Semivolatility-Managed Portfolios

Hi! Here's Iván with this week's exciting newsletter, brimming with insights and discoveries on building robust investment strategies and risk models using Machine Learning.

In this edition, I am presenting the following sections:

• 🕹️ AI-Finance Insights: I summarize two must-read academic papers that mix cutting-edge ML/DL with Asset Pricing & Quant Finance:

  • Semivolatility-managed Portfolios

  • Factor Dispersions

• 💊 AI Essentials: The section on top AI & Quant Finance learning resources: Today, I’m sharing Simplilearn's 2024 full course, perfect for mastering both fundamental and advanced machine learning concepts.

• 🥐 Asset Pricing Insights: In this edition, I present a simple analysis that identifies the top U.S. stocks generating long-term returns, revealing the critical role of holding high-performing stocks over extended periods.

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“Semivolatility-managed Portfolios”

The paper introduces an innovative approach to portfolio management by leveraging semivolatility to enhance risk-adjusted returns across various asset classes.

The main contributions and findings are as follows:

👉 The study shows that managing portfolios with a focus on semivolatility—accounting for both upside and downside risks—yields more robust risk-adjusted performances compared to traditional volatility management strategies. This approach proves particularly effective for factors, anomaly portfolios, and exchange-traded funds (ETFs).

👉 Empirical results highlight that semivolatility-managed portfolios significantly improve Sharpe and Sortino ratios, especially for the worst-performing factors and anomaly portfolios, by better capturing the impacts of skewness and downside risk.

👉 The research further demonstrates that controlling for higher-order moments like skewness and kurtosis in portfolio management leads to substantial performance gains, offering a more comprehensive and effective strategy for mitigating risk and enhancing returns.

“Factor Dispersions”

The paper introduces a comprehensive analysis of factor dispersions, revealing critical insights into the behavior of smart-beta indices through a linear factor model approach.

The main contributions and findings are as follows:

👉 The study uncovers that even portfolios designed to focus on a single factor are exposed to variances of multiple factors, driven by the cross-sectional weighted variances of factor betas. This highlights the complexity and interconnectedness of factor exposures in smart-beta indices.

👉 Empirical analysis demonstrates that dispersion risk premiums, which combine systematic and idiosyncratic variance components, provide valuable signals for future investment opportunities. These signals are closely linked to macroeconomic variables and can help in identifying shifts between alpha-harvesting and systematic investing regimes.

👉 The research further shows that dispersion trading strategies, when properly designed, can isolate exposure to specific factors and enhance portfolio performance, offering a novel approach to managing factor variance and covariance risk.

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AI-Essentials

Introducing a top-notch Machine Learning course for 2024 by Simplilearn! This video covers everything from the basics to advanced concepts, including linear vs. logistic regression and key statistics. It also includes essential interview questions to help you ace your machine learning interviews. Perfect for beginners and those looking to deepen their understanding!

Asset Pricing Insights

“Which U.S. Stocks Generated the Highest Long-Term Returns?”

The paper provides a detailed analysis of long-term stock performance, revealing surprising insights into which U.S. stocks delivered the most significant returns over nearly a century.

The main contributions and findings are as follows:

👉 The study identifies that a majority (51.6%) of U.S. stocks had negative cumulative returns, but a select few generated extraordinary wealth, with 17 stocks achieving over five million percent returns, highlighting the importance of long-term investing.

👉 Altria Group leads with a staggering 265 million percent cumulative return, affirming the "time in the market" principle, where moderate annual returns compounded over long periods create enormous wealth.

👉 The research underscores the skewness in stock returns, where a small number of stocks account for a disproportionate share of wealth creation, emphasizing the potential benefits of identifying and holding such outliers in an investment portfolio.

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