DRL for Put Option Hedging
The article discusses a study that shows deep reinforcement learning (DRL) is more effective than traditional methods for hedging American put options, especially in real-world situations.
7 shares2 citations todaySource ↗
Quant LetterNo. 49
May 2024, Week 3
166 items across 11 sections, as sent to readers on 15 May 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 166
- Papers
- 94
- Sections
- 11
- Issue
- No. 49
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
12 items
Finance6
Noarbitrage in Financial Markets
The paper presents a framework for continuous-time financial market models, demonstrating that no-arbitrage conditions apply in continuous time if they apply in discrete time, and super-hedging prices are the same in both times.
5 shares4 citations todaySource ↗
Trade Execution in Markovian Environment
The paper investigates a trade execution game for two large traders in a price impact model, showing that the execution strategy is dynamic and reflects various characteristics seen in financial markets.
3 sharesSource ↗
Dynamic Risk Measure
The article presents a revised version of the fundamental theorem of asset pricing in financial market models, demonstrating that all risk-hedging prices are consistent under the NA condition.
3 sharesSource ↗
Stock Market Order Dynamics
The research analyzes high-frequency stock market data to understand trading dynamics, revealing that similar strategies are used regardless of volatility during the 2018 USA-China trade war.
3 shares13 citations todaySource ↗
Joint Marginal Expected Shortfall
The paper introduces a new systemic risk measure, the joint marginal expected shortfall (JMES), to assess the impact of one entity's risk on another or overall risk, and compares its effectiveness with other popular measures.
2 shares8 citations todaySource ↗
Economics3
Unfair Research Evaluation Panels
A study suggests a new method to assess the fairness of research panels, using Italian panels as a case study, and finds that government-appointed panels had more connections than randomly selected ones, indicating potential bias.
10 shares4 citations todaySource ↗
Financial Knowledge and Borrower Discouragement
A survey of Italian micro-enterprises reveals that entrepreneurs with less financial knowledge are more likely to avoid applying for new financing due to high costs and fear of rejection, implying that financial knowledge can improve credit market conditions.
2 shares1 citation todaySource ↗
Shanghai Residents' Attitudes Towards Autonomous Vehicles
A study on Shanghai residents' views on autonomous vehicles shows that perceived usefulness, ease of use, and perceived benefits increase willingness to use them, while perceived risk decreases it, offering insights for policy and industry strategies.
2 shares1 citation todaySource ↗
Crypto & Blockchain1
Cryptocurrency Market Crash: Network Analysis
Network Analysis: The study examines cryptocurrency market crashes using complex network analysis. It found that during crashes, network density and information flow increase due to panic selling. After the crash, these parameters try to return to normal, offering insights for investors.
4 shares10 citations todaySource ↗
Historical Trending2
Hybrid Investment Portfolios
The paper presents KDD, a hybrid method combining portfolio theory and reinforcement learning for optimal investment portfolios, achieving high profitability with low risk.
3 shares1 citation todaySource ↗
AI NLP User Feedback Analysis
The paper explores the application of AI and NLP for analyzing user feedback on heavy machine crane products, offering insights for product improvement and enhancing customer experience.
3 shares8 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
40 items
Quantitative20
Hedge Fund Default Risk
The article explores the difficulties in determining the price and risk of hedge fund securities due to a disconnect between margin call defaults and default probability models.
4 sharesSource ↗
Peer Influence on Capital Structure
The study examines how peer financial decisions, commodity prices, and corporate hedging impact the capital structure choices of European and North American oil and gas companies.
8 sharesSource ↗
Liquidity Creation in Turkish Banking
The paper studies liquidity creation in the Turkish banking sector, emphasizing the importance of capital adequacy, ownership structure, and competition level.
41 sharesSource ↗
Temporal Kolmogorov-Arnold Networks
The article presents Temporal Kolomogorov-Arnold Networks (TKANs), a new neural network design that merges the benefits of Recurrent Neural Networks and Long Short-Term Memory for improved multistep time series forecasting.
