I will never be a direct participant in a market where the standard round lot is $1 million, but I nonetheless profited from reading *Leveraged Financial Markets: A Comprehensive Guide to High-Yield Bonds, Loans, and Other Instruments *by William F. Maxwell and Mark R. Shenkman (McGraw-Hill, 2010). Contributors analyze the major high-yield products, examine alternative credit risk metrics, and suggest ways to trade and manage high-yield assets. They also take the reader into the fascinating worlds of debtor-in-possession financing and distressed investing.

Today I’m going to look at a single chapter and a single credit model, Moody’s (NYSE:MCO) KMV EDF model, “the most widely used quantitative credit model around the world.” (p. 197) The financial crisis highlighted and called into question the competence of the credit rating agencies. But few of us know how the agencies go about rating the creditworthiness of individual companies.

A full-blown credit review involves both fundamental analysis and credit models. Fundamental analysis can be slow and is by its very nature subjective. Since most investors demand an analysis that is both timely and accurate, “quantitative risk models have gained widespread appeal and are now used to assess credit risk across a broad range of borrowers from large Fortune 500 companies to small businesses and consumers.” (p. 199)

Credit risk models are designed to measure the probability of default. They fall into two categories: accounting-based, such as the Altman Z-score model, and market-based, such as Moody’s KMV (a company Moody’s acquired in 2002) EDF (expected default frequency) model.

The KMV model is grounded in the principle that “a borrower will default if the market value of its assets falls below the value of its debt obligations.” (People who walk away from under-water mortgages exemplify this principle.) The math that informs the model traces its roots to Robert C. Merton’s option pricing model according to which “a borrower’s equity has the same payoff as a call option, where the strike price of the option is equal to the face value of the borrower’s debt.” (p. 201) So the equity will either be worthless or it will be worth the difference between the value of the assets and the debt.

The three main drivers of default are asset value, asset volatility, and leverage. The first two drivers are fairly straightforward, but leverage is something of a catch-all. It includes the maturity profile of a borrower’s liabilities where, as homeowners in the old days knew, “a borrower funded with liquid assets and long-term liabilities can avoid default.” (p. 202) The KMV model incorporates this maturity profile in a basic “default point” equation. Default point = short-term liabilities + 50% of long-term liabilities.

The KMV EDF model then calculates the distance to default, which equals (Market Value of Assets – Default Point) / (Market Value of Assets x Asset Volatility). From there it uses an extensive database of more than 250,000 companies and over 4,700 incidents of default or bankruptcy to map the distance to default to EDFs, “thus generating a cardinal measure of credit risk.” (p. 204)

I suspect that, were we to see the math used in this proprietary model, it would be a lot more sophisticated than the arithmetical description provided here. But at least we now have some idea of how credit rating agencies work.

*Leveraged Financial Markets*provides us with some answers.A full-blown credit review involves both fundamental analysis and credit models. Fundamental analysis can be slow and is by its very nature subjective. Since most investors demand an analysis that is both timely and accurate, “quantitative risk models have gained widespread appeal and are now used to assess credit risk across a broad range of borrowers from large Fortune 500 companies to small businesses and consumers.” (p. 199)

Credit risk models are designed to measure the probability of default. They fall into two categories: accounting-based, such as the Altman Z-score model, and market-based, such as Moody’s KMV (a company Moody’s acquired in 2002) EDF (expected default frequency) model.

The KMV model is grounded in the principle that “a borrower will default if the market value of its assets falls below the value of its debt obligations.” (People who walk away from under-water mortgages exemplify this principle.) The math that informs the model traces its roots to Robert C. Merton’s option pricing model according to which “a borrower’s equity has the same payoff as a call option, where the strike price of the option is equal to the face value of the borrower’s debt.” (p. 201) So the equity will either be worthless or it will be worth the difference between the value of the assets and the debt.

The three main drivers of default are asset value, asset volatility, and leverage. The first two drivers are fairly straightforward, but leverage is something of a catch-all. It includes the maturity profile of a borrower’s liabilities where, as homeowners in the old days knew, “a borrower funded with liquid assets and long-term liabilities can avoid default.” (p. 202) The KMV model incorporates this maturity profile in a basic “default point” equation. Default point = short-term liabilities + 50% of long-term liabilities.

The KMV EDF model then calculates the distance to default, which equals (Market Value of Assets – Default Point) / (Market Value of Assets x Asset Volatility). From there it uses an extensive database of more than 250,000 companies and over 4,700 incidents of default or bankruptcy to map the distance to default to EDFs, “thus generating a cardinal measure of credit risk.” (p. 204)

I suspect that, were we to see the math used in this proprietary model, it would be a lot more sophisticated than the arithmetical description provided here. But at least we now have some idea of how credit rating agencies work.

*Leveraged Financial Markets*is written for investors and managers who want an overview of the high-yield markets. It is broad in scope, yet there is also “meat on the bones.” I think it would be invaluable for anyone thinking about adding leveraged finance to their portfolio or their clients’ portfolios.