to determine necessary security measures.
5 shares6 citations todaySource ↗
Random Forest Proximity for Regression
The article introduces a new method for calculating quantile regressions from random forests, showing improved performance and efficiency in predicting the average daily volume of corporate bonds.
3 shares8 citations todaySource ↗
Peerinduced Fairness for Auditing
The study introduces peer-induced fairness, a new framework for auditing algorithmic fairness, differentiating between adverse outcomes due to algorithmic bias and individual shortcomings, and offering understandable feedback for those impacted by unfavorable decisions.
3 shares1 citation todaySource ↗
Crypto & Blockchain2
CLVR Algorithm for Transaction Ordering
The study introduces the CLVR algorithm, which organizes transactions to reduce price volatility in Automated Market Maker trading, balancing price stability and inequality reduction.
7 shares1 citation todaySource ↗
Stationarity Analysis of Bitcoin and S&P500
The paper finds that S&P500 price return achieves stationarity over 28 years, while Bitcoin price return only shows stationarity in periods of high volatility.
3 sharesSource ↗
Historical Trending2
Deep Hedging with Implied Volatility
A new hedging strategy for S&P 500 options is introduced, using a unique reinforcement learning algorithm and hybrid neural network, which performs better than traditional benchmarks in tests and simulations.
7 shares7 citations todaySource ↗
Deep Learning for Trading
A new machine learning algorithm for options trading strategies is presented, which uses market data to create optimal trading signals, showing notable performance improvements over current strategies, particularly when using turnover regularization.
6 shares4 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
27 items
Quantitative20
Unobservable Assets Comparison
CIOs find it challenging to compare liquid public assets and illiquid private assets due to real-world factors not reflected in reported returns.
5 sharesSource ↗
Machine Learning and Stock Market Index
A novel method combining machine learning and Monte Carlo simulation significantly improves returns in Chinese A-share markets, surpassing existing benchmarks.
3 sharesSource ↗
Mutual Funds and Asset Pricing Anomalies
The anomalies in stock returns, specifically low-risk and momentum, are due to demand pressure from mutual funds, especially those with high-beta assets.
3 sharesSource ↗
Score-Driven Model for Stock Indices
The BetatQVAR model, a volatility model for the t distribution, outperforms other models in statistical and density forecasting when used on 15 international stock indices.
3 sharesSource ↗
Analyzing Marginal Sharpe Ratio
The Marginal Sharpe Ratio (MSR) of an investment strategy considers the new strategy's impact on the portfolio's expected returns and the expected change in the portfolio risk profile due to diversification.
3 sharesSource ↗
Validity of Post hoc Explanations
The research explores the effectiveness of post hoc explainers, SHAP and LIME, in determining the significance of variables in machine learning models, questioning their accuracy in revealing the real marginal effects of these variables.
2 sharesSource ↗
Management Guidance
The research investigates the impact of management earnings guidance on market responses to earnings announcements in China, revealing that guidance increases trading volume but also raises bid-ask spreads and return volatility, especially for smaller, less visible firms.
4 sharesSource ↗
ECBs Impact
The research uses a GVAR model to study the effects of the European Central Bank's unconventional monetary policies on six Central and Eastern European countries, showing that these policies reduce liquidity spread and raise yield spread, suggesting increased economic activity and a preference for bonds among investors.
4 sharesSource ↗
Machine Learning for Lattice
The research introduces a machine-learning method for estimating the lattice constants of double perovskite materials, utilizing algorithms such as Support Vector Regression, Artificial Neural Networks, Gaussian Process Regression, and Ensemble Regression Tree methods.
3 sharesSource ↗
Hedge Accounting
The research shows that only derivatives designated for hedge accounting assist firms in overcoming underinvestment issues, implying that the Financial Accounting Standards Board has developed an effective signaling tool about the success of firms' hedging programs, but firms using complex strategies often cannot designate some of their successful derivatives due to strict criteria.
2 sharesSource ↗
Uninsured Depositors and Banks Risk
A study reveals that uninsured depositors react to changes in banks' economic value of equity and income-related interest rate risk, but not equity-related interest rate risk.
3 sharesSource ↗
Mutual Fund Ownership in China
A study finds that the identity of shareholders in Chinese fund management companies affects mutual fund returns, with foreign shareholders reducing returns and government control increasing them.
3 sharesSource ↗
Sparrow Search for Customer Retention
A new technique using machine learning models has been developed to predict and classify customer churn.
