The Duquesne University Investment Strategy Institute allows students to put their learning directly into practice by accessing databases, utilizing technology and producing results. Course assignments are designed around the research, testing and validation methods that are employed in the Investment Strategy Institute. Our goal is to expose students to technologies that reinforce learning while preparing them for assignments that they will likely encounter in their career.
The Investment Strategy Institute is used by professors from multiple disciplines. Listed below is a sample of project assignments that Investment Management majors might complete as a part of their coursework.
- Students analyze the riskiness of an investment portfolio and make recommendations to improve risk-adjusted rates of return. Consideration is given to the theoretical risk tolerance of the investor and the appropriate portfolio mix to maximize return, given risk. Additional analysis explores how changing the risk profile influences security selection.
- Performance data is gathered for a series of traditional market indices, such as the DJIA® and S&P 500®, which students then compare to the performance of less common indices or individual securities. An evaluation of the relative risk-return tradeoffs of these lesser-known investments compared to more common indices is presented.
- Students analyze the Return on Equity of a firm relative to industry peers. Using data collected from Standard & Poor's Research Insight®, financial ratios are evaluated over time and key trends and drivers are used to explain company performance relative to competitors.
- Stock Price valuation research is conducted by collecting and analyzing financial statements, SEC filings, annual reports, industry publications, conference call transcripts, news searches and interviews. Investment Center databases and tools provide a consolidated source for gathering information, which is used to perform fundamental security analysis.
- Using screening tools, students create hypothetical portfolios of securities that have common characteristics (i.e. strong Cash Flow per Share, E.P.S. growth, low Price to Book Value). These portfolios are back-tested to determine if the screens have the potential to predict strong stock performance.