Asset Allocation in Active Portfolio Management using Treynor-Black Model and Technical Trends

Asset Allocation in Active Portfolio Management using Treynor-Black Model and Technical Trends

Asset Allocation in Active Portfolio Management using Treynor-Black Model and Technical Trends Shekhar Karande September 2010 Dissertation submitted in partial fulfilment for the degree of Master of Science in Computing for Financial Markets Department of Computing Science and Mathematics University of Stirling Abstract Active Portfolio Management is considered to be a very costly process and the results of this process may not be entirely fruitful Conventionally, fundamental analysis is used to evaluate a stock, which is usually carried out by experts and consumes a lot of time The Treynor-Black model is a multifactor model applied to the equity universe Equities being relatively less risky to Derivatives, suit the appetite of a moderate risk friendly investor Today, with the amount of free and reliable data available, one can use it generate information to make profits It is required that this information is transferred into a form suitable to be used in portfolio optimisation models The main objective of the project is to use technical trends to analyse equities and use it to create optimum portfolios Thus the software is able to generate technical charts for a stock and calculates the expected returns, the sensitivity of the stock to the index The data however has to be manually collected and altered to be used by the software This is a project designed in Java following the object oriented methodology for emulating the entities of a stock market This allows extending the software to different kinds of investment instruments like bonds and derivatives The software package provides a GUI, divided into two distinct sections One for representing Technical Analysis and Regression analysis, and the second for emulating the Treynor-Black Model The first section allows the user to select a stock from a list of stocks and generate technical charts After evaluation, the user may proceed to add the stock to his portfolio and evaluate the portfolio using the Treynor-Black Model The software can be improved to show more detailed technical charts and allow the comparison of two or more portfolios -1- Attestation I understand the nature of plagiarism, and I am aware of the University's policy on this I certify that this dissertation reports original work by me during my University project except for the following (adjust according to the circumstances):  The section on Technical Analysis in Chapter was largely derived from http://www.investopedia.com  The Treynor Black model described in Chapter 2, uses information available on http://home.earthlink.net/~millerrisk/Papers/TreynorBlackRevisited.htm  The code discussed in Section 3.3, 3.4 and 3.5 was written by my supervisor Dr David Cairns which I have adapted to apply to this software package  The regression calculation code was adapted from regression analysis in the Statistics class available in jFreeChart  The Excel spreadsheet used to compare results of the Treynor-Black model was downloaded from http://highered.mcgrawhill.com/sites/007338237x/student_view0/chapter8/excel_templates.html Signature Date -2- Acknowledgements I would like to thank everyone who has helped me to complete this project Dr David Cairns, my supervisor, for supporting me and helping me on every step especially to implement jFreeChart I would like to thank Kevin Campbell, for pointing me towards the Treynor-Black model for Active Portfolio Management I would also like to thank Immanuel N N Kadhila for helping me understand the Treynor- Black model I would like to thank Boonisaed Thanyaworaanan for teaching me the concepts of technical analysis and help design the test cases to test the software application I would like to thank Prateek, Immanuel and Boonisaed to help me with the Usability Testing -3- Table of Contents Abstract Attestation Acknowledgements Table of Contents List of Figures Introduction 1.1 Background and Context 1.2 Scope and Objectives 1.3 Achievements 1.4 Overview of Dissertation State-of-The-Art 2.1 Modern Portfolio Theory 2.2 Technical Analysis 10 2.2.1 Technical Trends 11 2.2.2 Support and Resistance 12 2.2.3 Volume 12 2.2.4 Charts 13 2.2.5 Moving Averages 14 2.3 The Treynor Black Model 16 2.4 Current Software for Technical Analysis and Portfolio Optimisation 16 2.5 Issues addressed by the Software Package 17 Technical Overview 18 3.1 ActivePortfolioManagementApp class 19 3.2 ActivePortfolioManagementView class 19 3.2.1 Charts for Technical Analysis 21 3.2.2 The Treynor-Black Model results-Black Results 23 3.3 ActivePortfolioManagementEquity class 25 3.4 ActivePortfolioManagementPortfolio class 25 3.5 ActivPortfolioManagementHistory class 25 3.6 ActivePortfolioManagementTick class 25 Testing 26 4.1 Data Sets 26 4.2 Testing Functionality of the software 29 4.3 Usability Testing 29 -4- 4.4 Testing conclusions 29 Conclusion 31 5.1 Summary 31 5.2 Evaluation 31 5.3 Future Work 31 References 33 Appendix 1-Downloading and updating data files 34 Appendix – User guide 38 Appendix – Installation guide 39 -5- List of Figures Figure Example of Trend Investopedia.com[4] .11 Figure Support and Resistance Levels Investopedia.com[5] 12 Figure Line Chart example Investopedia.com[6] 13 Figure Candlestick Chart Example Investopedia.com[7] 14 Figure Moving Averages Investopedia.com[8] 15 Figure Trend indicator using Moving Averages Investopedia.com[9] 15 Figure Design Preview of GUI 20 Figure Chart for Alliance Trust from January 01, 2009 to January 01, 2010 22 Figure The Treynor-Black Model optimisation results 24 Figure 10 Risk Parameters[1] 26 Figure 11 Macro Forecasts[1] 27 Figure 12 Computation of Optimal Risky Portfolio using Treynor-Black Model[1] 27 Figure 13 Results of produced