Statistical Arbitrage Optimization
The research combines quantitative and machine learning techniques to enhance a statistical arbitrage strategy, resulting in improved returns and lower transaction costs.
8 shares6 citations todaySource ↗
Quant LetterNo. 54
June 2024, Week 3
138 items across 10 sections, as sent to readers on 20 June 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 138
- Papers
- 83
- Sections
- 10
- Issue
- No. 54
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
16 items
Finance9
Neural Implied Volatility Smoothing
A novel method for smoothing implied volatility using neural operators is presented, which maps data to smoothed surfaces, respects no-arbitrage rules, and is robust to input subsampling.
7 shares17 citations todaySource ↗
Robust Option Pricing with Multi-Marginal Computation
The article introduces an efficient computational framework for solving complex multi-marginal martingale optimal transport problems quickly and optimally.
6 shares3 citations todaySource ↗
NLP for Financial Risk Detection
The study shows that Natural Language Processing (NLP) can be effectively used to detect and predict potential risks in financial documents and communications.
4 shares22 citations todaySource ↗
Local Wealth Condensation
The article provides a new proof for Chakraborti's economic model, which suggests wealth concentration and poverty increase in a trading system.
3 shares2 citations todaySource ↗
MeanVariance Investment
The study offers solutions to an optimal investment-reinsurance problem for insurers under a specific model, using a system of complex mathematical equations.
3 shares2 citations todaySource ↗
Robust Dividend Policy
The research suggests that investors who care about dividends can select suitable firms by examining their dividend policies and financial statements.
2 shares1 citation todaySource ↗
Circular Steel Industry Transformation
The paper calls for a restructuring of global and European scrap trade to lower CO2 emissions in the steel industry, highlighting the strategic importance of scrap metal.
2 shares6 citations todaySource ↗
Generalized Dependence Analysis
The article demonstrates that a certain class of multivariate distributions is a convex polytope, providing precise analytical limits for convex risk measures.
2 shares4 citations todaySource ↗
Economics1
Rationalizability and Cost Efficiency in Consumer Demand
The article explores the relationship between approximate rationalizability and approximate cost-rationalizability in consumer demand, viewing Afriat's critical cost-efficiency index as a gauge of cost inefficiency.
2 shares6 citations todaySource ↗
Miscellaneous3
Universal Randomised Signatures
The article presents a new model for analyzing financial data over time, using a unique Wasserstein-type distance method, and compares its performance with current standards.
7 shares8 citations todaySource ↗
AI Replicating Human Decision-making
The study examines the use of large language models in mimicking human decision-making in economic experiments, emphasizing the importance of the models' reasoning capabilities in achieving realistic results.
4 shares18 citations todaySource ↗
Trading Devil
The research explores a specific type of audio data attack, called a Stochastic investment-based backdoor attack, and shows its effectiveness in tricking speech recognition systems.
4 shares3 citations todaySource ↗
Crypto & Blockchain1
DAO Business Value: Open Systems Perspective
Open Systems Perspective: The article introduces a new business model for decentralized autonomous organizations (DAOs), highlighting their potential for innovation and transformation. It also lays a theoretical groundwork for future studies on this topic.
2 shares1 citation todaySource ↗
Historical Trending2
Asset Allocation Forecasting
The article introduces a new framework that enhances multi-asset portfolio construction by creating custom regime forecasts for each asset, proven effective through a practical study on a multi-asset portfolio.
9 shares23 citations todaySource ↗
Forward Approximations Justification
The note discusses the theoretical basis for using weighted averages of overnight forwards to approximate arithmetic forwards, offering less expensive computational methods and aligning one method with an approximation proposed by Katsumi Takada.
4 sharesSource ↗
SSRN
Working papers in finance and economics from SSRN.
27 items
Quantitative18
Spatial Linkages of Positive Feedback Trading
Positive feedback trading impacts the stock index futures markets in 27 countries, with stronger effects in upward trends when market volatility is above 2 and in downward trends when it exceeds 4.
