Quantitative Analytics in Debt Valuation & Management

By Mark Guthner

A breakthrough methodology for profiting in the high-yield and distressed debt market

Global advances in technology give investors and asset managers more information at their fingertips than ever before. With Quantitative Analytics in Debt Valuation and Management, you can join the elite club of quantitative investors who know how to use that information to beat the market and their competitors.

This powerful guide shows you how to sharpen your analytical process by considering valuable information hidden in the prices of related assets. Quantitative Analytics in Debt Valuation and Management reveals a progressive framework incorporating debt valuation based on the interrelationships among the equity, bond, and options markets. Using this cutting-edge method in conjunction with traditional debt and equity analysis, you will reduce portfolio risk, find assets with the highest returns, and generate dramatically greater profits from your transactions.

This book’s “fat-free” presentation and easy-to-navigate format jump-starts busy professionals on their way to mastering proven techniques to:

• Determine the “equity risk” inherent in corporate debt to establish the causal relationship between a company’s debt, equity, and asset values
• Price and analyze corporate debt in real time by going beyond traditional methods for computing capital requirements and anticipated losses
• Look with an insider’s eye at risk management challenges facing banks, hedge funds, and other institutions operating with financial leverage
• Avoid the mistakes of other investors who contribute to the systemic risk in the financial system

Additionally, you will be well prepared for the real world with the book’s focus on practical application and clear case studies. Step-by-step, you will see how to improve bond pricing and hedge debt with equity, and how selected investment management strategies perform when the model is used to drive decision making.

• Language: English
• Publisher: McGraw-Hill Education
• Release date: May 21, 2012
• ISBN: 9780071790628

Book preview

Index

Introduction

The art of investing, be it for institutions or for individuals, is an extraordinarily difficult process. Thousands of books have been written over the decades suggesting optimal investment processes and themes designed to produce high rates of return. Buy stocks of companies with low price-to-earnings ratios, high growth rates, high free cash flows, or good management—all these are but a few of the strategies followed in the equity arena. Buy investment-grade bonds for safety, high-yield bonds for growth and income, short-term bonds for stability, or long-term bonds for capital appreciation—all these are but a few of the choices in the fixed-income arena. Buy real estate for growth and income, commodities for inflation protection, and investments denominated in foreign currencies for their return potential or diversification benefits. Use leverage to amplify returns or never use leverage to minimize risk. These are all strategies promoted from time to time. Buy and hold while being fully invested and ride the fluctuations of the market, always hold some cash and buy on dips, and dollar cost averaging are but a few of the macro decisions one must make. The multitude of choices and analytical methods creates complexity.

There are many radio and television shows, and newspaper columns and magazines dedicated to educating investors. Financial institutions publish research to both educate and sell investment products and services. The flow of information is often conflicting and therefore confusing. The big challenge for investors is to distinguish between information that is germane and information that is superfluous. Once the distinction is identified, the dilemma is how the investor should interpret and analyze the information. This all goes on as one publication says buy, another says sell, and a television personality says hold.

Emotions take their toll as well. Many people knowingly or unknowingly buy what others buy and sell what others sell because it is emotionally satisfying. There are times when going along with the crowd is the right thing to do, and there are other times when it is a disaster. Successful decision making under uncertainty requires a strict discipline that is independent of what other investors are doing. The best investors stick to their methods and look for opportunities where the odds are in their favor. Some judge the odds quantitatively, whereas others do so by judgment and experience.

By reading this book, you join a club of quantitative investors wishing to use technology to improve the investment decision-making process. By employing the model presented herein, in conjunction with traditional, time-tested methods of debt and equity analysis, the sophisticated investor will be able to identify assets with higher potential returns and reduce portfolio risk, leading to more robust investment outcomes. It is a rare day when one reads a book about new techniques employed by expert professional investors to beat the market and their competition. While the target audience for this book is sophisticated investors willing to add new depth to their decision-making process, individual investors may gain some insight into the market for credit-risky debt.

