Ponzi Funds
The study suggests that investors' pursuit of high returns from active funds can predict ETF bubbles and crashes, and that a fund's liquidity can indicate its potential for inflated returns.
4 shares5 citations todaySource ↗
Quant LetterNo. 50
May 2024, Week 4
159 items across 11 sections, as sent to readers on 22 May 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 159
- Papers
- 90
- Sections
- 11
- Issue
- No. 50
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
9 items
Finance5
Deep Penalty Methods
A proposed deep learning algorithm for optimal stopping problems shows accuracy and efficiency in American option pricing, with its error bound by the loss function and other parameters.
3 shares7 citations todaySource ↗
Microstructure Modes
Research using a double coarse-graining procedure and Principal Component Analysis on electronic order books reveals stable parameters in a Vector Auto-Regressive model, but fails to account for the square-root law of price impact.
3 shares6 citations todaySource ↗
Continuity of Risk Measures
A study proves that a convex, order bounded above functional on a Banach lattice is automatically norm continuous, enhancing previous findings and applying to various deviation and variability measures.
3 shares1 citation todaySource ↗
Risk Sensitivity
Research identifies the conditions that make a risk or utility functional sensitive to large losses, demonstrating that Value at Risk and Expected Shortfall can become sensitive to large losses if properly adjusted.
2 shares4 citations todaySource ↗
Economics1
Influencer Cartels and Consumer Welfare
The article talks about the emergence of 'influencer cartels' in social media marketing, where influencers work together to boost their ad revenue. It also examines how this could affect consumer welfare.
3 sharesSource ↗
Crypto & Blockchain1
Deep Learning for Crypto Price Prediction
The article discusses a study on deep learning models for predicting cryptocurrency prices. It reveals that univariate LSTM models perform the best. The study also notes significant price changes in cryptocurrencies during the COVID-19 pandemic.
8 shares18 citations todaySource ↗
Historical Trending2
Optimal Information Acquisition
The study suggests that acquiring information early is beneficial in reducing investment risk, and those less risk-averse are more likely to seek extra information.
3 sharesSource ↗
The Unfairness of Fairness
The article introduces a utility-based method to measure fairness in decisions, arguing that traditional probability-based evaluations may not accurately represent real-world fairness, using college admissions and credit risk assessment as examples.
2 sharesSource ↗
SSRN
Working papers in finance and economics from SSRN.
40 items
Quantitative20
Pricing Hybrid Asset-Volatility Derivatives
The article explains how the cost of hybrid asset-volatility derivatives can be estimated using the asset's implied volatility skew, assuming it's generated by a stochastic volatility model.
37 sharesSource ↗
Building Arbitrage-Free Implied Volatility Surface
The paper explores the creation of arbitrage-free implied volatility surfaces based on relative entropy minimization, addressing numerical issues and their solutions, and their importance for arbitrage-free models.
16 sharesSource ↗
RealTime Application Identification Through Network Packet Analysis
The article introduces a new method using AI and machine learning to identify the type of applications used by clients on public internet, improving security and controlling unwanted application usage.
5 sharesSource ↗
Integrated Text-Model Generation-Simulation Framework for Steel Beam
The paper emphasizes the advantages of automating modelling and simulation processes in research, design, and manufacturing, using machine learning to analyze large-scale simulation data and offer insights into unknown situations.
6 sharesSource ↗
Business Intelligence through Artificial Intelligence: A Review
A Review: The article reviews the incorporation of AI in business intelligence, focusing on AI-powered data analytics, natural language processing, and big data integration, and how this can improve data visualization and decision-making.
3 shares9 citations todaySource ↗
Stock Market Volatility Models
The paper finds the simple regression model as the most accurate in predicting daily volatility of the NIFTY 50 index among eight forecasting models.
2 sharesSource ↗
Common Ownership and Activism
The study suggests that common ownership can lead to anticompetitive outcomes, such as reduced wages and wealth transfer to shareholders.
3 shares1 citation todaySource ↗
AI for HR Management
The research highlights the benefits and challenges of Artificial Intelligence in Human Resource Management, including recruitment, performance management, skill gaps, and data privacy.
3 shares9 citations todaySource ↗
Downside Risk in China's Markets
The paper presents a new risk assessment model for financial markets, demonstrating that green bond markets are riskier than non-green ones using Chinese data.