2 shares189 citations todaySource ↗
Common Advisor Effect in Allocations
The study reveals that pension funds with the same asset manager or actuary tend to make similar asset allocation decisions, which may not align with their unique characteristics or sophistication level.
3 sharesSource ↗
Machine Learning for Embrittlement Forecasting
The research uses machine learning, specifically the Gradient Boosting algorithm, to predict how preirradiation hardening affects the transition temperature shift in RPV steel.
3 sharesSource ↗
Accelerating Fracture Simulations with ML
The paper suggests using unsupervised machine learning and kmeans clustering to speed up multiscale simulations of heterogeneous quasibrittle materials.
4 sharesSource ↗
Forecasting Shadow-Rate VARs with ML
The article examines the use of Shadow Rate Vector Autoregressions in macroeconomic forecasting, particularly the effects of shrinkage priors.
3 shares1 citation todaySource ↗
Hybrid Models for Heat Transfer Prediction
The study uses bioinspired optimization methods and hybrid models to examine heat transfer performance from a turbulent annular jet impingement.
4 sharesSource ↗
Computational Legal Studies Transformation
The article reviews the application of computational analysis techniques in empirical legal scholarship, emphasizing recent advancements in large language models and generative AI.
2 sharesSource ↗
ML in Marine Modeling Review
The study analyzes over 200 papers on the use of Machine Learning for managing marine and coastal environments, offering guidance for future research.
90 sharesSource ↗
Race Discrimination in Hedge Funds
Despite delivering higher returns, minority-operated hedge funds attract less capital, indicating racial discrimination in asset management.
373 sharesSource ↗
Bayesian Inflation Uncertainty
Using a Bayesian framework, the study finds that trade openness, COVID-19, and the Ukraine crisis increase inflation volatility in G20 countries.
2 sharesSource ↗
Corporate Bond IPO Underpricing
Bond IPO underpricing is common and rises during times of market uncertainty, suggesting underwriters struggle to estimate asset value in volatile periods.
2 sharesSource ↗
AI Discourse Analysis in German and Chinese Media
Analysis of Chinese and German media coverage on AI shows regional focus and differing attitudes, with Chinese media being positive and German media being more critical.
2 shares1 citation todaySource ↗
Reserve Currency
The article suggests a model that links global recessions to increased demand for U.S. safe bonds, strengthening the dollar and boosting U.S. wealth and consumption.
2 sharesSource ↗
Stock Price
The study identifies recency, cluster, and sign as three factors shaping investors' risk perceptions of a stock, influencing trading volume and future volatility.
3 shares88 citations todaySource ↗
Crypto Adoption in Africa
The report establishes a correlation between Bitcoin's market cap and closing price, forecasting increased adoption of the cryptocurrency despite its fluctuating value.
2 sharesSource ↗
Investment Bank Isolation
The article explores the expansion of modern banks into proprietary trading, private equity, and hedge fund services.
2 sharesSource ↗
AMLOs Populism
The study uses text analysis to examine how Mexico's President Andrés Manuel López Obrador uses his morning press briefings to propagate his populist agenda, using language that is people-focused but not anti-elite.
2 sharesSource ↗
Financial20
Intraday Momentum Strategy
The study investigates the success of an intraday momentum strategy on SPY, an ETF tracking the SP500, which resulted in a 1985 total return from 2007 to 2024.
1,012 shares2 citations todaySource ↗
FX Margin Trading Biases
A Japanese FX market survey shows that behavioural biases greatly affect the performance of over 1300 private investors, indicating that addressing and altering these biases can enhance investment results.
7 sharesSource ↗
Derivatives Optimization
The article presents a new type of portfolio optimization that considers parameter uncertainty in portfolios with derivatives, utilizing the Exposure Stacking method.
2 sharesSource ↗
Liquid Factor Models
The author recommends using liquid instruments in factor models, arguing that they are more transparent, tradeable, and can surpass other factors while lowering hedging expenses.