5 sharesSource ↗
Asymmetric Effects in China's Stock Market
In China's stock market, intraday returns influence overnight returns, and there's a mutual positive impact between overnight and intraday volatility, which intensifies as the quantile increases.
6 sharesSource ↗
Pricing of American Timer Options
The study provides analytic formulas for American timer option prices under stochastic volatility, using a finite stochastic variance clock as a time-to-maturity measure.
4 sharesSource ↗
Net Foreign Portfolio Inflows in Nigeria
Higher interest rates in Nigeria can boost net portfolio inflows and potentially stabilize the exchange rate, but this depends on the Central Bank's ability to manage foreign exchange.
6 sharesSource ↗
Basics of Technical Analysis
Technical analysis uses historical market data patterns to predict future price movements, employing tools like moving averages, relative strength index, and Bollinger Bands.
3 sharesSource ↗
Volatility Dynamics in Vietnam Stock Market
The study finds that single-regime models are more effective than multiple-regime models in forecasting short-term volatility in the Vietnam Ho Chi Minh Stock Index.
3 sharesSource ↗
Insurable Risk Portfolios with Data Uncertainty
The paper suggests that data uncertainty in investments is not a significant issue in insurance, using an insurance version of the Markowitz portfolio optimization procedure.
4 sharesSource ↗
GANs for Chemical Foam Detection in Low Data
The research uses Generative Adversarial Networks (GANs) to improve the classification of chemical foam, addressing the issue of scarce and poorly labeled datasets in the chemical sector.
5 sharesSource ↗
Mutual Funds Securities Lending: Value vs. Volume
Value vs. Volume: The study reveals that mutual funds with higher volume lending strategies generate more revenue, using securities lending patterns to identify shorting demand.
3 sharesSource ↗
MSBoost: Model Selection for Gradient Boosting
Model Selection for Gradient Boosting: The paper introduces a new gradient boosting approach that trains multiple models on residual errors simultaneously, proving especially effective for small and noisy datasets.
3 sharesSource ↗
Customizing Stock Portfolios
A study shows that including nontradable wealth like human capital in portfolio optimization reduces risk and improves returns, based on data from 263 US firms from 2013 to 2022.
4 sharesSource ↗
Impact of Privacy Regulations
Apple's stricter privacy measures have resulted in a significant decrease in iOS data availability for location-tracking services, contradicting concerns about underrepresentation of low-income populations.
4 sharesSource ↗
Machine Learning for Detecting Accounting
A new method using machine learning and text data from 10K reports can predict the likelihood of a firm misreporting financial information, with higher probabilities associated with higher risks and costs.
2 shares1 citation todaySource ↗
Hands-Free Mouse System
A Hands-Free Mouse system uses facial recognition and machine learning to improve accessibility for physically disabled individuals in the field of assistive technology.
3 sharesSource ↗
Equity Option Approximation
The article introduces an approximation for the equity BlackScholes model with fixed dividends, applicable to vanilla options and reverts to the classic model when dividends are null.
3 sharesSource ↗
Film Investment Model
The paper emphasizes the role of movie merchandise in income diversification in the film industry and presents a model predicting merchandise exploitability with 88.6% accuracy.
2 sharesSource ↗
Seismological Records Processing
The project aims to vectorise old seismograms using machine learning, focusing on reducing human interaction and increasing programming approach in the process.
2 sharesSource ↗
Mutual Fund Risk Shifts
The study investigates the impact of star ratings on mutual fund managers' risk-taking behavior, showing that managers adjust risk levels based on potential rating changes, leading to potential agency issues and increased managerial effort.
2 sharesSource ↗
Financial9
Option Returns with DL
A study uses deep learning to predict equity options returns, showing significant profits using a Convolutional Neural Network to identify patterns in volatility.
3 sharesSource ↗
Spot Crypto ETFs
The approval of Bitcoin and Ethereum ETFs offers investors a less volatile way to invest in cryptocurrencies, marking a significant financial market milestone.
