Marginal, Incremental and Component Value at Risk (VAR)
In the previous articles, we have studied how the value at risk (VaR) models should be used to calculate risks. However, the calculation of risks is not the ultimate end goal. Instead, it is efficient management of this risk that makes the value at risk (VaR) model valuable.
Lets assume that in a particular instance, the value at risk (VaR) model gives a value that is unacceptable to the organization. In such a situation, the organization would ideally have to divest a part of its portfolio in order to reduce the overall risk. Here it will be faced with the question about which part of their portfolio should be divested. Hence, the risk characteristics of sub-portfolios present within the portfolio will have to be measured in order to decide which part should be divested.
Such calculations are done using marginal, incremental, and component value at risk (VaR) models. These models allow the overall risk to be broken into its component parts for the purpose of analysis.
In other words, these models are used to drill down the overall value at risk (VaR) number into its constituent parts. In this article, we will have a closer look at what these statistics are and how they should be interpreted.
Define sub-portfolio: The first step in conducting and kind of drill-down analysis is to clearly define component parts. These component parts are then labeled as sub-portfolios and all the statistical analysis is done at a sub-portfolio level. Different organizations define their sub-portfolios in different ways.
Some organizations define their sub-portfolios at an asset class level. This means that the stocks will be considered to be one sub-portfolio, whereas bonds will be considered another one and derivatives will be considered a third one.
Similarly, it is also possible to define a sub-portfolio at the line of business level. For instance, corporate banking can be considered to be one sub-portfolio, investment banking can be considered to be a second portfolio whereas retail banking can be considered to be the third one.
Once the component parts have been decided, the next step is to break the overall value at risk (VaR) into these components.
- Marginal Value at Risk (VaR): The purpose of marginal value at risk (VaR) is to find out the risk each sub-portfolio is adding to the overall portfolio. Hence, the first step begins by assigning a dollar value to each sub-portfolio.
The next step is to completely eliminate one sub-portfolio and then recalculate the value at risk (VaR).
For instance, if a portfolio consists of stocks, bonds, and derivatives, we can remove derivatives and then calculate the value at risk (VaR) for stocks and bonds. The difference between the two value-at-risk (VaR) numbers will be the VaR for derivatives. This analysis is very useful since it explains how much risk each sub-portfolio is adding to the overall risk. This analysis then becomes the basis for hedging and risk management efforts. The divestment of portfolios is also often done on this basis.
- Component Value at Risk (VaR): The concept of component value at risk (VaR) is linked to the concept of marginal value at risk (VaR). In fact, component value at risk (VaR) can be thought of as being value at risk (VaR) expressed in a dollar amount. The component value at risk (VaR) is calculated by finding the weight of the position being deleted from the overall portfolio.
For instance, if assets worth $250 were being deleted from a $1000 portfolio, then the weight assigned would be 25%. This weight is then multiplied by the marginal value at risk (VaR) and the portfolio value of that position to be deleted.
- Incremental Value at Risk: The incremental value at risk (VaR) method is often confused with the marginal value at risk (VaR) method. However, they are different from one another.
In the case of incremental value at risk (VaR), none of the sub-portfolios are completely eliminated. Instead, small changes are made to the values of these portfolios and the resultant value at risk (VaR) is calculated. There are two methods that are commonly used to calculate the incremental value at risk (VaR).
- The first method is called the full valuation approach. Simply put, this means that the value of the entire portfolio is calculated once again. For instance, it is assumed that the value of the entire portfolio has been increased by 1%. As such, the entire value at risk (VaR) is calculated once again. The newly calculated value at risk (VaR) is then subtracted from the original value at risk (VaR). The residual value is the value of a 1% increment in the portfolio.
- The full valuation method may seem easy to use. However, there are several issues with using this approach. Firstly, the portfolios of large organizations typically consist of hundreds of assets. Hence, calculating the entire value at risk (VaR) again can be tedious and time-consuming. Hence, another method called the approximate solution approach is used. The approximate solution approach is a shortcut method that uses statistical methods to calculate value at risk (VaR) without losing the efficiency.
The purpose of incremental value at risk (VaR) is to explain how much additional risk is added if we increase another unit of the portfolio.
The bottom line is that marginal, component, as well as incremental value at risk (VaR), provide market risk managers with an important tool for understanding the root cause of the market risk. This helps risk managers identify the sub-portfolios which are creating disproportionately high risks and then eliminate them.
|❮❮ Previous||Next ❯❯|
Authorship/Referencing - About the Author(s)
The article is Written By Prachi Juneja and Reviewed By Management Study Guide Content Team. MSG Content Team comprises experienced Faculty Member, Professionals and Subject Matter Experts. We are a ISO 2001:2015 Certified Education Provider. To Know more, click on About Us. The use of this material is free for learning and education purpose. Please reference authorship of content used, including link(s) to ManagementStudyGuide.com and the content page url.
