Heather Sorcha

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  • Associate Professor, College of Business
  • PhD, Finance, Washington State University, 2011
  • MA, Applied Economics, Washington State University, 2010
  • BA, Actuarial Science, Roosevelt University, 1999


Dr. Sorcha earned a Bachelor of Arts in Actuarial Science from Roosevelt University in 1999,
working in industry as a pension actuary. Sorcha earned a Master of Arts in Applied Economics
(2010) and Doctorate in Business Administration – Finance (2011), both from Washington State
University. Sorcha researches financial technology (FinTech), insider trading, and investor
sentiment, with publications in the Financial Analysts Journal, the Journal of Business
Research, the International Review of Economics and Finance, the Journal of Financial
Education, and Managerial Finance.

Dr. Sorcha teaches Derivatives & Financial Engineering, FinTech Foundations, Global Finance,
Investment Analysis, and Principles of Finance. Sorcha has been nominated multiple times for
Michigan Technological University’s Distinguished Teaching Award. Sorcha was inducted into
Michigan Tech’s Academy of Teaching Excellence in 2018 and into Michigan Tech's Dean's
Teaching Showcase in 2017. In 2013, Sorcha received the College of Business Administration
Dean's Teaching Award as a faculty member at Central Michigan University. In 2010, Sorcha
received Washington State University's Graduate Student Teaching Excellence Award.

Dr. Sorcha currently serves on the Editorial Advisory Board for Managerial Finance, and is a
Past President of the MBAA Academy of Finance. At Michigan Technological University, Sorcha
serves as a member of the University Athletic Council, chairman of the College of Business
Strategic Planning Committee, and a member of the College of Business Undergraduate
Programs Committee.

Teaching Interests

• Derivatives & Financial Engineering
• FinTech Foundations
• Global Finance
• Investment Analysis
• Principles of Finance

Links of Interest

Google Scholar


Research Interests

• FinTech
• Insider Trading
• Investor Attention
• Market Efficiency