Global Economic Intersection
Advertisement
  • Home
  • Economics
  • Finance
  • Politics
  • Investments
    • Invest in Amazon $250
  • Cryptocurrency
    • Best Bitcoin Accounts
    • Bitcoin Robot
      • Quantum AI
      • Bitcoin Era
      • Bitcoin Aussie System
      • Bitcoin Profit
      • Bitcoin Code
      • eKrona Cryptocurrency
      • Bitcoin Up
      • Bitcoin Prime
      • Yuan Pay Group
      • Immediate Profit
      • BitQH
      • Bitcoin Loophole
      • Crypto Boom
      • Bitcoin Treasure
      • Bitcoin Lucro
      • Bitcoin System
      • Oil Profit
      • The News Spy
      • Bitcoin Buyer
      • Bitcoin Inform
      • Immediate Edge
      • Bitcoin Evolution
      • Cryptohopper
      • Ethereum Trader
      • BitQL
      • Quantum Code
      • Bitcoin Revolution
      • British Trade Platform
      • British Bitcoin Profit
    • Bitcoin Reddit
    • Celebrities
      • Dr. Chris Brown Bitcoin
      • Teeka Tiwari Bitcoin
      • Russell Brand Bitcoin
      • Holly Willoughby Bitcoin
No Result
View All Result
  • Home
  • Economics
  • Finance
  • Politics
  • Investments
    • Invest in Amazon $250
  • Cryptocurrency
    • Best Bitcoin Accounts
    • Bitcoin Robot
      • Quantum AI
      • Bitcoin Era
      • Bitcoin Aussie System
      • Bitcoin Profit
      • Bitcoin Code
      • eKrona Cryptocurrency
      • Bitcoin Up
      • Bitcoin Prime
      • Yuan Pay Group
      • Immediate Profit
      • BitQH
      • Bitcoin Loophole
      • Crypto Boom
      • Bitcoin Treasure
      • Bitcoin Lucro
      • Bitcoin System
      • Oil Profit
      • The News Spy
      • Bitcoin Buyer
      • Bitcoin Inform
      • Immediate Edge
      • Bitcoin Evolution
      • Cryptohopper
      • Ethereum Trader
      • BitQL
      • Quantum Code
      • Bitcoin Revolution
      • British Trade Platform
      • British Bitcoin Profit
    • Bitcoin Reddit
    • Celebrities
      • Dr. Chris Brown Bitcoin
      • Teeka Tiwari Bitcoin
      • Russell Brand Bitcoin
      • Holly Willoughby Bitcoin
No Result
View All Result
Global Economic Intersection
No Result
View All Result

A Top-Down Assessment of the U.S. Banking System

admin by admin
June 4, 2014
in Uncategorized
0
0
SHARES
20
VIEWS
Share on FacebookShare on Twitter

by Meru Bhanot, Beverly Hirtle, Anna Kovner, and James Vickery – Liberty Street Economics, Federal Reserve Bank of New York

Central banks and bank supervisors have increasingly relied on capital stress testing as a supervisory and macroprudential tool. Stress tests have been used by central banks and supervisors to assess the resilience of individual banking companies to adverse macroeconomic and financial market conditions as a way of gauging additional capital needs at individual firms and as a means of assessing the overall capital strength of the banking system. In this post, we describe a framework for assessing the impact of various macroeconomic scenarios on the capital and performance of the U.S. banking system—the Capital and Loss Assessment under Stress Scenarios (CLASS) model—and present some of its key outputs.

Supervisory Stress Testing

In the United States, the first formal supervisory stress tests—the Supervisory Capital Assessment Program (SCAP)—were performed during 2009, and stress tests have since become a permanent supervisory and macroprudential tool through the implementation of the stress test provisions of the Dodd-Frank Act (Dodd-Frank Act Stress Tests, or DFAST) and the Comprehensive Capital Analysis and Review (CCAR). Bank supervisors in Europe conducted coordinated stress tests of the largest European banking companies in 2010 and 2011. Economists at a number of central banks have also constructed system-wide stress test frameworks to assess the robustness of their banking systems to adverse macroeconomic environments and stressed funding conditions.

