The hottest Quantitative Substack posts right now

And their main takeaways
Category
Top Finance Topics

Quant Letter: June 2025, Week-3

The Parlour • 21 implied HN points • 19 Jun 25
💰 Finance Quantitative Investing Market Analysis Risk management Trading Strategies
  1. A new forecasting method called Bayesian VAR can predict complex time series data accurately by handling multiple variables and irregular data.
  2. Research on electricity markets reveals how hedging can be connected to market power abuse, which helps understand the economic behaviors in these markets.
  3. Recent studies show how machine learning and quantum methods are being applied to optimize trading strategies and predict market fluctuations.

Quant Letter: June 2025, Week-1

The Parlour • 21 implied HN points • 04 Jun 25
💰 Finance Quantitative Investing Machine Learning Market Analysis
  1. New methods are being developed to test asset pricing anomalies, showing that different paths on the same dataset can lead to similar outcomes. This means we need to be cautious about our assumptions in finance.
  2. Deep reinforcement learning is being used to improve risk management in life insurance. This method helps in making better decisions about profits and losses related to different risk factors.
  3. Large language models struggle with accuracy in specialized fields due to lack of specific training data. To improve their performance, fine-tuning techniques are essential.

Quant Letter: June 2025, Week-2

The Parlour • 4 implied HN points • 11 Jun 25
💰 Finance Quantitative Investment Market Analysis Financial Technology Risk management
  1. A new approach in finance is being developed to deal with model uncertainty, allowing better decision-making with limited data.
  2. Using deep learning and neural networks can help improve the accuracy of options pricing, especially during crucial events like earnings announcements.
  3. Current trends show that integrating climate considerations into investment strategies can be done without losing much performance.

CEO of DeepSeek's parent, High-Flyer Quant, spoke in 2020

Pekingnology • 143 implied HN points • 27 Jan 25
💰 Finance Investment Quantitative AI Market Analysis Emerging Markets
  1. High-Flyer Quant uses AI for its investment strategies. They rely on advanced models and lots of data to predict stock prices and make trades.
  2. The Chinese stock market is seen as less efficient, which gives AI-driven strategies a chance to find opportunities that traditional investing might miss. This leads to potential higher returns for the right strategies.
  3. As more institutions enter the market, competition will increase. High-Flyer focuses on research and development to stay ahead in this tough environment.

Quant Letter: January 2025, Week-4

The Parlour • 34 implied HN points • 23 Jan 25
💰 Finance Quantitative Machine Learning Portfolio Management Market Analysis Investment Strategies
  1. Advanced models like the MDQR help understand market dependencies, which can make it easier for traders to create effective strategies.
  2. New methods for portfolio optimization can handle many assets at once, moving beyond the traditional limits that were previously in place.
  3. Research shows AI can effectively forecast financial risks and rewards, highlighting the growing importance of technology in finance.
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Quant Letter: November 2024, Week-4

The Parlour • 21 implied HN points • 27 Nov 24
💰 Finance Quantitative Machine Learning Investment Strategies Portfolio Management
  1. Quanto options pricing can be improved using a mix of models that handle various aspects of finance and asset behavior. This could help in more accurate predictions and simulations.
  2. Hedge funds adapt their activist strategies to align with the preferences of major investors, leading to better results when trying to influence company decisions. This emphasizes the importance of understanding stakeholder interests.
  3. Simple machine learning models can sometimes outperform more complex ones when it comes to predicting financial markets. This shows that less can be more in data analysis.

Quant Letter: December 2024, Week-3

The Parlour • 12 implied HN points • 18 Dec 24
💰 Finance Quantitative Investing Market Analysis Machine Learning Cryptocurrency
  1. This week had exciting new research in quant finance, especially on generative AI and crypto forecasting. It shows that this field is active and evolving even during the holiday season.
  2. Recent studies highlighted the influence of machine learning on portfolio management, making it possible to choose better predictors and lower risks. This can help investors make smarter choices.
  3. Insights about investor behavior suggest that emotions and external factors can weigh heavily on trading volume and financial decisions. Understanding these factors can lead to better investment strategies.

Quant Letter: January 2024, Week-2

The Parlour • 30 implied HN points • 09 Jan 24
💰 Finance Quantitative Machine Learning Market Dynamics Financial Models
  1. The Combinatorial Purged Cross-Validation (CPCV) method is superior in financial analytics for reducing overfitting risks.
  2. SPX options data analysis finds limitations in accurately capturing implied volatility using Volterra Bergomi models.
  3. Incorporating Risk premia strategies in portfolios can lessen left-tail exposure, but diversification within options requires maximizing volatility parameters.

