Computational Economics and Financial Systems Lab (CEFS)

Economic and business system, have become highly instrumented in recent years. As a result, there is a tremendous amount of data available, yet the complexity of such systems has made them difficult to effectively model and control. Examples of such systems include:

  • International Markets
    • New York Stock Exchange
    • Capital Markets
  • Local Markets
    • BYU Bookstore Retail
    • Housing Markets

The CEFS develops methods for using accessible data to compute operational policies, such as pricing, promotion, inventory management, portfolio optimization, etc. These policies are then tested on novel learning platforms developed at IDeA Labs, such as our Retail Laboratory and Tour de France virtual fund management system.

Laboratory Platforms:


Demand Forecasting

Predictive modeling is essential for rational decision making, since understanding the consequences of various options is the first step toward choosing between them. Merchants need such models to understand how pricing and other decisions will impact revenue generated in their respective markets. This project details known algorithms for using a finite record of sales data to generate predictive models and forecast demand.

Retail Laboratory

Laboratories are widely available for biology, chemistry, and physics. This project develops the blueprints for, and implements, the first-of-its-kind economic laboratory for retail. We begin by making the subtle but important distinction between a laboratory, that uses controlled experimentation to generate new data about a phenomenon, and data processing algorithms that mine warehoused data for understanding. Every merchandising and marketing decision is based explicitly or implicitly on a model, or expectations, of how the market will react; the purpose of a laboratory is to verify that this model is good enough to make the proposed decisions worthwhile. We draw on the feedback structure of retail, between a firm and its market, to develop a concrete invalidation protocol, or marketing process, that allows decision makers to implement their ideas in a way that ensures errors in judgment become clear before they damage the enterprise. A prototype of these ideas is then executed at the on-campus retailer, the BYU Bookstore, to demonstrate their utility on a live retail operation; our retail laboratory is a real, functioning venture. Partners on the project include the Data Mining Laboratory at BYU.