Fundamental Analysis, Behavioral Finance and Technical Analysis on the Stock Market

Table of Contents

1. Introduction

2. Information Efficiency on the Stock Market

2.1. Efficient Market Hypothesis

2.1.1. Definition and Theoretical Assumptions

2.1.2. Efficiency Forms

2.1.3. Classification of Fundamental Analysis, Behavioral Finance and Technical Analysis

2.2. Empirical Studies

2.3 Preliminary Conclusion

3. Fundamental Analysis

3.1. Definition and Premises

3.2. Company Evaluation Methods

3.2.1. Separate Evaluation Methods

3.2.2. Overall Evaluation Methods

3.2.2.1. Present Value Methods

3.2.2.1.1. Capitalized Earnings Value Approaches

3.2.2.1.2. Discounted Cash Flow Approaches

3.2.2.2. Market Multiples

3.2.2.3. Real Options

3.3. Empirical Studies

3.4. SWOT Analysis

3.5. Preliminary Conclusion

4. Behavioral Finance

4.1. Definition and Premises

4.2. Anomalies

4.2.1. Anomalies Concerning the Investors Behavior

4.2.1.1. Information Perception

4.2.1.2. Information Treatment

4.2.1.3. Decision Making

4.2.2. Stock Market Anomalies

4.3. Sentiment Indicators

4.4. Empirical Studies

4.5. SWOT Analysis

4.5. Preliminary Conclusion

5. Technical Analysis

5.1. Definition and Premises

5.2. Analysis Methods

5.2.1. Chart Analysis

5.2.1.1. Basic Concepts

5.2.1.2. Formation Analysis

5.2.2. Indicator Analysis

5.2.2.1. Trend-Following Indicators

5.2.2.2. Oscillators

5.3. Empirical Studies

5.4. SWOT Analysis

5.5. Preliminary Conclusion

6. Synthesis Capabilities of Fundamental Analysis, Behavioral Finance and Technical Analysis

6.1. Objective and Procedure

6.2. Theoretical Synthesis Capabilities

6.3. Practical synthesis capabilities using the example of the DAX Performance Index

6.3.1. Practical Application of Fundamental Analysis, Behavioral Finance and Technical Analysis

6.3.1.1. Intrinsic Value

6.3.1.2. Sentiment Indicators

6.3.1.3. Technical Indicators

6.3.2. Practical Synthesis Capabilities

6.4. Preliminary Conclusion

7. Final Conclusion and Outlook

Research Objectives and Themes

This thesis examines the three primary stock market analysis concepts—fundamental analysis, behavioral finance, and technical analysis—to determine their individual efficacy and potential for a theoretical and practical synthesis. The research aims to understand whether these methodologies can complement each other by leveraging their respective strengths to mitigate individual weaknesses, particularly in predicting market movements and timing investments.

• Scientific examination of the premises, approaches, and empirical evidence for fundamental, behavioral, and technical analysis.
• Evaluation of each concept using SWOT analysis to identify specific strengths, weaknesses, opportunities, and threats.
• Theoretical development of a synthesis concept to combine the identified strengths of all three approaches.
• Practical empirical study using the DAX Performance Index to test the synthesis capabilities of these methods.

Auszug aus dem Buch

Summary of Chapters

1. Introduction: Outlines the recent stock market turbulence and establishes the thesis objective to scientifically examine three core analysis concepts and their potential for synthesis.

2. Information Efficiency on the Stock Market: Discusses the Efficient Market Hypothesis (EMH) as the theoretical foundation for market pricing and analyzes empirical studies regarding information efficiency forms.

3. Fundamental Analysis: Defines fundamental analysis and its premise of intrinsic value, evaluating various company evaluation methods like DCF and Market Multiples through a SWOT analysis.

4. Behavioral Finance: Explores irrational investor behavior, categorizing psychological anomalies during the investment process and explaining their impact on stock market phenomena.

5. Technical Analysis: Examines chart and indicator analysis based on the premise that historical price data and market trends can forecast future movements.

6. Synthesis Capabilities of Fundamental Analysis, Behavioral Finance and Technical Analysis: Provides a theoretical and empirical investigation into combining the three approaches, using the DAX Performance Index as a case study.

7. Final Conclusion and Outlook: Summarizes the thesis findings, confirming that the three methods can supplement each other to improve investment decision-making despite lingering market efficiency challenges.

Keywords

Fundamental Analysis, Behavioral Finance, Technical Analysis, Efficient Market Hypothesis, Intrinsic Value, Sentiment Indicators, Market Anomalies, Stock Market Prediction, DAX Performance Index, Discounted Cash Flow, Investment Strategy, Market Efficiency, Investor Behavior, SWOT Analysis, Synthesis Concept

Frequently Asked Questions

What is the core focus of this thesis?

The thesis focuses on three distinct methods of stock market analysis: fundamental analysis, behavioral finance, and technical analysis, exploring their theoretical premises and practical applications.

What are the central thematic fields covered?

The work covers market information efficiency, the valuation of companies based on fundamental factors, the psychological aspects of irrational investor behavior, and the use of technical indicators for trend forecasting.

What is the primary objective of the research?

The main goal is to determine if these three competing analysis concepts can be synthesized into a more robust framework that eliminates individual weaknesses and enhances predictive capabilities.

Which scientific methods are employed?

The author uses theoretical literature reviews, SWOT analyses for each concept, and a quantitative empirical study based on analyst recommendations and the DAX Performance Index.

What is addressed in the main body of the work?

The main body details each of the three analysis concepts individually, followed by a dedicated chapter that tests their combined practical application using historical DAX data from 2004 to 2008.

Which keywords best characterize this work?

Fundamental analysis, behavioral finance, technical analysis, intrinsic value, market anomalies, and the synthesis of financial forecasting methods.

How is the "intrinsic value" of a stock calculated in this study?

The study uses the average target price derived from a large dataset of equity analyst recommendations to approximate the intrinsic value, allowing for a comparison against actual market prices.

Why is the sentiment index relevant to the thesis?

Sentiment indicators are highlighted as a bridge between behavioral finance and technical analysis, helping to quantify irrational market moods and identify potential reversals or exhaustion points.