It’s 2015. Watson vanquished humans in Jeopardy 4 years ago and is now rapidly moving towards replacing as many oncologists as possible. Google is just one company running driverless cars and trucks around everywhere. Facebook is trying to monetize every eye twitch you make looking at a web page. Let’s check in on innovation in public finance:
- Rarely if ever calculate and manage relevant risk metrics. Check
- Analyses of all stripes performed in spreadsheets or 20+ year old bond software - despite massive limitations. Check
- Unexamined rules of thumb for when to refund bonds. Check
- Applying 25+ year old, black-box option models that are simply inappropriate for munis and few understand. Check
The last one might be considered an “innovation” given its somewhat more recent rise but with innovation like that…well, it seems like we could do better.
How about we start with improving the good ol’ yield calculation for issuers?!? We’ve used recent fixed income research, spawned from the obvious shortcomings of models during the financial crisis, to create a better yield mousetrap. We can now incorporate an issuer’s actual refunding criteria in cash flow calculations to create a lifetime cost of financing including 1st and 2nd generation refundings. For that reason, this is called the Refunding Adjusted Yield (RAY).
How’d we do it? Well, it’s just 4 simple steps:
- Implement a real world market model that realistically generates the issuer’s tax-exempt, taxable, and SLGS (escrow) curves in a single consistent model. Ideally make it fully transparent and testable. Examples are here and here. (We chose the latter as it has the benefit of capturing how yields actually change across levels.) You can test it yourself by playing Curve Quiz (free!) on iphone/ipad here or on your Android device here.
- Using issuer’s actual refunding criteria, determine when hypothetical refundings occur (make nice refunding probability graph).
- Given the timing of refundings in 2) and the future yield curves in 1) adjust the original debt service cash flows based on the new refundings. Do the same for 2nd generation refundings as applicable. Don't forget to enforce the rules: no tax-exempt refunding of advance-refunding bonds, just like the real world.
- Average the net cash flows from 3) and calculate a yield back to the purchase price of the bond or issue. This is the Refunding Adjusted Yield (a RAY of shining light on true lifetime project cost and muni bond structuring!)
What does RAY look like for an actual deal structure? For a 20 year level debt issue (amort and pricing at bottom of article) we have these statistics:
Issue Par $100,000,000.00
Issue Price $113,496,745.45
Arbitrage Yield 2.910%
True Interest Cost (TIC) 3.382%
RAY with 5% PV Savings Criterion 3.207%
For those not fully initiated into the mysteries of public finance yield calculations, the arbitrage yield is generally a yield to worst (from the investor’s perspective) calculation and as such is often to the call date for premium callables. The TIC on the other hand is to maturity. Armed with this information, it is intuitive that the RAY would sit somewhere between the arbitrage yield and TIC. In this case, obviously, the closer RAY is to the arbitrage yield the more likely the bonds are to be refunded and called. In this case the RAY calculation incorporated a refunding if the callable bonds hit a 5% PV savings target. Different refunding criteria lead to different RAYs. More on that to come...
This framework has a ton of really nice side benefits too, which we’ll look at over the next few weeks:
- How RAY Changes with Refunding Criteria/Policy
- The effect on RAY of 2nd Generation Refundings
- New stats like Avg Time to Refunding, Refunding Adjusted Avg Life, and % of Escrow Supported Cash flows
The information content in these numbers is staggeringly greater than simple arb yield or TIC. Ding dong...the TIC is dead
If you’d like to know more or would like to calculate a RAY for a new pricing or to compare structures, drop us a line - email@example.com or call 646.202.9446.
"What is the difference between a taxidermist and a tax collector? The taxidermist takes only your skin." - Mark Twain
Last week a real, live, honest-to-goodness “Tax Event”, as described in thousands of financial contracts and securities documents happened. This particular tax law change is likely not of sufficient magnitude to actually trigger the various remedies that your run-of-the-mill Tax Event provision lays out, but with tax reform talk still swirling it’s probably not a bad time to reflect on what those provisions might actually mean financially for borrowers.
Tax risk in public finance circles and in contrast to a “Tax Event”, is that oft-discussed yet stubbornly nebulous chance that a change in tax law might ultimately raise a borrower’s financings costs. Many mistakenly believe the prime example of this occurs when the interest rate component of a tax-exempt variable rate bond or floating rate note (pricing off of or indexed to SIFMA) is hedged with a LIBOR-based swap. People often think this somehow adds tax-risk to a borrower’s portfolio.1
Of course a change in tax law that somehow reduces the preference for tax-exempt income effects not just the performance of LIBOR synthetic fixed bonds. It certainly would also negatively impact the performance of:
1) ALL SIFMA-based tax-exempt variable rate securities/loans (hedged or not)
2) All future yet unissued fixed rate bond transactions
3) As a consequence of 1) above, drive the deterioration of any tax-exempt/taxable relationships on the balance sheet such as short duration taxable investments hedging tax-exempt VRDBs.
