By: Dra. Paula Morales, Dr. Francisco Guijarro and Dr. Janko Hernández

By nature, companies must pay–or be prepared to pay–a price for the goods and services they use in their activities, what ever their area of business. So clearly companies require financial resources in order to make those payments. As we all know, there are three main sources of funding: internal resources generated by the company’s operations, funds contributed by the company’s owners or partners, and funds raised through some form of debt.

Generally, companies take on debt according to the characteristics of the products or services offered, the commercial phase of the business, the type of market in which they operate, legal and tax restrictions, and other factors. According to the rating assigned to the company by a rating agency or credit institution, lenders decide what interest rate must be paid on the loans that will be extended to the company, or what yield at maturity a bond issued by that firm must offer.

Generally speaking, the credit rating determines the opportunity cost of the debt; but many private small and midsize companies that are not listed on a stock exchange do not have the economic capacity to be rated by a specialized agency.

Accordingly, the purpose of this article is to introduce the reader to the types of risk that exist in the economy, focusing particularly on credit risk, which affects the funding cost (or interest rate) of a loan. We will also explain some of the methodologies proposed in the literature for estimating that cost. Finally, we will try to convince company treasurers that these models are viable for application in emerging economies like Mexico, taking into consideration the nature of its business community.

Theoretic Models

Amid an intense pace of globalization among countries in financial markets, and as transactions become increasingly complex, it is indispensable that organizations take risks to survive and prosper. According to Hull (2007), “A risk manager’s job is primarily to take responsibility for understanding the portfolio of risk the company is assuming at a given time, as well as the risk it will assume in the future, so that it can decide if those risks should be considered, and the actions that should be taken.”

Duffie and Singleton (1999) divide the risks facing financial institutions into five categories: (a) market risk, which the risk of unexpected change in prices or rates; (b) credit risk, which the risk of changes in value associated with unexpected changes in credit quality; (c) liquidity risk, which is the risk associated from the cost of adjusting financial positions, which can increase substantially and even jeopardize access to funding; (d) operating risk, which is the risk of fraud, system failures, trading errors, and any other factor internal to the organization; and (e) systemic risk, which is the risk of a drop in market liquidity or reactions in the chain of default.

Risk metrics depend on the time horizon, liquidity-evaluated through company financial statements-and, of course, the state of the economy. Accordingly, risk managers focus on the conditional distribution of profits and current losses, and predicting market values, volatilities and correlations. Basically, credit risk is included in market risk, because the former is a source of the latter. Therefore, this investigation will focus on evaluating credit risk.

The risk of default plays a key role in pricing and hedging credit. Moody’s defines default as follows: (a) a delay in payment; (c) a filing for bankruptcy; and (c) a restructuring of the balance or reduction in payments. The probability of default represents the possibility that the value of assets are below the point of default. Crosbie and Bohn (2003) define the point of default as a firm value somewhere between the amount of the company’s short and long-term liabilities.

For this reason, it is indispensable that firms offer a premium over the risk-free rate (spread), to compensate lenders for this risk of default. The premium should be high if the probability of default is high, and low when the probability of default is low. According to Crosbie and Bohn, these concepts can be combined into a single measurement of default risk called distance to default (DD), which compares net market value with the standard deviation of the annual percentage change in the asset value.

Based on distance to default, we can calculate the probability of default if we know the probability distribution of the company’s assets, or the default rate for a certain distance to default. The most important sources of information for a company to determine its probability of default are its financial statements, the market prices of its debt and its capital stock, and the risk ratings issued by rating agencies. This information is important, because it can be used to formulate projections on the future performance of the company. According to studies by Crosbie and Bohn, market information is a good predictor of estimated probability of default.

Types of Models for Determining Credit Spreads

The models for determining credit spreads are divided basically into statistical, structural and reduced-form. Statistical models, as their name would indicate, are based primarily on statistical and econometric tools, such as simple or multiple regression. Cossin and Pirotte (2001), however, point out that the problem of these models is their complete dependence on historic data, so they project expected default based on past information.

Like the financial options valuation model, credit risk theory is based on financial economics, developed early in the year 1974. Merton (1974) began with a relatively simple model, based on the structure of the firm. That is why these models are called structural models, because they are based on the division of firm value (V) between shareholders and lenders. In brief, the idea is to use the valuation of options to estimate the credit spread associated with the risk of default. With this method, we can analyze and evaluate the impact on credit spreads of changes in asset volatility, interest-rate volatility, different expiration terms, etc.