2 sharesSource ↗
Detecting Criminal Firms with ML
A machine learning algorithm has been created to identify private firms linked to organized crime using financial accounting data, with a 91.4% accuracy rate.
2 sharesSource ↗
Customer Churn Prediction in Telecom
Telecom operators are using a combination of customer segmentation and churn prediction, aided by four machine learning classifiers, to understand and retain customers at risk of leaving.
2 sharesSource ↗
Fintech in SWF Operations
The chapter explores the use of fintech like big data, blockchain, and AI in sovereign wealth funds, discussing their uses and potential issues.
2 sharesSource ↗
Transmissions Among Assets
The study examines volatility and return spillovers in a network of variables, emphasizing the portfolio diversification benefits of commodities, fiat currencies, and crypto coins.
2 sharesSource ↗
Stock Market Prediction with DL
The paper finds that Long Short-Term Memory networks are more accurate and reliable than Recurrent Neural Networks in predicting stock prices.
2 sharesSource ↗
Evaluating Risk Knowledge
The article proposes an adjustment to volatility forecasts to address potential risks, highlighting the economic value of risk knowledge in trading strategies.
3 sharesSource ↗
Dutch Book Argument for Banks
The paper outlines seven mathematical rules to prevent bank arbitrage, pointing out that existing models like Black-Scholes and the Heston model violate these rules.
2 sharesSource ↗
Financial7
Data Privacy Misconduct's Financial Impact
A study using Chinese regulatory data reveals that data privacy breaches through mobile apps can lead to significant financial losses for companies, especially those with high media visibility and in competitive data-driven sectors.
3 sharesSource ↗
Cryptocurrencies and Geopolitical Uncertainties
The Russia-Ukraine conflict has boosted the trading volume of most cryptocurrencies, particularly payment tokens and utility coins, with Ripple being significantly affected, as per an event study analysis.
3 shares7 citations todaySource ↗
Liquidity Providers in Price Jumps
Institutions are more likely to provide liquidity during price jumps than individuals, and higher order matching frequency encourages institutional liquidity provision but discourages it for individuals, based on an analysis of Taiwan Stock Exchange data.
2 sharesSource ↗
Investor Expertise in Private Investments
Professional investors favor venture capital managers with strong past returns, while individual investors prefer those with elite education but less emphasis on past performance, potentially accounting for a 20% return difference between the two groups, according to a limited partners' experiment.
2 sharesSource ↗
Mutual Fund Returns
Research shows no significant difference in mutual fund returns during earnings season compared to non-earnings season, indicating other factors are more influential.
6 sharesSource ↗
AI Trading
AI can predict NFT prices accurately, but struggles with emotional dividends, potentially leading to financial losses over time.
5 sharesSource ↗
Chinese Mutual Funds
A study on Chinese mutual funds reveals a significant positive risk premium, with lottery preferences accounting for nearly 40% of this premium, impacting investor decisions and risk regulation.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
30 items
Finance6
International Multi-Asset Fund Performance
Research shows that from 2004 to 2021, international multi-asset funds underperformed, but funds with more bonds did well in non-crisis times, while those with more equities did well in market downturns.
22 sharesSource ↗
Fintech Lending Impact on Small Business Credit
Fintech lenders are using alternative data and complex models to provide loans to small businesses in high-risk areas, potentially filling the credit void left by traditional lenders.
22 sharesSource ↗
Carbon Risk Hedging with Beta Hedge Ratio
A new hedge strategy has been created to reduce carbon risk in diverse portfolios, which lowers carbon beta without major losses in risk-adjusted returns, making it a suitable strategy for investors and fund managers.
21 sharesSource ↗
Predicting FX Returns
The study finds that long-term straddle momentum, implied volatility, and illiquidity are the main predictors of cross-sectional FX options returns, making other factors insignificant.
19 sharesSource ↗
Bankruptcy Regulations in Vietnam
The research shows a consistent negative link between distress risk and corporate profitability in Vietnam, which vanishes after bankruptcy regulations are implemented.
15 sharesSource ↗
Forecasting Covariance Matrices
The paper suggests a model for predicting large realized covariance matrices of returns for S&P 500 companies, using standard firm-level factors and sectoral restrictions, resulting in improved forecasting accuracy and better minimum variance portfolio estimates.
14 sharesSource ↗
Statistical3
Multicriteria Optimization for Deep Learning
The study introduces a new machine learning model that reduces bias and minimizes loss function in data sets, successfully tested on digit classification.