I started out in the investment business as a quantitative research analyst looking for better ways to maximize return for institutional investors while hedging their pension or annuity liabilities. Growing surplus (the difference between the market value of assets and liabilities) was the name of the game. As my employer grew, opportunities to manage fixed-income portfolios arose, and I found myself trading bonds, managing portfolios, and marketing my employer’s services. Two years into managing institutional assets, one of the holdings in one of the portfolios under my care suffered a default. The day before the company defaulted, the bond enjoyed a low investment-grade rating of Baa3/BBB—by Moody’s and Standard & Poor’s, respectively. Needless to say, I was quite surprised when the company announced a bankruptcy filing. Before making the investment decision, I did the credit analysis and had a good handle on the collateral committed by the borrower against the bond held. I ultimately recovered 100 percent of the investment with interest. My client, nonetheless, was quite unhappy, and I learned a valuable lesson about the risk tolerance of institutional, investment-grade, fixed-income investors. There is nothing like a mistake to focus the mind, and I began to look at credit analysis with an eye toward the probability that a company might go under or simply suffer a downgrade in credit quality. Thinking back, the equity market was signaling financial distress far more than a Baa3/BBB—rating and traditional credit analysis would suggest. Through this experience, I began to develop the view that one can use equity analysis to improve on credit analysis. Companies with growing earnings are likely to see their share prices rise. Should the company not recapitalize or experience a critical event, the company is likely to de-lever and enjoy higher cash flow available for debt service, and the credit rating of the company’s debt should improve. In short, a rising share price often signals falling credit risk. This begs the question, How one can extract information from the equity markets to improve the credit analysis process and improve the accuracy of debt valuation? and, Can signals from equity markets help fixed-income investors avoid the potential of unexpected outcomes based on traditional analytical methods? and, Can one quantify the analysis?

Years later, my professional career turned from the public bond market to the origination, syndication, and trading in the bank and private debt markets. Without price histories readily available or comparable bonds of the issuer outstanding, the pricing decision was more challenging. At that time, bank capital regulations were in flux, and the Basel II capital rules were taking shape. Basel II presents a quantitative, risk-based method of pricing loans and bonds based on historical default and recovery factors that drive expected credit losses, and economic capital requirements for bank or bond portfolios. This opened my eyes to more sophisticated methods of pricing credit-risky bonds and determining prudent levels of financial leverage at financial institutions.

The Basel II approach builds on traditional credit analysis by incorporating credit-event statistics. While this approach makes strides toward better loan pricing and quantification of risk, it depends at least in part on credit ratings and historical experience. This is where the battle begins. Loan officers and front-line credit analysts make loans to customers whom they believe to be good credit risks. They may rate a customer the equivalent of agency ratings of A2/A and price a loan accordingly. Credit risk managers apply a more skeptical eye to loan transactions and often assign ratings below those expressed by the deal team. They may believe that the loan under review should carry a rating of Baa2/BBB.

With a BBB rating, the loan would demand a higher yield than the A-rated loan, making the borrower unhappy and potentially pricing the loan out of the market. To complicate matters still further, potential buyers of the syndicated loan may have another idea of the appropriate rating for the loan. In the end, rating and pricing were issues of discussion and negotiation, not a pure science. Such is the nature of traditional credit analysis and the loan origination process.

Relying on credit ratings does have its problems. For the 10+ years leading up to the 2008 credit crisis, investment banks packaged loans into large pools. Investors did not necessarily want the pools as constructed. Some wanted pools with higher credit quality for safety, whereas others were prepared to accept higher risk for the potential of earning a higher rate of return. Still others wanted shorter maturities to match their investment horizons, whereas others wanted longer maturities to lock in yields for an extended period.

The collateralized debt obligation (CDO) market was developed, at least in part, to address market needs. Investment banks would break the loan pools into smaller pieces called tranches. The so-called equity tranche absorbs credit losses first. The assigned ratings for these tranches fall into the NR (not rated) to CCC to B range. These securities pay a high nominal yield to compensate for taking the first loss risk, and realized returns generally are much less. Those that absorb the second losses capture a rating in the B to A range and pay a lower nominal yield because they are protected by the first-loss tranches. Those at the end of the line enjoy an AA to AAA rating and pay an even lower yield because they have additional layers of protection. Some CDOs have 8 to 10 tranches, whereas more complicated ones may have 20 to 30 tranches or even more.

The concept of a CDO is sound in theory, and the construction of CDOs is relatively straightforward. However, the analysis from an investor’s perspective is a huge challenge in application. A proper analysis of each CDO tranche starts with an in-depth analysis of each loan in the underlying pool to estimate the potential for default and an expected recovery rate should the borrower default. The second step entails an analysis of correlation. Are defaults likely to be a one-off or a series of one-offs, or will many loans default from a common cause? In a diversified pool of well-understood loans, the A- to AAA-rated tranches have real protection. If diversification is poor (i.e., correlation is high), the senior tranches are vulnerable. In the event one loan fails, high correlation suggests that many loans will fail. To do this analysis properly, one must bring a high level of computational power to bear.