7 sharesSource ↗
Decentralized Options Trading
The research looks at OnChain options traded on a decentralized Ethereum blockchain exchange, underlining the differences in implied volatilities compared to OffChain options traded on centralized exchanges.
3 shares4 citations todaySource ↗
Inflation and Investor Response
Research indicates that investors often hold unrealistic expectations about stock returns during high inflation, and lack knowledge about inflation-hedging strategies, affecting their trading decisions.
14 shares12 citations todaySource ↗
Bank Performance Factors
A new bank performance metric reveals that structural issues like cost inefficiencies primarily cause underperformance, with high-performing banks being less dependent on government aid and more shock-resistant.
4 shares2 citations todaySource ↗
Portfolio Risk Measure
A novel portfolio measure of risk-adjusted excess returns is introduced, which views any negative impact on compound return as risk, addressing some criticisms of the Sharpe ratio.
7 sharesSource ↗
Foreign Signals and Stock Prices
Machine learning algorithms can predict daily U.S. stock returns based on foreign market signals, with a portfolio based on these predictions yielding abnormal returns of 5.77 basis points daily.
15 sharesSource ↗
Stock-Based Compensation Valuation
The study introduces a closed-form approximation for the fair value of market-based awards and SPAC transactions, providing a strong alternative to Monte Carlo simulation methods.
4 sharesSource ↗
Machine Learning for Trading
Machine learning is being used to explore the link between high-frequency trading and financial market trends, offering new ways to identify different trading strategies and their effects on market information.
3 shares1 citation todaySource ↗
Network Beliefs Impact Prices
A new model suggests that asset prices are influenced by network properties and investor performance, which can explain price bubbles and fluctuations.
167 sharesSource ↗
Macroeconomic Announcements and Pricing
Machine learning has improved the prediction of stock returns, with a model that combines data from different trading days proving more accurate than others.
5 sharesSource ↗
Mutual Fund Managers and Volatility
Research shows that mutual fund managers reduce market exposure during times of high market volatility, indicating a sensitivity to market volatility changes.
2 sharesSource ↗
CoTrading Networks in US Markets
A study examines how simultaneous trading across different stocks influences US equity market structures and stock prices, introducing a new method to create dynamic stock networks and showing a positive correlation between low-latency co-trading and return covariance.
2 sharesSource ↗
Stock-Bond Correlation
The study discusses the significance of stock-bond correlation modeling in portfolio allocation, emphasizing the current preference for negative correlation due to its risk reduction during equity market distress.
3 shares2 citations todaySource ↗
Social Media Trading Impact
The paper investigates the effect of presidential tweets on equity markets, revealing that market volatility increases and liquidity worsens more quickly during extended trading hours.
2 sharesSource ↗
Margin Models for MBS
The article delves into the challenges of modeling for mortgage-backed securities trading, including housing market dynamics, changes in mortgage regulations, and government interventions.
5 sharesSource ↗
Bond Portfolio Optimization
The research compares the effects of integrating credit risk and interest rate risk in bond portfolio optimization with traditional risk measures, introducing a new approach called Duration Spread Ratio (DSR) optimization that outperforms in all scenarios.
2 shares1 citation todaySource ↗
Earnings Forecast Accuracy
The study examines the link between model-based earnings forecast accuracy and portfolios sorted on implied cost of capital, highlighting that machine learning models provide the highest return spreads and the importance of considering transaction costs in financial analysis.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
26 items
Finance5
Feedback Trading in Indian Equity Markets
The article explores how institutional investors' feedback trading impacts Indian equity markets during COVID-19, with foreign investors favoring positive feedback trading and domestic investors opting for negative feedback trading.
23 sharesSource ↗
Information Asymmetry and Volatility in Indian Stock Market
The study analyzes the link between the Indian stock market and the top four global economies pre and post-COVID-19, showing significant volatility spillover from these markets to India, which can guide investment choices.
18 sharesSource ↗
Explainable AI in Finance
The paper reviews current research on Explainable Artificial Intelligence (XAI) in Finance, emphasizing its crucial role in highly-regulated sectors like Finance for ensuring decision-making transparency and traceability.