3 sharesSource ↗
Sorghum Detection Accuracy
The study introduces an intelligent system for classifying sorghum varieties using machine learning and cloud computing, with the SqueezeNetLR stacking model being the most accurate.
3 sharesSource ↗
Machine Learning in Accounting and Finance
Research shows a rising interest in the effects of machine learning on accounting and finance, with a notable increase in studies focusing on Asian markets from 2020-2022.
2 sharesSource ↗
Operational Loss Recoveries in U.S. Banking
A study indicates that operational loss recovery rates in large U.S. banks decrease during economic downturns, implying that economic shocks can affect banking losses.
126 sharesSource ↗
Economic Risk in Disability Income Insurance
Research suggests an asset portfolio that matches unemployment levels can effectively manage disability income insurance portfolio liabilities, as demonstrated using UK data from 2004-2016.
2 sharesSource ↗
Credit Land Speculation and Growth
A paper claims that sector-specific credit expansions, particularly in real estate, can impact long-term economic growth and productivity, rather than overall credit expansion.
2 sharesSource ↗
AI Discourse in German and Chinese Media
Analysis of Chinese and German media coverage on AI from 2018 to 2023 shows regional differences, with Chinese media being more positive and German media more critical.
8 sharesSource ↗
SP500 Earnings Straddle Strategies
The study suggests that using straddle derivatives strategies around SP 500 earnings announcements can be profitable, but also risky and costly.
3 sharesSource ↗
Public Data Ecosystems Evolution
The research identifies the elements that create value-adding public data ecosystems and how they evolve, based on a review of 148 studies.
3 shares29 citations todaySource ↗
CPI Data Collection Optimization
The paper presents a framework for National Statistical Institutes to assess their data collection for the Consumer Price Index, using electricity and gas prices in Italy in 2023 as a case study.
2 shares2 citations todaySource ↗
Airline Stocks and Oil Price Volatility
The study finds a negative correlation between oil price volatility and international airline stock prices, recommending diversification and technology implementation to reduce fossil fuel reliance.
3 sharesSource ↗
Corporate Liquidity and Bondholder Fragility
The research shows that firms with higher bondholder fragility risk tend to hold more cash, indicating that bond mutual fund fragility significantly affects corporate liquidity policy.
2 sharesSource ↗
Financial20
Public Firms Transformation
The number of public firms in the US has decreased by half since the 21st century due to heavy legal burdens, but their economic influence remains the same.
414 sharesSource ↗
Convex Volatility Method
Convex Volatility Interpolation (CVI), a new method for calibrating implied volatility surfaces using quadratic programming, has been introduced, eliminating the need for hyperparameter tuning.
6 shares2 citations todaySource ↗
Term Spreads and Recessions
Research shows that credit market sentiment affects the real economy through the term premium, with term spreads predicting recessions and affecting future growth.
13 sharesSource ↗
Highfrequency Data Analysis
Recent studies on issues in high-frequency financial data analysis, such as nonstationarity and low signal-to-noise ratios, are categorized into data preprocessing and quantitative methods.
6 shares20 citations todaySource ↗
Portfolio Optimization for M6
The M6 forecasting competition paper introduces a data-driven approach that directly optimizes portfolio weights, achieving a 9.5 global rate of return and an information ratio of 5.045.
3 shares7 citations todaySource ↗
Tick Size Reduction in Commodity Futures
The Dalian Commodity Exchange improved market quality by reducing the tick size for two commodity futures contracts, encouraging quote competition and cross-asset arbitrage activities.
2 sharesSource ↗
Interim Valuations in Private Equity
The history of valuations, including staleness and markdown frequency, can predict the future performance of portfolio companies in U.S. buyout and VC investments.
6 sharesSource ↗
Size Effect in Appraisal Proceedings
The capital asset pricing model (CAPM) may not accurately predict the returns of small public companies, suggesting a negative risk-free rate may be more accurate.
2 sharesSource ↗
Cultural Influence on Bond Investments
Cultural differences, particularly between Italian and Germanic origins, significantly affect investment in government bonds, especially during the European sovereign debt crisis.
5 sharesSource ↗
Climate Change and Shareholder Value
Companies more susceptible to climate change saw negative market reactions after Donald Trump's unexpected 2016 election victory, showing the impact of political stances on climate change on company value and shareholder wealth.