The 2008 experience was a double whammy. Investors underestimated the risks of the underlying loans in most CDOs, and they underestimated the default correlation between loans as well. This was particularly true for mortgage CDOs, which simply held a large number of home or commercial real estate mortgages. This resulted in ratings on CDOs that were too high and disconnected from reality. The ratings on individual mortgages were too high, and all the loans came from the same sector of the loan market. The argument that a portfolio of 1,000+ mortgage loans created diversification proved inaccurate. Investors who relied on these ratings found out the hard way that they were taking more risk than the ratings implied. Many of the AA- and AAA-rated tranches now suffer ratings well below investment grade, and many of the support tranches pay no interest at all and have all but gone away. Such is the pitfall of relying purely on a third-party ratings–based system and not doing your own homework.

Years later, while working as an equity and equity derivatives analyst/strategist, I noticed that there was little communication between debt and equity market participants. The investment industry traditionally has organized itself by asset class. Investment management firms have equity managers, fixed-income managers, real estate managers, and so on. The funds they manage have a distinct focus in terms of their investment-opportunity set.

It is quite rare for an equity expert to also be a fixed-income expert, and vice versa. As a result, few managers seek out value in asset classes beyond their primary focus. The same is true for the sell side of the investment industry. Broker-dealers have separate equity and bond departments. Fixed-income analysts focus on company debt levels, collateral, liquidation values, cash flow, and so on to assess a company’s ability to service its debt. Equity analysts focus on growth opportunities, cash flow, sum-of-the-parts breakup value, and so on. While the analyses share common ground, organizational structure, reporting lines, and compensation arrangements generally do not encourage cross-pollination between these two groups. Communication between the sales and trading department of the debt and equity groups tends to be equally void for similar reasons.

Equity managers and bond investors generally pursue differing mandates. Equity managers look for opportunities to grow assets and are willing to risk the loss of capital to do so. Over the long term, the goal is to grow purchasing power (i.e., earn an after-tax rate of return that exceeds the rate of inflation). Equity managers are more focused on the upside potential of their investments because their goal is to grow assets. Fixed-income managers focus on the opposite side of the return distribution. They generally have a mandate of capital preservation as the primary objective, whereas capital appreciation is a secondary objective.

Since equity managers look at companies from a growth point of view and fixed-income managers examine companies with downside risk in mind, it is natural to assume that participants in these markets will have differing opinions about the investment merits of a company and its securities. They are, however, looking at the same companies. The equity manager may see great growth opportunities for a company and may buy shares of that company. The fixed-income manager may see a high potential for disaster should the company fail in its growth plans and may avoid or be a seller of that company’s debt securities. The buy/sell transactions of these traders and portfolio managers send signals to the marketplace concerning the value of the securities transacted and the value of the underlying firm’s assets. In such a circumstance, the equity securities of the company may trade at a premium in the marketplace, whereas the debt securities simultaneously may trade at a discount.

This institutional structure reveals the underlying compartmentalization of markets. Even within the equity markets, there can be compartmentalization. Equity derivative traders tend to be more concerned with volatility of stock prices than with direction. Many focus only on volatility, comparing historical realized volatility relative to the implied volatility imbedded in option prices. Underlying fundamentals that drive that volatility often are a consideration, but technical conditions often garner a heavier weight. Volatility analysis tends to the short term in nature and focuses on catalysts or the lack thereof.

Traditional fundamental analysis focuses on growth opportunities and longer-term valuation. The compartmentalization between these related markets owing to differences in investment horizon and analytical methods may result in different opinions. Compartmentalization results in information voids between all these markets. This begs the question, What can the bond investor learn from the stock and options market? What can the equity investor learn from the bond market?

Debt, equity, and volatility (i.e., option) markets all have a voice in the valuation of company assets. As a result, one would think that there is value to extract by integrating these opinions and market signals. Bond managers may want to incorporate the view of the equity market with its traditional credit analysis to improve the buy/sell decision-making process for individual securities. They may be able to improve portfolio composition as well. The pricing of equity options may signal the potential for a one-off event such as a leveraged buyout (LBO) or management takeover, which could damage the valuation of their debt holdings. The compartmentalization of markets creates an opportunity for the manager who trades across asset classes. The arbitrageur may buy the debt securities and sell the equity security (or buy put options or sell call options) of the same firm, as a hedge against a drop in credit quality and value of the debt securities. This is the essence of capital structure hedging and arbitrage.

