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

Doctor of Philosophy, The Ohio State University, 2014, Business Administration

This dissertation examines three distinct questions within the international portfolio choice literature. In chapter one, I study the change in the equity home bias during the financial panic of 2008. Using a sample of 45 countries, I document that the equity home bias fell. This is puzzling because theories of home bias and portfolio choice under uncertainty predict that during a crisis, the home bias should increase. With a novel methodology, I show that the active trades of investors, which increased the home bias, were subsumed by the passive valuation changes in their portfolio holdings, which decreased the home bias. I find evidence consistent with a role for portfolio rebalancing, increased information asymmetries, and the familiarity bias in portfolio allocations during the crisis. In chapter two, I analyze the impact of aggregate changes in U.S. demand for foreign stocks on U.S. firm-level stock prices. Separating U.S. net flows into outflows and inflows, I document that stocks with higher sensitivity to outflows earn significantly lower risk-adjusted returns. High outflows-beta firms tend to be smaller, younger, more volatile, and less globally diversified. Using firm-level, risk-adjusted returns, I find that the significantly negative premium is not subsumed by these characteristics or others commonly associated with misvaluation or limits to arbitrage. I show that the return on an outflows-mimicking portfolio is predictable and largely concentrated during periods when the demand for foreign equity is likely to fall, i.e., following reduced wealth, increased uncertainty, and reduced sentiment. The results are consistent with sensitivity to aggregate changes in U.S. demand for foreign stocks affecting firm-level U.S. stock returns. In chapter three, I study why U.S. investors' foreign portfolio share nearly doubled from 1994 to 2010. Using a sample of monthly bilateral equity holdings between investors in the U.S. and 45 countries, I document that (open full item for complete abstract)

Committee: René Stulz Ph.D. (Committee Chair); Kewei Hou Ph.D. (Committee Member); Ingrid Werner Ph.D. (Committee Member) Subjects: Finance

BA, Oberlin College, 2011, Economics

Using historic return inputs in a stylized computational financial market, this paper explores how participant outcomes are affected by the degree to which their asset allocation behavior responds to new market information. Findings support the efficient market hypothesis in that no alternate trading rule shows consistent improved outcomes relative to a full market exposure buy-and-hold strategy over the given time period. The only exception occurs briefly at the bottom of the 2008 financial crisis. Market participants that drastically alter market exposure in response to volatile returns, however, do outperform those who alter their exposure less drastically. Furthermore, the trading rules used here appear to offer a tradeoff between risk, return volatility and wealth development that is in-part at odds with efficient market hypothesis.

Committee: Ellis Tallman (Advisor) Subjects: Economic History; Economic Theory; Economics

Doctor of Business Administration, Cleveland State University, 2010, Nance College of Business Administration

For at least the last six decades optimal portfolio selection has been one of the main focuses of financial research. Since Markowitz (1952) many authors have developed ideas about the optimal allocation of assets that have reached today's mainstream portfolio decision-making. However, many of them miss the single largest investment most people make in their lifetime, their home. Therefore, this research seeks to analyze the impact of the owner-occupied home on the portfolio in order to determine its optimal allocation. The motivation for this analysis is derived from the individual investor who spends a lifetime saving in order to maximize their long-term wealth. The advantage of this study over previous research is the use of directly available assets through the use of Vanguard Funds. By using this dataset, three goals are achieved: (1) investing over the largest set of asset classes included in the research to date, (2) minimizing the cost of investing for the portfolio owner, and (3) providing a source of investable assets that are available to the small investor.The results have a substantial impact on the wealth accumulation of owner-occupier investors. First, the results show that including unleveraged owner-occupied housing in the portfolio is beneficial only at low levels of portfolio risk. Second, the results show that including leveraged owner-occupied housing in the portfolio is beneficial across all levels of portfolio risk. At low levels of portfolio risk all of the MSAs have some allocation to leveraged owner-occupied housing, however this allocation changes as the Loan-to-Value (LTV) Ratio increases. However, regardless of the LTV ratio, risk reduction at the lowest portfolio risk level is visible, but less so as the LTV ratio increases. Third, investors looking to allocate their investable funds across their portfolio without adding the mortgage will be over-investing in leveraged housing and potentially taking on too much unsystematic risk for the (open full item for complete abstract)

Committee: Ken Borokhovich PhD (Committee Chair); Haigang Zhou PhD (Committee Member); Walter Rom PhD (Committee Member); Brian Mikelbank PhD (Committee Member) Subjects: Finance