What’s the present value impact of the above to the borrower? Given the sensitivity, that depends on how many variable rate bonds exist on the balance sheet today, and also how much debt is expected to be issued in the future. Great tools do exist to get a read on this type of exposure.
Obviously difficult to say how it all shakes out, but needless to say the uncertainty is spooking both borrowers and investors alike. In the meantime, we’ll just update our marginal tax rate chart with 2013 info (assuming no additional legislative changes) giving us a full century of data.
The left vertical axis (red) is the marginal tax rate in percent and the right vertical axis (black) is the income level at which the top marginal rate applies. Interesting to note that in the lead up to and during much of WWII there was a top FMTR of nearly 80% but it only hit annual income over $5 million. Adjusting for CPI that would apply to earners today pulling in over $82 million! Any guesses how many people take down that kinda green today?
1This mistake has risen even to the level of the audited financials of very large cities. Auditors have erroneously stated that synthetic fixed LIBOR structures somehow have a tax risk element in them that doesn't exist in plain VRDBs. Those audits introduce some legal risk with statements like that!
The first word in our company name means we do a lot more than calc pv savings. We often work with investment banking or financial advisor clients to come up with the clearest way to express complex analyses to tax-exempt issuers. Frequently this leads to crafting ways to convey key messages as part of a broader strategy to get hired. What often surprises me about these discussions is how little people know about their position. Let me explain
The concept of “strategy” is inextricably interwoven with the idea of “position”. How could you have a strategy in checkers if you don’t know where your pieces are, or in what direction to move them in order to improve that position relative to your opponent? Yet time and time again when I ask a banker to tell me about their position with an issuer, or their competitor’s position with an issuer, they have only a vague idea if any at all. How can you execute a sales/marketing strategy without knowing your position?
What are you bringing to the table from the issuer’s perspective? A relationship of trust with senior management or the Board, balance sheet strength in the form of letters or lines of credit or other credit product, or maybe cutting edge ideas and analytics that help illuminate the tough financial decisions the issuer faces? Perhaps some combination? How do you rank in these areas relative to your peers?
If you don’t know then you don’t know your position...and you don’t have a strategy.
Last week I embarked down a path
of trying to get the NYT to correct their errors in an article ostensibly on municipal swaps. This is the second round exchange (of three) with the NYT editors justifying their mistakes in the article, The Swaps That Swallowed Your Town
. My response was simple, though I was forced to use a three number example.
I'll try and keep this brief.
Given Ms. Morgenson's response, it is clear she is sorely confused about what has caused financial strain for states/municipalities. I'll prove this simply, although I will use a few numbers - 3 to be exact. Let's take the last year to represent our time period of market stress (though you could pick any reasonable representative period, the answer will be substantively identical). The first number is 0.20%, which is the average of 67% of 1M LIBOR over the last year. I use 67% because it is the most common rate municipalities have used in swaps to hedge variable rate bonds. The second number is 0.34%. This is the average of the SIFMA index, the index against which all tax-exempt variable rate bonds are priced. The difference between these two numbers is the spread that Ms. Morgenson shockingly claims is outside the "narrow range." It is this crushing differential that she, and worse, the NYTimes has told its entire readership is going to imminently "swallow" all the swap-exposed towns near you in a madly corrupt, swap induced, financial maelstrom. And how big is this staggering, non-narrow differential??? 0.14%. Please look carefully at where the decimal point is on that number; it is no mistake.
This would be funny if it weren't exposing such flagrant misinformation and flat out bad reporting. And if 0.14% isn't in the "narrow range," I would ask Ms. Morgenson what is, exactly? As a point of reference, the 2 year average differential is 0.32% so this wild differential has only gotten narrower over the last year. The simple undeniable fact as it relates to this "narrow range" issue is that the current period actually shows one of the narrowest spreads we've seen historically, because the actual level of interest rates is so close to zero. Again, this is simple, unalterable, basic fact that anyone can check. I urge you to run this by your "municipal experts" in the story, or anyone else who knows something about public finance - I assure you they will agree with me. Your readers deserve better and this egregious mistake should be corrected.
Again, the actual reasons states and municipalities are under stress from their debt programs are exactly those that I described in my first letter: failed auction rate securities and variable rate bond programs which have lost the support of the banks. Whether those programs were hedged with interest rate swaps is an entirely separate issue, though admittedly can cause additional stress if the state/municipality chooses to terminate the swap.
I'm sure Ms. Morgenson is a good writer; as an NYT reader I have enjoyed some of her articles in the past. Unfortunately in this case, she is in over her head, knows only enough about the subject matter to be factually wrong, and has embarrassed the New York Times. I believe an editor's job is in part to acknowledge and correct when the paper doesn't have its facts straight. The premise of this entire article is clearly mistaken (I hope in good faith and not just to sell papers), and your readers deserve to know it. There's enough falsehood in our public discourse without news organizations throwing their own rubbish onto the heap.
