Estimating Shadow Rate
The research introduces a computational method to calculate the shadow riskless rate (SRR) in a risk-free market, which can help differentiate between investment asset classes.
3 shares1 citation todaySource ↗
Quant LetterNo. 74
November 2024, Week 2
146 items across 10 sections, as sent to readers on 13 November 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 146
- Papers
- 86
- Sections
- 10
- Issue
- No. 74
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
10 items
Finance6
Credit Risk with Copulas
The study presents a new model to analyze large losses from credit portfolio defaults using the Archimedean copula family and two algorithms that improve traditional Monte Carlo methods.
3 shares8 citations todaySource ↗
ajdmom: Python AJD Moment Package
Python AJD Moment Package: The article presents ajdmom, a Python package that automatically generates moment formulas for affine jump diffusion processes, useful for sensitivity analysis and can be downloaded from GitHub or the Python package index.
3 shares2 citations todaySource ↗
Improving FX Volatility Imputation
The study explores enhancing the prediction of missing implied volatilities in FX options using modified variational autoencoders (VAEs), which better manage data uncertainty.
3 shares1 citation todaySource ↗
Optimal Liquidation in HFT
The research introduces a high-frequency trading model using a hidden Markov process to examine optimal liquidation strategies under limited information, offering a practical algorithm to simulate the original liquidation issue.
3 shares5 citations todaySource ↗
Equilibrium Relationships in Models
The paper establishes that a two-cycle equilibrium in a model with infinitely-lived agents can also exist in an overlapping generations (OLG) model, indicating that both models can experience equilibrium indeterminacy and rational asset price bubbles.
2 shares1 citation todaySource ↗
Miscellaneous1
AIAgent Collaboration in Investment Analysis
The study suggests a multi-agent system for financial investment research that performs better than traditional models by adapting to market conditions and optimizing performance. This shows the potential of multi-agent systems in improving financial analysis and investment decisions.
3 shares42 citations todaySource ↗
Historical Trending3
Testosterone Peaks in Startup Founders
A study of 107 male Y Combinator founders shows a link between testosterone levels and company stage, with testosterone rising by 55.7% from pre-seed to seed funding, peaking at Series B, then dropping by 42.2% after Series B, indicating early startup success boosts confidence, while later-stage pressures increase stress.
42 sharesSource ↗
Random Coefficients in Volatility
The article suggests an arbitrage-free framework for randomizing parameters from the parametric implied volatility formula, improving existing parametrizations and expanding the range of acceptable implied volatilities shapes, proving especially effective in modeling the implied volatility curves of short expiry options before an earnings announcement.
5 shares4 citations todaySource ↗
Fast Bass Volatility
The paper introduces a new method for the Bass Local Volatility Model that merges local quadratic estimation and lognormal mixture tails for creating state price densities, showing that trapezoidal rule based schemes for numerical convolutions perform better than commonly used Gauss-Hermite quadrature.
3 shares2 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
35 items
Quantitative20
SafeHaven Assets in COVID-19
The COVID-19 pandemic showed that gold, Treasury Bonds, and the Euro were effective safe haven assets in reducing risk during the equities bear market.
6 sharesSource ↗
Transfer Function Prediction with Autoencoders
A deep learning framework has been developed to predict transfer functions in structure-acoustic models, reducing computational time compared to traditional methods.
6 sharesSource ↗
Generalizability of Surrogate Models
A study highlights the potential of deep learning models to extract input data from output data in building energy modelling.
3 sharesSource ↗
Riemannian Approach for Fluctuations
The article explores the extension of classical fluctuation theory to meet the requirement of general covariance, discussing its implications for entropy production.
6 sharesSource ↗
RealTime Proppant Optimization
A new real-time optimization framework for proppant concentration during hydraulic fracturing is proposed, addressing limitations of current prediction methods.
3 sharesSource ↗
Magnetic Field Effects on Crystal Growth
A study using simulations and machine learning found that a traveling magnetic field significantly alters the growth of βGa2O3 crystals.