16 sharesSource ↗
Fund Portfolio Mismatch and Market Volatility in China
The research indicates that the level of network connection in financial markets can either stabilize or intensify market volatility, with over-connection of networks leading to increased market volatility.
14 sharesSource ↗
Optimizing Cryptocurrency Returns
The study applies the robust framework of factor investing to cryptocurrency assets, proposing a weekly rebalancing strategy to manage market fluctuations and underlining the predictive power of momentum and value factors in predicting cryptocurrency returns.
13 sharesSource ↗
Statistical3
Ensemble Boosting Trees for Volatility Forecasting
The study finds ensemble boosting tree models, particularly CatBoost and LightGBM, more effective than traditional models in predicting China's crude oil futures volatility, with macroeconomic and HAR-type variables impacting forecasts differently.
20 sharesSource ↗
Predicting Employee Turnover
The research uses machine learning to predict employee turnover based on various factors, with the Decision Tree model proving most accurate.
17 sharesSource ↗
Feature Selection for Financial Fraud Detection
The article emphasizes the role of feature selection in financial fraud detection, advocating for correlation-based filter selection methods to enhance classification effectiveness and reduce computational burden, as tested on Indian companies' financial data.
11 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 can enhance credit risk modeling across a company, improving underwriting and enabling profit and volatility predictions at the account level.
20 sharesSource ↗
Urban GDP Growth Forecasting in South Sudan
A machine learning model using remote sensing data can predict future urban light patterns in South Sudan, which can be used to estimate urban GDP growth.
19 sharesSource ↗
Stock Return Forecasting with Machine Learning
The long short-term memory (LSTM) classifier, a machine learning technique, can predict future stock prices more accurately than random choice, questioning the validity of certain market theories.
17 sharesSource ↗
Firm Adaptation in a Changing World: Prosper Marketplace
Prosper Marketplace: A new approach has been suggested to understand how companies adapt to changes, with a case study on Prosper indicating it uses a collective algorithm for adaptive learning.
16 sharesSource ↗
Credit Risk Assessment for MSMEs
A new study presents a machine learning model that improves risk assessment for Micro Small and Medium-sized Enterprises (MSMEs).
14 sharesSource ↗
Accelerating Tax Statistics Prediction
The German Federal Statistical Office is using machine learning to predict pension taxation data, aiming for quicker statistics publication.
12 sharesSource ↗
Enhancing Project Cost Estimates
Machine learning is being used in a study to increase the accuracy of project cost forecasting throughout a project's life cycle.
12 sharesSource ↗
Modeling Paid-Ups in Life Insurance
Predictive models are being used to forecast the future of premium payment policies in life insurance, identifying less likely payers and the effect of surrender fees.
12 sharesSource ↗
Anomalies and Market Returns
A study using machine learning suggests that equity anomalies do not predict overall market returns, challenging the belief that they are useful for forecasting market risk premia.
11 sharesSource ↗
Deep Learning1
Bitcoin Crash Prediction Framework
The article talks about a new deep learning framework that uses contrastive learning to predict Bitcoin market crashes. This model outperforms six other models by 15.8% in terms of balanced accuracy.
14 sharesSource ↗
Historical Trending7
Asset Pricing in Sustainable Equity Portfolios: Evidence from Pakistan Stock Exchange
Evidence from Pakistan Stock Exchange: Research shows multifactor models effectively price sustainable equity portfolios in the Pakistan Stock Exchange–Karachi Meezan Index, despite not supporting the capital asset pricing model.
16 sharesSource ↗
Investor Sentiments and Stock Valuation
Studies indicate that asset valuation models should account for both market and stock-level investor sentiments, with the latter being more impactful, to prevent significant model deficiencies.
8 sharesSource ↗
Factors Influencing Gold Prices in Malaysia
A study is investigating the factors affecting gold prices in Malaysia, using macroeconomic indicators like GDP, inflation rate, interest rate, unemployment rate, and exchange rate.