Happy to discuss this or the real challenges municipalities face with whomever cares about accurate reporting. At minimum I look forward to a correction of this error.
I was a bit edgy that day so the tone wasn't quite as constructive as I would've liked. Nonetheless, here was the response from Dan Cooreman of the NYT Sunday biz section:
Thank you for the additional information in your email message of last evening. But it seems that you and Gretchen Morgenson are discussing two different things.
Here is a summary of her explanation:
The spread that was referred to in the column did not refer to the difference between 67% of LIBOR and the average of the SIFMA index. When the column said the contracts assumed that the rates in the deals would stay in a narrow range, it was referring to the problems associated with spikes in interest rates on variable rate debt. When the spread between this rate and that received by the issuer from the swap counterparty blew out, it created significant problems for tax-exempt debt issuers. A crucial reason for this, as you and the column both pointed out, was the seizing up of the auction rate securities market.
As outlined in the Annual Performance Report from the New York State Division of the Budget: "In 2008-09, the crisis in the credit markets negatively affected the performance of the swap portfolio. The global credit crisis has highlighted that the use of these financial instruments can expose municipal debt issuers to large unanticipated costs. In particular, the increased costs associated with credit risk, basis risk and early termination payment risk have had a significant impact on the performance of synthetic fixed rate swaps. During the past year, the collapse of the auction rate and bond insurance market, in conjunction with rising credit concerns for a number of liquidity providers (commercial banks) caused the interest rates on certain variable rate bonds to increase to unprecedented levels. For example, interest rates on auction rate bonds in the Tobacco bond program rose to 14.2 percent from 4 percent over a one month period. The dislocation in the credit markets negatively affected more than half of the state's variable rate portfolio ($5.2 billion)."
This is the aspect of the deals that the column was referring to, not the difference between 67% of LIBOR and the SIFMA index.
Sunday Business section
Ahh. So the article was referring "to the problems associated with spikes in interest rates on variable rate debt"? Wait, what was the title of her article again? Somehow I don't remember seeing anything about interest rates on variable rate debt. Read the third and final chapter
It's 2010 and time to raise the bar. Public finance software has remained substantially unchanged for over a decade, and probably more like two. In this day and age your public finance software, in addition to all the other stuff it's done since TRA86, must add the following five features:
1. Reflect Uncertainty and Quantify Risk
Because so much brainspace is bogged down in satisfying tax rules coupled with analysts' difficulty implement models outside the ubiquitous spreadsheet, public finance analytics tend to force single point forecasts for market elements: variable rates, SIFMA/LIBOR ratios, VRDN support costs, etc. What does this mean? It means uncertainty is modeled with certainty which today borders on the absurd and exacerbates our species' now well documented tendency towards overconfidence. Your public finance software needs to at least provide for the identification of cash flow risks and their modeling in a straightforward, efficient way.
2. Visual Interaction with the Problem
Have you seen a video game made any time in the last 5 years? These are true technological achievements. What fraction of the computing power going into a video game rendering the bad guy around the corner finds its way to helping you visualize the complex financial decisions you or your clients make? 0.1%? 1% maybe? Let's raise the bar - make it 10% and let's see what that looks like. Unless you're able to quickly get a visual read of the problem and interact with it visually (move revenue lines, modify risk constraints, etc) your public finance analytics need a makeover.
3. Calculate Solutions Subject to Explicit Risk Constraints
Public finance analytics that solve for the minimum bond size achieving an overall expected debt service shape, wrapping around existing bonds and derivatives as applicable, while also measuring additional marginal risk contribution are now just a baseline. Public finance analytics in 2010 must also allow the user to enter an explicit risk constraint to which the solution is bound. In this way, the user sees the most cost effective, risk-adjusted solution determined from multiple financing sources on a maturity by maturity basis.
4. Accommodate Swaps and Other Derivatives
Tax-exempt variable rate bonds aren't going away any time soon. Therefore and despite some reporters confusion over what "speculation" is, interest rate swaps, caps, and collars probably aren't going away either. If your public finance software doesn't analyze these very non-trivial instruments in very non-trivial ways, you're missing a very big part of the financial analysis for you or your clients.
5. Include Refunded Bond Selection as Integral to Solution
Selecting what bonds to refund isn't always as simple as firing up your refunding screen and grabbing everything above 3% pv savings. A number of interrelated factors go into determining the marginal contribution that an additional refunded bond has to the economics of a refunding. Your public finance analytics should rise to the challenge.
If you're an issuer, the features above offer you a deeper understanding of what's going on with your capital structure. This makes you a far more knowledgeable consumer of banking and advisory services. If you're a pubfin banker or advisor, these features are a pre-requisite to demonstrating you understand your clients.
The world is changing fast... and public finance is no exception.