3 sharesSource ↗
Sentiment and Price Resilience in Recycling
Machine learning research revealed that Southeast Asian economies are key to the vessel recycling industry, despite tighter regulations.
3 sharesSource ↗
Peer-to-peer Risk-sharing with Losses
A study on catastrophic loss insurance suggested that diversifying such losses could be detrimental, recommending no diversification instead.
4 sharesSource ↗
Fiscal Policy Uncertainty and Multiplier in China
Research indicated that fiscal policy uncertainty in China reduces the fiscal multiplier, implying that reducing this uncertainty could enhance fiscal policy effectiveness.
4 sharesSource ↗
Financial Impact of COVID-19 vs. Disasters
A study showed that large pandemic-related losses during COVID-19 were recovered faster than in previous bear markets, with gold and Treasury bonds offering some relief for equity investors.
2 sharesSource ↗
Geoffrey Hinton's Neural Network Contributions
The article highlights Geoffrey Hinton's key contributions to neural networks, including backpropagation, deep learning, and Capsule Networks, and their impact on AI.
224 sharesSource ↗
Machine Learning in Business Research
The study reveals a lack of transparency in predictive machine learning studies in top business and economic journals, leading to less citations due to not benchmarking against traditional models.
15 sharesSource ↗
SHODH SAGAR ® Research Reports
The article discusses the potential of Big Data analytics in improving risk management in IT service delivery through real-time risk identification, assessment, and mitigation.
2 sharesSource ↗
DataDriven Inventory Management
The study presents a data-driven approach to inventory and financial hedging for new products, using proxy return factors to understand derivatives returns and demand-return relationships.
4 sharesSource ↗
Statistical Arbitrage with Spectral Clustering
The paper proposes a method for identifying similar assets using high-frequency intraday data and tests various trading rules based on these asset clusters.
7 sharesSource ↗
CSFs in Risk Management in Nigerian Banks
The study examines the key factors for successful risk management in the Nigerian banking system from 1960 to now, using interviews and questionnaires.
6 sharesSource ↗
Machine Learning for Gas-Liquid Flow
The article explores the use of machine learning to improve the accuracy and predictability of multiphase flow modeling in oil and gas production.
6 sharesSource ↗
Testing $\Alpha$-Attractor Inflation
The research looks into the consistency and limitations of alpha-attractor quintessential inflation using data from various cosmic observations.
5 sharesSource ↗
Predicting M&A Outcomes with ML
The study investigates the effectiveness of machine learning algorithms in predicting the success of merger and acquisition deals, highlighting the accuracy of nonlinear models.
3 sharesSource ↗
DeFi Arbitrage in Liquidity Tokens
The paper explores arbitrage opportunities in liquidity token market prices, suggesting a method to calibrate volatility to data to prevent arbitrage.
3 sharesSource ↗
Financial15
Market Beta Benchmarking
The article introduces a new method for comparing market beta estimates to unobserved true betas, applicable to any beta estimate and requiring minimal assumptions about the true asset pricing model.
5 sharesSource ↗
Financial Response to COVID-19
The piece discusses the initial reaction of financial markets to the COVID-19 crisis, emphasizing the role of underestimated risks and delayed information in the drastic drop in asset prices.
5 sharesSource ↗
LongRun Disaster Risk Models
The article reviews literature on long-term risk and rare disaster risk models in asset pricing, introducing new methods to address criticisms and explain the influence of climate change on asset prices.
3 sharesSource ↗
Gold in Decision-Making
The article presents an educational framework to understand the role of gold in economic theory, focusing on its function as a safe-haven asset, a store of value, and its relationship with inflation and market volatility.
2 sharesSource ↗
Disaster Risk, Inequality, Fiscal Sustainability
The paper examines the impact of climate change on budget sustainability and inequality, suggesting that climate-related disaster risks increase government debt and inequality, especially among low-income households.
3 sharesSource ↗
Trend-Following Beta Replication
The article discusses the challenges of trendfollowing investment strategies and suggests mitigating them by replicating a broad index of such funds, despite potential tracking errors.