3 shares18 citations todaySource ↗
Portfolio Management with Python
The lecture notes discuss portfolio management, highlighting the use of Python for practical applications and the importance of understanding different types of returns for accurate performance assessment.
502 sharesSource ↗
MeanVariance Efficient Portfolios
A 1992 study found that a composite model of financial variables outperformed equity benchmarks by 400 basis points annually, a finding later confirmed by Markowitz and Xu in 1994.
92 sharesSource ↗
Cheap Stock Options
The research investigates cheap stock - equity-based compensation granted pre-IPO at a lower price, finding it leads to greater IPO underpricing, lower post-IPO investment, and higher CEO compensation.
152 sharesSource ↗
Insurance Investments
The study presents a theory connecting insurance premiums, insurers' investment behavior, and asset prices, showing that insurers with stable funding take more investment risks and earn higher returns.
209 sharesSource ↗
Informed Trading Risk
The research uses abnormal undercutting activity to measure informed trading risk, finding it predicts imminent information events and positively predicts stock returns up to six months forward, especially for stocks with tight short sale constraints.
192 sharesSource ↗
Hedge Fund Performance Decline
The study shows that top-performing hedge funds continue to add value, but their persistence has weakened and can only be observed using a specific method.
370 sharesSource ↗
Stock and Option Market Response to ESG News
The research finds that negative ESG incidents have minimal immediate impact on stock prices but cause increased volatility for severe incidents, particularly those related to Natural Capital.
2 sharesSource ↗
Future Value of Mutual Fund Investments
The paper suggests that mutual fund investment forecasts are best presented in currency terms and that the precision of past and predicted values can help analyze sampling errors.
56 sharesSource ↗
Central Bank Haircut Policy
The study reveals that a decrease in the Eurosystem collateral framework leads banks to replace other high-quality government bonds with EU bonds, especially German banks.
2 sharesSource ↗
Equity Premium Events
The research identifies equity premium events using daily S&P 500 option expirations, finding that economic, political events, and macroeconomic releases cause the largest abnormal equity premia.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
24 items
Finance5
Feedback Trading and Return Autocorrelations in India
The article explores how institutional investors in India have reacted to the COVID-19 pandemic, with foreign investors continuing positive feedback trading and domestic investors pursuing negative feedback trading, causing negative autocorrelation in market returns during high volatility.
23 sharesSource ↗
Structural Change and Volatility in Indian Stock Market
The study looks at the relationship between the Indian stock market and the top four economies' markets during the COVID-19 pandemic, finding significant volatility spillover from these markets to India, which should be considered by investors and policymakers.
18 sharesSource ↗
Explainable AI in Finance
The paper reviews current research on Explainable Artificial Intelligence (XAI) in Finance, noting that areas like risk management and portfolio optimization are well-studied, while anti-money laundering is not.
16 sharesSource ↗
Fund Portfolio Mismatch and Market Volatility in China
The research indicates that the level of network connection significantly affects its impact on market volatility, with over-connection of networks increasing market volatility and reducing the stability effect from the optimal network.
14 sharesSource ↗
Optimizing Cryptocurrency Returns
The study examines cryptocurrency investment strategies using the robust framework of factor investing, finding that momentum and value factors have significant predictive power in forecasting cryptocurrency returns, emphasizing the need to adapt traditional investment frameworks to the cryptocurrency context.
13 sharesSource ↗
Statistical2
Boosting Trees for Oil Futures Volatility Forecasting
The research finds that ensemble boosting tree models, especially CatBoost and LightGBM, are more effective in predicting China's crude oil futures volatility than traditional models, with macroeconomic and HAR-type variables impacting the forecasts differently.
20 sharesSource ↗
Predicting Turnover with Machine Learning
The study reveals that the Decision Tree model is the most accurate in predicting employee turnover, with factors such as education, joining year, city payment tier, age, gender, ever benched status, and domain experience being key predictors.
17 sharesSource ↗
Machine Learning10
Machine Learning for Research Identification
A machine learning framework has been developed to identify significant research papers that initially went unnoticed, proven effective in a chemistry study.
21 sharesSource ↗
APC Framework for Profit Modeling
Age-period-cohort models are being used to streamline credit risk modeling, improving underwriting and setting financial targets.
20 sharesSource ↗
Urban GDP Growth Estimation in South Sudan
A machine learning model using remote sensing data has been used to estimate economic activities in urban South Sudan, converting nighttime lights into urban GDP growth estimates.
