25 years: Treasury & ALM
Any transaction undertaken by a bank carries an element of risk. Value-at-risk, or VaR, quantifies the probability of loss to a dollar value. Moorad shows how this is achieved using the variance-covariance method.
Any transaction undertaken by a bank carries an element of risk. Value-at-risk, or VaR, quantifies the probability of loss to a dollar value. Moorad shows how this is achieved using the variance-covariance method.
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15 mins 25 secs
Value-at-Risk (VaR) is a methodology used to estimate the risk exposure of assets such as equities, bonds, or loans, within a specific time horizon and confidence level. VaR measures the volatility of the change in value of a bank’s specified balance sheet assets, and so the greater the volatility, the higher the probability of loss. It quantifies the potential loss in market value of a portfolio. The different VaR methodologies are correlation method, historical simulation method, and the Monte Carlo simulation method. To calculate the VaR using the variance-covariance method, you need to determine the time horizon over which the firm wishes to estimate a potential loss, select the confidence level, create a probability distribution of likely returns for the relevant investment, and then finally calculate the VaR estimate.
Key learning objectives:
Define VaR
Outline the main VaR methodologies
Learn how to calculate VaR using the variance-covariance method
This content is also available as part of a premium, accredited video course. Sign up for a 14-day trial to watch for free.
This content is also available as part of a premium, accredited video course. Sign up for a 14-day trial to watch for free.