Risk Measurement for the Trading Book

This reading is a part of the syllabus for FRM Part 2 Exam in the section 'Market Risk Measurement and Management'.

This report summarises the findings of an ad hoc working group that reviewed the academic literature relevant to the regulatory framework for the trading book. This project was carried out in the first half of 2010 acting upon a request from the Trading Book Group to the Research Task Force of the Basel Committee on Banking Supervision. This report reflects the views of the individual contributing authors and should not be construed as representing specific recommendations or guidance by the Basel Committee for national supervisors or financial institutions.

The report builds on and extends previous work by the Research Task Force on the interaction of market and credit risk (see Basel Committee on Banking Supervision (2009a)). The literature review was complemented by feedback from academic experts at a workshop hosted by the Deutsche Bundesbank in April 2010, and reflects the state of the literature at this point in time. Please note that the term “value-at-risk” (VaR) should be interpreted henceforth in a broad sense as encompassing other common risk metrics, with the exception of Section 3 in which risk metrics are compared directly.

[gview file="http://www.bis.org/publ/bcbs\_wp19.pdf" save=1]

Finance Train Premium
Accelerate your finance career with cutting-edge data skills.
Join Finance Train Premium for unlimited access to a growing library of ebooks, projects and code examples covering financial modeling, data analysis, data science, machine learning, algorithmic trading strategies, and more applied to real-world finance scenarios.
I WANT TO JOIN
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Saylient AI Logo

Accelerate your finance career with cutting-edge data skills.

Join Finance Train Premium for unlimited access to a growing library of ebooks, projects and code examples covering financial modeling, data analysis, data science, machine learning, algorithmic trading strategies, and more applied to real-world finance scenarios.