7 sharesSource ↗
Robust Portfolio Optimization
The article presents a new method for building strong investment portfolios using the Chance Constrained Data Envelopment Analysis model, which has proven to reduce risk and increase returns on the Brazil Stock Exchange.
6 sharesSource ↗
International CPI Inflation Post-Crisis
The study reveals a significant shift in the international consumer price index inflation comovement in 2008, with global factors having a greater impact on national inflation rates, especially noncommodity global factors.
6 sharesSource ↗
US National Housing Market Bubble
The research, using a time-varying parameter dynamic factor model, indicates that the national factor is key in explaining house price fluctuations, suggesting a possible national bubble in the US housing market since 2014.
5 sharesSource ↗
Financial Statements Fraud Detection
The article introduces a new accounting tool for immediate fraud detection and prevention, created by testing the significance of certain financial statement positions and combining them with existing ones.
5 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
16 items
Recently Published10
Distilling Conditional GANs
A new method has been proposed to simplify a complex multistep diffusion model into a single-step conditional GAN model, which speeds up inference and maintains image quality, performing better than other models on the zero-shot COCO benchmark.
160 shares105 citations todaySource ↗
FineTuning LLMs
Research shows that large language models have difficulty acquiring new factual knowledge through fine-tuning, learning new information slower than consistent knowledge, and are more likely to hallucinate, indicating the risks of introducing new facts through fine-tuning.
158 shares323 citations todaySource ↗
Lumina-T2X: Text Transformation
Text Transformation: The Lumina-T2X family, a series of Large Diffusion Transformers, is introduced as a unified framework for transforming noise into various forms of media based on text instructions, allowing for training across different modalities and flexible multimodal data generation.
89 shares146 citations todaySource ↗
CuMo Scaling Multimodal LLM
CuMo, a model that integrates Co-upcycled Top-K sparsely-gated Mixture-of-experts blocks into the vision encoder and the MLP connector, improves multimodal LLMs with minimal additional activated parameters during inference, outperforming other multimodal LLMs across various benchmarks.
55 shares78 citations todaySource ↗
Safe AI Framework
The paper introduces guaranteed safe (GS) AI, a set of AI safety approaches that aim to provide AI systems with high-assurance quantitative safety guarantees, achieved through the interaction of a world model, a safety specification, and a verifier, arguing for the necessity of this approach to AI safety.
26 shares139 citations todaySource ↗
Conformal Validity for Any Data Distribution
The article explores the creation of prediction algorithms for machine learning systems that self-collect data, focusing on managing risk in optimization and active learning tasks.
22 shares27 citations todaySource ↗
AgentClinic: AI Evaluation in Clinical Environments
AI Evaluation in Clinical Environments: The paper introduces AgentClinic, a benchmark for assessing large language models in simulated clinical environments, highlighting the significant impact of biases on diagnostic accuracy and patient interactions.
21 shares256 citations todaySource ↗
Federated Combinatorial Bandits for Multi-Agent Learning
The study presents a federated learning framework for online combinatorial optimization, transforming single-agent algorithms into multi-agent ones, proving efficient in a stochastic data summarization problem.
21 shares14 citations todaySource ↗
The Platonic Representation Hypothesis
The authors suggest that AI models, especially deep networks, are moving towards a common statistical model of reality, known as the platonic representation, and discuss its implications and limitations.
19 shares429 citations todaySource ↗
Decomposing Weather Forecasting with Neural Networks
The research introduces a machine learning model for weather forecasting that separately learns horizontal and vertical atmospheric movements, surpassing existing methods in accuracy and efficiency.
13 shares2 citations todaySource ↗
Historical Trending6
YOCO Decoder-Decoder Architecture
YOCO architecture improves large language models by reducing GPU memory usage and speeding up the prefill stage, outperforming the Transformer model.
272 shares155 citations todaySource ↗
The Un-Kidnappable Robot
Scientists have created a technique for robots to identify and track humans based on the subtle sounds they make while moving, even when they're attempting to be silent.