205 sharesSource ↗
Machine Learning in Finance
The paper reviews machine learning methods in portfolio management, discussing their limitations, potential future developments, and applications in systematic trading strategies.
8 sharesSource ↗
Optimal Hedge Fund Allocation
The research justifies significant allocations to hedge funds due to their diversification benefits, particularly equity and event-driven hedge fund strategies, even without alpha generation.
7 sharesSource ↗
Strategic Trading in Bank Portfolios
The study reveals that US banks are reluctant to sell underwater bonds at a discount, especially those not recognizing unrealized losses in regulatory capital and banks with low stock market valuations.
6 sharesSource ↗
LLMs for Time Series Forecasting
The article evaluates the performance of Large Language Models (LLMs) for stock market forecasting, indicating varying effectiveness in different data scenarios and suggesting the need for further model refinement.
21 sharesSource ↗
Fund Flows: Prospectus vs. Ratings
Prospectus vs. Ratings: Retail and institutional fund flows are primarily driven by sustainability statements in fund prospectuses, not external sustainability ratings, based on an analysis of over 23,000 equity mutual funds and ETFs.
22 sharesSource ↗
Index Investing: Sentiment Spillover
Sentiment Spillover: A model of index investing shows that index stocks have higher, more volatile prices, comove more with other index stocks, and have higher trading volume due to sentiment spillover from index investors.
4 sharesSource ↗
Private Game Equity Performance
Private video game companies that receive private equity investment generally outperform other markets, making them attractive investments in terms of absolute return relative to the public market, based on an analysis of 540 deals.
2 sharesSource ↗
Hidden Liquidity on U.S. Exchanges
Despite the goal of transparent trading, hidden orders account for a significant portion of trading volume, and an AI model can predict where price-improving non-displayed orders are likely to appear.
4 sharesSource ↗
Memory and Beliefs in Markets
Sell-side stock analysts' belief formation is influenced by memory distortions, with analysts often over-recalling distant historical episodes and under-recalling them during crises, according to a machine learning model.
7 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
22 items
Finance4
Clustering for Portfolio Optimization
The article suggests a new investment strategy using clustering to select fewer assets, potentially outperforming traditional equal weight strategies.
21 sharesSource ↗
LowFrequency Trading Algorithm
The study introduces an improved algorithmic trading model that uses price indicators and a volume factor, yielding high returns with a high success rate and low maximum loss.
19 sharesSource ↗
Peak Price Tracking for Portfolio Selection
The paper investigates the use of Online Gradient Update and Online Newton Update meta-algorithms in online portfolio selection, proving their effectiveness in various financial settings.
19 sharesSource ↗
Sustainable Investment Portfolio Optimization
The research presents a portfolio optimization approach based on a multi-index model that includes environmental, social responsibility, and corporate governance factors, providing a flexible alternative to large-scale covariance matrix estimation.
18 sharesSource ↗
Statistical3
Online Investor Sentiment & Stock Market Risk Premium
The study proposes using machine learning to predict stock market risk premium based on online investor sentiment, improving portfolio performance.
22 sharesSource ↗
Stock Market Index Forecasting with DLWR-LSTM Model
The paper presents a DLWR-LSTM model for stock index forecasting, offering consistent accuracy regardless of time series variance.
15 sharesSource ↗
Impact of ERM on Performance & Risk Indicators of XBANK Companies
The article investigates the link between enterprise risk management and firm performance, with data from Turkish banks indicating ERM enhances performance and value while managing risks.
12 sharesSource ↗
Machine Learning10
Financial Stress in Banks
Machine learning was used to predict default risk in financial institutions, with bailout probability, market share, and market-to-book ratio being key variables.
24 sharesSource ↗
Volatility Forecasting: Linear vs. Nonlinear
Linear vs. Nonlinear: Machine learning models were found to be effective in forecasting global stock market volatility, with simpler models performing better for volatility-timing portfolios.
22 sharesSource ↗
Hyperparameters in ML Models
A review of political science journals revealed a lack of transparency in machine learning models, with only 20.31% reporting hyperparameters and their tuning.
