Spero Consulting

‘Valuation’ Category

We Missed It a Few Months Ago

On the front page of the The ‘Money & Invest­ing’ sec­tion of today’s edi­tion of The Wall Street Jour­nal, there is an arti­cle enti­tled, At SEC a Scholar Who Saw It Com­ing.

The arti­cle is about Henry Hu, who man­ages the newly-​formed Risk, Strat­egy and Finan­cial Inno­va­tion divi­sion at the SEC.

Though he sounds like a good guy, we don’t know much about Mr. Hu, but that’s not why we’re writ­ing. It also men­tions that in Novem­ber, Mr. Wu hired Richard Book­staber to lead staff train­ing and data analy­sis, and that is a good thing. (The print ver­sion incor­rectly iden­ti­fies him as David Bookstaber.)

If you haven’t heard of Mr. Book­staber, he has much knowl­edge and much expe­ri­ence work­ing at large trad­ing firms and hedge funds. In fact, he takes “par­tial credit” for a few of the past crises, includ­ing the Crash of 1987.

Mr. Book­staber is also the author of the 2007 book, A Demon of Our Own Design, which dis­cusses those crises, his roles in them, as well as his approach to risk (and uncer­tainty) management. We highly rec­om­mend the book to any­one in the finan­cial ser­vices indus­try and within par­tic­u­lar roles in other indus­tries, too. For exam­ple, we recently rec­om­mended it to the chief of secu­rity at a large, U.S. based, multi­na­tional that oper­ates fac­to­ries and plants through­out the world.

In the book, Mr. Book­staber makes the excel­lent point that overly-​rigid or overly-​complex risk mon­i­tor­ing and safety sys­tems can actu­ally increase the prob­a­bil­ity of fail­ure and the loss given fail­ure and dis­cusses it both within and out­side of finan­cial ser­vices. (Recently, we made sim­i­lar points in our analy­sis of intel­li­gence fail­ures and bad infor­ma­tion sys­tem design.)

Besides read­ing the book, we also encour­age our read­ers to visit Mr. Bookstaber’s blog, espe­cially to read his tes­ti­mony before Con­gress – the links in the right-​hand col­umn). It is well-​written and not overly-​technical.

Regard­ing risk and uncer­tainty man­age­ment, Mr. Book­staber makes points sim­i­lar to ours, with the main inter­sec­tion being that not every cri­sis is pre­dictable, but thought­ful­ness and con­tin­gency analy­sis goes a long way to mit­i­gat­ing crises. In fact, prepar­ing (rather) gen­eral responses to pos­si­ble, spe­cific crises can pre­pare one for com­pletely unknown ones, too. (See our essay on uncer­tainty man­age­ment and almost any of our posts cat­e­go­rized as uncer­tainty or risk. By the way, we really like our post with the tongue-​in-​cheek title, The Role for Sur­vival­ists and Depres­sives in Uncer­tainty Man­age­ment, because we think that per­son­al­ity traits like skep­ti­cism and pes­simism are under-​weighted and under-​valued in most risk man­age­ment hir­ing process.)

The best that we can tell, we tend to place more empha­sis on stress-​testing and sce­nario analy­sis than he does, but that’s because we think that imag­i­na­tion, like skep­ti­cism, is under-​estimated, too.

One topic where we do dis­agree is his insis­tence that every­one (that mat­ters) under­stands the lim­i­ta­tions of the use of nor­mal dis­tri­b­u­tions in risk mea­sures like VaR (Value at Risk). To explain, 2e’ll try to be con­cise but thor­ough but will err on the side of brevity.

It is well-​known – though not wholly-​agreed-​upon – that assum­ing nor­mal­ity (or log-​normality) mis-​specifies mod­els of returns, and we think that many ‘quants’ do know that, but they use those assump­tions nonethe­less, and that’s for a few reasons:

1. There is no other choice, or no other tractable choice.
2. Depend­ing upon the con­text, it may not mat­ter much.
3. Ease of cal­cu­la­tion and effort. (This is dif­fer­ent than (1).)
4. As a way to reduce mea­sures of risk characteristics.
5. Ease of com­mu­ni­ca­tion to others.

