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    Comparing retirement investing with fixed and life-cycle funds using a variety of asset classes

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    DrinvilleT_Final_2021.pdf (980.8Kb)
    Author
    Drinville, Trevor
    Advisor
    Cline, Kelly; Wendt, Theodore; Larsen, Peter
    Date of Issue
    2021
    Metadata
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    URI
    https://scholars.carroll.edu/handle/20.500.12647/10471
    Title
    Comparing retirement investing with fixed and life-cycle funds using a variety of asset classes
    Type
    Thesis
    Abstract
    There are many different studies that both reinforce and discourage the use of life-cycle funds for retirement investing, but a majority of these studies only look at life-cycle funds that include the three main asset classes, which are stocks, bonds, and cash. This study compares fixed funds, four different types of life-cycle funds, and the use of three other non-traditional asset classes in the life-cycle funds. The three non-traditional classes which we add to the study are real estate, commodities, and high yield bonds. We evaluate these different portfolios based on the average rate of return and their level of risk, by conducting random simulations based on historical data. Our simulations found that the use of non-traditional assets (commodities, real estate investment trusts, and high yield bonds) can be useful in a portfolio as they produce a higher mean rate of return than the portfolios with traditional assets (bonds and cash) that we studied. The downside of the use of non-traditional assets in a portfolio is that on average they are riskier than the traditional portfolios. In the study, we tested two portfolios that were focused primarily on high yield bonds, which showed that high yield bonds are a valuable asset class. These two portfolios are the only ones that have a mean rate of return that is indistinguishable from our 100% stock portfolio. They also have a much lower risk than the all-stock portfolio which is very rare to see.
    Semester
    Spring
    Department
    Mathematics
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    • Mathematics, Engineering and Computer Science Undergraduate Theses

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