19 sharesSource ↗
Equity Returns Predictability with Machine Learning
Machine learning techniques' predictability of global stock returns decreases over time, but firm-specific characteristics can still be profitable despite transaction costs.
18 sharesSource ↗
Firm Adaptation in a Changing World
A new approach has been proposed to understand how firms adapt to change, with a case study on a lending platform suggesting the use of an ensemble algorithm.
16 sharesSource ↗
Knowledge Graph Credit Risk for MSMEs
A machine learning model has improved credit risk assessment for MSMEs, achieving a 92% accuracy in identifying risk-free enterprises.
14 sharesSource ↗
Modeling Paid-Ups in Life Insurance
Life insurance predictive models suggest that surrender fees may increase the risk of policies becoming paid-up under certain conditions.
12 sharesSource ↗
Accelerating Tax Statistics with ML
The German Federal Statistical Office is using machine learning to predict pension taxation data, aiming to speed up the release of these statistics.
12 sharesSource ↗
Comparative Analysis of KNN and Naive Bayes for Storm Prediction
The K-Nearest Neighbours algorithm has proven more accurate than the Naive Bayes method in predicting storm warnings, with a 68.20% accuracy rate.
12 sharesSource ↗
ML for Project Cost Estimates
A machine learning study has developed a model that improves project cost forecasting, providing more accurate estimates throughout a project's life cycle.
12 sharesSource ↗
Deep Learning2
Bitcoin Crash Prediction
A new deep learning framework using contrastive learning has been developed to predict Bitcoin market crashes, performing 15.8% better than six other models.
14 sharesSource ↗
Multi-Currency Modeling
A new framework for modeling multiple currencies using CBI-time-changed Lévy processes has been created, offering a semi-closed pricing formula for currency options and two calibration methods using deep-learning techniques.
10 sharesSource ↗
Historical Trending5
Asset Pricing in Sustainable Equity Portfolios
The research examines asset pricing in Shariah-compliant equity on the Pakistan Stock Exchange, finding that multifactor models are generally effective despite some exceptions.
16 sharesSource ↗
Carbon Risk in European Equity Returns
The study measures the effect of carbon risk on European equity prices, indicating it's a systematic risk factor that can be estimated from stock returns.
14 sharesSource ↗
Investor Sentiments Impact on Asset Valuation
The paper highlights two types of investor sentiments - general market sentiments and specific asset biases - that significantly influence asset valuation models.
8 sharesSource ↗
Robust Portfolio Optimization in Worst-Case Scenarios
The article introduces a new method for creating robust portfolios using stochastic efficiency analysis, which lowers systematic risk and boosts returns, especially during market downturns.
6 sharesSource ↗
Financial Statements Fraud Identifiers
The article proposes a new accounting tool for immediate fraud detection and prevention, utilizing financial statement relations and comparing the quality of current research in financial statement fraud detection models.
5 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
17 items
Recently Published10
CATD: Multi-View Diffusion Models
Multi-View Diffusion Models: CAT3D is a novel technique for generating 3D scenes from any number of images, surpassing existing methods in speed and efficiency.
157 shares482 citations todaySource ↗
BiomedParse: Image Parsing Model
Image Parsing Model: BiomedParse is a new tool for biomedical image analysis, capable of identifying 82 object types across 9 imaging modalities, enhancing accuracy in biomedical research.
137 shares193 citations todaySource ↗
Octo Robot Policy
Octo is a large transformer-based policy for robotic manipulation, trained on a vast dataset, that can be instructed via language or images and adapted to new domains.
128 shares1,880 citations todaySource ↗
Slicedit: Video Editing
Video Editing: Slicedit is a new text-based video editing method that uses a pretrained model to process spatial and spatiotemporal slices, creating videos that maintain the original structure and motion.
48 shares50 citations todaySource ↗
ToonD: 3D Cartoons
3D Cartoons: A new technique has been developed to recover the 3D structure of non-geometrically consistent scenes, such as cartoons and anime, correcting 2D inconsistencies and enabling novel-view synthesis reconstruction.
29 shares3 citations todaySource ↗
Energy Rank Alignment
The article discusses the energy rank alignment (ERA) algorithm, which effectively generates molecules with specific properties using autoregressive policies.
