Information sharing and financial market regulation

Abstract

In testimony on April of 2012 before the House Financial Services Committee, U.S. Securities and Exchange Commission (SEC) Chairman, Mary Schapiro, stated that effective information sharing between financial market actors and their regulatory bodies is critical to fulfilling the regulatory obligations of the SEC. The 2008 financial crisis is recognized as a show case for the risks to the stability of the markets that ineffective information sharing among supervisory authorities represents. This paper constitutes a preliminary exploration of the challenges facing financial regulators building on prior research in the computing and information science community (CIS). Current literature as well as data from a recent study of financial market regulation is used to identify key actors in financial market regulation information sharing relationships and to begin to outline the challenges faced in this unique context and the resulting risk if those challenges go unaddressed. A recently developed theoretical framework for cross-boundary information sharing (Garcia et al 2007) is used to present insights about challenges and risks from the literature and the field.

Information Sharing in the Regulatory Context

“…These challenges are not mutually exclusive and include issues of disclosure, proprietary information, and security of trade-secret information and so forth [24]. For public and private sector entities to work together and share information new understanding of each partner's IS capability is required [26]. Furthermore, there is a need to better understand the value and risk associated with certain types of information shared for specific purposes.…”

An Associative Analysis Method to Estimate Impact between Financial Market Risk and Macroeconomic Risk

“…Therefore, this study builds upon existing research and considers the complexity of financial risk, macroeconomic risk, and their interactive behavior [6]. It attempts to construct financial stress index and macroeconomic risk index and adopts the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to systematically analyze the dynamic interactions between financial risk and macroeconomic risk from a time-varying perspective [7][8].…”