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This report will provide an analysis of frontier market equity-based investment funds with respect to bivariate correlation analysis, global integration analysis, and US optimized portfolio statistics. My analysis has indicated strong diversification benefits of including frontier market equities in a US portfolio, given its low correlation to US equity concentrated portfolios especially portfolios that would consist of midcap and smallcap stocks. With the drawbacks of the bivariate correlation test, an additional global integration analysis has been included to reaffirm the value frontier markets offer in the form of integration. Integration is a second layer of the diversification analysis. I find that when analyzing frontier markets (FM) against developed markets (DM) there exhibits significantly less integration as compared to emerging markets against developed markets. This analysis goes one step further and quantifies integration of specific frontier market funds against the broader emerging and developed markets. This study finds that iShares MSCI frontier 100 ETF (Ticker: FM) exhibits the least integration amongst Guggenheim Frontier Markets ETF (Ticker: FRN), Templeton Frontier Markets A (Ticker: TFMAX), and Morgan Stanley Frontier Emg (Ticker: MFMIX). Lastly, this analysis covers the inadequacy with using Sharpe ratios and minimum volatility parameters to achieve portfolio optimization under a Monte-Carlo style 1000 portfolio simulation with frontier market funds in a broader US equity portfolio but finds better results when using a US equity and US bond combination portfolio. Overall, this analysis of frontier markets and frontier market funds has shown there still exists significant diversification benefits to US Investors when they engage in FM investments, specifically through diversified FM investment funds.
ContributorsHardy, Gunner Laine (Author) / Pruitt, Seth (Thesis director) / Brada, Josef (Committee member) / W.P. Carey School of Business (Contributor) / Economics Program in CLAS (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis aims to promote financial literacy in the community. It was driven by the realization that there was a lack of basic financial knowledge among people at ASU and beyond. The people involved in the reason for the guide had all heard of bonds and understood the basic concepts, but lacked the knowledge of the finite details. The research starts with an overview of the United States bond market and focuses on the creation of a short simple guide. The goal is that anyone can read the guide and have a basic understanding of bonds, talk to financial managers, and do some basic investing. The easy guide is basically a two-page crash course on investing in bonds. Anyone can take a class or watch a video on bonds, but how do they actually start investing in them? This thesis works to answer this question by providing knowledge of real world application. The goal is to take knowledge beyond a book or video and learn from actively investing in a safe and clear way. Bonds are a very useful tool in investing and provide safe returns. The investing proposed is one that would be an alternative to putting money into a savings account. The guide recommends a good starting point of a way to invest in bonds (Specifically the US Treasury). At the same time does some analysis on other investing options for more advanced investors. The work includes an analysis of five bond portfolios and the calculations of finding their actual returns after loads and other fees.
ContributorsIrwin, Carter E. (Author) / Pruitt, Seth (Thesis director) / Schreindorfer, David (Committee member) / W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This dissertation studies how forecasting performance can be improved in big data. The first chapter with Seung C. Ahn considers Partial Least Squares (PLS) estimation of a time-series forecasting model with data containing a large number of time series observations of many predictors. In the model, a subset or a whole set of the latent common factors in predictors determine a target variable. First, the optimal number of the PLS factors for forecasting could be smaller than the number of the common factors relevant for the target variable. Second, as more than the optimal number of PLS factors is used, the out-of-sample explanatory power of the factors could decrease while their in-sample power may increase. Monte Carlo simulation results also confirm these asymptotic results. In addition, simulation results indicate that the out-of-sample forecasting power of the PLS factors is often higher when a smaller than the asymptotically optimal number of factors are used. Finally, the out-of-sample forecasting power of the PLS factors often decreases as the second, third, and more factors are added, even if the asymptotically optimal number of the factors is greater than one. The second chapter studies the predictive performance of various factor estimations comprehensively. Big data that consist of major U.S. macroeconomic and finance variables, are constructed. 148 target variables are forecasted, using 7 factor estimation methods with 11 information criteria. First, the number of factors used in forecasting is important and Incorporating more factors does not always provide better forecasting performance. Second, using consistently estimated number of factors does not necessarily improve predictive performance. The first PLS factor, which is not theoretically consistent, very often shows strong forecasting performance. Third, there is a large difference in the forecasting performance across different information criteria, even when the same factor estimation method is used. Therefore, the choice of factor estimation method, as well as the information criterion, is crucial in forecasting practice. Finally, the first PLS factor yields forecasting performance very close to the best result from the total combinations of the 7 factor estimation methods and 11 information criteria.
ContributorsBae, Juhui (Author) / Ahn, Seung (Thesis advisor) / Pruitt, Seth (Committee member) / Kuminoff, Nicolai (Committee member) / Ferraro, Domenico (Committee member) / Arizona State University (Publisher)
Created2021
ContributorsMarine Biological Laboratory (Woods Hole, Mass.) (Publisher) / Arizona Board of Regents (Publisher)
Created1939
ContributorsMarine Biological Laboratory (Woods Hole, Mass.) (Publisher) / Arizona Board of Regents (Publisher)
Created1944
ContributorsMarine Biological Laboratory (Woods Hole, Mass.) (Publisher) / Arizona Board of Regents (Publisher)
Created1945
ContributorsMarine Biological Laboratory (Woods Hole, Mass.) (Publisher) / Arizona Board of Regents (Publisher, Publisher)
Created1948
ContributorsMarine Biological Laboratory (Woods Hole, Mass.) (Publisher) / Arizona Board of Regents (Publisher)
Created1955
Description
Breast cancer affects about 12% of women in the US. Arguably, it is one of the most advertised cancers. Mammography became a popular tool of breast cancer screening in the 1970s, and patient-geared guidelines came from the American Cancer Society (ACS) and the US Preventative Task Force (USPSTF). This research focuses on ACS guidelines, as they were the earliest as well as the most changed guidelines. Mammography guidelines changed over time due to multiple factors. This research has tracked possible causes of those changes. Research began with an extensive literature search of clinical trials, the New York Times and the Washington Post archives, systematic reviews, ACS and USPSTF archives.
ContributorsZiganshina, Dina (Author) / Tuoti, Whitney Alexandra (Editor) / Arizona State University. School of Life Sciences. Center for Biology and Society. Embryo Project Encyclopedia. (Publisher) / Arizona Board of Regents (Publisher)
Created2021-02-16
Description
Science fiction works can reflect the relationship between science and society by telling stories that are set in the future of ethical implications or social consequences of scientific advancements. This thesis investigates how the concept of reproduction is depicted in popular science fiction works.
ContributorsDayoung Kim, Grace (Author) / Tuoti, Whitney Alexandra (Editor) / Arizona State University. School of Life Sciences. Center for Biology and Society. Embryo Project Encyclopedia. (Publisher) / Arizona Board of Regents (Publisher)
Created2021-02-10