21 sharesSource ↗
Investors' Risk Perception
An unsupervised machine learning algorithm analyzed corporate disclosures, finding that most risk factors decrease return volatility when disclosed.
19 sharesSource ↗
Asset Pricing Uncertainty
A machine learning-constructed economic uncertainty index effectively predicted stock market returns, especially during high uncertainty and sentiment periods.
18 sharesSource ↗
Public Debt Analysis with ML
The research uses machine learning to determine that income channel significantly affects welfare changes due to public debt, while investment ratio channel has the least effect.
17 sharesSource ↗
Stress Testing US Banks with ML
The article highlights the role of machine learning in improving risk analysis during stress tests, uncovering complex macro-financial connections and enhancing risk evaluation in economic downturns.
17 sharesSource ↗
Naïve Bayes for Spam Detection
The research uses the Naive Bayes Classifier machine learning algorithm to categorize emails as spam or not, utilizing the Kaggle spam mails dataset and R software for data analysis.
16 sharesSource ↗
Support Vector for Gender Classification
The paper introduces a new stopping criterion for support vector optimization algorithms to identify a person's gender from biographical text, especially in strongly inflected languages like Spanish.
13 sharesSource ↗
AI for Innovation: Bibliometric Analysis
Bibliometric Analysis: The study discusses the significant role of AI, machine learning, and big data in fostering innovation, and highlights new potential research areas for scholars and practitioners.
13 sharesSource ↗
Deep Learning2
DeepVol: Volatility Forecasting with Dilated Causal Convolutions
Volatility Forecasting with Dilated Causal Convolutions: The study introduces DeepVol, a model using Dilated Causal Convolutions, which effectively uses high-frequency data to predict next-day market volatility.
27 sharesSource ↗
Index Tracking with Shapley Explanations
The paper suggests using a one-dimensional Pointwise Convolutional Autoencoder and Shapley Additive Explanations for index tracking, outperforming other stock selection strategies in various financial markets.
17 sharesSource ↗
Historical Trending3
Asset Pricing from News
A study uses Wall Street Journal news text to develop a superior narrative factor pricing model that predicts investment opportunities with fewer errors.
6 sharesSource ↗
EU News Engagement on Facebook
Research finds that negative news about the EU gets more reactions and shares on social media, emotional content gets more comments, but conflict reduces engagement.
4 sharesSource ↗
Collusion Regulation
The article stresses the need to understand the existing legal system to effectively regulate collusion, rather than relying on economists' idealized views.
1 sharesSource ↗
Machine learning
The general machine-learning papers the letter carried in 2023-25.
19 items
Recently Published10
Shared Semantic Representations
Modern language models can process various languages and forms by learning a shared representation space used during input processing.
65 shares82 citations todaySource ↗
Sparse Multi-Modal Transformer
The Mixture-of-Transformers (MoT) is a sparse multi-modal transformer architecture that reduces pretraining costs and allows modality-specific processing with global self-attention.
58 shares161 citations todaySource ↗
Building Large Knowledge Bases
A large general-domain knowledge base (GPTKB) can be built entirely from a large language model, containing 105 million triples for over 2.9 million entities.
45 shares18 citations todaySource ↗
Generative Diffusion
The generative performance of diffusion models can be enhanced by using noise sources with temporal correlations for data destruction in the forward process.
25 shares2 citations todaySource ↗
Generative Video Camera Controls
ReCapture is a method for creating new videos with unique camera trajectories from a single video, allowing for the regeneration of the video from different angles and cinematic camera motion.
23 shares76 citations todaySource ↗
DynaMem: Mobile Manipulation
Mobile Manipulation: DynaMem is a new method that uses dynamic spatio-semantic memory to help robots explore and adapt to new environments and track object movements.
20 shares59 citations todaySource ↗
Stronger Models vs. Tuning
A study introduces Compatibility-Adjusted Reward (CAR), a new metric to evaluate the effectiveness of language models, challenging the belief that larger models are better for instruction tuning.
19 shares17 citations todaySource ↗
Watermark Locally
The Watermark Anything Model (WAM) is a deep-learning model that can embed and extract hidden watermarks in specific areas of an image.