2 sharesSource ↗
Retail Investors and Factsheet
A study finds that retail investors react more to performance measures in factsheets from Morningstar, but this doesn't necessarily improve investment decisions.
3 sharesSource ↗
Demat Trading in India
A new technology enabling paperless trading on India's National Stock Exchange led to a decrease in bid-ask spread and increased trading volume, especially for previously illiquid stocks.
2 sharesSource ↗
Corporate Social Irresponsibility in Stock Trading
A study finds that investors in cities with high social capital trade less frequently in stocks of companies involved in corporate social irresponsibility events.
2 sharesSource ↗
Green Investments in European Ventures
More corporations are investing in eco-friendly startups for genuine reasons, with green corporate venture capital investors fostering green innovation.
4 sharesSource ↗
Liquidity Risk in Indian Stock Market
A study investigates the impact of systematic liquidity risk on the Indian equity market, focusing on the effects of illiquidity on market volatility.
2 sharesSource ↗
Idiosyncratic Entropy and Stock Returns
The research introduces a risk factor for idiosyncratic entropy and reveals a negative correlation between expected idiosyncratic entropy and returns, providing insight into the idiosyncratic volatility puzzle.
2 sharesSource ↗
ESG Ratings and Financing Decisions
Higher ESG scores correlate with increased equity issuance and reduced net debt issuance, but do not affect capital expenditures or noncash asset accumulation, indicating ESG ratings do not impact investment choices.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
23 items
Finance9
Machine Learning for Financial Forecasting
Machine learning models performed better than market benchmarks during the Russia-Ukraine war, but not prior to the conflict, indicating caution should be used when forecasting stock prices with these models.
33 sharesSource ↗
Market Efficiency of Chinese Copper
The study found no significant arbitrage opportunities in China's copper futures market, suggesting it adheres to the market efficiency rule despite its growth and internationalization.
31 sharesSource ↗
Algorithmic Trading and NYSE Efficiency
Increased algorithmic trading reduces the predictive power of market order imbalance and limit order book imbalances, indicating it enhances market efficiency.
29 sharesSource ↗
Forecasting Volatility in Taiwan Futures
A new model considering information from non-trading and trading periods significantly improves the forecasting of stock market volatility.
27 sharesSource ↗
Alpha Testing in Linear Factor Models
The article introduces a new, faster test for alpha in linear factor pricing models, which remains valid even with a large number of securities and can account for some pricing errors, finding evidence against certain asset pricing models during the Great Recession.
23 sharesSource ↗
Hedge Funds and Low Beta Anomaly
The article reveals that the average hedge fund benefits from the low beta anomaly, attributing about 2.3% per year of apparent alpha to the anomaly rather than manager skill, especially among low skill managers.
22 sharesSource ↗
Machine Learning for ETF Forecasting
The article suggests a machine learning method for analyzing the direction of returns from exchange traded funds, with models generally outperforming control metrics in terms of risk and return, particularly the linear regression and certain classification models.
22 sharesSource ↗
Implied Roughness in Oil Volatility
The article examines the roughness of oil market volatility using unspanned stochastic volatility models, demonstrating that adding an extra parameter indicating the volatility's roughness improves the calibration nearly tenfold.
19 sharesSource ↗
Diversification Costs & Benefits
The article empirically demonstrates that diversification not only reduces risk but also returns if the expected returns can be estimated, supporting the claim that diversification is protection against ignorance.
17 sharesSource ↗
Statistical4
Machine Learning for Financial Scenarios
The article introduces a new machine learning method for predicting one-day-ahead scenarios for portfolio optimization, which could lead to more precise forecasts and less risky portfolios.
27 sharesSource ↗
Enhanced Inflation Forecasting in Emerging Economies
The study combines traditional forecasting and machine learning to predict inflation in an emerging economy, finding machine learning to be more effective, especially when foreign exchange reserves are included.