25 shares7 citations todaySource ↗
Strategy-Proof Auctions
The paper introduces a deep learning approach for ensuring strategy-proofness in auctions, offering statistical guarantees and proving its effectiveness through experiments.
19 sharesSource ↗
Metacognitive Capabilities of LLMs
The study investigates the metacognitive abilities of large language models, showing their capacity to label math questions with skill levels and improve problem-solving accuracy.
17 shares96 citations todaySource ↗
Progress Towards AGI
The paper offers an in-depth analysis of Artificial General Intelligence (AGI), detailing its definitions, objectives, development paths, and potential realization strategies.
15 shares32 citations todaySource ↗
Modeling Citation Worthiness
The research introduces a Bidirectional Long Short-Term Memory (BiLSTM) network with an attention mechanism for detecting citation-needed sentences in scientific texts, proving its efficiency and potential use in pre-submission and pre-archival checks.
15 shares19 citations todaySource ↗
Historical Trending7
Minimalist DL Benchmark
The article presents MNIST-1D, a cost-effective, low-memory alternative to traditional deep learning benchmarks, designed for efficient study of deep learning structures.
614 shares35 citations todaySource ↗
Lumina-T2X: Text to Modality
Text to Modality: The Lumina-T2X family is introduced as a unified system for converting noise into various media formats, including images and videos, allowing for the creation of high-definition content with lower computational expenses.
217 shares146 citations todaySource ↗
FlashBack: Efficient LM
Efficient LM: The paper introduces FlashBack, a Retrieval-Augmented Language Modeling system that enhances inference efficiency by adding retrieved documents to the context, leading to quicker inference speed and lower costs.
82 shares2 citations todaySource ↗
DeepSeek-V2: MoE Language Model
MoE Language Model: DeepSeek-V2, a language model with 236B parameters, offers enhanced performance and cost efficiency compared to its predecessor, ranking high among open-source models.
51 shares1,459 citations todaySource ↗
Efficiency of CNNs
A novel approach to convolutional neural networks prioritizes computational efficiency over arithmetic complexity, resulting in faster, more accurate, and cost-effective models.
35 shares5 citations todaySource ↗
Wasserstein Gradient Boosting for Regression
Wasserstein gradient boosting, a new type of gradient boosting, improves probabilistic prediction by approximating the output-distribution parameter's posterior distribution.
35 shares7 citations todaySource ↗
DREAM: Multi-Robot Navigation
Multi-Robot Navigation: A proposed decentralized multi-robot trajectory planning algorithm improves success rates and efficiency in both single and multi-robot scenarios by avoiding collisions with static and dynamic obstacles.
27 shares21 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
15 items
Trending7
NaiboWang EasySpider
Webcrawling is an essential research instrument for scientists in both computational and non-computational fields.
25,232 shares
googleresearch GIVT
The article introduces Generative Infinite-Vocabulary Transformers (GIVT), which produce sequences of vectors with real values rather than discrete tokens.
1,725 shares
sbailab LightAutoML
The article presents LightAutoML, an AutoML system designed specifically to cater to the unique needs of a large European financial services company.
945 shares
MS MARCO Web Search Dataset
The article emphasizes the significance of data scale labels and modals in large models, showcasing recent developments.
227 shares
KolmogorovArnold Networks
The paper demonstrates that Gaussian radial basis functions can effectively approximate 3-order B-splines in KolmogorovArnold Networks.
168 shares
Platonic Representation Hypothesis
The article suggests that AI models, particularly deep networks, are developing increasingly similar representations.
144 shares
Sora World Simulator
The article highlights the crucial role of general world models in progressing towards Artificial General Intelligence, useful in virtual environments and decision-making systems.
131 shares
Rising8
Cartoon Research with Sakuga42M Dataset
The article explores the use of scaling paradigm to improve cartoon research.
106 shares
UserFriendly News Scraper Fundus
The article presents Fundus, a tool designed for efficiently scraping large amounts of news articles.
95 shares
Detecting Undertrained Tokens
The article discusses the problem of misalignment between tokenizer creation and model training in language models.
86 shares
Efficient Inference with KV Cache
The article suggests a new method to reduce memory usage and increase inference throughput by computing and caching only a few layers.
68 shares
MoRA Update
Lowrank adaptation is a popular technique for efficiently fine-tuning large language models.