100 shares3 citations todaySource ↗
Imagine Flash: Emu Diffusion Models
Emu Diffusion Models: A new distillation framework for diffusion models allows for high-quality sample generation in fewer steps, surpassing current methods in both numerical measurements and human assessments.
57 shares37 citations todaySource ↗
Impact of Imperfect XAI
A study shows that incorrect explanations from explainable AI (XAI) can influence human decision-making, with the impact varying based on the level of human expertise and the quality of the AI.
39 shares84 citations todaySource ↗
Attention-Driven Efficiency Enhancement
The new AT-EDM framework uses attention maps to remove unnecessary tokens without retraining, enhancing efficiency and preserving image generation quality.
36 shares44 citations todaySource ↗
Embodied Generalist Agent
LEO, a multi-modal generalist agent, is designed to perform various tasks in a 3D environment, including 3D captioning, question answering, and navigation.
30 shares443 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
7 items
Trending3
TimeGPT: Time Series Predictions
Time Series Predictions: TimeGPT, the first foundational model for time series predictions, is introduced, capable of accurately predicting diverse datasets unseen during training.
1,606 shares
Decoder-Only Forecasting Model
The article explores a time-series foundation model for forecasting, inspired by large language models for NLP, which competes with top supervised forecasting models on multiple public datasets.
1,405 shares
DeepSeekV2: Mixture-of-Experts Language Model
Mixture-of-Experts Language Model: The article introduces MLA and DeepSeekMoE, tools that optimize inference efficiency by compressing the KeyValue cache into a latent vector and facilitate cost-effective training of robust models via sparse computation.
1,370 shares
Rising4
Open Foundation Models for Code Intelligence
Software development is being improved with the integration of Code LLMs to boost productivity and manage complex tasks.
478 shares
Autonomous LLM-Driven Research
The impact of AI on speeding up scientific discovery is unclear, especially regarding transparency, traceability, and verifiability.
204 shares
Consistency in Large Language Models
Jacobi decoding, a parallel decoding technique, may enhance LLM inference efficiency by converting the sequential decoding process into parallel computation.
188 shares
MultiLevel Superoptimizer for Tensor Programs
Mirage, the first multilevel superoptimizer for tensor programs, has been launched.
166 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Quantitative Finance Notebooks
The article offers educational insights on quantitative finance, algorithmic trading, financial modelling, and investment strategy using notebooks.
940 shares
Portfolio Engineering Framework
The piece explores a portfolio engineering and backtesting framework, created by expert quantitative investors, from a personal viewpoint.
137 shares
Open Source ML Platform
The article presents an open-source platform for managing all aspects of the machine learning lifecycle.
17,388 shares
Differential ML Reproduction
The piece explains the application of findings from the Risk articles Differential Machine Learning 2020 and PCA with a Difference 2021 by Huge and Savine.
133 shares
Robotics ML State-of-the-Art
The article introduces LeRobot, an advanced machine learning tool for practical robotics, built in Pytorch.
2,338 shares
Trending5
Electricity Forecasting Benchmark
The article introduces a new benchmark and toolbox aimed at enhancing electricity price prediction via open access.
180 shares
WTF Python
The article explores the unexpected features and peculiarities of the Python programming language.
35,148 shares
Quality TTS System
The article outlines the creation of a superior multivoice Text-to-Speech (TTS) system.
11,893 shares
Jupyter Trace Extension
The article presents a JupyterLab extension that assists in error resolution by searching Google, Stack Overflow, or consulting Bing Chat.
5 shares
Instrumented PCA
The article delves into the theory and use of Instrumented Principal Components Analysis in data analysis.
182 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Hedge Funds Global Adaptation
Dynamo Software's survey indicates that geopolitical and economic factors may lead to a significant change in hedge fund investment strategies, including more fundraising and diversification.
7 shares
EEX Power Markets Record Break
EEX Group saw a record monthly high in April with a 72% YoY increase in trading on its global spot and derivatives power markets, particularly in European power derivatives.
7 shares
Point72 Hires EM Bond Chief
Point72 has hired Ketan Gada, former Head of Total Return Emerging Markets Fixed Income at Pictet Asset Management, as a new Portfolio Manager.