26 sharesSource ↗
Credit Spread Changes Analysis with AI
The research compares linear regression and machine learning in modeling credit spread changes, with machine learning proving superior due to its handling of complex non-linearities, and uses these models to measure the impact of various economic and financial factors.
19 sharesSource ↗
Intraday Volatility Forecasting for Indian Stocks
The paper evaluates the effectiveness of range-based volatility estimations against standard models using Indian stock market data, concluding that range-based models are superior and the GKYZ volatility estimator is the most accurate.
18 sharesSource ↗
Machine Learning6
Cryptocurrency Options Pricing
Machine learning models, particularly regression-tree methods, are more efficient at pricing cryptocurrency options than traditional models due to their adaptability to cryptocurrency market dynamics.
45 sharesSource ↗
Interpretable Machine Learning
The study shows that interpretable machine learning is more effective in modeling corporate bond recovery rates and identifying key drivers that traditional methods can't detect.
39 sharesSource ↗
Predicting Stock Market Direction
The research indicates that machine learning methods, especially random forests and bagging, are better at predicting the US stock market direction using volatility indices than classical linear regression models.
26 sharesSource ↗
Cryptocurrency Predictability
Machine learning models effectively predict cryptocurrency market returns, with key predictors being market price and momentum, and most strategies remain profitable even after trading costs.
25 sharesSource ↗
Dividend Prediction in Vietnam
The Random Forest algorithm in machine learning models successfully predicts dividend payouts in the Vietnamese stock market, enhancing decision-making and financial market transparency.
23 sharesSource ↗
Machine Learning for GDP
Ridge, elastic net, and SVR machine learning algorithms are the most effective for nowcasting GDP, outperforming other methods by up to 28% in out-of-sample RMSE.
21 sharesSource ↗
Deep Learning1
Bitcoin Volatility Forecasting with Deep Learning Model
The study uses a deep learning model and a particle swarm optimization (PSO) algorithm to predict Bitcoin's volatility, improving accuracy by up to 34.79%. It also suggests a risk warning system and trading strategy for investors.
21 sharesSource ↗
Historical Trending3
Accounting Journals: Research and Practice
Research and Practice: The study uses machine learning to highlight a significant gap between academic research and practical application in accounting, more so in the US than Europe.
6 sharesSource ↗
Board Gender Diversity Impact on Firm Risk
Research shows that companies with gender diverse boards have reduced risk due to improved group dynamics, positively impacting risk management and financial performance.
6 sharesSource ↗
Employer Preferences for Older Workers
Finnish employers tend to hire older workers during labour shortages, particularly if they value the experience-related qualities of older workers.
2 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
17 items
Recently Published10
Factual Knowledge in Large Language Models
Large language models (LLMs) learn factual knowledge during pretraining, but this knowledge is often forgotten in subsequent steps.
124 shares118 citations todaySource ↗
Language Models & Probabilistic Reasoning
Language models have difficulty with numerical reasoning and understanding probability distributions, but can improve with real-world context and simplified assumptions.
73 shares29 citations todaySource ↗
Encoder-Free Vision-Language Models
The EVE model, a vision-language model without an encoder, performs well across multiple benchmarks, offering an efficient way to develop a decoder-only architecture.
73 shares102 citations todaySource ↗
LLARVA: Robot Learning Enhancement
Robot Learning Enhancement: The LLARVA model, trained with a new method, successfully unifies various robotic learning tasks and performs well in different robot environments.
59 shares96 citations todaySource ↗
Language Models & External Knowledge Utilization
Retrieval Augmented Generation (RAG) enhances language models' reasoning abilities using external context, but models tend to rely heavily on this context and less on their parametric memory.
37 shares20 citations todaySource ↗
Scalable Dense Scene Rendering
The research introduces RetinaGS, a new method for training 3D Gaussian splatting models, which improves scaling behavior and reconstruction quality.