We are very sym­pa­thetic to the first two rea­sons, and being some­what lazy, we are also sym­pa­thetic to the third. However, the fourth rea­son hints at cyn­i­cism and greed and, depend­ing upon who is using the mea­sure, it can be very destruc­tive. Also, if such assump­tions are used for oppor­tunis­tic rea­sons, that can indi­cate the tra­di­tional weak­ness of risk man­age­ment vis-​a-​vis revenue-​generating departments.

The fifth rea­son hints that maybe – just maybe – not every­one under­stands the cal­cu­la­tions and assump­tions and their flaws.

We have dealt with very high-​level man­agers at very large firms who are quite igno­rant of the basic char­ac­ter­is­tics of nor­mal dis­tri­b­u­tions. To their credit, a few were quite will­ing to admit as much. (They are the least harm­ful of the bunch.) But given those expe­ri­ences, it is dif­fi­cult to believe that most board direc­tors under­stand the arith­metic; so, it is dif­fi­cult to accept that all senior man­agers (at such firms) under­stand the cal­cu­la­tions; so, it is dif­fi­cult to believe that all other man­agers, traders, sales­men, and investors are knowl­edge­able and well-​informed. (And, boy, could we tell you sto­ries!) The fact that, as Mr. Book­staber points out in his tes­ti­mony, such top­ics appear in text­books is a non sequitur.

When one com­bines cyn­i­cism with mis­com­mu­ni­ca­tion – whether pur­pose­ful or not – there’s a good chance that the orga­ni­za­tion is bear­ing more uncer­tainty and risk that it imag­ines or mea­sures, and that’s not good. So, that fact that “every­one knows” some­thing – even if it that some­thing is true – doesn’t mean that it’s not abused. For exam­ple, pick any vice that every “knows” is wrong but folks do it any­way. The abuse of ille­gal drugs and obe­sity are two anal­o­gous exam­ples. (Oh, by the way, gov­ern­ment reg­u­la­tion doesn’t seem to help much there, either.)

Finally – almost – these last two issues hint at incen­tive prob­lems – both moral haz­ard and adverse selec­tion – that exist within firms, and we’ve writ­ten exten­sively about that, too, e.g., Incen­tives and the Finan­cial Cri­sis and many more.

In sum, while we have never met Mr. Book­staber and likely never will, we are encour­aged to see the SEC hire such a knowl­edge­able and wise per­son. We wish him the best in his new role. (We only wish that we would have done so a few months earlier.)

Here’s a great sports– and science-​related arti­cle in today’s edi­tion of The Wall Street Jour­nal: The Africans Are Hear­ing Foot­steps. We think it’s great because it exposes what claims to be a “sci­en­tific” approach to long-​distance train­ing as some­thing that seems to be quite the oppo­site, i.e., some­thing that seems to be quite non-​empirical.

The arti­cle describes how Amer­i­can long-​distance, Kara Goucher, is suc­cess­fully using “African” meth­ods – which were, in fact, used by most Amer­i­cans prior to the 1980’s – to train for marathons. As described, her method seems to focus more on run­ning than on the mea­sure­ment of var­i­ous aspects of run­ning. (We under­stand that one might argue that today she is in posi­tion to dis­card the meth­ods that put her in that posi­tion, but we”ll ignore that point-​of-​view for the sake of argument.)

Any­way, the arti­cle reminds of of our favorite Ein­stein quotes: “Not every­thing that counts can be counted, and not every­thing that can be counted counts.”

Now, to be able to say any­thing about the sub­ject in less than many, many pages, requires us to keep much con­stant and gen­eral. So, we’ll ignore issues like whether African run­ners are genet­i­cally supe­rior as well as whether they are bet­ter moti­vated because, they’re, well, from Africa. (That seems to be the argu­ment.) More­over, we know that Ms. Goucher is a very small sam­ple size of one, and we don’t fol­low run­ning care­fully enough to know about other run­ners who have switched train­ing meth­ods and have failed miserably.