25 sharesSource ↗
Predicting Marine Accident Severity
The research suggests a new method for predicting marine accident severity using a two-stage feature selection and six machine learning models, with the Light Gradient Boosting Machine performing best.
14 sharesSource ↗
Google Search Volume Index and Investor Attention
The study finds that Google Search Volume Index can be used to predict stock market movements and volatility, improving forecasting models.
12 sharesSource ↗
Machine Learning10
Machine Learning in Credit Scoring
A study reveals that machine learning models using unconventional data are more efficient in predicting credit losses and defaults, particularly during economic crises.
30 sharesSource ↗
Cryptocurrency Portfolios Diversification
A stock-bond portfolio can gain significant diversification benefits by incorporating size- and momentum-based cryptocurrency factors, which can be further enhanced using machine-learning strategies.
23 sharesSource ↗
Improved Crayfish Optimization for Feature Selection
The newly developed Improved Binary Crayfish Optimization Algorithm (IBCOA) enhances feature selection in data mining and machine learning, thus improving classification accuracy.
19 sharesSource ↗
CoDe Model for Risk Perception
The Risk Co-De model, a machine learning-based system, can automatically classify social media posts about risk events with an accuracy of 86%.
16 sharesSource ↗
Machine Learning in Business
The use of machine learning techniques in international business can address complexity and aid theory development, as per an article that also offers practical advice for implementing a machine learning process pipeline.
16 sharesSource ↗
ML Price Indices in Commercial Real Estate
The article introduces a new way of creating property price indices using machine learning, which is more accurate but less stable with small samples.
15 sharesSource ↗
Flexible Truck Appointment System Design
The paper proposes a model for smart ports using Industry 4.0 concepts, which uses real-time data to manage truck flow disruptions.
14 sharesSource ↗
Predictor Variables with Random Forests
The study compares variable selection with random forests, a machine learning method, with linear models in behavioral sciences, providing practical advice.
14 sharesSource ↗
ML Predicting Stock Indexes with Sentiment Analysis
The research uses sentiment analysis and machine learning to predict stock indexes, showing that investor sentiments and exchange rates greatly affect the Shanghai Composite Index.
14 sharesSource ↗
Forecasting Race Outcome with ML
The paper uses machine learning to predict the results of standard battles in the Chinese solid-state lighting industry, finding the random subspace-MultiBoosting approach most effective with small datasets.
12 sharesSource ↗
Deep Learning1
Deep Learning for Newsvendor Problems
The study uses a deep learning algorithm to effectively solve complex control models for supply and demand problems, financial risk management, and competitive scenarios, showing successful risk reduction.
12 sharesSource ↗
Historical Trending10
Performance Evaluation Models for Brazilian Mutual Funds
The study assesses Brazilian equity mutual funds' performance using various models, finding that three- or five-factor models minimize market anomalies and conditional methods offer greater explanatory power.
14 sharesSource ↗
Machine Learning System for Financial Disinformation Detection
The research develops a machine learning system to identify financial misinformation on social media, using a unique dataset of financial news scrutinized by the Securities and Exchange Commission.
32 sharesSource ↗
Transnational Machine Learning for Bid-Rigging Cartels
The study explores the applicability of statistical screening methods for detecting bid-rigging cartels from Switzerland to Japan, revealing that while machine learning methods can achieve high accuracy, their performance drops when used in different countries.
24 sharesSource ↗
Anomalies and Market Return Predictability
The research shows that the returns of long-short anomaly portfolios can predict the overall market excess return, suggesting this predictive ability comes from asymmetric limits of arbitrage and overpricing correction persistence.
116 sharesSource ↗
Sparse Temporal Disaggregation for Economic Indicators
The article introduces a new sparse temporal-disaggregation procedure for high-frequency economic indicators like GDP, showing its superiority over the traditional Chow-Lin method when handling large data volumes.
10 sharesSource ↗
Property Uniqueness in Real Estate Sales
Machine learning can determine the uniqueness of residential properties from ads, which can increase sale prices but also lengthen market time.
4 sharesSource ↗
Corporate Governance and Failure
Palestinian companies with independent boards, institutional ownership, and high-quality external audits are less likely to fail.
3 sharesSource ↗
Macroeconomic Impact of AI
The paper studies the effects of AI and digitalization on the macroeconomics of EU countries, including Romania, using correlation analysis and interdependence studies.
