Expected Default Frequency (EDF)
Expected default frequency (EDF) is an important metric to be considered during the mitigation of credit risk. It is commonly used in many formulas used to predict future credit risks and default rates.
The term expected default frequency (EDF) actually refers to the KMV model which was developed by credit rating agency Moodys. The model is also called the KMV model since it represents the initials of the three researchers who developed the model viz. Kealhofer, McQuown, and Vasicek. In this article, we will understand what the expected default frequency (EDF) model is and how it helps firms make better decisions when it comes to credit risk management.
What is the Expected Default Frequency (EDF) Model?
The expected default frequency (EDF) is a method to gauge the probability that the firm will default on its debts. For the purposes of this model, default is actually defined as the point wherein the market value of all the assets of the firm goes below the outstanding value of the debt obligations that need to be paid. This is in contrast with the other credit risk models wherein the firm is said to be in default if it does not have enough money to make scheduled interest or principal payments.
The results of the expected default frequency (EDF) models are time-specific. The most common time period used in this model is of one year. However, it is not uncommon to use this model with a time horizon as long as 5 years.
The Components of the Expected Default Frequency (EDF) Model
From the above definition of the expected default frequency (EDF) model, it is relatively easy to guess the three components of the model. The three components have been explained below:
Distance To Default
The expected default frequency (EDF) model is used to calculate what is known as distance to default. This is a popular ratio that is known to accurately predict the probability of default.
The distance to default metric is simply derived by dividing the net worth of the firm by its own volatility. Both these values are derived from the market data and hence this is considered to be a superior alternative to other bookish models.
The bottom line is that the expected default frequency (EDF) model is an important arrow in the quiver of any credit analyst. It is important to know and fully understand the results given by this model before making a decision about the mitigation of credit risk of any counterparty.
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