17 shares72 citations todaySource ↗
Recycled Attention for Inference
Recycled Attention is a method for large language models that alternates attention between full context and a subset of input tokens, improving performance and reducing computational load in long-context tasks.
14 shares12 citations todaySource ↗
Add-it: Object Insertion
Object Insertion: Add-it is a training-free approach for semantic image editing that uses diffusion models to add objects into images based on text instructions, ensuring natural placement and detail preservation.
11 shares48 citations todaySource ↗
Historical Trending9
API LLMs Info Leak
Researchers have discovered a method to extract hidden information from large language models like OpenAI's gpt-3.5-turbo using API queries, exploiting a weakness known as the softmax bottleneck.
615 shares53 citations todaySource ↗
ChatGPT in Academic Writing
A study of a million arXiv papers shows that large language models, specifically ChatGPT, are significantly impacting the writing style of academic abstracts, especially in computer science.
293 shares40 citations todaySource ↗
Qwen.5-Coder Report
The Qwen2.5-Coder series, an upgrade from CodeQwen1.5, shows remarkable code generation abilities and achieves top performance in multiple code-related tasks, potentially advancing code intelligence research.
121 shares1,558 citations todaySource ↗
SelfSupervised Gradients Representation Enhancements
The FUNGI method improves transformer encoders' features using self-supervised gradients, enhancing performance in vision, natural language processing, and audio tasks and datasets.
78 shares6 citations todaySource ↗
AI for Health in Africa
Research highlights the potential of AI in African healthcare, but emphasizes the need for culturally sensitive approaches and addresses concerns about trust, ethics, and systemic barriers.
77 shares4 citations todaySource ↗
Optimization on Random Generalized Stiefel Manifold
A new method for optimization over matrices is proposed, which is cost-effective and efficient in various machine learning applications.
57 shares15 citations todaySource ↗
Transformers and Propositional Logic Problems
A study reveals the internal mechanisms of large language models that enable complex logical reasoning, identifying specific planning and reasoning circuits.
40 shares16 citations todaySource ↗
Metamodels for Transfer Learning in Source Localisation
A Bayesian multilevel approach is used to predict model hyperparameters in acoustic emission experiments, demonstrating its use in source localization.
40 shares2 citations todaySource ↗
SynCode: LLM Generation with Grammar Augmentation
LLM Generation with Grammar Augmentation: SynCode, a new framework for syntactical decoding with large language models, is introduced, significantly reducing syntax errors in Python and Go code generation.
37 shares87 citations todaySource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
11 items
Trending5
OpenHands: AI for Generalist Agents
AI for Generalist Agents: OpenDevin is an AI platform capable of writing code, interacting with command lines, and browsing the web similarly to a human developer.
35,480 shares
Geometric Transformer for Molecular Modeling
Transformer architectures are now being used in molecular modeling, expanding their applications in data modalities.
322 shares
SVDQunat: Absorbing Outliers in Diffusion Models
Absorbing Outliers in Diffusion Models: Nunchaku is an inference engine that merges the kernels of the low-rank branch into the low-bit branch to minimize redundant memory access.
165 shares
WebRL: Training LLM Web Agents
Training LLM Web Agents: WebRL employs a self-evolving curriculum, a robust outcome-supervised reward model, and adaptive reinforcement learning strategies for consistent progress.
146 shares
ADOPT: Modified Adam Convergence
Modified Adam Convergence: Adam is a popular optimization algorithm used extensively in deep learning.
126 shares
Rising6
HTML for Modeling Retrieved Knowledge
The article introduces HtmlRAG, a tool that uses HTML in place of plain text for RAG, with the code accessible on GitHub.
118 shares
Training Android Autonomous Agents
The article explores a code that accommodates both large language models and multimodal models within the same action space, available on GitHub.
115 shares
Large Multimodal Model with Tabular Data Integration
The article presents TableGPT2, a model trained with a vast amount of table-related data, with the code available on GitHub.