by the software package 28 Figure 14 Yahoo!Finance 34 Figure 15 Symbol lookup for Tesco 34 Figure 16 Stock information 35 Figure 17 Selecting Daily price list 35 Figure 18 Download the file 36 Figure 19 Saving the file in the "Data" folder 36 Figure 20 Updating headers of data files 37 -6- Introduction This chapter gives a brief overview of the project and the software development lifecycle It outlines the background and context of the project It spans into the scope and objectives continuing into the achievements 1.1 Background and Context The Treynor-Black model was designed in 1973, with an effort to understand the relationship of risk and return while constructing a portfolio of assets "According to Miller [1], this model is being used extensively in many portfolios optimising software It is an easy to understand model requiring little information providing the solution in an easy to understand algebraic formula." Fundamental Analysis has been the conventional tool of stock evaluation; however this project tries to implement the alternate to fundamental analysis Technical analysis is traditionally used for identifying trends in intraday trading However, the same theories can be applied to evaluate long term trends The results of this analysis can be used as inputs to the Treynor-Black model This project tries to use Technical Analysis for analysis to help investors who are relatively new to investment 1.2 Scope and Objectives The main aim of this project is to build an independent desktop application to help a moderately knowledgeable investor to analyse stocks listed on FTSE100 and create a viable portfolio The functions of the software are: Create technical charts for analysis using previously downloaded data Display results of regression Evaluate results for the Treynor-Black Model The first two sections can be used as a standalone tool for technical analysis as well 1.3 Achievements The software developed performs all functions stated in the scope and objectives section The software was tested using predefined test cases and was able to reproduce the same results as generated in Excel Spreadsheet [1] -7- 1.4 Overview of Dissertation The rest of this dissertation will introduce the State of the Art in chapter 2, presenting a general discussion of Technical Analysis and The Treynor Black model Chapter introduces the technical implementation of the classes related to the software architecture Chapter discusses the testing of the software Chapter will provide the conclusion reached by this project -8- State-of-The-Art This chapter introduces the concepts of modern portfolio theory to be used in the overall design and structure of an investment portfolio The chapter introduces the concepts of Technical Analysis to be used in evaluating the value of a stock Later on a brief description of the Treynor-Black model tries to lay the foundation of portfolio design using Equities 2.1 Modern Portfolio Theory All investors will look forward to maximise their profit on their investments with the least risk as possible The risk appetite of the investor will determine the cost of profit It is highly likely that a risk averse investor will make less profit as compared to an investor who is willing to take more risks, in the same market environment However, this does not undermine the fact that both types of investors stand to make a loss/profit at the end of their investment horizon which is equivalent to their risk appetite All investors are exposed to the same kinds of risk irrespective of their risk appetite The risks are mainly of two different kinds First the systematic risk, which is inherent to the equity that the investors invest in Inherent risks arise due to the performance of the equity The underlying factors supporting the instrument For example, consider an investment in buying stocks of a car manufacturer The systematic risk will include the sales of the company, the manufacturing capacity of the company, the competition in the car market, the demand of cars manufactured by the company, etc If an investor is keen on purchasing stocks for a car manufacturing company, he is exposed to all of the above mentioned risks for one single company To reduce one's risk, the best option is to diversify the investment to minimise systematic risk If applied properly, diversification can help eliminate systematic risk completely The unsystematic risk on the other hand depends on macro economic factors, for example the state of the economy (recession/depression), the interest rates, external influential factors like natural disasters, war All investments are equally exposed to the unsystematic risks and will react to bad news in the same manner An investor at all times will expect to minimise the unsystematic risk and eliminate the systematic risk Thus, it implies that investing will always be a trade off between the expected return on an investment whilst being exposed to risk As commonly observed, investments with higher expected returns tend to be more risky This leads to classifying investments based on their systematic risks Traditional investments in financial markets include bonds, equities and derivatives Bonds are considered to be the least risky of the three and derivatives the most risky An investor will invest -9- ... constructing a portfolio of assets "According to Miller [1], this model is being used extensively in many portfolios optimising software It is an easy to understand model requiring little information... 3.2.2 The Treynor-Black Model results-Black Results 23 3.3 ActivePortfolioManagementEquity class 25 3.4 ActivePortfolioManagementPortfolio class 25 3.5 ActivPortfolioManagementHistory... into the scope and objectives continuing into the achievements 1.1 Background and Context The Treynor-Black model was designed in 1973, with an effort to understand the relationship of risk and