1 sharesSource ↗
Generational Financial Inclusion in Kenya
Financial inclusion in Kenya varies by generation, gender, and location, with Generation Y, males, and urban residents having greater access to financial services.
1 sharesSource ↗
Agency Costs in Auditor Choice
Iranian nonfinancial companies with high agency costs often choose lower-quality auditors, but this is less common if the board has more financial experts.
1 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
17 items
Recently Published10
Optimal Compute Scaling for LLMs
The research investigates enhancing Large Language Models' (LLMs) performance using more test-time computation, suggesting a compute-optimal scaling strategy based on prompt difficulty.
214 shares2,189 citations todaySource ↗
Full Duplex Modeling for Speech Models
The paper presents a new model, the listening-while-speaking language model (LSLM), that improves real-time interaction in speech language models, including handling interruptions.
131 shares83 citations todaySource ↗
AgentGen: Enhancing LLM Planning
Enhancing LLM Planning: The study improves the planning abilities of Large Language Models (LLMs) using instruction tuning and a framework called AgentGen, which generates diverse environments and planning tasks.
44 shares93 citations todaySource ↗
Tamper-Resistant Safeguards for LLMs
The research introduces a method called TAR to build tamper-resistant safeguards into Large Language Models (LLMs), improving tamper-resistance while maintaining benign capabilities.
43 shares150 citations todaySource ↗
TurboEdit: Text-Based Image Editing
Text-Based Image Editing: The study proposes a shifted noise schedule and a pseudo-guidance approach to address visual artifacts and insufficient editing strength in text-based image editing frameworks, enabling editing with minimal diffusion steps.
35 shares80 citations todaySource ↗
Policy-Gradient for Imperfect-Information Games
The study demonstrates that policy gradient methods can be effectively used in two-player zero-sum games with imperfect information, leading to a regularized Nash equilibrium.
30 shares6 citations todaySource ↗
Hedge Fund Portfolio with PolyModel Theory
The article shows that using PolyModel theory and deep learning can enhance hedge fund portfolio construction, improving Sharpe ratio and annualized return.
28 shares12 citations todaySource ↗
NeuralBeta: Estimating Beta with Deep Learning
Estimating Beta with Deep Learning: The paper introduces NeuralBeta, a new method using neural networks to estimate beta in finance, showing improved performance in tracking beta's dynamic behavior during market shifts.
20 shares4 citations todaySource ↗
Coarse Correspondence for 3D Spacetime Understanding
The paper presents Coarse Correspondence, a visual prompting method that enhances multimodal language models' understanding of 3D and temporal dimensions, achieving top results on various benchmarks.
13 shares20 citations todaySource ↗
KaPO Knowledge-aware Preference Optimization
The study introduces a Knowledge-aware Preference Optimization method to improve large language models' knowledge selection, showing enhanced performance in managing knowledge conflicts and robust generalization across different datasets.
10 shares22 citations todaySource ↗
Historical Trending7
Efficient Pre-training
The MoMa model is a new architecture designed for pre-training mixed-modal language models, providing improved efficiency in processing images and text in any order.
348 shares78 citations todaySource ↗
Reinforcement Learning
The review explores the development of reinforcement learning in neuroscience, drawing comparisons between machine learning techniques and neuroscience, and introduces modern deep reinforcement learning methods.
174 shares10 citations todaySource ↗
Improved JumpReLU SAEs
The paper presents JumpReLU Sparse Autoencoders (SAEs), which provide high-quality reconstruction of language model activations at a specific sparsity level, while maintaining interpretability.
125 shares305 citations todaySource ↗
ShieldGemma
ShieldGemma is a safety content moderation model that excels in predicting safety risks such as explicit content and hate speech, surpassing models like LlamaGuard and WildCard.
55 shares245 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
10 items
Trending5
Efficient Matrix Profile
The ACAMP algorithm has been found to be quicker than the SCRIMP matrix profile algorithm for z-normalized Euclidean distance.
3,281 shares
MindSearch AI
MindSearch uses a multi-agent framework, inspired by human cognition, for web information search and integration.
802 shares
SelfReflective Agents
A flaw in the evaluation protocol used in previous studies has resulted in an inflated pass rate.
248 shares
Large Language Model Quantization Benchmark
Large language models (LLMs) are advancing towards artificial general intelligence due to their emerging abilities and reasoning skills.
175 shares
RelBench Benchmark
RelBench is utilized for the first extensive study of Relational Deep Learning, integrating graph neural network predictive models with deep tabular models.
