Mapping Heat In The U.S. Financial System by Federal Reserve
Aikman, David, Michael T. Kiley, Seung Jung Lee, Michael G. Palumbo, and Missaka N. Warusawitharana (2015)
Finance and Economics Discussion Series 2015-059. Washington: Board of Governors of the Federal Reserve System
Q2 Hedge Funds Resource Page Now LIVE!!! Lives, Conferences, Slides And More [UPDATED 7/12]
Simply click the menu below to perform sorting functions. This page was just created on 7/1/2020 we will be updating it on a very frequent basis over the next three months (usually at LEAST daily), please come back or bookmark the page. As always we REALLY really appreciate legal letters and tips on hedge funds Read More
We provide a framework for assessing the build-up of vulnerabilities to the U.S. financial system. We collect forty-four indicators of financial and balance-sheet conditions, cutting across measures of valuation pressures, nonfinancial borrowing, and financial-sector health. We place the data in economic categories, track their evolution, and develop an algorithmic approach to monitoring vulnerabilities that can complement the more judgmental approach of most official-sector organizations. Our approach picks up rising imbalances in the U.S. financial system through the mid-2000s, presaging the financial crisis. We also highlight several statistical properties of our approach: most importantly, our summary measures of system-wide vulnerabilities lead the credit-to-GDP gap (a key gauge in Basel III and related research) by a year or more. Thus, our framework may provide useful information for setting macroprudential policy tools such as the countercyclical capital buffer.
The theory developed here argues that the structural characteristics of the financial system change during periods of prolonged expansion and economic boom and that these changes cumulate to decrease the domain of stability of the system. Thus, after an expansion has been in progress for some time, an event that is not unusual size or duration can trigger a sharp financial reaction.
– Hyman P. Minsky
Mapping Heat In The U.S. Financial System – Introduction
The monitoring of risks to financial stability has become an issue of first-order importance for banking supervisors and monetary authorities around the world. Such efforts are crucial to mitigating threats to financial stability through macroprudential tools or other policy actions. In this analysis, we propose a method for summarizing the information in a wide array of indicators to highlight financial stability risks in the U.S. economy. Our framework is intended to capture the build-up of vulnerabilities in the financial system that can contribute to the amplification of economic and financial shocks.
Our analysis pulls together a wide range of indicators to inform an assessment of the extent of vulnerabilities in the financial system, reflecting the view that no single data series is appropriate for gauging the build-up of risks in a complex and evolving financial system. The indicators we choose for our analysis are drawn from an extensive literature (e.g., Cecchetti, 2008; BIS, 2010; Schularick and Taylor, 2012; Krishnamurthy and Vissing-Jorgenson, 2013; and Drehmann et al, 2014). Overall, we gather and synthesize data on forty-four indicators. Following the framework of Adrian, Covitz, and Liang (2013), we group these indicators into three broad classes of vulnerability: investor risk appetite in asset markets, nonfinancial sector imbalances, and financial sector vulnerabilities linked to leverage and maturity transformation.
In practical terms, we face challenges related to how to aggregate indicators along such varying dimensions of financial activity. Our approach is to define narrow sets of indicators (subsequently referred to as components) along well-defined economic concepts. Within the risk appetite category of vulnerabilities, the component measures we focus on include equity valuations, volatility, and pricing and lending standards in corporate credit markets, housing, and commercial real estate. For the nonfinancial sector (households and nonfinancial businesses) imbalances category, we consider the degree of borrowing and debt service burden associated with business credit, mortgage borrowing, and consumer credit, as well as the sector’s net savings. Within the financial sector (banks and shadow banks) category of vulnerabilities, we consider the sector’s leverage, maturity transformation, reliance on short-term funding, and size/interconnectedness.
We use data visualization tools to explore patterns in the data and inform subsequent statistical analysis.3 Building on what we see an emerging interest in data visualization (for example, see IMF, 2014), we illustrate the use of “circular” or polar-coordinate charts – emphasizing a radar chart – to provide a detailed comparison across a few specific time periods. In addition, we use “ribbon” heat maps to examine the time-series variation in our components more comprehensively. These tools may be helpful in communicating financial stability conditions to a broad audience and facilitating the deliberation of countercyclical macroprudential tools by policymakers.
Our analysis provides a lens through which to view historical patterns of vulnerability in the U.S. financial system. Risk appetite was elevated in some areas in the late 1990s, most particularly in equity and business credit markets, but also, to some extent, in the housing market (Case, Quigley and Shiller 2005). But household borrowing was muted at that time, despite a low saving rate, and leverage in the financial sector was notably below levels that would prevail by the mid-2000s. By 2004, however, risk appetite was elevated everywhere except for equity markets, while mortgage-related imbalances were growing rapidly as was financial sector leverage and its reliance on short-term wholesale funding. This resulted in sizeable system-wide vulnerabilities that signaled substantial potential for the kind of amplification and transmission of shocks observed in the subsequent financial crisis.
See full PDF below.