Posted tagged ‘corporate bonds’

Why Stress Test Really Means Guesswork

March 15, 2009

Well, we’ve heard a ton about stress tests recently. Want some details on what a stress test entails? The Journal has some details about the tests here. Now, as much as I think GDP and unemployment are fine things to project forward for economists, let’s walk through the way one would use this to actually price an asset. Let’s start with something simple, like a 10-year treasury note (note that treasury bond specifically refers to bonds with a 30-year maturity). Here are all the components one would need to stress test the value of a treasury note.

  1. Characteristics of the note itself: coupon, payment dates, maturity dates, etc.
  2. What the yield curve would look like at the date you’re pricing the note.

Why would one need to know the shape of the yield curve (term structure of rates)? This is important, in order to “PV” the bond’s cashflows most accurately, one would discount each cashflow by it’s risk–the simplest proxy is to discount each cash flow by the rate of interest one would need to pay to issue a bond maturing on that date. For the government, this rate of interest is the point on the treasury yield curve (actually, the par zero curve) with the same maturity date. An example would be, if I were going to price a cash payment I will receive in two years, and the government can currently issue two-year debt at 5%, I should discount my cash payment (also from the government, since it’s a treasury note) at 5%. Treasuries are the simplest of all instruments to value.

Here’s an example, form the link above, of what a treasury yield curve might look like:

Normal Yield Curve

Now, it is completely and totally guesswork to figure out, given unemployment and GDP figures, what the yield curve will look like at any date in the future. Indeed, one can plug these projections into a model and it can come up with a statistical guess… But the only thing we know for sure about that guess is that it won’t be accurate, although it might be close. However, things like inflation will drive the longer end of the yield curve and monetary policy will drive the shorter end, so these certainly aren’t directly taken from the stress test parameters, but would need to be a guess based on those parameters. This is a large source of uncertainty in pricing even these instruments in the stress test.

Next, let’s examine a corporate bond. What would we need for a corporate bond?

  1. Characteristics of the bond: coupon, payment dates, maturity dates, special features (coupon steps, sinking funds, call schedules, etc.), where in the capital structure this bond sits, etc.
  2. What the yield curve would look like at the date you’re pricing the bond.
  3. The spreads that the corporation’s debt will carry at the date you’re pricing the bond.

Oh no. We already saw the issues with #2, but now we have #3. What will this corporations credit spread (interest/yield required in excess of the risk free rate) at the time of pricing? Will the corporations debt, which could trade at a spread of anywhere from 5 to 1500 basis points, be lower? higher? Will the corporations spread curve be flatter? steeper?

Here is a good illustration of what I’m referring to (from the same source as the figure above):

Credit Spread

There, the spread is the difference between the purple line and the black line. As you can see, it’s different for different maturity corporate bonds (which makes sense, because if a company defaults in year two, it’ll also default on it’s three year debt.. but the companies’ two year debt might never default, but the company might default during it’s third year, creating more risk for three year bonds issued by that company than two year bonds). It shouldn’t be a surprise, after our exercise above, to learn that the best way to compute the price of a corporate bond is to discount each cashflow by it’s risk (in my example above, regardless of whether the company defaults in year two or year three, the interest payments from both the three year and two year debt that are paid in one year have the same risk).

Well, how does one predict the structure of credit spreads in the future? Here’s a hint: models. Interest rates, however, are an input to this model, since the cost of a firm’s borrowing is an important input to figuring out a corporation’s cashflow and, by extension, creditworthiness. So now we have not only a flawed interest rate projection, but we have a projection of corporate risk that, in addition to being flawed itself, takes our other flawed projections as an input! Understanding model error yet? Oh, and yes unemployment and the health of the economy will be inputs to the model that spits out our guess for credit spreads in the future as well.

Next stop on the crazy train, mortgage products! What does one need to project prices for mortgage products?

  1. Characteristics of the bond: coupon, payment dates, maturity dates, structure of the underlying securitization (how does cash get assigned in the event of a default, prepayment, etc.), etc.
  2. What the yield curve would look like at the date you’re pricing the bond.
  3. The spreads that the debt will carry at the date you’re pricing the bond.
  4. What prepayments will have occurred by the date you’re pricing the bond and what prepayments will occur in the future, including when each will occur.
  5. What defaults will have occurred by the date you’re pricing the bond and what defaults will occur in the future, including when each will occur.