34 shares21 citations todaySource ↗
Scene Synthesis at Scale
The article presents MegaScenes, a large dataset from internet photos, which enhances the consistency of novel view synthesis methods.
26 shares66 citations todaySource ↗
Neural Network Symmetrisation
The study proposes a new framework for symmetrising neural networks using group homomorphism and Markov categories, demonstrating their usefulness in machine learning.
21 shares7 citations todaySource ↗
Language Modeling with External Knowledge
The paper presents ERASE, a method that improves the performance of retrieval-augmented generation models by incrementally modifying the knowledge base when new documents are added.
16 shares9 citations todaySource ↗
Privacy Preserving Federated Learning
The research reviews Federated Learning in medical imaging, discussing its challenges, potential for privacy preservation and uncertainty estimation, and suggesting future research directions.
13 shares34 citations todaySource ↗
Historical Trending7
MatMul-free Language Modeling
Scientists have developed a method to remove matrix multiplication from large language models, reducing memory usage by up to 61% during training and over 10x during inference, making these models more efficient.
610 shares45 citations todaySource ↗
Transformers on Pixels
A study shows that vanilla Transformers can treat each pixel as a token and still perform well, questioning the need for locality in computer vision architectures and suggesting a new direction for future designs.
228 shares75 citations todaySource ↗
Simple Adaptive Attacks on LLMs
Research reveals that even the latest safety-aligned large language models are susceptible to simple adaptive jailbreaking attacks, with almost 100% success rate, emphasizing the significance of adaptivity in these attacks.
214 shares580 citations todaySource ↗
Depth Anything V2
Depth Anything V2 is a new model for monocular depth estimation, using synthetic and large-scale pseudo-labeled real images for faster, more accurate results and setting a new evaluation benchmark.
134 shares2,228 citations todaySource ↗
Rethinking Score Distillation
The article explores Score Distillation Sampling (SDS), a tool for data-poor domains, suggesting that source distribution calibration can enhance image generation and translation across various domains.
75 shares43 citations todaySource ↗
HyperFields
HyperFields, a method for generating text-conditioned Neural Radiance Fields (NeRFs), is introduced, offering faster prediction of novel scenes and highlighting the significance of dynamic architecture and NeRF distillation.
72 shares15 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
9 items
Trending4
Efficient Context Language Modeling
Samba, a model trained on 4K sequences, can be effectively extended to 256K context length, enhancing token predictions up to 1M context length.
546 shares
ProG Learning Benchmark
Despite advancements, artificial general intelligence on graphs struggles with inefficiencies and negative transfer problems in complex and few-shot scenarios.
437 shares
MeshAnything Mesh Generation
D assets produced through reconstruction and generation have achieved the quality of handcrafted assets, suggesting potential for substitution.
414 shares
GPT Mathematical Olympiad Solutions
The MCT SelfRefine algorithm combines Large Language Models with Monte Carlo Tree Search, enhancing performance in complex mathematical reasoning tasks.
278 shares
Rising5
TextGrad: Auto Diff via Text
Auto Diff via Text: TextGrad improves the performance of GPT4o in answering complex questions and solving difficult coding problems without changing the existing framework.
190 shares
MLBench: Eval Large Language Models
Eval Large Language Models: GPT4, a large language model, has difficulties in understanding and interacting with large-scale code repositories.
126 shares
CleanDiffuser: Modular Diffusion Library
Modular Diffusion Library: CleanDiffuser's core consists of crucial submodules, identified by reevaluating the roles of decision-makers in the decision-making domain.
80 shares
LibriTTSP: Text-to-Speech Corpus
Text-to-Speech Corpus: A hybrid method is used to create prompt annotations, merging manual annotations of speaker traits and synthetic annotations of speaking style.
50 shares
AsyncDiff: Parallel Diffusion Models
Parallel Diffusion Models: AsyncDiff is a new acceleration scheme designed to facilitate model parallelism across several devices.
44 shares
GitHub
Repositories the letter featured.
