Stock market crashes had occurred in the financial market since the very beginning and in every generation (Sornette, 2003a). “Greed, hubris and systemic fluctuations have given us the Tulip Mania, the South Sea bubble, the land booms in the 1920s and 1980s, the U.S. stock market and great crash in 1929, the October 1987 crash, to name just a few of the hundreds of ready examples“ (Sornette, 2003a, p. 7.).
This essay will compare and contrast the last three major stock market crashes in 1987, 2000 and 2007. To do this, the essay will pay special emphasis on the causes of the three crashes. From there the essay will draw out the similarities and differences and will answer the question if boom and bust can be predicted.
Table of Contents
2 INTRODUCTION
3 STOCK MARKET CRASH IN 1987 – BLACK MONDAY
3.1 CAUSES
4 THE STOCK MARKET CRASH IN 2000 - .COM BUBBLE
4.1 CAUSES
5 THE STOCK MARKET CRASH IN 2007 – THE MORTGAGE CRISIS
5.1 CAUSES
6 COMPARISON AND CONTRAST
6.1 COMPARISON
6.2 CONTRAST
7 CONCLUSION – CAN BOOM AND BUST BE PREDICTED?
Objectives and Topics
The primary objective of this paper is to examine the underlying causes of the three major stock market crashes of 1987, 2000, and 2007. By analyzing these events, the study explores whether historical patterns and bubble formations can be identified to predict future market volatility and potential economic downturns.
- Analysis of Black Monday (1987) and its trigger factors.
- Examination of the .com Bubble (2000) and the influence of the "New Economy".
- Investigation of the 2007 Mortgage Crisis and the role of securitization.
- Comparison of market behaviors and similarities in speculative bubbles.
- Evaluation of predictive theories regarding financial boom and bust cycles.
Excerpt from the Book
3.1 Causes
Since the crash in 1987, a lot of research had been carried out to explain the crash and what really triggered it. Today, though, it is still not completely clear what caused the enormous decline. Sornette, D. mentions fife essential reasons for the crash in 1987, computer trading, derivate securities, illiquidity, trade and budget deficits and overvaluation (Sornette, 2003a).
1. Program trading
The financial markets, especially within the Wall Street, have seen a strong increase in program trading over the last years. Computers were programmed in a way to automatically sell or buy stocks if certain market conditions occur. These automatically triggered sell or buy orders where blamed to have initiated a domino effect after the decline of the previous days (Carlson, 2007).
2. Financial Innovation and Deregulation
The rise in derivate trading caused a rise in volatility in the stock markets, which increases the "variability, risk and uncertainty" (Sornette, 2003a, p. 6). Overall deregulations supported the increase in trading with high-risk financial products (Sornette, 2003a).
3. Illiquidity
The illiquidity of the market intensified the drop in share prices since there was just not enough money in the market for all the market participants who wanted to sell their shares (Sornette, 2003a).
Summary of Chapters
2 INTRODUCTION: This chapter provides an overview of historical financial crises and outlines the scope of the study regarding the 1987, 2000, and 2007 crashes.
3 STOCK MARKET CRASH IN 1987 – BLACK MONDAY: This section details the events of October 1987 and analyzes critical factors such as program trading, illiquidity, and overvaluation.
4 THE STOCK MARKET CRASH IN 2000 - .COM BUBBLE: This chapter discusses the technology-driven market boom and the subsequent burst of the .com bubble due to overvaluation and speculative investment.
5 THE STOCK MARKET CRASH IN 2007 – THE MORTGAGE CRISIS: This chapter examines how the housing bubble, credit expansion, and complex financial innovations like mortgage-backed securities triggered the global financial crisis.
6 COMPARISON AND CONTRAST: This section synthesizes the similarities and differences between the three crashes, highlighting shared patterns of speculative bubbles alongside unique socioeconomic causes.
7 CONCLUSION – CAN BOOM AND BUST BE PREDICTED?: This final chapter evaluates the feasibility of predicting financial crashes using statistical models and existing economic theories.
Keywords
Stock market crash, Black Monday, .com Bubble, Mortgage Crisis, Financial speculation, Market volatility, Overvaluation, Securitization, Economic recession, Predictive modeling, Boom and bust, Financial innovation, Didier Sornette, Market efficiency, Investment risk
Frequently Asked Questions
What is the core focus of this research paper?
The paper focuses on comparing three major financial crises (1987, 2000, and 2007) to determine if there are recognizable patterns that could help predict future market crashes.
What are the primary themes addressed in the text?
The central themes include speculative bubbles, the role of financial innovation, market liquidity, the impact of government deregulation, and the influence of investor psychology.
What is the central research question?
The central question is whether financial "boom and bust" cycles are predictable by identifying statistically significant patterns and trends that precede a market collapse.
Which methodology does the author employ?
The author utilizes a comparative, theory-based approach, synthesizing existing literature, historical market data, and econometric theories to analyze the causes of past crises.
What topics are discussed in the main body of the work?
The main body investigates the specific triggers for the 1987 crash, the 2000 dot-com bubble, and the 2007 subprime mortgage crisis, followed by a comparative analysis of their commonalities and differences.
Which keywords best describe this study?
Keywords include stock market crash, speculative bubble, overvaluation, financial innovation, market predictability, and systemic financial crisis.
How does the paper differentiate the 2007 crisis from the 1987 and 2000 crashes?
The author distinguishes the 2007 crisis as a "systematic" financial event that led to a global recession, whereas the previous two were more contained within the financial and technology sectors.
Is it possible to predict market crashes according to the conclusion?
The conclusion suggests that while we can identify warning signs and statistical outliers, human behavior and the complex nature of markets make a 100% accurate prediction impossible.
What is the role of "outliers" in the context of crash prediction?
The text references Didier Sornette's work, suggesting that market crashes can be analyzed as statistical outliers, which may serve as potential indicators or warning signals for future instability.
- Citar trabajo
- Arthur Ritter (Autor), 2014, The Last Three Stock Market Crashes. Can Boom and Bust Be Predicted?, Múnich, GRIN Verlag, https://www.grin.com/document/299134