67 shares
RLHF Workflow
The report discusses the superior performance of Online Iterative Reinforcement Learning from Human Feedback in large language models compared to offline learning.
66 shares
MarkLLM Toolkit
The intricate and numerous watermarking algorithms for large language models pose comprehension and evaluation difficulties for researchers.
33 shares
Linearizing LLM
Linear transformers, an alternative to softmax attention, are gaining attention due to their fixed-size recurrent state that lowers inference cost.
32 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Bisheng: LLM DevOps Platform
LLM DevOps Platform: Bisheng is a platform designed for the development of AI applications.
6,806 shares
QuantEssential: Grad Internships
Grad Internships: A job compilation is available for new graduates and interns in software engineering, quantitative analysis, and data science.
85 shares
Fortitudo.tech: CVaR Portfolio Optimization
CVaR Portfolio Optimization: Python is utilized for portfolio optimization and stress-testing through Conditional Value-at-Risk and Entropy Pooling views.
152 shares
DataDreamer: Synthetic Data Generation
Synthetic Data Generation: DataDreamer Prompt is a tool designed to generate synthetic data and train alignment models.
680 shares
Binancegridtrader: Grid Strategy Bot Trading
Grid Strategy Bot Trading: Binancegridtrader is a trading bot for grid strategy on Binance Spot and Binance Futures Exchange.
726 shares
Trending5
Financial Time Series
The article analyzes patterns and momentum trends in financial timeseries data.
204 shares
Pure Python Web Apps
The piece details the process of building web applications solely with Python.
17,078 shares
Fast Terminal File Manager
The article presents a fast terminal file manager created in Rust, using async IO.
8,932 shares
Python Frame Info
The article offers guidance on extracting information about the current operations of a Python frame, focusing on the executing AST node.
309 shares
Llama3
The article explains the process of implementing llama3 via matrix multiplication.
5,772 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Tide Capital investment from Wealthink AIInnovation
Hong Kong's Wealthink AI Innovation Capital has invested in a bitcoin-focused hedge fund managed by Tide Capital.
8 shares
Jain Global commodities push
Ex-Millennium Management CIO Bobby Jain's new hedge fund, Jain Global, plans to heavily invest in both derivatives and physical commodities.
7 shares
ExJPMorgan exec joins Deutsche Bank
Deutsche Bank has hired a seasoned professional in algorithmic trading technology.
6 shares
Ovata Capital adds four PMs
Ovata Capital Management has expanded its team with four new Portfolio Managers after its assets surpassed $1.1bn.
6 shares
CME bitcoin trading for hedge funds
CME Group plans to introduce bitcoin spot trading to cater to the increasing demand for cryptocurrency among money managers.
4 shares
New York lawmakers target investors
New York legislators are contemplating a revision to a law that sets a 9% interest rate on defaulted sovereign emerging-market bonds, potentially avoiding conflicts like the one between Elliott Investment Management and Argentina.
3 shares
Hedge funds boost Chinese holdings
According to Goldman Sachs, global hedge funds have increased their Chinese equities holdings for the fourth consecutive week, expecting a market recovery.
3 shares
BCA Research names China Strategist
Jing Sima has been named China Strategist at BCA Research, where she will work closely with the firm's Chief EMChina Strategist, Arthur Budaghyan.
3 shares
Eisler Capital replaces ex-Goldman Sachs MD
Eisler Capital has named a new head of infrastructure.
3 shares
Kind new hedge fund hires ex-Citadel founder
Aquatic Capital Management operates differently from typical hedge funds.
3 shares
Miscellaneous10
Shah Capital ends Novavx campaign
Shah Capital ended its campaign against Novavax's board directors after Novavax signed a licensing deal with Sanofi.
3 shares
Hedge funds struggle in April
Despite a negative performance in April 2024, hedge funds still hold a positive year-to-date return of 6.5%.
3 shares
Blackwells' Ashford Trust campaign fails
The CEO and a director of Ashford Hospitality Trust resigned following a campaign by shareholder Blackwells Capital.
2 shares
Wall Street quant doubts A.I.
Wall Street quant Cliff Asness has shown doubt about the effectiveness of Artificial Intelligence.
2 shares
Qube grows assets to 20bn
Qube Research & Technologies experienced a 22% increase in 2024, raising the company's assets from $16bn to $20bn.
