Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: After the credit crunch: How much capital is enough?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > After the credit crunch: How much capital is enough?
Data MiningPredictive Analytics

After the credit crunch: How much capital is enough?

DavidMSmith
DavidMSmith
4 Min Read
SHARE
With several large banks in the US and elsewhere effectively insolvent, all banks are now focusing on the question of their economic capital: how much capital must a financial institution have on hand to survive in a worst-case scenario? Naturally, this is an assessment of risk. How, exactly, that risk is calculated is the focus of a white paper by  John Morrison, Solution Architect in Rick Management at Asymptotix. (REvolution Computing also provided support for this white paper.) Obviously, failure to quantify this risk correctly was a major contributor to the credit crunch, in particular the practice of packaging debt into derivatives. Says John:

It is folly to believe that financial innovation which slices exposures into ever more thin slices and thence packages them up into different products to disperse them across a geographic and risk appetite disparate set of counterparties does any more than distribute that risk. It does not fundamentally diminish the rest, Risk is always with us; we either learn the language to describe it (mathematics) and go some way to approximating it or we are not actually in the risk business.

The paper is intensely detailed and supported by myriad …

With several large banks in the US and elsewhere effectively insolvent, all banks are now focusing on the question of their economic capital: how much capital must a financial institution have on hand to survive in a worst-case scenario? Naturally, this is an assessment of risk. How, exactly, that risk is calculated is the focus of a white paper by  John Morrison, Solution Architect in Rick Management at Asymptotix. (REvolution Computing also provided support for this white paper.) Obviously, failure to quantify this risk correctly was a major contributor to the credit crunch, in particular the practice of packaging debt into derivatives. Says John:

It is folly to believe that financial innovation which slices exposures into ever more thin slices and thence packages them up into different products to disperse them across a geographic and risk appetite disparate set of counterparties does any more than distribute that risk. It does not fundamentally diminish the rest, Risk is always with us; we either learn the language to describe it (mathematics) and go some way to approximating it or we are not actually in the risk business.

The paper is intensely detailed and supported by myriad references, and perhaps more suited to those with a background in risk than as an overview of the credit crisis and estimation of economic capital. In section 5.6 is does give some practical steps for using R to implement a stress test for economic capital, so if you’ve thought about using R for risk analysis but needed a good jumping-off point, this might be a good place to start. There are some also some excellent examples of customized R charts used to illustrate concepts in the paper, such as the one shown below.
John Morrison: After the Credit Crunch: The importance of Economic Capital and how to calculate it. (White paper, PDF, 2.3Mb.) John has also provided a detailed reference list for the paper.

Credit default swaps
UK Banks’ Credit Defaut Swap Premia

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

business recovering from data loss
How Data-Driven Businesses Protect MySQL Databases from Shutdown
Big Data Exclusive
ai driven task management
Reducing “Work About Work” with AI Task Managers
Artificial Intelligence Exclusive
data center uptime
Why Rodent-Resistant Conduits Are Critical for Data Center Uptime
Big Data Data Management Exclusive Risk Management
big data and AI
The Intersection of Big Data and AI in Project Management
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Conjoint / Discrete Choice In Segmentation

1 Min Read

Content in Context – Better, Smarter Decisions Powered by Analytics

4 Min Read

E-Government: Out With the Old or In With the New?

4 Min Read

The Analytics of Terrorism

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?