How­ever, given the lit­tle that we do know, it does seem that – at least at world-​class, élite lev­els – there isn’t much empir­i­cal sup­port for the rather tech­ni­cal approach that most Amer­i­can run­ners and run­ning pro­grams adopted in the 1980s and con­tinue to use today.

More pre­cisely, if the hypoth­e­sis is that com­pre­hen­sive record-​keeping, etc., improves run­ning per­for­mance – as mea­sured by world cham­pi­onships – then it seems that such a con­jec­ture should be rejected. Again, there are any num­ber of rea­sons why our crit­i­cism may be incor­rect: per­haps the for­eign­ers have been able to mask their use of per­for­mance enhanc­ing drugs.

Regard­less, our point is that mak­ing a process overly-​quantitative and struc­tured doesn’t make it the least bit “sci­en­tific.” It may make it abstruse and bureau­cratic and, there­fore, may obscure the real dri­vers of suc­cess and rea­sons for losses, espe­cially when one (or many) take com­fort in those cal­cu­la­tions rather than actual performance.

Given our back­ground and skills, we’re cer­tainly not den­i­grat­ing quan­tifi­ca­tion, esti­ma­tion, and the use of data or the advanced appli­ca­tion of math, but – per our motto – we are say­ing that there should be thought before cal­cu­la­tion and after­wards, too. In that respect, there is no dif­fer­ence between train­ing for marathon run­ning and val­u­a­tion or risk management.

It is ironic that so much infra­struc­ture is devoted to mon­i­tor daily per­for­mance and results, but there seems to be so lit­tle mea­sure­ment and feed­back (eval­u­a­tion) of the effi­cacy of the infra­struc­ture. Expen­sive train­ing reg­i­mens that lead to decades of fail­ure aren’t much dif­fer­ent than “risk” man­age­ment report­ing processes that record ter­abytes of daily data and sense­lessly extrap­o­late things like daily volatil­i­ties and cor­re­la­tions to deter­mine worst-​case sce­nar­ios, yet left so many unpre­pared for the finan­cial crisis.

In both cases, the system-​wide feed­back loops seem to be dis­con­nected and dan­gling in the ether.

Every Mon­day, L. Gor­don Crovitz pub­lishes his Infor­ma­tion Age col­umn in The Wall Street Jour­nal.

We’ve men­tioned his col­umn sev­eral times – some­times agree­ing with him, but usu­ally chid­ing and crit­i­ciz­ing him.

We do like his inten­tions, which seem to be to intro­duce and describe new the­o­ries as they per­tain to infor­ma­tion and eco­nom­ics. Unfortunately, usually he isn’t able to write knowl­edge­ably about these top­ics. By that we mean that he seems to have a journalist’s, or MBA’s, or pop-​science reader’s depth (more pre­cisely, shal­low­ness) of under­stand­ing. So, he is often insuf­fi­ciently uncrit­i­cal – i.e., too accept­ing – of a par­tic­u­lar hypoth­e­sis or exam­ple and its generality.

Today’s col­umn, enti­tled Deriv­a­tives and the Wis­dom of Crowds, pro­vides an excel­lent case to illus­trate his weakness.

If you are unfa­mil­iar with the phrase, “The Wis­dom of Crowds,” it’s the title of a pop-​sci book, which you’re wel­come to read about else­where. We thought it was bor­ing and don’t recall being able or will­ing to fin­ish it. If you’re unfa­mil­iar with the top­ics, then per­haps its an inter­est­ing book with a few sur­pris­ing and counter-​intutive examples.

Prior to the book’s pub­li­ca­tion date, and in recent years, many econ­o­mists have stud­ied related notions, like equi­lib­rium con­cepts, herd­ing behav­ior and, per today’s arti­cle, var­i­ous effi­cient mar­ket hypothe­ses. Like most notions in eco­nom­ics, herd­ing behav­ior can lead to good or bad out­comes, and, of course, we rec­og­nize that we’re not being very pre­cise in using terms like “good” or “bad.”

Effi­cient mar­ket the­o­rists and their antag­o­nists, behav­ioral econ­o­mists, have been argu­ing their respec­tive sides for many years.

