Summer 2011 Funded Projects

Summer 2011 GIASR Funded Projects


Wanding Shi

Mentor: Andrew Mun, Department of Business Administration

A Statistical Test  of Benjamin Graham’s Stock Selection Criteria


Project Results: Nobody can resist the temptation of money. Due to the inefficiency of the financial market, a lot of speculation opportunities exist. However, it is really hard to identify gold mines from pitfalls. Benjamin Graham, widely respected as the introducer of value investing and is considered to be the Father of Fundamental Analysis, bequeathed to us his ten criteria for identifying undervalued stocks. However, for small individual investors, it is often not practical, time-efficient or economical to perform the ten tests for each stock. Most of the time, investors prefer an easy model with fewer variables or they would like to identify the most suitable one for themselves. A Statistical Test of Benjamin Graham’s Stock Selection Criteria was to explore his famous ten stock selection criteria and provide guidance to small passive investors. It picked out four most accessible rules for small investors, tested their efficiency and concluded a regression equation for easy use. By combining the seven criteria Benjamin Graham provided in the Intelligent Investor with the ten rules, we found out there are five areas that are important for an investor: earning to price yield, dividend yield, stock price to current asset ratio and earning growth.

In order to ensure that the stocks we choose have a long healthy enough history and have complete SEC files, this paper will adopt the thirty stocks in Dow Jones Industry Average and the period from 2004 to 2007, to avoid the negative efforts of those crisis and identify the real factors behind stock price fluctuations. After testing the independence, normality and equal variance, we concluded that the regression equation with four is y = 1.67 + 0.306 (factor 1) – 0.101 (factor 2) + 0.00229 (factor 3) + 0.046(factor 4). However, the ANOVA analysis proved that this is not the most efficient model. The most efficient model we can get is y = 1.59 + 0.256 (factor 1) + 0.00253 (factor 3). Please note here: the conclusion we get here might be different from other professional researches. There are several reasons for this:

  1. The data base is small: we only included 30 stocks and 3years’ stock price range.
  2. There are other kinds of relationship between the stock price and the criteria, like quadratic ones. However, we only tested linear relationship here.
  3. There is interactive relationships between different criteria.

Maggie Winkelmann

Mentor: Barbara Kramer, Department of Chemistry

Influence of Chicken Habitat on Nutritional Value of Their Eggs


Project Results: The goals of this research project were to obtain, analyze, and compare the concentration of vitamin D3 in eggs from free-range chickens and commercially supplied eggs. This summer I used High Performance Liquid Chromatography (HPLC) to find the ratio between the area of the peaks obtained from the HPLC and the concentration of both vitamin D2 and vitamin D3. I optimized the separation of these two vitamins using the HPLC and produced a standard curve. After creating a standard curve, I used many resources as well as trial and error to determine a way to extract the vitamin D3 from the eggs. I used vitamin D2 as an internal standard to have an estimate of how much vitamin D3 was lost throughout the extraction process. This summer I was able to complete the analysis of one set of free-range eggs and one set of commercial eggs. For further research I plan to conduct more trials for both types of eggs, as well as examine other nutrients such as riboflavin and fatty acids.


Tim Sullivan

Mentor: Matthew Beaky, Department of Physics

Observing Changes in the Hα line of Delta Scorpii


Project Results: Over the summer I was able to use equipment available at the Truman Observatory to take several spectra of the Be binary star system Delta Scorpii. The system has a highly eccentric elliptical orbit and an orbital period of eleven years. The last time it reached periastron was in September of 2000. At that time, the relative intensity of the Hα line increased from about 1 to a maximum of 1.6.1 The data that was collected and analyzed showed the relative intensity of the Hα line range from 1.7 to 2.5 with an average of 2.0. This suggests an ongoing change in the composition of the system and could be due to interaction between the main star’s circumstellar disc and the secondary star.2

(2011): n. pag.


Olivia M. Wikle

Mentor: Shirley McKamie, Department of Music

The Singing Never Stopped: Exloration Concering the Transformation of European and American Supernatural Balladry


Project Results: /The_Singing_Never_Stopped.pdf


Melissa Wright

Mentor: Chad Montgomery, Department of Biology

Morphological Variation and Assessment of Subspecific Taxonomy in Boa Constrictor


Project Results: During this past summer, I finished my Thesis research project (titled: Morphological clinal variation and assessment of subspecific taxonomy in Boa constrictor) and presented it in Magruder 1096 on the morning of July 6th. There were some flaws with the analysis, which I have redone since the presentation, and I am now in the process of applying those changes to my Thesis. I also plan to try to publish my research findings in the Journal of Herpetology and the Journal of Evolution, both very high goals, but with the help of my advisors, I think that those goals are reachable. The grant I received was used as a stipend, and research activities that I accomplished during the grant period included data gathering, analyzing and writing up of the final project. Thank you for all your support!


Whitney Harris

Mentor: Glenn Wehner, Department of Agricultural Science

Determination of Behavioral Characteristics in Cattle: Result of Genetic Heritability


Project Results: My name is Whitney Harris and I am an Agricultural Science major.  Over the course of the summer I have been working on research with Dr. Glenn Wehner, Professor of Animal Science.  My research involves working with the spring calving Gelbvieh cattle herd at the University Farm.  Our goal that we set out on at the beginning of the summer was to collect data on the cattle’s behavior by observing them in three different settings.  The first setting was out at pasture and we took data at three different times (morning, noon, and night), three times each for a total of nine collections.  The second setting was in a confined area, or lot, where their flight zones were greatly decreased.  This was also done at three different times, but only once each.  In order to run these trials, I would calmly approach each cow individually, recording the distance at which each one stepped back or turned to move.  During this, I also recorded their tag number and the activity they were doing (eating, laying down, etc) at the time of approach.  The third setting, which we have yet to complete, is going to be examining them in a very confined area by recording their exit speeds from a chute.  Chutes are used to safely handle cattle by limiting the space they have to move freely and keeps them moving in one direction, which decreases the chances of injury to the animal and the handlers.  We will measure the amount of time it takes each cow to leave the chute, correlating to the docility of that individual.  Lastly, we will bring them back through the chute in order to photograph the whorl on their foreheads.  Research conducted by Dr. Temple Grandin, Colorado State University, indicates that the position of the whorl on the head suggests the docility and behavior of that individual so we will use the pictures to examine with our other data.  After all of the final data trials are collected, we will then carefully sort and examine the materials to determine any patterns suggested by the data.  We will then compare the results amongst the herd on an individual basis to see if there is any similarities along the maternal lines.  Our overall goal is to be able to suggest that docility and behavioral characteristics are genetically heritable.