Cossin y Pirotte (2001) establish that reduced-form models, unlike structural models, work directly with the probability of default, but as an exogenous variable, calibrated on some data; in fact, the name (reduced-form) comes from the reduction of economic credit factors that are behind the probability of default. In these models, the default event is unpredictable, so we assume it behaves as a jump process.

As we can see, it is a little more complex to determine the parameters needed to develop any of the reduced-form models, because this requires an analysis of the default time series of various firms or instruments to determine the transition intensity matrix of default, as well as the average of the jumps. These difficulties are even greater in the case of emerging markets, and particularly for Mexico, because it is much more complicated to empirically determine the parameters required to apply the reduced form models, given the lack of databases, or because private firms or banks do not publish the necessary information.

In order to apply any of the models described in this article, it is indispensable that we know the characteristics of the economy and the efficiency of financial markets. Therefore, we will below briefly analyze the characteristics of the Mexican market in order to evaluate the viability of application of the above-mentioned models.

Characteristics of Mexico’s Business Community

According to Salas-Porras (1992), in Mexico, “there is still a high concentration of capital in a few families, which even today fear losing control of their equity. Even among publicly traded firms, families own at least 60%-70% of the capital stock in most cases. In the United States, on the other hand, a group of major corporations is considered totally controlled by shareholders’ interests if one individual or group of related individuals hold at least 10% of the voting stock, or 5% of the capital stock and have a strong position on the company’s Board of Directors.”

The same author notes that pressing financial needs oblige many companies to go public and to issue stock on domestic and international markets. In Mexico’s case the process of securitization is far behind what we see in industrialized countries, which is not surprising, given the peculiarities of capitalist development in Mexico. At the same time, the Mexican capital market has been stagnating, reflected in a limited number of initial public stock offerings and a decline in the number of stocks listed on the Bolsa. One way to solve the problem of the Mexican stock market is to introduce better corporate governance practices.

Corporate governance is defined as “a set of principles that govern the design, integration and functioning of a company’s governance bodies, like the Board of Directors and its support Committees.” According to a study by Castañeda (1998) into the characteristics of corporate governance among Mexican companies, protection of minority shareholder rights in this country is among the lowest in the world, even below what is found in other Latin American countries like Argentina and Chile.

In fact, comparing the Mexican capital market against its international peers, it seems obvious that it still needs to reach a higher degree of development, and other words, it is not a tremendously efficient market, largely because of the lack of protection for minority shareholders, as well as the heavy concentration of stock in a few hands.

Conclusions

Taking into account the information required to apply structural models, and considering the characteristics of the Mexican securities market, it would be relatively “easy” to use these models in the Mexican economy, because we could use the corporations listed on the Mexican Stock Exchange as a proxy to study small and mid-sized businesses. The companies listed on the stock market have all the elements to apply structural models with no difficulty, since the required factors can be calculated according to stock price time series, risk-free rates, and publicly available financial information. If an unlisted company decides to apply the structural models, it would be necessary to obtain information on comparable listed companies; but one of the difficulties that may arise when applying models in the Mexican market is the lack of efficiency in the financial markets, so it is important to use data that reflect as precisely as possible the characteristics of the firm being analyzed.?

References

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Black, F. y Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy 81. pp. 637-659.

Black, F. y Cox, J. (1976). Valuing corporate securities: Some effects of bond indenture provisions. The Journal of Finance Vol. 31. pp. 351-367.

Castañeda Ramos, G. (1998). La empresa mexicana y su gobierno corporativo. Antecedentes y desafíos para el siglo XXI. México. Alter Ego, S.A. de C.V.

Crosbie, P. y Bohn, J. (2003). Modeling Default Risk-Modeling Methodology. Moody’s KMV Company LLC. pp. 6-31.

Duffie, D. y Singleton, K. (1999). Modeling Term Structures of Defaultable Bonds. The Review of Financial Studies Special. Vol. 12. No. 4. pp. 687-720.

Hull, J.C. (2007). Risk Management and Financial Institutions. Prentice-Hall, Upper Saddle River, New Jersey, first edition, international edition.

Hull, J.C. (2008). Options, Futures and Other Derivates. Prentice-Hall, 7th. edition.

Merton, R. (1974). On Pricing of Corporate Debt: The Risk Structure of Interest Rates. Journal of Finance, 29. pp. 449-470.

Salas-Porras, A. (1992). Globalización y proceso corporativo de los grandes grupos económicos en México. Revista Mexicana de Sociología. Vol. 54. No. 2. pp. 133-162.