Quant Letter: January 2024, Week-4

The Parlour • 21 implied HN points • 23 Jan 24
🕹 Technology Quantitative Machine Learning Finance Blockchain Artificial Intelligence
  1. The blog post discusses various research papers on topics like financial risk modeling, interest rate models, and credit risk stress testing.
  2. New methods for predictive modeling in finance, including data-driven option pricing and generative modeling for financial time series, are introduced in the presented papers.
  3. The research covers diverse areas such as economics, crypto, and blockchain, offering insights on market responses, equity premium puzzles, and AI investment rankings in Latin America.

Quant Letter: December 2023, Week-3

The Parlour • 21 implied HN points • 20 Dec 23
💰 Finance Quantitative Financial Market Analysis Investment Strategies
  1. Recent research is exploring innovative methods for quantitative investing, such as using deep learning algorithms and new portfolio optimization models.
  2. There are profitable opportunities in the ETF lending market due to cost differences between borrowing ETFs and stocks, creating room for cross-ETF arbitrage.
  3. Studies are showcasing the importance of adaptive investment strategies focused on resilience, active ownership, and broader financial models to navigate fast-changing environments.

Quant Letter: February 2024, Week-2

The Parlour • 17 implied HN points • 14 Feb 24
🕹 Technology Finance Crypto Machine Learning GitHub Quantitative
  1. Using Autoencoder architectures in Statistical Arbitrage can simplify strategy development and improve returns compared to traditional methods.
  2. A new method, Causal-NECOVaR, provides reliable risk predictions for financial risk analysis regardless of market shocks and systemic changes.
  3. The Merton investment-consumption problem is expanded to incorporate transaction costs and stochastic differential utility in Portfolio Optimization for a better understanding of parameter combinations.

Quant Letter: December 2023, Week-2

The Parlour • 12 implied HN points • 13 Dec 23
🕹 Technology Quantitative Blockchain Machine Learning Finance Social Sciences
  1. The ML-Quant website has been revamped and is now free for all users to enjoy the newsletter.
  2. Research papers on SSRN cover various topics like volatility modeling, portfolio asset selection, and sentiment analysis using machine learning.
  3. In the field of quantitative finance, there have been recent advancements in areas such as optimal portfolio selection, volatility forecasting, and financial sentiment analysis.

Quant Letter: July 2023, Week 2

The Parlour • 17 implied HN points • 12 Jul 23
💰 Finance Quantitative Financial Market Dynamics
  1. Weekly quantitative finance newsletter discussing 'Informed Trading Intensity' using ML indicators in asset management.
  2. Machine learning techniques in finance include diversifying portfolios, tabular learning, and predicting fund performance.
  3. Research in financial markets covers topics like bond fund performance, equity premia, thematic investing, and corporate bond returns prediction.

Quant Letter: July 2023, Week 1

The Parlour • 12 implied HN points • 05 Jul 23
💰 Finance Quantitative Newsletter
  1. The newsletter discusses a study on intraday stock predictability with a large dataset.
  2. The author asks for suggestions about papers they might have overlooked in the comment section.
  3. Readers are encouraged to subscribe for a 7-day free trial to access the full post archives.

On Jim Simons // "The Man Who Solved The Market"

Parth's Playground • 2 HN points • 11 May 24
💰 Finance Investing Quantitative Market Analysis Financial history Economic Theory
  1. Jim Simons believed that markets have a structure and hired smart people to help figure this out. This teamwork was crucial for his success.
  2. Simons faced many challenges for years before he found success in investing. His breakthrough came from building a strong team and creating the right environment for innovation.
  3. Quant investing was not accepted at first, but with advancements in computing, it became possible to turn data into profitable strategies. Simons capitalized on this shift at just the right time.

What would you most like to learn in Quant Finance?

Quantitative Finance - Research, Trading, Investing, & Algos • 0 implied HN points • 03 Jun 25
💰 Finance Investing Trading Research Analytics Quantitative
  1. Learning about stochastic calculus, like Brownian motion and Itô’s Lemma, is important for understanding financial models. These concepts help us predict how prices will change over time.
  2. Mastering derivatives pricing, including the Black-Scholes model, is crucial for anyone dealing with options and risk management. It helps you figure out how much options should be worth.
  3. Exploring portfolio optimization techniques, like mean-variance, can help investors make better choices about how to allocate their money. It's about balancing risk and return effectively.