Xiaolou Yang Assistant Professor, Accounting and Finance Stock volatility, the impact of annual earnings announcement delays on stock performance, risk-taking investments and managerial incentives – these are just a few of the interests that have stimulated the innovative and analytical mind of Xiaolou Yang over the past few years. Her groundbreaking research in finance and investment theory and practice have lead to a plethora of prestigious, scholarly publications and presentations at conferences in China, England and across the United States. Yang’s passion for research and analysis is equaled by her love of teaching and mentoring her students as an assistant professor in the Lariccia School of Accounting and Finance at YSU. Today she is an enthusiastic champion of students who share her zeal for the study of finance. “Many of my students are very gifted scholars, already pursuing advanced research projects and studies,” she notes. “So many Youngstown State students are very hard-working and serious about their studies.” As a very hard-working and serious student herself, Yang graduated from Jilin University in China with a bachelor’s degree in finance in 1996. She then moved to Austin, Texas, to continue her education, earning her master’s degree and a Ph.D. in financial economics at the University of Texas. Before coming to YSU in 2008, Yang spent two years as an assistant professor of finance at Humboldt State University in California. In her recent research at YSU, Yang has pioneered the use of applied dynamic genetic algorithm – which is more commonly used in engineering, computer and biological research – for the study of investment strategies and performance. Her studies indicate that dynamic genetic algorithm can be used to select the best possible financial portfolio because it is a problem-solving procedure that allows both forward-looking and backward-induction, incorporating historical information as well as future uncertainty. Compared to traditional approaches such as the classical mean-variance model, Yang said, dynamic genetic algorithm can significantly improve the accuracy of return estimation and thus can improve overall portfolio efficiency and model performance. Yang’s research acumen combined with her love of teaching industrious students make YSU a great fit for her, one that is likely to pay handsome dividends to the university for years to come.
FALL 2011
7