This book explores a framework that establishes debt valuation based on the interrelationships among the equity, bond, and volatility markets. It will start with a method for estimating an absolute value of debt securities based on traditional credit analysis and an EVA (economic value added) framework. It will go on to examine debt-valuation implications that draw from the equity and equity option markets. Fisher Black and Myron Scholes won Nobel prizes for their work deriving a closed-form solution to the options-pricing problem. Robert C. Merton also won a Nobel prize for his work on equity options and the idea that equity is simply a call option of the value of a firm’s assets. The model presented incorporates the work of these giants with modification to connect debt, equity, and asset valuation. For clarity, the discussion will present and develop the concepts through a generic example to show how one can employ this method to improve bond pricing or to hedge debt with equity. In addition, the model will be applied to historical data to show how various investment-management strategies would perform by using the model to drive various decision-making rules. Finally, the model has more to offer than simply securities pricing. It also provides analytics surrounding some risk-management issues applicable to banks and hedge funds that operate with financial leverage. This answers the question, How much leverage is appropriate to maximize returns while minimizing the risk of a marginal call or default?

While this book focuses on a quantitative method of credit analytics, the objective is not to replace the existing time-tested methods of credit or equity analysis. Rather, the goal of this book is to introduce a new device to the asset-management toolbox. In this way, professional managers can improve returns, reduce risk, and avoid the kinds of mistakes that make investors a victim of or contributor to systemic risk to the financial system.

Chapter 1

Traditional Techniques in Credit Analysis

Investors who make loans or buy debt securities understand that they are taking on a host of risks in pursuit of maximizing returns on their investments. Most loans will pay off with interest, whereas a few will not. An assessment of those risks is critical to determining an appropriate rate of interest to charge when making a loan or what yield to maturity to demand when purchasing a bond as compensation for the risks taken. These risks fall into three broad categories—market risk, company-specific risk, and political risk. The following is an explanation of these key risks:

• Market risk. There are a number of components of market risk that are endemic to the entire economy. Diversification will not eliminate or reduce this risk. The following is a detailed listing of the components of market risk:

Interest-rate risk. A loan typically locks in a rate of interest the borrower must pay to the lender over a predefined period. If the general level of interest rates rises after a loan closes, the pricing of new loans will incorporate those higher rates. The value of old loans written at lower rates will fall, raising their yield to maturity to reflect the new market conditions. This puts the old loans with lower coupons on par with a new loan paying a higher coupon. This is interest-rate risk.

Inflation risk. The purchasing power of currency changes over time. When making a loan, one exchanges currency today for currency in the future and an interest payment along the way. In so doing, the lender takes the risk that the purchasing power of the currency returned in the future will be less than it was on the day the loan closed. Interest-rate and inflation risk are related. When inflation is high, investors will demand a high rate of interest to compensate for the depreciating future value of the currency. In this way, the investor earns more currency to compensate for the fact that the purchasing power of each currency unit will fall in the future.

Liquidity risk. There are times when an investor will need to sell an investment to raise cash. A mutual fund may have redemptions by its individual investors, depositors at a bank may withdraw funds, and an insurance company may have to pay claims following a natural disaster, for example. In such circumstances, the owner of securities will need to work with a broker to find another investor who is interested in purchasing the securities the owner wishes to sell. The owner of an investment may not be able to sell the asset quickly at its fair value when the need arises because buyers for that particular investment may be scarce. The owner of the investment may need to discount the price of the investment and suffer a loss in value to close a sale. This is liquidity risk.

Call risk. Some loans allow the borrower to repay the loan before the maturity date. If interest rates fall, the borrower may find it advantageous to refinance by calling the loan and taking out a new one at the lower prevailing rates. Under these circumstances, the lender gets his or her money back but will have to reinvest the proceeds at lower rates, lowering his or her expected future rate of return. In addition, the lender may have to reinvest at an even lower rate than the drop in the general interest rate because market risk premiums may be lower, resulting in lower credit spreads. Furthermore, the lender may not be able to find lending opportunities at the same level of risk, forcing him or her to write a loan to a higher-quality borrower at a lower rate of interest that is below his or her target rate of return. Alternatively, the lender may have to lend to a higher-risk borrower at a higher rate of interest but at a risk level that is higher than he or she desires. This is call risk.

Reinvestment risk. Reinvestment risk has similar characteristics to call risk, just smaller. As a borrower pays interest on his or her loan, the lender will have to reinvest those funds at the prevailing interest rate. Should the general level of interest rates and risk premiums fall after loan origination, the lender may not be able to reinvest coupon payments at the same rate with the same level of risk as the original loan. In short, the lender may have to reinvest at a lower yield for all the same reasons associated with call risk. This is reinvestment risk.