113 shares
LLMtimesMapReduce: LongSequence Processing
LongSequence Processing: The LLMtimesMapReduce framework splits documents into sections for LLMs to handle and merges the results for the final product.
104 shares
Addressing Representation Collapse
VQ models often struggle with representation collapse in the latent space, which results in poor codebook usage and hinders scalability for extensive training.
89 shares
MVSplat360: 360 Scene Synthesis
360 Scene Synthesis: MVSplat360's performance surpasses other methods in visual quality for wide-ranging or 360-degree NVS tasks when tested on the DL3DV10K dataset.
41 shares
GitHub
Repositories the letter featured.
10 items
Finance5
Algorithmic Trading
The course provides a comprehensive understanding of algorithmic trading, targeting individuals with basic Python programming and financial market knowledge.
127 shares
Shapley ML Interactions
The article explores the use of Shapley values in machine learning in the piece Shapley Interactions for Machine Learning.
213 shares
FactorLab Library
FactorLab is a Python tool designed to assist in identifying and analyzing alpha and risk factors in investment algorithm creation.
13 shares
Price Data Downloader
The project enables users to access historical price tick data for various financial instruments such as Crypto Stocks, ETFs, CFDs, and Forex through CLI and Node.
362 shares
Pairs Trading Project
The project employs statistics and financial theory to demonstrate the Pairs Trading strategy often used in equity markets.
308 shares
Trending5
DearPyGui
Dear PyGui is an article about a fast and reliable GUI toolkit for Python with few dependencies.
13,270 shares
Sharebookkrpykrx
KRX stock information scraping discusses the process of extracting stock data from the Korea Exchange.
696 shares
Aphroditeengine
Largescale LLM inference engine discusses a large-scale inference engine designed for logical latent models.
1,122 shares
AwesomeFastAPI
A curated list of awesome things related to FastAPI is a collection of useful resources and tools for FastAPI.
8,658 shares
News
Industry news: funds, hiring, markets and regulation.
20 items
Quantitative10
Hedge Fund Risk on the Rise
Beacon Platform's research reveals that hedge funds are boosting their risk management budgets due to increasing regulatory scrutiny.
11 shares
Brigade Gets 300m from Blackstone
Brigade Capital has received a $300m investment from Blackstone to enhance its private credit strategy and collateralised loan obligations platform, according to Reuters.
8 shares
Graduates Making 250k in Algorithmic Trading
The article offers advice on landing a lucrative job in the finance industry.
6 shares
Raptor Group Invests in US Housing Market
Raptor Group is investing in Trevally Capital, a new hedge fund focusing on distressed US housing market sectors, as per Bloomberg.
5 shares
Free Resources for Quant Finance
In his 2024 article for DataDrivenInvestor, Jovan S Hernandez lists five free tools he utilized to enter Quant Finance.
4 shares
SFERS Boosts Allocations
The San Francisco City & County Employees Retirement System (SFERS) plans to invest in a new hedge fund and venture capital allocation ahead of its November board meeting.
3 shares
FTX Sues Scaramucci
Bankrupt cryptocurrency exchange FTX is suing Anthony Scaramucci and his hedge fund SkyBridge Capital to recover funds for its creditors.
3 shares
Citadel Hires Elliott Partner
Citadel, a hedge fund owned by Ken Griffin, has hired Nabeel Bhanji from Elliott Investment Management in a significant recruitment move.
3 shares
Brazil’s Verde Invests in Bitcoin
Brazilian hedge fund Verde Asset Management strategically invested in bitcoin prior to the US election, benefiting from the cryptocurrency's rally triggered by Trump's return to office.
2 shares
Hedge Funds Lose on Tesla Shorts
Hedge funds that bet against Tesla have suffered over $5bn in losses since Trump's election victory, due to a surge in Tesla's shares after CEO Elon Musk endorsed Trump.
2 shares
Miscellaneous10
WTI Bullish Hedge Funds
Due to OPEC's delayed output increase and rising Middle East tensions, hedge funds have raised their positive outlook on West Texas Intermediate crude to a March high.
