Risk is an enormous and growing concern in finance — from investment, decision making, corporate management, security, catastrophe resilience and more. And the interconnected nature of markets and the increasing sophistication of cyberattacks has made risk a top-of-mind concern for investors and managers alike. At the Hanlon Financial Systems Center, researchers rely upon economics, stochastic modeling, dependence modeling and data mining to better understand, plan for and manage risk in finance. Faculty are investigating market liquidity measures, stochastic volatility modeling, detection and prevention of rare events and applications of machine learning in risk management. The advanced software tools and databases provided through the Hanlon lab facilities support the resting of new research ideas and the quantifying of risk.
Since 2012, faculty associated with the Hanlon Financial Systems Center have been published books and papers in some of the most prestigious journals in finance, technology, math and business, including the Journal of Financial Econometrics and Quantitative Finance. An indicative list follows.