10 items
Finance5
ML Foundations
The article provides an overview of the fundamental components of machine learning such as linear algebra, calculus, statistics, and computer science.
3,103 shares
MultiFactor Backtesting
The article outlines the development of a MultiFactor Backtesting Framework based on a financial engineering report from Huatai Security, discussing processes like data gathering and risk assessment.
46 shares
Airbyte Integration
The article presents a top data integration platform for ETL ELT data pipelines, offering options for either self-hosting or cloud-hosting.
14,567 shares
Cryptocurrency Arbitrage
The article delves into the idea of funding rate arbitrage within the cryptocurrency sector.
111 shares
Dockerized Quant Environment
The article introduces a dockerized Jupyter environment designed for quantitative research.
67 shares
Trending5
Boltzmann Entropy Interviews
The book is recommended for postgraduates, jobseekers, and experienced researchers for its valuable content.
4,461 shares
Crowd Cent Numerblox
The article delves into the process of building solid pipelines in Numerai.
106 shares
Deep Charles Ruptures
The piece investigates the use of ruptures in Python for detecting change points.
1,520 shares
Chain Lit Chain Lit
The article offers a tutorial on the quick and efficient construction of conversational AI.
5,903 shares
News
Industry news: funds, hiring, markets and regulation.
19 items
Quantitative9
Convertible Arbitrage Revival
AQR Capital Management is encouraging the return of convertible arbitrage, a method that gains from debt that can be converted into equity.
7 shares
Point72 Launches AI Hedge Fund
Point72 Asset Management aims to gather about $1bn for a new AI-centric hedge fund, marking its first in several years.
4 shares
Terraform Labs Settles with SEC
Terraform Labs and former CEO Do Kwon have settled for $4.5bn with the US SEC after a fraud conviction related to cryptocurrency securities.
3 shares
Saba Capital Seeks Injunction against BlackRock
Saba Capital Management has requested a US judge to prevent BlackRock from employing a strategy that allegedly restricts investors' ability to choose the board of a closed-end fund.
3 shares
Castle Ridge AI Launch
Castle Ridge Asset Management has introduced an AI multistrategy powered by its own AI platform, WALLACE.
3 shares
Tidan Capital Head
Tidan Capital, a Swedish hedge fund firm, has named Linus Nilsson as partner and head of systematic strategies.
3 shares
Hedge Funds Cautious
A Goldman Sachs report indicates that hedge funds are becoming more cautious towards equities, despite Wall Street's optimistic outlook.
3 shares
Hazeltree Presales Director
Hazeltree, a treasury and operations technology provider for the alternative asset industry, has hired Paul Yates as senior presales director in London.
3 shares
Jain Global Asia Launch
Jain Global, Bobby Jain’s new hedge fund firm, plans to hire over 30 staff members in Asia, with local leaders playing crucial roles in hiring and risk management.
3 shares
Miscellaneous10
Hedge Funds Outperform
Goldman Sachs reports that hedge fund managers focusing on mergers and acquisitions have seen a 7.7 return in the first five months of 2024, outperforming other strategies.
2 shares
Geopolitical Uncertainty Affects Trade
TD Securities strategists note a trend of clients unwinding the carry trade, a strategy that exploits interest rate differences between countries, according to MarketWatch.
2 shares
Balyasny AM Workforce Cut
Balyasny Asset Management has reduced its workforce from 266 to 219 employees by the end of 2023, as reported by Financial News.
2 shares
Top Financial Engineering Courses
The article highlights courses that promise 100% employment and an average post-graduation salary of 120k.
1 shares
Tech Jobs in Finance: Coding Needed
Coding Needed: The article recommends Java developers outside of New York to consider relocating for potential benefits.
1 shares
Hedge funds bullish on Magnificent Seven
A Bank of America survey reveals that a strategy focusing on US megacap tech companies is the most crowded trade for the 15th consecutive month.