170 shares
Rising5
RecurrentGPT Generation
AIGC is investigating the use of RecurrentGPT to create interactive stories that directly involve consumers.
134 shares
OVDINO OpenVocabulary Detection
A new method called OVDINO has been introduced to handle large-scale datasets in a unified system.
97 shares
Multimodal Discrete Representation
The Dual Crossmodal Information Disentanglement model uses a single codebook for detailed representation and crossmodal generalization.
49 shares
XHand Expressive Hand Avatar
Hand avatars play a vital role in digital interfaces, improving user engagement and interaction in virtual settings.
43 shares
GSMesh Reconstruction
D Gaussian Splatting is now acknowledged as a successful technique for accurately depicting scenes.
37 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Advanced Trading Strategies
The repository offers research papers and code samples for sophisticated financial engineering and trading strategies.
17 shares
Automating Technical Analysis
The article explores the use of data analytics in making trading decisions based on price action.
240 shares
AI for Trading Projects
The repository contains comprehensive notes and Python projects focusing on AI and Finance.
283 shares
Pair Trading Environments
The article investigates the use of reinforcement learning in cryptocurrency trading using Backtrader.
18 shares
Quantorch: Derivatives Pricing Library
Derivatives Pricing Library: The article presents a high-efficiency PyTorch library specifically created for pricing derivatives.
135 shares
Trending5
Event Backtester
The article reviews a tool that tests trading strategies based on specific events.
85 shares
Audio/Video Downloader
The piece describes a command-line tool for downloading multimedia content.
78,885 shares
SP 500 Components
The article offers updated and historical lists of S&P 500 components since 1996.
386 shares
Attention Transformer
The article investigates a full-attention transformer incorporating features from different studies.
4,437 shares
JSON Generator
The article introduces a reliable method for creating structured JSON from language models.
4,154 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
SEI Canoe streamline fund valuations for family offices
SEI and Canoe Intelligence have introduced a new feature for family offices on the SEI Archway Platform, allowing automated transmission of private equity and hedge fund valuations.
7 shares
SEBIs options curbs impact quants, HFTs
The Securities and Exchange Board of India is proposing new rules to control the increase in index options trading, impacting high-frequency traders, quantitative funds, and brokerage firms.
7 shares
Hedge funds accused of market chaos
The recent rise in the yen, causing hedge funds to unwind carry trade bets, has been identified as a major cause for the global stock market selloff.
7 shares
CoinShares chooses TS Imagine for hedge fund
CoinShares has selected TS Imagine's TS One trading and risk management solution for its new Relative Value equities hedge fund.
6 shares
Novare names Portfolio Manager
Novare, a South African investment solutions provider, has named Handré Retief as its new equity and fixed income portfolio manager.
5 shares
Hedge Funds Tech Stock Losses
Major hedge funds like Light Street Capital Management and Pershing Square Capital Management faced significant losses in mid-July due to a drop in global markets and their heavy investments in tech stocks.
5 shares
Case Hedgefond Merges Case Credit
Swedish hedge fund, Case Hedgefond, plans to merge into Case Fonder’s credit hedge fund, Case Credit Opportunity, after its assets fell to €100m.
5 shares
Perkins Coie Hires Private Funds Partner
Kerry Potter McCormick, a private funds partner, has been hired by international law firm Perkins Coie to join their corporate and financial regulation practices in New York.
4 shares
ExLiontrust Tortoise Managers Launch QSM Fund
Former Liontrust Tortoise fund managers Matthew Smith and Tom Morris have started a new hedge fund, QSM Capital, that combines traditional and alternative investment strategies.
4 shares
Digital Assets Funds Outflows
Digital asset investment products saw outflows for the first time in four weeks, totaling 528m, due to fears of a US recession, geopolitical issues, and a wider asset selloff.
3 shares
Miscellaneous10
APAC Hedge Funds Q2 Outperformance
Hedge funds focused on the Asia-Pacific region outperformed those focused on North America and Europe in Q2, with an average net return of 3.5%, as per Preqin's report.
3 shares
Jain Global Trading Update
Jain Global, a hedge fund firm founded by ex-Millennium Management Co-CIO Bobby Jain, reported a slight loss of 0.65% in its first trading month, according to Business Insider.
3 shares
MFA Urges FINRA Reporting Rules
The Managed Funds Association has requested the Financial Industry Regulatory Authority to limit its proposed securities loan reporting rules to the scope defined by the SEC.
