Profitability Evaluation of Major Technical Analysis Trading Strategies Applied to the S&P 500 from 2005 to 2023

Table of Contents

1 Introduction

2 Background and Theory

2.1 Classification of Different Technical Analysis Strategies

2.2 Efficient Market Hypothesis

2.3 Martingale Model

2.4 Random Walk Models

2.5 Augmented Dickey-Fuller Test

2.6 Additional Models

3 Literature Review

4 Methodology

4.1 Data

4.2 Technical Analysis Strategies

4.2.1 Moving Average Crossover

4.2.2 Bollinger Bands

4.2.3 Relative Strength Index

4.2.4 Moving Average Convergence Divergence (MACD)

4.3 Descriptive Statistics

4.3.1 Underlying and Buy-and-Hold Strategy

4.3.2 Strategies

5 Results

6 Conclusion

Appendix A R Methodology, Return Analysis, and Trading Signals Overview

A.1 R Analysis Excerpt: MA5-150 Profit and Sharpe Ratio Calculation

A.2 Yearly Mean Daily Returns of Technical Analysis Strategies

A.3 Volume Analysis across Technical Analysis Strategies

A. 4 Entry and Exit Points following Technical Analysis Strategies

Objectives & Research Themes

This thesis investigates the profitability of various technical trading strategies when applied to the S&P 500 index between 2005 and 2023, assessing whether these rules can outperform a traditional buy-and-hold approach in a modern, more efficient market environment.

• Evaluation of four distinct technical analysis strategies, including both mean-reversion and trend-following approaches.
• Statistical assessment of S&P 500 market efficiency using ADF tests from 2005 to 2023.
• Robustness checks incorporating transaction costs to determine practical strategy viability.
• Analysis of risk exposure during major market crashes to test potential market-timing benefits.
• Comparison of Sharpe ratios and annual returns between active technical trading and passive buy-and-hold investments.

Excerpt from the Thesis

Summary of Chapters

1 Introduction: This chapter highlights the ongoing debate surrounding technical analysis and outlines the thesis goal to evaluate the profitability of trading strategies using recent S&P 500 data.

2 Background and Theory: This section details core financial theories such as the Efficient Market Hypothesis, random-walk models, and disequilibrium dynamics that serve as the foundation for the analysis.

3 Literature Review: The chapter summarizes previous academic findings on the profitability of technical trading systems and addresses common methodological challenges like data snooping.

4 Methodology: This chapter explains the dataset selection, the four technical strategies implemented (Moving Average Crossover, Bollinger Bands, RSI, MACD), and the metrics used for performance evaluation.

5 Results: This chapter presents the quantitative findings, evaluating the profitability of the selected strategies and their risk exposure compared to a buy-and-hold strategy.

6 Conclusion: The final chapter summarizes the thesis, confirming that while technical strategies offer superior Sharpe ratios in some cases, they generally do not outperform a buy-and-hold approach after transaction costs.

Keywords

Technical Analysis, S&P 500, Efficient Market Hypothesis, Moving Average Crossover, Bollinger Bands, Relative Strength Index, MACD, Profitability Assessment, Risk-Adjusted Returns, Transaction Costs, Market Crises, Data Snooping, Sharpe Ratio, Quantitative Finance, Trading Heuristics

Frequently Asked Questions

What is the core focus of this research?

The research evaluates the profitability of major technical analysis strategies applied to the S&P 500 index over the period from 2005 to 2023.

Which technical analysis strategies are examined?

The paper examines four main strategies: Moving Average Crossover, Bollinger Bands (BB), the Relative Strength Index (RSI), and the Moving Average Convergence Divergence (MACD).

What is the primary goal of this study?

The goal is to determine if these technical strategies can consistently outperform a simple buy-and-hold strategy, accounting for transaction costs in a modern market environment.

Which scientific methodology is utilized?

The study uses quantitative analysis involving daily market data, applying statistical performance metrics like the Sharpe ratio and conducting robustness checks for transaction costs and crash risk.

What is covered in the primary body of the thesis?

The main body covers a review of theoretical market models, an analysis of prior academic literature, detailed technical strategy definitions, and an empirical evaluation of trading performance.

Which keywords best characterize this work?

Key terms include Technical Analysis, S&P 500, Market Efficiency, Sharpe Ratio, and Quantitative Strategy Testing.

How does this study address the impact of market crises?

The thesis evaluates crash risk susceptibility by analyzing how the chosen strategies behaved during 10 major S&P 500 daily market declines, specifically looking at how they avoid or accumulate exposure.

What is the conclusion regarding market efficiency?

The research concludes that the S&P 500 likely exhibits at least weak-form efficiency during the observed period, as the strategies fail to consistently yield excess returns after considering transaction costs.