- Risk Management - Introduction
- Benefits of Risk Management
- Principles of Risk Management
- Risk Management Process
- Risk Identification and Assessment
- Aspects of Risk Management
- Steps in Risk Management Process
- Approaches to Risk Management
- Risk Management Policy
- Commonly Used Measures of Risk
- Risk Management Plan
- Evaluation of Risk Management Plan
- Risk Treatment
- Role of HRD in Risk Management
- Enterprise Risk Management
- Implementing ERM
- Risk Management and Stock Market
- Outsourcing Risk Management Program
- Risk Management as a Profession
- Anticipating and Mitigating Organizational Risks in the Digital Age
- Challenges Facing the Australian Economy
- The Economic Costs of MeToo
- Automated Claims Processing
- Challenges in Global Insurance And International Claims
- Conflicts of Interest in the Insurance Business
- The Cost Structure in the Insurance Industry
- How Drones Will Impact the Insurance Industry?
- How Is Health Insurance Funded?
- How Self Driving Cars Impact Insurance?
- How Stock Market Volatility Affects Insurance Companies?
- Insurance Agents vs. Insurance Brokers
- The ABCs of Insurance Fraud in India
- Technological Advances in the Insurance Industry
- The Basics of Unemployment Insurance
- The Pros and Cons of Unemployment Assistance and Why it Matters in the Present Times
- The Role of Insurance In #MeToo Movement
- Why the Flood Insurance Market should be Privatized?
- Basics of Pet Insurance
- Cannabis Insurance
- Challenges Facing Cryptocurrency Insurance
- Evolution of Insurance Regulation
- Food Delivery Apps and Insurance
- How Does Captive Insurance Work?
- On-Demand Insurance
- Reinsurance vs. Double Insurance
- Solvency Regulations in the Insurance Industry
- Terrorism and Insurance
- The Basics of Microinsurance
- The Basics of Reinsurance
- Types of Captive Insurance Companies
- What is P2P Insurance?
- How Risks Affect Companies Providing Financial Services
- Risk Management Information System
- Disadvantages of Risk Management Information Systems
- The Known-Unknown Classification of Risk
- Operational Risk: Definition and Drivers
- How Regulations Have Affected Operational Risk?
- Identification of Operational Risks
- How to Identify Operational Risks
- Using Internal Loss Data to Mitigate Operational Risks
- External Loss Data in Operational Risk Management
- Risk Control Self Assessment (RCSA)
- Scenario Analysis in Risk Management
- Key Risk Indicators
- Basel Approaches in Operational Risk Management
- The Basel Risk Categories
- Cause Categories in Operational Risk Management
- Loss Distribution Approach
- The COSO Framework for Internal Control
- Mistakes to be Avoided While Building a Risk Management System
- Credit Rating Terminology
- Types of Exposures to Determine Credit Limit
- Types of Credit Events
- Active Credit Portfolio Risk Management
- Metrics to Measure Credit Risk
- Credit Derivatives: An Introduction
- Credit Linked Note
- How do Credit Default Swaps Work?
- Why are Credit Default Swaps Dangerous?
- Total Returns Swap
- What are Collateralized Debt Obligations and How do they Work?
- Collateralized Debt Obligations: Advantages and Disadvantages
- Mark To Market Accounting
- What are Recovery Rates? - Different Types of Recovery Rates
- Netting, Close Out, and Acceleration
- Expected Default Frequency (EDF)
- Expected Default Frequency: Advantages and Disadvantages
- Altmans Z Score Model
- Unexpected Loss and Economic Capital Buffer
- Stress Testing in Credit Risk Management
- Provisioning in Credit Risk Management
- How Corporate Governance Impacts Credit Risk
- Exit Strategies In Credit Risk Management
- What is Market Risk? - How its Measured and Sources of Market Risk
- Why is Market Risk Management Important?
- Introduction to Value At Risk (VaR)
- The Three Types of Value at Risk (VaR)
- Marginal, Incremental and Component Value at Risk (VAR)
- How Value at Risk (VaR) is Implemented?
- Backtesting Value at Risk (VaR)
- Advantages of Using Value at Risk (VaR) Model
- Disadvantages of Using the Value at Risk (VaR) Model
- How Margins Are Calculated Using Value at Risk (VaR)
- Market Risk Limits
- Tail Risk
- The Upside of Market Volatility
- Relationship between Volatility and Risk
- Importance of Data Quality in Risk Management
- Impact of Using Poor Quality Data and Metrics to Measure Data Quality
- Enterprise Risk Management (ERM) vs Traditional Risk Management
- Benefits of Enterprise Risk Management
- Corporate Risk Governance
- International Risk Governance Committee (IRGC) Framework
- Failure of Market Risk Management
- Mistakes to Avoid in Risk Management