The CLASS model is a “top-down” model of the U.S. commercial banking industry that generates projections of commercial bank and bank holding company (BHC) income and capital under different macroeconomic scenarios. These projections are based on a set of twenty-two regression models of components of bank income, expense, and loan performance, combined with assumptions about provisioning, dividends, asset growth, and other factors (see the exhibit below). The macroeconomic scenarios are defined by a set of economic and financial market variables—such as GDP growth, the unemployment rate, housing prices, equity prices, short-term and long-term interest rates, and credit spreads—that are likely to affect the profitability of banking institutions. The key outputs of the CLASS model are projections of net income and capital given assumed paths for these economic and financial market variables over the stress test horizon. Following practice in the DFAST and CCAR stress tests, the primary capital metric is Tier 1 common equity, defined as common equity minus the deductions from Tier 1 capital required under U.S. regulatory capital rules.

Structure of the CLASS Model

Why a Top-Down Stress Testing Model?

The CLASS model’s top-down approach is intended to complement more detailed supervisory models of components of bank revenues and expenses, such as those used in the DFAST, CCAR, and European stress tests. Unlike such models, the CLASS model relies only on public information, namely, macroeconomic and financial market data combined with bank and BHC regulatory report filings. The use of regulatory report data allows us to compute projections easily for a much larger number of firms and with greater frequency than is practical using detailed bottom-up analysis using supervisory data collected directly from BHCs. In addition, the CLASS framework is relatively simple to understand, and can produce quarterly income and capital projections quickly (in only a few minutes), given a particular macroeconomic scenario. Thus, it can be used both for simulations and to provide immediate back-of-the-envelope estimates of the effect of a particular macroeconomic shock on the U.S. banking system.

What Does This Model Miss?

Balanced against these advantages, the CLASS model’s top-down approach also has some significant limitations. For example, it ignores many idiosyncratic differences between individual institutions. For this reason, while the model can reasonably be used to model aggregate net income and capital, and the overall distribution of capital across institutions, caution should be exercised in using the model to project the capital of a specific bank or BHC.

How Well Capitalized Is the U.S. Banking System?

The chart below presents one key resiliency measure generated by the CLASS model: the capital “gap,” which captures the systemwide shortfall in capital under stressed economic conditions calibrated relative to a specified threshold capital ratio. The capital gap is an indicator of the U.S. banking system’s vulnerability to undercapitalization, given a particularly stressful macroeconomic scenario. The chart shows the capital gap relative to an 8 percent Tier 1 common capital ratio, assuming a repeat of macroeconomic and financial market conditions experienced during the recent financial crisis (specifically, the period from 2007:Q3 to 2009:Q3). The capital gap figures should be interpreted in relative terms and not as absolute measures of a capital shortfall relative to any specific supervisory capital requirement. The time path of the capital gap shows how the vulnerability to undercapitalization of the U.S. banking system has evolved over time.

These projections suggest that the U.S. banking industry’s vulnerability to undercapitalization has declined not only relative to the financial crisis of 2007-09, but also relative to the period preceding the crisis. The capital gap is approximately $100 billion in 2002, and then rises over time, particularly during 2007 and 2008, reaching a peak of $540 billion in 2008:Q4. This upward trend in the capital gap is reversed from 2009:Q1 onward—the capital gap falls sharply between 2009 and 2013, reflecting equity issuance by firms, lower dividends, and other capital distributions, as well as a return to profitability for most banks and BHCs. The measured capital gap as of 2013:Q3, the final bar in the chart, is $8.4 billion, only about one-tenth of its level in 2002.

