Today’s mutual fund managers face an increasingly complex and dynamic investment environment. Their performance is evaluated every quarter, by the financial press, against broad based market indices. This attention has sometimes been criticized as creating incentives for a short term investment focus. However, to the contrary it also creates incentives that are consistent with a long term focus. First, it has the immediate advantage that fund costs (i.e., management fees, loads, taxes, and turnover costs) are closely scrutinized. That is, the returns from active portfolio management net of transaction costs are compared to the returns from passive investment in a broad based index. Second, the benchmark has normative properties as prescribed by the two fund theorem from CAPM. Therefore, this evaluation practice serves to highlight the opportunity costs of departing away from a normative investment strategy. As such, important incentives are created for fund managers to pursue efficient forward looking (i.e., ex ante) approaches to managing risk and return.

As a result of these incentives there has been increased interest in focusing upon forward looking measures of risk, such as the total Value-at-Risk (VaR). This forward looking measure provides a method for monitoring predicted portfolio performance. In particular, it can be integrated directly with the relevant benchmark (e.g., S&P500 index) that one is being evaluated against. To the extent that this approach results in better investment decisions is one of the main objectives of this project.

Suppose you are a fund manger with a large mutual fund company. You have noticed that within your company that Value-at-Risk statistics are routinely disclosed in internal daily reports. As a result, you are curious as to whether this information can add value to the portfolio selection problem. To test this out you decide to introduce a new fund that has the following simple investment and reporting objective:

To attain a better portfolio return and Value-at-Risk than provided from an investment in the S&P500 index.

That is, you will use realized at-risk numbers to judge whether your portfolio is "in-" or "out-of-control" relative to the benchmark.

Your investment goals for this project are twofold:

1. Outperform the S&P 500 index in return
2. Given i. minimize the VaR of your portfolio net of the value fluctuations had you invested the same amount in the S&P500 index.

In this project you will work with the Web and CAPM Tutor 2.0 to construct your portfolio and contrast predicted VaR with realized performance. Relevant theory behind this project, is described in the Applications Guide to Portfolio Theory.

This project is to be completed within a small group (not exceeding 3-members). Your portfolio should not exceed 25 securities, consisting of stocks and or mutual funds. Each team is required to prepare a both a formal report and a PowerPoint presentation covering the following issues:

1. The investment style that you selected to attain the above investment goals. Examples of different investment styles are active versus passive, growth versus value, analytical, beta, technical, timing and so on. You should describe your investment style and provide reasons in support of your style relative to the project’s objective.
2. A concise summary of your portfolio, prepared in a traditional manner, and designed to both inform and attract investors. In this report be careful to use the language and the form that is consistent with the mutual fund industry. Examples of this are provided by major funds (e.g., Fidelity (www.fid-inv.com) and Vanguard (www.vanguard.com)). You can use the results from CAPM Tutor back testing experiments for this report.
3. An analysis of your portfolio’s Value-at-Risk relative to the S&P 500 that compares predicted with realized performance. The length of time for realized performance is constrained by the duration of this course. However, you can also provide additional evidence from back testing experiments in your analysis if you want.

Note: For part iii. you should check that your actual portfolio is predicted to dominate the S&P500 along risk and return. That is, your portfolio should have smaller predicted volatility than the S&P 500 without sacrificing expected return. If this is not the case then you may want to modify your investment style (i.e., stock selection/portfolio construction technique in part i.)

4. A comparison and critique of parts ii. and iii. In particular, you should draw conclusions (and provide support for these conclusions) regarding the advantages/disadvantages of VaR as a portfolio management and control technique.

Each team’s presentation/report will be graded in terms of both form and substance. A team is not penalized for poor realized portfolio performance. Instead each team is rewarded for how well they analyze their realized performance.

Each team should prepare a PowerPoint presentation of their report for oral presentation in the last class. Each team member must participate in this presentation which should be (approximately) a 10-minute executive report. A copy of these slides should be submitted along with the formal report for grading purposes.

Relevant background material is the Applications Manual to Portfolio Theory, the Internet, Classroom Exercises and other sources of investment data. In particular you should use:

1. Chapter 2: CAPM Tutor and the Internet, Chapter 3: Portfolio Statistics
2. Investment theories (Chapters 7-9) Applications Guide.
3. Chapter 10 Back testing Investment Strategies. This chapter is important for testing different investment strategies.
4. Markowitz Backtesting or Index Backtesting Subjects in CAPM Tutor.
5. Chapter 11 Risk Management. This chapter lets you test forward looking (i.e., ex ante) investment strategies. For example, this chapter introduces Value-at-Risk and demonstrates how to perform this analysis on your portfolio.

(C) Copyright 1999, OS Financial Trading System