Momentum Crashes

Table of Contents

1. Introduction

2. The Momentum Investment Strategy – a General Overview

2.1 Mode of Operation

2.2 Sources of Momentum

2.3 Momentum in Equities and Other Asset Categories

2.4 Correlation with the Fama French Factors

3. Data, Construction and Application of the Momentum Portfolio

3.1 Data Origin and Portfolio Construction

3.2 Application of the Portfolio

4. Momentum Crashes

4.1 The Major Crash Periods

4.2 Crash Triggers

4.2.1 Skewness and Kurtosis

4.2.2 Bear Markets and Portfolio Betas

4.2.3 Non-Linearity of Market Returns in and after Bear Markets

5. The 2009 Momentum Crash – a Detailed Analysis

5.1 Qualitative Analysis: Companies in the Winner and Loser Portfolio

5.2 Quantitative Analysis: Insights into risk, size, trading volume, and value factors

6. Conclusion

Objectives and Research Themes

The primary objective of this thesis is to investigate the structural characteristics and underlying causes of extreme momentum underperformance, commonly referred to as momentum crashes, with a specific focus on the 2009 market crash period. The paper seeks to explain why momentum strategies, which are generally profitable, fail during specific market states and whether common financial models can adequately account for these performance deviations.

• Mechanisms and theoretical underpinnings of momentum investment strategies.
• Identification of common triggers for historical momentum crashes (e.g., 1930s, 2001, 2009).
• Quantitative evaluation of momentum portfolio composition using risk, size, and value metrics.
• Comparison of crash periods against non-crash benchmark market conditions.
• Analysis of portfolio beta variations and non-linear market relationships during bear market recoveries.

Excerpt from the Book

Summary of Chapters

1. Introduction: This chapter introduces the momentum strategy, its historical success, and the phenomenon of momentum crashes that can lead to significant losses.

2. The Momentum Investment Strategy – a General Overview: This section details how momentum strategies operate, explores behavioral finance theories regarding its origins, and confirms that the strategy exists across various asset classes.

3. Data, Construction and Application of the Momentum Portfolio: This chapter explains the methodological approach for constructing the winner and loser portfolios using NYSE, AMEX, and NASDAQ data and illustrates the historical performance of these portfolios.

4. Momentum Crashes: This chapter investigates historical crash periods and identifies key triggers, including higher-order return statistics, changing beta profiles during market reversals, and non-linear return relationships.

5. The 2009 Momentum Crash – a Detailed Analysis: This chapter provides a deep dive into the 2009 crash through both qualitative analysis of corporate composition and quantitative examination of risk, size, and value factors.

6. Conclusion: The final chapter summarizes the findings, reiterating that momentum crashes are driven by specific risk factors and structural portfolio imbalances that manifest during post-bear market recoveries.

Keywords

Momentum Strategy, Momentum Crashes, Winner Portfolio, Loser Portfolio, Bear Markets, Portfolio Beta, Market Reversal, Fama French Factors, Behavioral Finance, Stock Price Development, Market Capitalization, Value Factors, Financial Crisis, Skewness, Kurtosis

Frequently Asked Questions

What is the core focus of this thesis?

The thesis focuses on the phenomenon of momentum crashes, specifically examining the structures and characteristics that cause momentum investment strategies to underperform during certain market conditions.

What are the primary themes discussed?

Key themes include the operational logic of momentum trading, the identification of crash triggers, the analysis of portfolio beta variations, and the specific dynamics observed during the 2009 momentum crash.

What is the main objective of the research?

The objective is to explain the driving forces behind momentum crashes and to evaluate the performance of the momentum portfolio quantitatively when compared to benchmark periods.

Which methodology is applied?

The research replicates momentum strategies using historical data from the Kenneth French Data Library and CRSP, applying statistical analyses like OLS regressions to evaluate portfolio returns and risk factors.

What topics are covered in the main body?

The main body covers the practical application of the strategy, theoretical explanations for momentum, a detailed analysis of historical crash periods (1930s, 2001, 2009), and statistical insights into crash triggers.

Which keywords best characterize this work?

Key terms include Momentum Crashes, Winner/Loser Portfolios, Bear Market Betas, Fama French Factors, and Market Reversals.

Why do momentum strategies fail after bear markets?

The paper suggests that during bear markets, the loser portfolio becomes loaded with distressed, high-beta firms; when the market recovers, these firms experience disproportionately strong gains, causing massive losses for the short side of the momentum strategy.

How does the author categorize companies in the loser portfolio during the 2009 crash?

Companies are categorized into those with high book-to-market ratios representing distressed assets, and firms with strongly negative book-to-market ratios indicating that debt outstanding exceeds asset value.