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Pavlic, Theodore P.Optimal Foraging Theory Revisited
Master of Science, The Ohio State University, 2007, Electrical Engineering
Optimal foraging theory explains adaptation via natural selection through quantitative models. Behaviors that are most likely to be favored by natural selection can be predicted by maximizing functions representing Darwinian fitness. Optimization has natural applications in engineering, and so this approach can also be used to design behaviors of engineered agents. In this thesis, we generalize ideas from optimal foraging theory to allow for its easy application to engineering design. By extending standard models and suggesting new value functions of interest, we enhance the analytical efficacy of optimal foraging theory and suggest possible optimality reasons for previously unexplained behaviors observed in nature. Finally, we develop a procedure for maximizing a class of optimization functions relevant to our general model. As designing strategies to maximize returns in a stochastic environment is effectively an optimal portfolio problem, our methods are influenced by results from modern and post-modern portfolio theory. We suggest that optimal foraging theory could benefit by injecting updated concepts from these economic areas.


Kevin Passino (Advisor)


robotics; automation; autonomous vehicles; behavior; behavioral ecology; intelligent control; portfolio theory; modern portfolio theory; MPT; post-modern portfolio theory; PMPT; optimal foraging theory; OFT; optimal diet selection; predator; prey

Niro, Michael M.Asset Allocation with the Inclusion of the Owner-Occupied Home
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 level of return received. Fourth, higher tax bracket investors have greater allocation to leveraged owner-occupied housing than lower tax bracket investors and achieve higher rates of return in comparison to the same Tax Bracket Renter Portfolio.


Ken Borokhovich, PhD (Committee Chair); Haigang Zhou, PhD (Committee Member); Walter Rom, PhD (Committee Member); Brian Mikelbank, PhD (Committee Member)




Asset Allocation; Diversification; Real Estate; Investments; Portfolio Theory; Housing; Mutual Funds; Wealth; Taxes

Fisher, Patricia JSaving behavior of U.S. households: a prospect theory approach
Doctor of Philosophy, The Ohio State University, 2006, Family Resource Management
The main purpose of this dissertation is to explore household saving using a prospect theory approach through the use of the loss aversion model and behavioral portfolio theory. The research begins by investigating the effect of having expected per-period income above or below the reference level as well as the effect of uncertainty on the likelihood of saving based on the loss aversion model. The focus then moves to saving motives based on the ideas of behavioral portfolio theory. The direct measure of saving available in the dataset is saving over the previous year. Saving horizon is also investigated since the saving measure is a short-term measure and some regular savers may not have saved during the past year. The dataset used is the 2004 Survey of Consumer Finances. The sample excludes retired U.S. households for a final number of 3,694 households. Having expected per-period income above the reference level increases the likelihood of saving. Having expected per-period income below the reference level is significantly and negatively related to the likelihood of saving, and has a greater effect on the likelihood of saving than having expected per-period income above the reference. The group of uncertainty variables is significant in explaining the likelihood of saving. In contrast to the theories reviewed, most of the uncertainty variables are not found to increase the likelihood of saving. Saving motives and saving horizon are significant in explaining the likelihood of saving. Saving for a foreseeable expense significantly increases the likelihood of saving in both the models with and without interaction terms. Having a motive to save for the education of children or grandchildren significantly decreases the likelihood of saving in the model without interactions, while this variable is not significant when interactions are added. Inclusion of interactions of saving horizon variables with the saving motive variables is found to be significant in explaining the likelihood of saving, indicating that saving motives do differ by saving horizon.


Catherine Montalto (Advisor)


saving behaviors; household saving; prospect theory; behavioral portfolio theory; loss aversion; saving motives; saving horizon