Risk premiums. Risky assets require a higher rate of return to compensate the investor for fluctuations in the market value of an investment and the risk of permanent loss. Risk premiums fluctuate continuously, and this affects the valuation of all risky assets. In the case of fixed-income investments, changes in the market risk premium change the credit spread borrowers will have to pay for new loans and change the value of debt instruments already in place.

• Company-specific or unique risk. This is risk associated with a particular company or security. Since this type of risk is inherent to a particular investment and not shared by all investments, diversification will manage and reduce unique risk. The following is a listing of the key elements of company-specific or unique risk:

Credit risk. Broadly defined, credit risk represents the probability that a borrower may not be able to repay principal and interest as promised. When this occurs, the lender generally loses money. Credit risk consists of two key unknowns: (1) the probability of a default occurring and (2) the amount the lender will recover in a default scenario. Credit risk is not a static risk. After a loan origination, the financial condition of the borrower may decline for a whole host of reasons. It is important to note that the owner of the loan does not have to sell the bond to suffer a loss. The higher risk reduces the value of the loan on a mark-to-market basis. When the lower market price of the loan is accepted, the value lost is recognized. It is certainly possible that the fortunes of the borrower might improve causing the loss to diminish. Alternatively, the loss may be recovered as the loan ages and is eventually repaid. Even though the risk is higher, the borrower still may be able to honor the terms of the lending agreement. Therefore, the investor does not suffer a loss, at least not nominally. Should the owner of the loan wish to sell that loan, he or she will have to work with a broker to find a suitable buyer. Now that the loan has higher credit risk, a potential buyer of the loan will demand a higher yield (credit spread) than was demanded at the time of loan origination. In this case, the mark-to-market loss is crystallized. Changes in the potential for default and the amount one might recover in a default scenario, which change the value of a credit-risky loan, constitute credit risk.

Event risk. Big changes happen at companies all the time. The possibility of an exogenous one-time event such as an accident, a lawsuit, or a takeover by another company or a private equity firm is ever-present. This also could represent a random periodic event initiated by management, such as a sudden repurchase or sale of stock or some other operating restructuring, such as the selling of a division or the purchase of another company. These events tend to cause a shock to the financial condition of the company, potentially altering the future financial performance of the borrower. Sometimes these shocks affect the value of the firm as a whole. At other times it may result in wealth transfers between lenders and owners. This is event risk.

• Political risk. Companies exist under some governmental jurisdiction. Some governments take a more positive stance toward businesses than others. The actions of national or local governing authorities can influence a business’s performance and viability. The following is a listing of the key elements of political risk:

Law and regulation risk. Governments frequently change laws and regulations as they attempt to govern the behavior of corporations, entrepreneurs, and small businesses that provide goods and services to the marketplace. They often write laws that affect consumer behavior as well. Changes in laws may harm or enhance a company’s ability to compete in the marketplace. Such changes can force an alteration in product design or manufacturing process and even eliminate a product from the marketplace altogether. At the extreme, regulations can even put a corporation out of business, but this is quite rare. Poorly designed laws and regulations may result in lower returns on assets or even financial losses because they distort the marketplace and give an advantage to some products, while creating obstacles for others. International trade laws often change the competitive landscape of entire industries. The effects of changing laws and regulations are a critical element of political risk.

Tax risk. Governments modify tax laws all the time as well. Most of the time, their intent is to raise more revenue. Sometimes the intent is to encourage or discourage certain behaviors of businesses and/or consumers. An increase in tax rates will reduce the aftertax return to shareholders and lenders. Fortunately, there tends to be stability in tax rates. More often than not, government modifies the tax laws by fine-tuning certain aspects of the tax code. Such changes tend to create a new tax or a tax credit for a particular targeted industry. A tax break for a competing technology can make a company less competitive in the marketplace. A tax credit can make an economically nonviable company or industry profitable. Changes in taxes or subsidies on international trade can change the entire competitive environment, particularly between international and domestic producers. Tax risk is a key element of political risk as well.

As a category, diversification will not reduce market risk. Fortunately, a host of financial instruments with deep markets such as Treasury bond futures contracts and interest-rate swaps enables lenders to hedge interest-rate risk. Equity investors have a host of index future and exchange-traded funds (ETFs) to use as hedging vehicles. These instruments also make the price of these risks well known. Some market risks are difficult to hedge, forcing investors to live with those risks. For example, liquidity risk can be systemic and is difficult, if not impossible, to hedge. When credit dries up, it does so across the economy and financial markets, making it difficult to trade any security without giving away a liquidity premium. Political risk is an element of systemic risk as well because laws and regulations generally affect all companies in a particular country or industry. Political risk is also difficult, if not impossible, to hedge. All the investor can do is try