Over the last 25 years, the finance industry has undergone a fundamental transformation. Deregulation and technological advancements beginning in the 1990s has resulted in a proliferation of competing markets and greatly reduced execution costs, while extensive regulation implemented after the 2008 financial crisis now requires firms to better measure and control risk in their portfolios. In addition, the increased granularity and volume of data available for financial decision making has created new opportunities for computer-savvy quants to lend and manage money.
To survive in this new environment, bankers, traders and money managers must understand the probabilistic distributions driving economic forecasts, be able to manage and analyze large financial data sets to build trading, investment and risk models and understand the proper use and limitations of the mathematical models on which much financial decision-making is based. The industry looks to financial engineers for the knowledge, training and skillsets to perform these functions.
Introduced in 1994, Carnegie Mellon’s pioneering Master of Science in Computational Finance (MSCF) is the interdisciplinary collaboration of the Heinz College, the Mathematical Sciences Department, the Department of Statistics, and the Tepper School of Business. It is the close interworking of these four departments that has made the MSCF program the premiere program of its kind.