The Parlour $249 / month

The Parlour is a Substack that delves into management science, finance and society, and quantitative studies, offering insights into quantitative finance analytics, risk management strategies, financial modeling, machine learning applications in finance, and portfolio optimization. It provides summaries and analysis of recent academic research, highlighting innovations and trends in the field.

Quantitative Finance Analytics Risk Management Strategies Financial Modeling Machine Learning in Finance Portfolio Optimization Financial Market Simulations Algorithmic Trading Predictive Modeling in Finance Cryptocurrency and Blockchain Statistical Arbitrage Strategies

The hottest Substack posts of The Parlour

And their main takeaways

Quant Letter: March 2024, Week-1

12 implied HN points • 06 Mar 24
💰 Finance Quantitative finance Machine Learning Predictive Models
  1. The author analyzed over 3,450 sources to compile 80 relevant links for their subscribers, who now total 5,200.
  2. The SSRN recently published papers on predicting inflation volatility, intraday volatility in financial data, assessing banking stability, and investment advice.
  3. Readers can access the full post archives with a 7-day free trial to Machine Learning & Quant Finance.

Quant Letter: February 2024, Week-3

17 implied HN points • 21 Feb 24
💰 Finance Research Analysis Simulation Detection
  1. Research suggests Double Deep Q-learning can learn optimal trading strategies in fluctuating liquidity conditions.
  2. Investors decide to buy additional information about an asset's trajectory based on the indifference price of information.
  3. The RAGIC model predicts future stock prices accurately with a consistent 95% coverage using a Generative Adversarial Network.

Quant Letter: February 2024, Week-2

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: January 2024, Week-2

30 implied HN points • 09 Jan 24
💰 Finance Quantitative Machine Learning Market Dynamics
  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

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.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Quant Letter: January 2024, Week-1

21 implied HN points • 03 Jan 24
🕹 Technology Finance Miscellaneous Cryptocurrency
  1. The post shares summaries and links to various recent articles and research papers related to quantitative finance and machine learning in finance.
  2. Topics covered include forecasting models, risk management strategies, trading algorithms, AI applications, and financial market simulations.
  3. Quantitative finance professionals can stay updated on the latest developments and trends in the industry through various sources like podcasts, news articles, research papers, and online communities.

Quant Letter: December 2023, Week-3

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: November 2023, Week 4

21 implied HN points • 29 Nov 23
💰 Finance Machine Learning Quantitative finance Financial Modeling Portfolio Management
  1. The paper introduces a methodology using Shapley values to understand the contribution of different factors in portfolio performance.
  2. It presents the versatile SPPC method for evaluating predictor group contributions to portfolio success.
  3. The SPPC method quantifies predictor impacts and offers insights into changing dynamics over time in financial machine learning.

Quant Letter: December 2023, Week-2

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: November 2023, Week 2

17 implied HN points • 08 Nov 23
💰 Finance Quantitative finance Machine Learning
  1. Machine learning methods can enhance portfolio predictability and performance in finance.
  2. Research on transfer risk shows its relevance in stock return prediction and portfolio optimization.
  3. Understanding power-law behavior in volatility models can lead to more accurate pricing and risk management strategies.

Quant Letter: October 2023, Week 3

17 implied HN points • 18 Oct 23
💰 Finance Quantitative finance
  1. Don't rely solely on influencers or academics with a marketing budget for the latest quantitative finance techniques.
  2. Access information directly from academic-practitioners at blog.ml-quant.com for a broader view of quantitative finance research.
  3. Subscribe to Machine Learning & Quant Finance for a 7-day free trial to access more content and archives.

Quant Letter: November 2023, Week 1

12 implied HN points • 02 Nov 23
💰 Finance Quantitative finance
  1. A new method for analyzing high-frequency financial data shows intraday market changes are mainly driven by intraday correlation changes.
  2. The Chiarella-Heston model, an advanced agent-based model, enhances deep hedging in finance.
  3. Subscribe to Machine Learning & Quant Finance to access more content with a 7-day free trial.

Quant Letter: September 2023, Week 2

12 implied HN points • 14 Sep 23
💰 Finance Quantitative finance
  1. Quant Letter: September 2023, Week 2 is a weekly quantitative finance newsletter.
  2. A research on improving high-frequency trading systems through low-latency code optimization was recently published.
  3. You can get 7-day free access to Machine Learning & Quant Finance to read more.

Quant Letter: July 2023, Week 2

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: August 2023, Week 1

12 implied HN points • 02 Aug 23
💰 Finance Quantitative finance Machine Learning Research Financial Markets
  1. The featured papers discussed in the newsletter are 'Displaced by Big Data,' 'Deep Learning for Corporate Bonds,' and 'Exploiting the dynamics of commodity futures curves.'
  2. The newsletter highlights research on whether new data diminishes the advantages of active fund managers with industry expertise.
  3. Readers are encouraged to subscribe for a 7-day free trial to access the full post archives.

Quant Letter: July 2023, Week 1

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.

Quant Letter: June 2023, Week 3

12 implied HN points • 14 Jun 23
💰 Finance Quantitative finance
  1. The newsletter won't be available on the 21st, returning on the 28th with some changes.
  2. There are around 4,700 non-paying subscribers showing interest in research content.
  3. Interested readers can access a 7-day free trial for the full archives.

Quant Letter: March 2024, Week-2

0 implied HN points • 13 Mar 24
💰 Finance Quantitative finance
  1. The post discusses a new rank volatility model for large equity markets that aligns well with empirical data and allows for relative arbitrage.
  2. A new framework for pricing debt securities under varying short-rate differences is introduced.
  3. Readers can access the full post and archives with a 7-day free trial subscription to Machine Learning & Quant Finance.