StockTrak Project Summary

1.

I chose to passively manage my portfolio for a number of reasons. The first reason was in order to minimize trading costs and therefore increase overall real return of my portfolio. The second reason was that finding mispriced securities is a hard task to undertake, and therefore would increase the volatility of your returns. Since I don’t have previous trading experience, I would be taking a risk by trying to outperform the market. For that reason, I decided to passively hold the indexed portfolio. My third reason for choosing a passive management style was that the current state of the market is very volatile. Even experts from top banks have had a hard time correctly predicting the future outlook on equities. Another big reason I chose to passively manage my portfolio is that capital gains taxes are drastically lowered using this strategy. By holding securities for long periods of times, you decrease the capital gains taxes owed when you sell the securities. For active managers, high capital gains tax on sold securities is a big cost to consider. I wanted to avoid this issue and factored it into my decision to be a passive portfolio manager.

2. My final tracking error was .74%. This tracking error shows a fairly close relationship between the returns of my portfolio and the S&P 500 index. This tracking error was consistent with the initial optimization objective of closely modeling the returns of the S&P 500 as indicated by the tracking error. The following chart shows the returns of my portfolio versus the S&P 500. Figure 1.1

As you can see in Figure 1.1, my portfolio was pretty consistent with the returns of the S&P 500 index with a small tracking error. My tracking error could have probably been smaller if I had traded a day or two earlier, since the market returns were very volatile the two days before I executed my trades. My portfolio was not actually as diversified as I had hoped through the stratified sampling method. My portfolio industry breakdown can be seen in the following chart:

Figure 1.2

As you can see in Figure 1.2, my stratified sample did not come out to be as diversified in terms of sector as I had expected initially. This was probably due to chance when I used the random function to select a subsample of securities. My portfolio was, however, diversified when it comes to size and style. An equal number of small cap and large cap securities were chosen with high and low price to book ratios. The goal was to have a portfolio diversified in style, size, and sector. My portfolio came out to be mainly diversified in size and style, but still managed to model the S&P 500 index pretty closely. The significance of this kind of diversification is that your portfolio is exposed to less macroeconomic risk through diversification of style, size, and sector.

3. The biggest advantage in my opinion of selecting a subsample of securities from the S&P 500 versus each constituent is that you minimize trading costs by only purchasing 100 different securities, while still modeling the overall returns of each constituent in the S&P 500 index. For example, through our stratified sampling method, we came up with 100 securities that were well diversified to model the returns of the S&P 500. By only having 100 securities, we only had to pay trading costs for 100 securities. If we had chosen all 500 securities, we would have had to pay 5 times the amount of trading costs. Also, the difference in the returns would be minimal with considering we chose a well diversified subsample of 100 securities.
A disadvantage is always trying to keep your portfolio weights in each industry at your target weight. When prices of certain securities rise or drop dramatically, you have to adjust your portfolio in order to reach your target weights again. This can be a a hassle in the day to day management of a passive portfolio. It can also increase trading costs, resulting in a lower return on investment. Even though you have to constantly adjust your portfolio to achieve desired weights, this is not by any means an active strategy. Active managers try to identify mispriced securities to gain a profit by “beating” the market. They do not adjust for target weights. Despite using a stratified sampling method to choose a subsample of securities, there is still active risk present that can lead to a portfolio that lacks diversification in terms of sector. This is the case with my portfolio. Even though the securities were chosen in a fairly random manner given size and style requirements, my portfolio was heavily invested in Consumer Discretionary by chance. This results in a potentially large risk. If the consumer discretionary industry were to take a hit, my portfolio would suffer dramatic losses. On the other hand, if the consumer discretionary industry were to fare really well, my portfolio would benefit greatly. This results in a portfolio with a high volatility of returns. Thankfully, during the three months of this project, the consumer discretionary industry was fairly stable. Systematic risk is still a large real world risk that is present when managing a passively held portfolio. Macroeconomic factors can dramatically change the return on investment. These risks are not diversifiable and therefore affect all equity securities.

4. My Sharpe Ratio of 4.03 was significantly better than the 1.416 Sharpe Ratio of the S&P 500 index. The Sharpe Ratio is an appropriate comparison tool because it measures the excess portfolio return for the portfolio’s degree of volatility. My portfolio, as indicated by the Sharpe Ratios, is the better portfolio since it offers more reward for the degree of risk involved. While the Sharpe Ratio can be a good measure of risk/return for the S&P 500, it is not as accurate when describe the risk/return relationship for hedge funds and private equity investors. The Sharpe ratio is meant for investments that are liquid and have normally distributed returns. Hedge fund investments are often times illiquid due to lock up periods, etc. For hedge funds, you need more measures such as skewness and kurtosis. Since hedge funds often times produce small positive returns and sometimes have a big negative return, Sharpe Ratios can be unreasonably high until the big loss occurs. For these reasons, the Sharpe Ratio is better suited to represent the risk/return relationship of liquid and normally distributed securities and indexes such as the S&P 500.

5. The most eye opening statistic to me after doing this project was the return achieved at the end. When most projects are assigned in business school, you work on an assignment to help you understand a bigger concept. While this definitely holds true for this project, I found it really interesting how this project was very close to the real world process for constructing an index portfolio. Projects are usually simplified to give you a basic understanding of a concept, but with this project we actually did the exact same thing an index fund manager would do. I turned my $500,000 into roughly $550,000 over the course of this semester. This means that if I actually had $500,000 at the beginning of this semester and decided to create a stratified subsample of the S&P 500, I would have had an unrealized holding gain of $50,000. Seeing that statistic is really eye opening and shows you the world of possibilities that are there when it comes to money managing and creating the optimal portfolio. Another thing I found really interesting was how closely we were able to model the S&P 500, despite only holding 1/5 of the securities in the index. Intuitively, you would think that at least more then half of the securities would be needed to accomplish this goal. Through this project, I’ve learned that stratified sampling methods allow you to model the returns of an index with significantly less securities, which ultimately reduces your trading costs and increases overall return.