2 shares
Tang rules out Fed rate cuts
Richard Tang of Rokos Capital Management believes the US Federal Reserve is unlikely to reduce interest rates this year.
2 shares
Digital assets funds inflows
CoinShares' weekly report shows digital asset investment products received inflows of $932m in a second week of positive flows.
2 shares
Quants CDOs blending
The Waters Wrap article explores the merging of job titles in quantitative analysis and collateralized debt obligations.
2 shares
Former Odey AM top performers
Two funds formerly managed by Odey Asset Management were among the top 10 best performing funds globally in April, according to Société Générale data.
2 shares
Private credit trends tech
A Hedgeweek report discusses the growth and future prospects of the $1.6tn private credit sector on Wall Street since the pandemic.
2 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
US Treasury Futures Roll
In a podcast, Srini Ramaswamy and Ipek Ozil discuss the upcoming Treasury futures roll cycle and its dynamics.
10 shares
Commodities and Gold
Elisa Piscopiello and Francisco Blanch explore the intersection of geopolitics, commodities, and the transition to clean power in a podcast.
9 shares
Equity Strategy
Savita Subramanian talks about her role as the head of US equity and quantitative strategy at Bank of America Corp in a Bloomberg Radio interview.
7 shares
Value Investing
Tobias Carlisle shares his journey from being a lawyer to a value funds manager and his unique value investing approach in a podcast.
6 shares
Real Estate Strategies
The Strategic Investment Advisory Group discusses the long-term growth potential of real estate as an investment asset class in a CenterForInvestmentExcellence special edition.
6 shares
Related5
Yen Weakness
In a podcast, Arindam Sandilya, Ayako Fujita, and Junya Tanase discuss the future of Japan's macroeconomic policy and the Yen.
5 shares
HMMs in Ecology
Théo Michelot's research uses Hidden Markov Models to transform GPS location data into useful information for ecological studies.
5 shares
Darren Voges
Darren Voges discusses the influential Yodlee credit card dataset and its market impact in a podcast interview.
5 shares
Tony McManus Interview
Tony McManus talks about Bloomberg's approach to AI and GenAI, and the skills needed for graduates to join Bloomberg.
3 shares
Leonid Mironov on China
Leonid Mironov shares his views on China's successes, failures, and his predictions for the future of the commodities market.
3 shares
Blogs
Posts from quant and economics blogs and newsletters.
5 items
Quantitative2
REI Rules
Financial market traders are always looking for new indicators to improve their technical analysis and trading performance.
5 shares
RVI Returns
Traders in the financial sector are constantly seeking out new tools such as the ... to improve their analysis of market trends.
5 shares
Related3
AUDNZD Strategy Guide
The article offers a detailed guide on how to effectively trade AUDNZD using strategies designed for its specific volatility and correlation.
4 shares
Cliffs Perspectives
The article compiles various opinion pieces discussing a wide range of topics from quantitative finance to baseball statistics.
3 shares
RVI Strategy Guide
The article emphasizes the significance of technical indicators in financial markets, particularly the Relative Strength Index.
2 shares
Videos
Talks, lectures and tutorials.
5 items
Quantitative5
Resume Tips for Quant Finance Jobs
The quantitative finance job market is tough, with subpar resumes hindering applicants' success rates.
49 shares
Costs of Starting a Hedge Fund
Establishing a hedge fund and recruiting employees entails substantial expenses.
0 shares
Project Astra AI Demo
Project Astra, an AI assistant prototype, can instantly solve mathematical problems and rectify graphs.
996 shares
Market Participants vs Government Regulations
Government interference can potentially cause more damage than free market players due to its authority.
0 shares
Reliability of Program Rankings
A significant number of students are dissatisfied with the existing ranking system for educational courses.
1 shares
X / Twitter
Posts from quant researchers on X.
4 items
Quantitative2
Liquid Factor Models
The article explores the application of Liquid Factor Models for generating Alpha Model.
3 shares
Kolmogorov-Arnold Networks
The article proposes the use of KolmogorovArnold Networks (KANs) as a better option than MLPs for analyzing time series data.
2 shares
Miscellaneous2
Trendfollowing strategies beat equities
Trendfollowing strategies offer comparable long-term returns to equities, performing particularly well when equities do not, without any correlation to them.
0 shares
Interview with Clifford Asness
A comprehensive interview was carried out with financial expert, Clifford Asness.
0 shares