3 shares
Global Hedge Funds Increase Chinese Stock Exposure
Global hedge funds increased their investment in Chinese domestic stocks and American depositary receipts in July, according to a report by the South China Morning Post.
3 shares
BNP Paribas WM Head Exits in HK and Singapore
Agnes Sng, the Regional Head of Investment Funds Advisory for Hong Kong and Singapore, has left BNP Paribas Wealth Management.
3 shares
Japan Hedge Funds Rebound with Record Gains
Japan-focused hedge funds saw record single-day returns after a 3.7% loss caused by poor US jobs data and a Bank of Japan rate increase.
3 shares
Citadel Securities Tech Lead Departs in Chicago
Citadel Securities is currently experiencing a successful period.
2 shares
Hudson River Trading Hires Female Data Scientists
An individual is relocating internationally for work.
2 shares
Large Hedge Funds Using AI
Major hedge funds such as AQR, Balyasny, and Man Group are using artificial intelligence, as reported by Pensions & Investments.
2 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Jesse Felder: Insider Trading & Algorithmic Investing
Insider Trading & Algorithmic Investing: Jesse Felder highlights the importance of insider trading in predicting market trends, drawing parallels between today's market and the dotcom bubble, and questioning the S&P 500's forward PE ratio's alignment with current economic data.
12 shares
Diego Parrilla: AntiBubble Investing & Market Risks
AntiBubble Investing & Market Risks: Former trader Diego Parrilla presents his anti-bubble investment strategy, discussing the influence of disruptive technologies on the market and the use of gold volatility to navigate through unstable periods.
11 shares
Mark Yusko: AI, Data Security & Fintech
AI, Data Security & Fintech: Mark Yusko, founder of Morgan Creek Capital Management, shares his transition from traditional to digital assets, his belief in Bitcoin as a superior value store, and his predictions for blockchain technology's future.
9 shares
Álvaro Cartea: AI Trading Strategies Evolution
AI Trading Strategies Evolution: Professor Álvaro Cartea explores the development of AI trading strategies, the unexpected outcomes of AI market makers, and the regulatory considerations of AI in finance.
8 shares
TPG CEO Jon Winkelried: Private Equity & Alternative Markets
Private Equity & Alternative Markets: TPG CEO Jon Winkelried talks about the transformation of private markets, the merging of alternative asset managers, and the management of companies during crises.
6 shares
Related5
Brand Power
Podcast explores the importance of global brands, their role in sports sponsorships, and potential investment opportunities.
6 shares
Bill Martin's Fed
Podcast series interviews authors about influential US Federal Reserve Chairs, with a focus on William McChesney Martin Jr.
2 shares
Eccles' Influence
Podcast series on influential US Federal Reserve Chairs begins with a discussion on Marriner S. Eccles' impactful tenure.
2 shares
Risks in Oil Market
Podcast episode features Rory Johnston discussing crude oil aspects, President Trump's OPEC claims, and U.S. Shale growth limits.
2 shares
Sector Outlook
Podcast with Gary Christie discusses the current U.S. stock market, sector trends, earnings impact, and shift from large to small cap stocks.
1 shares
Blogs
Posts from quant and economics blogs and newsletters.
2 items
Quantitative1
Related1
Days in Charts
The article discusses the current election cycle, describing it as the most astonishing in living memory, with three months still to go.
0 shares
X / Twitter
Posts from quant researchers on X.
8 items
Quantitative4
TSlib: Time Series Analysis Library
Time Series Analysis Library: TSLib is an open-source tool for deep learning-based time series analysis with multiple models.
3 shares
Private Funds Performance
A study evaluates the performance of private funds across asset classes, highlighting potential diversification benefits for investors.
3 shares
Free Historical FX Data
A free resource for historical FX data offers detailed millisecond data for various currency pairs.
2 shares
Portfolio Optimization Practice
A new two-stage method for portfolio optimization is suggested, designed to produce portfolios applicable to real-world investment.
2 shares
Miscellaneous4
Market Returns During Recessions
Research shows that investors who convert to cash at the beginning of recessions can dodge initial market declines and enhance their Sharpe ratio.
1 shares
Weekly Recap Expansion
The author intends to publish more detailed articles frequently due to the positive feedback on their weekly summary.
0 shares
Macro Model Forecast Errors
A new study indicates that a basic macro model can predict inaccuracies in analysts' predictions of S&P 500 earnings, which could be beneficial for investors.
0 shares