Evolution of Capital Gap-chart

Stress Tests and Early Warning Signals

An important policy question is whether stress testing frameworks such as the CLASS model can provide early warning signals of potential undercapitalization in the banking system. Note that the estimated capital gap begins to increase in 2004, well before the onset of the financial crisis. This increase partially reflects growth in the nominal size of the banking system, although this isn’t the main explanation: Between 2004:Q1 and 2007:Q1, banking system assets increase by 33 percent, but the capital gap rises by a much larger 84 percent. This time path of the capital gap implies deterioration in the banking system’s capital adequacy, relative to stressful economic conditions, in the years leading up to the financial crisis.

Of course, these results are generated by applying the actual macroeconomic conditions that occurred during the 2007-09 financial crisis to the banking industry in the years before the crisis, in essence assuming perfect foresight about the risks facing the banking system. Can stress tests provide meaningful early warning signals as the banking system evolves and the risks it faces change? Although this question is difficult to answer, we view the CLASS model results as an encouraging sign about the value of stress testing as a risk management tool for macroprudential policy. In the future, we plan to refine the CLASS model to facilitate additional policy analysis by improving the model estimates for individual banks and BHCs and enhancing the sensitivity of the model to different types of macroeconomic and financial market scenarios. We also plan to explore simplifications to the model that would allow us to run many scenarios very quickly and thus to take a statistical approach to determining the underlying vulnerabilities of the banking system (for example, explore the characteristics of scenarios that generate capital declines in the tail of the distribution, to see what these scenarios have in common). In short, the CLASS model is a living framework that’s expected to develop over time.

Disclaimer

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Source: http://libertystreeteconomics.newyorkfed.org/2014/06/the-class-model-a-top-down-assessment-of-the-us-banking-system.html#.U47_-vldVio


About the Authors

Meru Bhanot is a senior research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

Berverly Hirtle, Federal Reserve Bank of NYBeverly Hirtle is a senior vice president in the Research and Statistics Group.

Anna Kovner, Federal Reserve Bank of NYAnna Kovner is a research officer in the Research and Statistics Group.

James Vickery, Federal Reserve Bank of NYJames Vickery is a senior economist in the Research and Statistics Group.

Previous Post

What We Read Today 04 June 2014

Next Post

Market Commentary: Markets Open Marginally Lower On Not-So-Good US Financial Reporting

Related Posts

Lebron James And Several Other Celebs ‘Effectively Wiped Out’ As Fitness App Tonal Loses 90% Value
Business

Lebron James And Several Other Celebs ‘Effectively Wiped Out’ As Fitness App Tonal Loses 90% Value

by John Wanguba
March 28, 2023
Petrobras Ready To Remain As The Last Oil Producer Standing
Business

Petrobras Ready To Remain As The Last Oil Producer Standing

by John Wanguba
March 28, 2023
What Is The LHINU Crypto And How Does It Work?
Econ Intersect News

What Is The LHINU Crypto And How Does It Work?

by John Wanguba
March 28, 2023
What Is Andrew Tate’s Crypto Investment Portfolio?
Business

What Is Andrew Tate’s Crypto Investment Portfolio?

by John Wanguba
March 27, 2023
US Banks: The Good, The Bad, And The Ugly
Business

US Banks: The Good, The Bad, And The Ugly

by John Wanguba
March 27, 2023
Next Post

Market Commentary: Markets Open Marginally Lower On Not-So-Good US Financial Reporting

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Browse by Category

  • Business
  • Econ Intersect News
  • Economics
  • Finance
  • Politics
  • Uncategorized

Browse by Tags

adoption altcoins bank banking banks Binance Bitcoin Bitcoin adoption Bitcoin market Bitcoin mining blockchain BTC business China crypto crypto adoption cryptocurrency crypto exchange crypto market crypto regulation decentralized finance DeFi Elon Musk ETH Ethereum Europe FTX inflation investment market analysis Metaverse mining NFT nonfungible tokens oil market price analysis recession regulation Russia stock market technology Tesla the UK the US Twitter