4 shares
Qube Appoints Quant Tech Director
Qube Research & Technologies has appointed Simon Bannister, former Infrastructure Programme Director at the London Stock Exchange Group, as its new Quantitative Technology Director.
4 shares
European Retail Hedge Fund Asset Drop
European retail investors are decreasing their hedge fund investments due to higher interest rates and poor performance, leading to an eight-year low in assets under management in alternative UCITS, as per Kepler Absolute Hedge data.
4 shares
Quant King Simons Dies
Renaissance Technologies' billionaire founder, James Simons, has passed away at the age of 86.
4 shares
Bernie Yu: CIO Patronus Capital
CIO Patronus Capital: Bernie Yu, CIO at Patronus Capital Management, shares insights on fiscal conservatism and investing in young talent ahead of the Hedgeweek Emerging Managers US Summit.
4 shares
TOBAM's LBRTY Strategy Reaches 100m
Paris-based asset management firm TOBAM has reached over $100m in AUM within six months of launching its LBRTY strategy, due to an investment from a US endowment fund.
3 shares
Prop Trading Firm Thriving
Trading firm Maven Securities is considering a change in its business strategy.
3 shares
Bed Bath Beyond Sues Hudson Bay
Bankrupt company Bed Bath & Beyond is suing Hudson Bay Capital Management for over $300m in lost trading profits as part of a business rescue plan.
3 shares
Miscellaneous10
UBS Worried about Credit Suisse IT
UBS may encounter problems with IT migration due to insufficient efforts to retain its tech Managing Directors.
2 shares
Bridgewater Firm Revamped
Bridgewater Associates, the world's biggest hedge fund, is restructuring to improve investment performance, according to new CEO Nir Bar Dea.
2 shares
LTX Joins MultiLynq
LTX, a subsidiary of Broadridge Financial Solutions, is partnering with MultiLynq to improve electronic fixed income trading connectivity on the LTX platform.
2 shares
Quant Fund Founder Jim Simons Passes Away
A former Cold War codebreaker turned mathematician has founded one of the most successful hedge funds on Wall Street.
2 shares
Archegos Boss on Trial for Fraud
Bill Hwang, the founder of the collapsed hedge fund Archegos, is due to stand trial for alleged securities fraud and market manipulation.
2 shares
Best Salaries in HFT
The article ranks the top companies for women in the electronic trading sector.
2 shares
Digital Assets Fund Inflows
The article reports a $130 million investment in digital assets last week, according to CoinShares.
2 shares
GIP Gains from Grifols
The article details how General Industrial Partners profited from a short bet on Grifols, while Frank Tuil suffered losses from a bullish bet.
1 shares
ExDeutsche Bank Head in Hedge Fund
The article indicates that Qube's 2024 plans include more than just tech infrastructure projects.
1 shares
Millennium's Olympiad Brain teaser
The article invites readers to measure their intelligence against a middle school student's.
1 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Finance Kernels
Dr. JeanMarc Mercier explores the use of RKHS theory-based generative and predictive algorithms in finance, including their application in time series prediction and reverse stress tests.
10 shares
Maiden Century
Qaisar Hasan, founder of Maiden Century, shares his experience with alternative data at Point 72 and discusses the future of data-driven investing in a podcast interview.
8 shares
Trendy Investors
In a podcast episode, Eric Crittenden and Jason Buck discuss the current sentiment around trend-following, optimal diversifiers, and portfolio construction.
8 shares
EM Income
JP. Morgan strategists and economists discuss the future of Emerging Markets fundamentals and markets in a monthly podcast.
7 shares
Volatility Navigation
Dr. Russell Rhoads reflects on the causes and effects of episodic volatility throughout his five-decade career as a trader and options educator in Chicago.
5 shares
Related5
Nick Rohatyn on EM and China
In a podcast, Nick Rohatyn, CEO of The Rohatyn Group, talks about the effects of low rates and China's growth on emerging markets.
