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  • 1. Lynch, Dustin Asset Allocation Technique for a Diversified Investment Portfolio Using Artificial Neural Networks

    Master of Science (MS), Ohio University, 2015, Industrial and Systems Engineering (Engineering and Technology)

    As part of planning for the future and retirement, people typically build their investment portfolio. Investment portfolios are made up of four different asset classes, and typically managed by one of the major investment firms such as the Edward Jones Company. This research works with artificial neural networks (ANN) and closely with an advisor from the Edward Jones Company to provide a machine learning decision making aid for them to use when allocating the four main asset classes that make up a portfolio. The asset class prediction results and trends are then compared by the advisors consulted to decide if this methodology would be a useful aid during high volatility times in the stock market, such as the market crash of 2008. The use of this successful machine learning aid will benefit the investment portfolio that shows promise for yielding higher return on investment (ROI). This research was determined to be a successful machine learning aid to assist advisors with the asset allocation of an investment portfolio.

    Committee: Gary Weckman Ph.D. (Advisor); Andy Snow Ph.D. (Committee Member); Tao Yuan Ph.D. (Committee Member); Namkyu Park Ph.D. (Committee Member) Subjects: Engineering; Finance