1 shares
Sissener Canopus sells Golden Ocean
Sissener Canopus, a Nordic-focused hedge fund, has sold its holdings in the Oslo-listed shipping company, Golden Ocean Group.
1 shares
Shares appoints Head of US Business
Federico Brokate has been appointed as Vice President, Head of US Business for 21Shares US, a crypto exchange traded funds issuer, to assist in its US market expansion.
0 shares
ExGoldman Sachs MD predicts AI impact
The article discusses a potential beneficial situation, but does not specify what it is.
0 shares
Citadels engineering prodigy drops out
The article is about a person who runs a popular TikTok channel.
0 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Decoding EM Volatility
Jonny Goulden and Saad Siddiqui analyze the reasons behind the rising volatility in emerging markets in a podcast from June 14, 2024.
10 shares
PostPandemic Investing
Lori Calvasina of RBC Capital Markets talks about the sentiment-driven US market post-COVID and shares her market predictions for 2025.
9 shares
Recent Events Impact on US Rates
Jay Barry and Phoebe White discuss the effects of recent European events on Treasury market liquidity and their forecasts for US rates and inflation markets, as of June 14, 2024.
7 shares
US Interest Rate Derivatives Trends
Srini Ramaswamy and Ipek Ozil discuss recent trends in US interest rate derivatives markets in a June 17, 2024 podcast.
6 shares
Global FX Forecasting
Meera Chandan and Patrick Locke discuss the impact of US inflation, the FOMC, and recent volatility shocks on the dollar and foreign exchange markets in a June 14, 2024 podcast.
5 shares
Related5
Fixed Income 2024
Colin Reedie discusses the factors influencing financial markets, drawing comparisons with the 1970s, which he predicts will shape the financial landscape in 2024 and 2025.
5 shares
Coding Journey
Three individuals at varying stages of their coding careers share their experiences, from a novice to a professional mathematician and Machine Learning Research Engineer.
4 shares
Portfolio Outlook 2024
Christian Mueller-Glissmann and Alexandra Wilson-Elizondo from Goldman Sachs share their predictions for asset classes and portfolios for the latter half of the year and potential shifts in asset allocation.
3 shares
European Rate Update
Francis Diamond and Aditya Chordia discuss the main themes for European rate markets, with a focus on French politics and its effect on French spread and other intra-EMU spreads.
3 shares
Commodities Forecast
Despite a decrease in drilling activity, US crude oil production is predicted to rise in 2024 and 2025 due to operational efficiencies compensating for declining productivity and a low rig count.
3 shares
Blogs
Posts from quant and economics blogs and newsletters.
4 items
Quantitative2
Quant Researcher at Citadel Securities
Will Kaufhold is a quantitative researcher at Citadel Securities in Miami, who joined in 2021 after completing his PhD in physics at the University of Cambridge.
4 shares
First Trading Day Strategy
The first day of each month often shows significant market trends, leading to increased interest in trading strategies at the start of the month.
3 shares
Related2
Cryptonite 6/24
The 132nd Wilmott Magazine issue in 2024 presents unique contributions from leading columnists, educators, and researchers.
0 shares
Shyam S.
An article named Contents by D. Tudball is featured in the 132nd issue of Wilmott Magazine in 2024.
0 shares
X / Twitter
Posts from quant researchers on X.
3 items
Quantitative1
AI in Asset Management: Opportunities & Advances
Opportunities & Advances: The article talks about the major developments in artificial intelligence and how it could be utilized in the field of investment management.
2 shares
Miscellaneous2
Decentralized Exchanges: Benefits, Risks, Regulation
Benefits, Risks, Regulation: Article 1: The paper discusses the benefits, risks, and possible regulatory methods related to decentralized exchanges (DEXs), focusing on the function of private and public liquidity pools.
1 shares
Multimanager CTA Portfolios, Convexity
Multimanager Commodity Trading Advisor (CTA) portfolios are discovered to yield superior convexity, referred to as the 'CTA smile'.
0 shares