Posted by Peter Orr on Wed, Jul 28, 2010 @ 06:59 AM
Here’s a quick quiz. If over the last 10 years 1M LIBOR reset weekly averaged 2.814%, and the average of SIFMA / 1M LIBOR was 82.0%, what was the SIFMA average over the same time period (all rates unadjusted for day counts, holidays etc.)?
A. 2.05% B. 2.31% (2.814% * 82.0%) C. 2.62%, or D. None of the above but it seems like a trick’s in here somewhere
The correct answer is in fact A, which is a testament to how strongly the Fed has been stepping on the money accelerator over the last decade. Monetary policy aside, if you answered B (simply multiplying the LIBOR average by the SIFMA/LIBOR ratio average) you would’ve made a very common mistake which falls into the category of the Flaw of Averages. Overreliance on simple averages, partly induced by overreliance on simple spreadsheets, can very easily lead to errors of calculation and ultimately judgment. In this case, the seemingly more intuitive answer B is over 25 basis points wrong!
How does this work? When rates are low, SIFMA/LIBOR has been high and vice versa i.e. the two rates have been negatively correlated. If you don’t capture this fact in your analysis, you’re missing a critical component of how the tax-exempt markets have worked. This ultimately leads to over-hedging, misunderstanding of balance sheet hedges, and other unintended consequences.
Luckily, there are readily accessible public finance analytics that capture these very easily.
Posted by Peter Orr on Tue, Jul 20, 2010 @ 07:56 AM
Credit markets are certainly not “normal” (in any sense of the
word) but at least they’re stable enough for issuers to make some decisions. That said, keeping in mind the answers to three deceptively simple yet vitally important questions will always serve CFOs, governing boards, finance committees, and other financial decision makers very well.
Notice that these questions are not framed in terms of some specific risk metric or probability. That’s because they are intended to address decision making in a way that we (as a species) are best suited to understanding. Despite the fact that banking regulation has often focused on extremely remote events like 99.9% annualized confidence intervals i.e. events that happen every 1,000 years, it’s a well researched fact that we human types simply don’t do very well making decisions about such tiny likelihoods. We tend to overemphasize the dramatic remote risks (shark attacks and plane crashes) over the far more dangerous yet mundane occurrences (auto accidents and drowning).
Can we make it through the worst plausible scenario?
The nature of risk management comes first in defining a plausible event or set of events to be concerned about. Without some sense for what that the downside concern is and how it will impact a corporation’s financial position, risk management doesn’t exist. Notice that this is where the entity’s level of risk aversion comes explicitly to the surface.
“Make it through” will mean different things to different entities since incentives and consequences, including political fallout, are obviously not uniform across institutions. For many, this concept is tied to liquidity access – a topic that’s found a great deal of interest over the last 18 months.
“Plausible” is also an important word here. An issuer I know, when answering this question for themselves, looked at the marks on their swaps if the entire yield curve moved to 0%. This is obviously a definable event and it gives one boundary value for their swaps; some people may consider it so implausible however that it should not be the focus in response to this question.
How much might we gain in the best plausible scenario?
This is an important question in that if there’s very little gain expected relative to the “do nothing” scenario, absorbing the risk may not be worth it. This question wraps in it whether you want to evaluate the best scenario in terms of the individual transaction in isolation, or evaluate the overall impact against the backdrop of the entire portfolio (debt and/or investment).
The answer to this question in conjunction with the first helps determine the nature of the strategy’s distribution. A remote but large downside with a modest but likely upside is similar to a “sold option” situation. A fairly uniform upside and downside is a simple long position in some risk, etc.
What is the breakeven?
How far do the factors that affect the performance of the instrument(s) need to move in order for the strategy to break even with the “do nothing scenario”? For instance, do you want exposure to SIFMA based variable rates as a tax-exempt borrower if you believe significant inflation will arrive eventually and you can lock in a rate at 3.75% fixed? How fast to floating rates need to rise for this strategy to break even (download model here)?
Understanding the break even helps us evaluate the likelihood that the transaction will work in your favor in a way that no other calculation really does. It allows us to directly assess a tangible, quantified event and the subjective probability that that event will occur. With that information in hand, evaluation of the best course of action is often much more clear.
For analytics that help answer each of these questions using rigorous, comprehensive decision frameworks see
here.
Posted by Peter Orr on Fri, Jul 16, 2010 @ 12:29 PM
I’ve always believed there are actually three certainties in life (in contrast to the far less archetypal two): death, taxes, and finance people’ love of spreadsheets. Spreadsheets are excellent for doing certain types of work given their flexibility. Though frankly, these “electronic chalkboards” as their inventors called them are simply not the right medium for others. For instance, heavy duty simulation based number crunching and optimization shouldn’t be done on a chalkboard, electronic or otherwise. The memory management and numerics simply aren’t suitably industrial strength for big jobs like that. As a data store the spreadsheet also has drawbacks. Sure it’s flexible and easy to add new bits, but that same flexibility is a problem when it comes to compatibility and consistency, virtues in and of themselves.
Here’s a top 10 list explaining how a database (sometimes) simply eats a spreadsheet’s lunch:
10) Database is a single, accessible location for complete, accurate information
9) Database offers on-demand distribution of data to professionals in all regional offices in your business
8) Impress your friends by confidently exclaiming, “We’ve implemented a best-practice abstraction of our data from our data format”
7) Easy to connect to a database from a spreadsheet to grab what you need
6) Much harder for an employee to email themselves their fancy, custom database before quitting and going to a competitor
5) Analytic tools can be built to apply to entire database, increasing accuracy and boosting productivity – BIG time
4) Put your database in the cloud and join the millions of people who talk about cloud computing but only have a very foggy idea of what it is!
3) With a database you have a specific manager providing crystal clear responsibility for data integrity, completeness, and security
2) Sure Excel now has 16,000 columns and a million rows (on Sheet1), but just try and use them all! For gobs and gobs of data, a database is the solution, hands down.
And the number 1 reason a database kicks a spreadsheet’s butt is
1) Capturing data in a spreadsheet to run some #s is soooo 90s. Nowadays you’ve got to apply your fancy numerical recipes to an entire database and auto-email results to your pre-defined audiences – 100x more efficient and infinitely cooler!
Posted by Peter Orr on Wed, Jul 14, 2010 @ 08:50 AM
I know evolutionary biology comparisons to business are a bit
tired at this point, but having just checked off an item on my personal bucket list (diving in Galapagos!) I can’t resist reciting a few quotes from my friend Chuck Darwin. After seeing some of his famous finches firsthand one day and dealing with a balance sheet market risk analysis the next, I can’t help myself:
“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one most adaptable to change.”
“In the long history of humankind (and animal kind, too) those who learned to collaborate and improvise most effectively have prevailed”
“A man who dares to waste one hour of time has not discovered the value of life.”
- Charles Darwin
Have a full and evolving day!