Case Study 3

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University of Utah *

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4740

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Finance

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Apr 3, 2024

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Beta Management Market timing is the strategy of attempting to predict the future movements of financial markets in order to buy and sell assets at the most advantageous times for maximum profit. Ms. Wolfe has used the market timing strategy before in 1990, she opted to invest in the Vanguard Index 500 and employed market timing to transfer funds between money market accounts that have a beta close to 0; she allocated 100% of assets to the Vanguard fund during favorable market conditions in October-December and shifted 50% into money market accounts when anticipating a market downturn June-September. However, Ms. Wolfe strategy worked once doesn’t mean it will always work, predicting the market is a very hard task to do. In addition, exposing her client’s money to a risk like this while she’s trying to expand her work and clients is not the best choice. Variability is an important measure of investment risk because it significantly impacts the short-term performance of an investment. We’ll calculate the variability using the standard deviation. That assesses both systematic and
idiosyncratic risks associated with security, providing a useful measure for evaluating the risk of a single investment. Covariance is also a good tool to use for assessing different opportunities. investments perform in relation to one another. A positive covariance indicates that two assets tend to perform well at the same time, while a negative covariance indicates that they tend to move in opposite direction. If Ms. Wolfe were to invest 99% of her equity in Vanguard index fund and 1% in either stock California REIT, Brown Group. We’ll calculate the the standard deviation of each stock with 99% in Vanguard and 1% in each. The California REIT tends to be a lower risk than the Brown Group when invested 99% in Vanguard and 1% in California REIT. This is because of the Covariance we calculated above; investments perform in relation to one another. During the decline of Vanguard, we observed that the California REIT will have an increase that is why the covariance is very low compared to Brown 23.66 and 3 for California REIT.
One of the best measures is beta is a measure of a stock's sensitivity to movements in the overall market. It indicates how much a stock's price is likely to change in relation to a change in the market index. Now we’ll measure the stocks beta by performing a regression model in Excel using data analysis. California REIT: Brown Group: The beta of the California REIT is 0.15 and Brown Group is 1.16. This makes sense because the California REIT tends to move in the opposite direction of what we are compared to which is the index fund. The covariance also proves this point of what we discussed above. Lastly is the Risk/Return tradeoff which means that the higher risk is the higher return. But obviously this is not always the case, but this is what investors expects when investing in stocks or any investment. We’ll use the Capital Asset Pricing Model to calculate the expected return for both stocks. However, first we need the risk-free rate in 1990 is 8.55% and the risk premium is -7.45% because we are in a recession during that time. Formula:
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Expected return for California REIT: (CAPM) Formula: Expected return for Brown Group: (CAPM) In Conclusion, If Ms. Wolfe had to pick a stock to invest in, I would recommend the California REIT, that is because it has a low covariance, and it is really good to have a diversified portfolio. Brown Group tends to be risky and doesn’t have any return in comparison with risk. Even though the California REIT had a higher standard deviation after completing all the analysis, California would be a better option. It is also worth mentioning that the California REIT had a much lower beta than the Brown Group.