Oh crap. We’ve covered #1-3. But, look at #4 and #5 … To price a mortgage bond, one needs to be able to project out, over the life of the bond, prepayments and defaults. Each is driven bydifferent variables and each happens in different timeframes. Guess how each projection is arrived at? Models! What are the inputs to these models? Well, interest rates (ones ability to refinance depends on where rates are at the time) over a long period of time (keep in mind that you need rates over time, having rates at 5% in three years is completely different if rates where 1% or 15% for the three years before). General economic health, including regional (or more local) unemployment rates (if the south has a spike in unemployment, but the rest of the country sees a slight decrease, you’ll likely see defaults increase). And a myrid of other variables can be tossed in for good measure. So now we have two more models, driven by our flawed interest rate projections, flawed credit projections (ones ability to refinance is driven by their mortgage rate, which is some benchmark interest rate [treasuries here] plus some spread, from #3), and the unemployment and GDP projections.

I will, at this point, decline to talk about pricing C.D.O.’s … Just understand, however, that C.D.O.’s are portfolios of corporate and mortgage bonds, so they are a full extra order of magnitude more complex. Is it clear, now, why these stress tests, as they seem to be defined, aren’t all that specific, and potentially not all that useful?

Mindset Arbitrage

February 6, 2008

One interesting observation about the securitization process is that many of the securitized products are meant to aggregate a risk so it can be distributed to capital market participants (hedge funds, opportunity funds, insurance companies that buy securities, and money managers and banks).

For example, Commercial Mortgage Backed Securities are used to source risk from real estate investors that own and operate real estate assets. This is a cash flow based market where people that manage buildings have a well defined plan for extracting more dollars to the bottom line (raise rents, lower expenses, re-capitalize the entity that owns the building, etc.). When your day-to-day business is servicing tenants, collecting rents, staffing a building, and maintaining the property you aren’t use to thinking about duration or what rating the rating agencies have assigned your loan. Things like day count conventions and their effect on the yield vs. the coupon isn’t your expertise. These are all esoteric things that some traders and bankers spend years not understanding in any rigorous way.

Residential Mortgage Backed Securities source risk from homeowners and mortgage originators. Here people’s assets secure loans and allow risk to be quantified by analyzing statistical data which, in aggregate, should hold closely to some historical trends. One can view how high LTV loans made to borrowers with a FICO score between 600 and 620 have performed in a given state over the past five years and extrapolate the performance of other loans with the same characteristics (recent problems arose when people didn’t care about the loan characteristics, just that they could get bonds or what rating the bonds had).  I don’t think I have to explain that, given all the examples in the media trying to explain CDOs (but really securitized products in general), it should be Q.E.D. that people taking out mortgages didn’t fully understand how the risk was being laid off nor how it would affect them (even the banks got sloppy).

Even corporate CDOs took instruments from a market where securities are valued based on the fundamental credit quality and technical factors and sold instruments that were valued using correlation trading models.  Obviously this is a bit different since these are all sophisticated (theoretically) institutional accounts. However, no one was prepared for, nor did they understand fully, the implications of things like the Ford and G.M. downgrades to junk or how the price movement in CDO tranches was going to show a disconnect because of the types of accounts that held them. (What this means is that the lowest tranches, which take losses first, become the worst risk in the pool. Essentially, then, these “equity tranches” became proxies for Ford and G.M. Since these equity tranches were held by accounts that have to mark to market, they dropped in price to reflect liquidity concerns. The tranches above them were generally held by insurance companies, or non–mark to market accounts. Dealers, proprietary trading desks, and hedge funds had all put on trades that went long equity tranches and short the tranches above them assuming the relative spread would move predictably. Unfortunately, for them, there was no price movement in the tranches they were short, since those accounts didn’t have to mark to market, and thus didn’t need to sell to prevent further losses while the equity tranches dropped in value.)

Even starting a fund is an exercise in mindset arbitrage. Some manager looks to buy assets, like mezzanine debt, which generally trades on price or as a spread to a benchmark interest rate, by raising equity for a fund. All they are doing is taking the returns they know are out in the capital markets, adding leverage, and going to investors that are very focused on R.O.E. (return on equity). This is probably the worst example here, despite being quite valid, because the level of sophistication can be quite high. However, with lots of money chasing high returns, sometimes due diligence and other metrics of reliability and quality fall by the wayside.

It should become apparent, now why there is money to be made re-packaging risk–essentially you are outsourcing the placement and structuring of that risk so that the person who is willing to get paid the least for taking a particular risk gets it. This is why it is possible for one to sell securitized products at a net interest rate less than the underlying assets.