Archives

  • March 2023
  • February 2023
  • January 2023
  • December 2022
  • November 2022
  • October 2022
  • September 2022
  • August 2022
  • July 2022
  • June 2022
  • May 2022
  • April 2022
  • March 2022
  • February 2022
  • January 2022
  • December 2021
  • November 2021
  • October 2021
  • September 2021
  • August 2021
  • July 2021
  • June 2021
  • May 2021
  • April 2021
  • March 2021
  • February 2021
  • January 2021
  • December 2020
  • November 2020
  • October 2020
  • September 2020
  • August 2020
  • July 2020
  • June 2020
  • May 2020
  • April 2020
  • March 2020
  • February 2020
  • January 2020
  • December 2019
  • November 2019
  • October 2019
  • September 2019
  • August 2019
  • July 2019
  • June 2019
  • May 2019
  • April 2019
  • March 2019
  • February 2019
  • January 2019
  • December 2018
  • November 2018
  • October 2018
  • September 2018
  • August 2018
  • July 2018
  • June 2018
  • May 2018
  • April 2018
  • March 2018
  • February 2018
  • January 2018
  • December 2017
  • November 2017
  • October 2017
  • September 2017
  • August 2017
  • July 2017
  • June 2017
  • May 2017
  • April 2017
  • March 2017
  • February 2017
  • January 2017
  • December 2016
  • November 2016
  • October 2016
  • September 2016
  • August 2016
  • July 2016
  • June 2016
  • May 2016
  • April 2016
  • March 2016
  • February 2016
  • January 2016
  • December 2015
  • November 2015
  • October 2015
  • September 2015
  • August 2015
  • July 2015
  • June 2015
  • May 2015
  • April 2015
  • March 2015
  • February 2015
  • January 2015
  • December 2014
  • November 2014
  • October 2014
  • September 2014
  • August 2014
  • July 2014
  • June 2014
  • May 2014
  • April 2014
  • March 2014
  • February 2014
  • January 2014
  • December 2013
  • November 2013
  • October 2013
  • September 2013
  • August 2013
  • July 2013
  • June 2013
  • May 2013
  • April 2013
  • March 2013
  • February 2013
  • January 2013
  • December 2012
  • November 2012
  • October 2012
  • September 2012
  • August 2012
  • July 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • May 2011
  • April 2011
  • March 2011
  • February 2011
  • January 2011
  • December 2010
  • August 2010
  • August 2009

Categories

  • Business
  • Econ Intersect News
  • Economics
  • Finance
  • Politics
  • Uncategorized
Global Economic Intersection

After nearly 11 years of 24/7/365 operation, Global Economic Intersection co-founders Steven Hansen and John Lounsbury are retiring. The new owner, a global media company in London, is in the process of completing the set-up of Global Economic Intersection files in their system and publishing platform. The official website ownership transfer took place on 24 August.

Categories

  • Business
  • Econ Intersect News
  • Economics
  • Finance
  • Politics
  • Uncategorized

Recent Posts

  • Lebron James And Several Other Celebs ‘Effectively Wiped Out’ As Fitness App Tonal Loses 90% Value
  • Petrobras Ready To Remain As The Last Oil Producer Standing
  • What Is The LHINU Crypto And How Does It Work?

© Copyright 2021 EconIntersect - Economic news, analysis and opinion.

No Result
View All Result
  • Home
  • Contact Us
  • Bitcoin Robot
    • Bitcoin Profit
    • Bitcoin Code
    • Quantum AI
    • eKrona Cryptocurrency
    • Bitcoin Up
    • Bitcoin Prime
    • Yuan Pay Group
    • Immediate Profit
    • BitIQ
    • Bitcoin Loophole
    • Crypto Boom
    • Bitcoin Era
    • Bitcoin Treasure
    • Bitcoin Lucro
    • Bitcoin System
    • Oil Profit
    • The News Spy
    • British Bitcoin Profit
    • Bitcoin Trader
  • Bitcoin Reddit

© Copyright 2021 EconIntersect - Economic news, analysis and opinion.

en English
ar Arabicbg Bulgarianda Danishnl Dutchen Englishfi Finnishfr Frenchde Germanel Greekit Italianja Japaneselv Latvianno Norwegianpl Polishpt Portuguesero Romanianes Spanishsv Swedish