2 shares
BlackRock Talks Millennium Stake
BlackRock is in preliminary discussions with Millennium Management about a potential strategic partnership, which could lead to BlackRock acquiring a minority stake in the hedge fund firm.
2 shares
Elliott IM's Female Partner
Elliott Investment Management has named Samantha Algaze as its first female Partner and promoted two other Partners to its management committee.
2 shares
Family Offices in 2025
A Hedgeweek report indicates growing opportunities for family offices in 2025, particularly in APAC and the Middle East, with increased investments in private credit and other non-traditional asset classes.
2 shares
Elliott Urges Honeywell Split
Elliott Investment Management is pushing Honeywell International to split its Aerospace and Automation divisions to increase value.
2 shares
Point72 Japan Head Steps Down
Point72 Asset Management is looking for a new Japan Head as Toby Bartlett is set to resign next year.
1 shares
Nissan Stock Surges post Activist Acquisition
Nissan Motor's shares experienced their biggest rise in 15 years after Suntera Cayman bought a 2.5% stake in the company.
1 shares
Trump Rally Nets Rokos 1bn Profit
Chris Rokos of Rokos Capital Management earned nearly 1bn in profits during the market surge after Trump's reelection.
1 shares
Podcasts
Episodes on markets, quant methods and economics.
10 items
Quantitative5
Futures Trading Evolution
Trader Anthony Crudele discusses his transition from CME Group floor to mindful trading, focusing on strategies for market navigation and risk management in futures trading.
24 shares
Options Market Insights
Cem Karsan talks about the evolution of options from derivatives to key elements in market analysis, highlighting risk management, collateral leveraging, and the impact of geopolitical tensions.
15 shares
Gold Investing Strategies
Axel Merk provides insights into gold investing, discussing the influence of economic cycles, Federal Reserve policies, and strategies of mining firms on gold's trajectory.
14 shares
Technical Analysis Mastery
Katie Stockton shares tips on mastering technical analysis in investing, emphasizing diversified exposure, strategies to limit losses, and the role of technical analysis in assessing liquidity and macro trends.
8 shares
US Election Impact
Jonny Goulden and Saad Siddiqui discuss the effects of recent market developments on the EM fixed income asset class post-US elections in a November 2024 podcast.
8 shares
Related5
Treasury Roll Dynamics
In a podcast, Srini Ramaswamy and Ipek Ozil discuss the dynamics of the upcoming Treasury futures roll cycle.
7 shares
ChinaScope Insights
Tom Liu talks about China's changing attitudes towards data and the market for alternative data in a podcast interview.
6 shares
Andrew O'Connell: Trading Champ
Trading Champ: Andrew O’Connell shares his investment strategies and experiences in a podcast episode.
6 shares
Implied Volatility
Dmitry Pargamanik and Will McBride discuss the impact of implied volatility on option quotes in a podcast with Jeff Praissman.
6 shares
David Kelly: Diversification
Diversification: Dr. David Kelly discusses economic themes such as inflation, consumer sentiment, and government deficit in a podcast episode.
5 shares
X / Twitter
Posts from quant researchers on X.
3 items
Quantitative1
Research Recap: Fixed Income, Stock Returns, ML Models, Arbitrage, and More
Fixed Income, Stock Returns, ML Models, Arbitrage, and More: The article summarizes recent research on various financial topics including fixed-income investing, stock return predictability, economic constraints in machine learning models, and statistical arbitrage. It also mentions resources like blogs, repositories, and podcasts.
0 shares
Miscellaneous2
Competitive Advantages & Market Performance
Firms with significant competitive edges usually outperform those without, but not always the overall market.
0 shares
Stocks Added to S&P 500
The article investigates the performance of stocks when they are included in the S&P 500, a crucial measure of the U.S. economy's health.
0 shares
Threads from r/quant, r/algotrading and friends.
6 items
Quantitative5
Signs of Closure
80 shares
Grafana Users
78 shares
Thinkers in Quant
647 shares
Years of Investment Data
74 shares
Impact of No PhD
59 shares
Rising1
Started Guide
836 shares