4 shares
Understanding DB Scheme Endgames
Lisa Purdy and Ian Blake explore various endgame strategies for quickly maturing DB schemes with high funding levels.
3 shares
SPs CTO on AI and Datacenters
Frank Tarsillo, CTO at S&P Global Market Intelligence, discusses the company's AI strategy and the significance of ready-to-use data in a podcast.
2 shares
Mitchell OHaraWild on Forecasting
Mitchell O'Hara-Wild, a data scientist, talks about his experience in data science and the future of forecasting in the AI era.
2 shares
Global FX and Central Bank Policy
A webinar recording discusses the potential differences in policies among global central banks, key macroeconomic themes, and their influence on future policy rates and currencies.
2 shares
Blogs
Posts from quant and economics blogs and newsletters.
10 items
Quantitative5
Avoiding Survivorship Bias
The article examines the issue of survivorship bias in trading, where focus is often on successful trades while ignoring unsuccessful ones.
9 shares
GBPCHF Trading Guidelines
The article offers strategies for trading the GBPCHF forex pair, a popular currency pair in the forex market.
4 shares
True Strength Index Rules
The article delves into the use of the True Strength Indicator, a tool used to interpret price movements in financial markets.
3 shares
Medallion Fund Algorithm
The article announces the resignation of Jim Simons from his position as chairman of Renaissance Technologies, a highly profitable fund management group.
3 shares
Choppiness Index Strategy
The article underscores the significance of the choppiness index in identifying suitable market conditions for trading.
3 shares
Related5
EMV Strategy Rules
The article discusses how the Ease of Movement indicator can help predict financial market trends.
1 shares
Economics Update
The team behind Interactive Economics is shifting focus to distribution and instructional video creation after releasing four modules.
0 shares
The Red Handkerchief
The article discusses witness intimidation in relation to the Stormy Daniels case.
0 shares
Preference Falsification
Dartmouth students widely supported a vote of no confidence in President Sian Beilock.
0 shares
Videos
Talks, lectures and tutorials.
5 items
Quantitative5
Modeling a Twosided Limit Order Book
Joshua Reed gave a lecture on high frequency regime at the Peter Carr Brooklyn Quant Experience BQE Lecture Series, hosted by NYU Tandon's Department of Finance and Risk Engineering.
3 shares
Smile Dynamics in Volatility Models
Florian Bourgey discussed smile dynamics in rough volatility models at the Peter Carr Brooklyn Quant Experience BQE Lecture Series, an event organized by NYU Tandon's Department of Finance and Risk Engineering.
1 shares
Math and Stats in Trading
Quants and traders differ in their skills and thinking speeds, with quants being more methodical and slower.
1 shares
DFW Quaint Quant Conference
The first DFW Quaint Quant Conference is being held, providing a platform for quants to present and discuss industry research and methods.
2 shares
Talent Acquisition in Finance Industry
Success in the quant space is driven by personal interest in research and companies allocating time for it.
1 shares
X / Twitter
Posts from quant researchers on X.
10 items
Quantitative5
Pitfalls in Quantitative Investing
Deutsche Bank highlights common errors and issues in backtesting in the context of quantitative investing.
4 shares
Time Series Modeling
An open-source foundation presents a range of models for broad use in time-series analysis.
1 shares
Forecasting Overview
The article gives a comprehensive review of different models and techniques used for forecasting.
0 shares
Miscellaneous5
Exchange Rate Strategy Outperforms
The author presents strategies based on exchange rate fluctuations that perform better than traditional momentum or reversal strategies, achieving high Sharpe ratios.
0 shares
AI Agent Ops Report
The report discusses the operations of AI agents from various perspectives.
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Machines Time Markets?
The AQR paper explores the intricacies of predicting returns and the potential of machines to time markets.
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Short Interest Stock Returns
The article provides global evidence that a high level of short interest generally predicts a decrease in stock returns in most countries.
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Commodity Prices Exchange Rates
The article proposes that fluctuations in a country's commodity export prices can be used to predict its exchange rate.
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