We’re sym­pa­thetic to the effi­cient mar­kets hypothe­ses, but there does seem to be sub­stan­tial evi­dence in favor of investor irra­tional­ity (and in some cases, mar­ket manip­u­la­tion). That’s why we’re writ­ing today: to crit­i­cize the fol­low­ing paragraph:

This pub­lic dis­clo­sure could bring the wis­dom of crowds — many investors pro­cess­ing infor­ma­tion — to a new area of the mar­ket. Infor­ma­tion about equi­ties makes stock mar­kets highly effi­cient, with prices quickly reflect­ing accu­mu­lated knowl­edge among investors. Dis­clo­sure of deriv­a­tives posi­tions could like­wise help make fore­cast­ing more accu­rate for more eso­teric top­ics like inter­est rates, foreign-​exchange move­ments and cor­po­rate credit risk.

He rightly uses the wishy-​washy and non-​committal “could” a few times, but we’re won­der­ing about his or any­one else’s evi­dence for the sec­ond sen­tence. Equity prices are highly effi­cient we ask rhetor­i­cally? No kid­ding? The wide ride of the last 18 months – with val­ues being cut almost in half – is evi­dence of effi­cient mar­kets? The panic? The highly-​leveraged com­put­er­ized trad­ing? The insider-​trading? The behav­ior and mis­be­hav­ior of many hedge funds? We could go on, but the Basen­jis want a walk on a beau­ti­ful Spring after­noon; so, writ­ing ad infini­tum and nau­seum will have to suffice.

Mr. Crovitz, for a num­ber of rea­sons, it’s not clear that more infor­ma­tion is nec­es­sar­ily bet­ter for soci­ety. You may want to read what we and oth­ers have writ­ten about trans­parency through the years. Here;s a very recent post where we dis­cuss the issue and crit­i­cize you: Finan­cial Report­ing Trans­parency and Reg­u­la­tion.

We may edit and append this post later.

How Much Have They “Gained” From Becom­ing Worth Less?

Since the begin­ning of April, when many large banks reported unex­pected (or unex­pect­edly large) first-​quarter prof­its, we’ve won­dered what per­cent­age of those prof­its could be attrib­uted to the account­ing rule that lets them rec­og­nize a gain because their own lia­bil­i­ties have become worth less. (We think “worth less” is the cor­rect form, but for the extreme cases, it should indeed be “worthless.”)

We wrote about this issue of rec­og­niz­ing gains from losses in mid-​December in our post Mark­ing Debt to “Mar­ket” or Addi­tion Through Sub­trac­tion. Basi­cally, if cred­i­tors don’t want your bonds, the value of the secu­ri­ties decrease, and yields (and credit spreads) increase. Firms are allowed to rec­og­nize the fact that oth­ers view them as worth less as an unre­al­ized gain to share­hold­ers. (“Unre­al­ized” means that no trans­ac­tion occurred between the firm and its cred­i­tors.) It doesn’t seem to be a very com­pelling argu­ment because as cred­it­wor­thi­ness declines, equity val­ues tend to do so, also. (Ask Citigroup.)

We wish we had more time, or at least more patience, to scan the banks’ first-​quarter finan­cial state­ments on their web sites, but based upon the sites we vis­ited, it doesn’t seem that those gains (from becom­ing riskier and worth less) are some­thing that banks want to pub­li­cize, sep­a­rately iden­tify, or explain. (You can’t blame them for that.)

In our brief on-​line search this morn­ing, we found this blog post, Mark-to-market’s strange account­ing ben­e­fits for Citi and BofA, which notes that Citigroup’s gain – or at least part of the gain – was $2.5 bil­lion but its over­all net profit was only $1.6 bil­lion, and Bank of America’s net gain because it was worth less was about half of its net profit of $4.2 bil­lion. In the pre­vi­ous sen­tence, we wrote the qual­i­fier – between the dashes – to empha­size that it’s pos­si­ble that such gains were actu­ally big­ger but may have been split among dif­fer­ent seg­ments or cat­e­gories. We looked at another bank’s first-​quarter income state­ment, and it showed the com­bined, net, unre­al­ized, gain on assets and lia­bil­i­ties of about $1.5 bil­lion; so, it’s con­ceiv­able that it actu­ally rec­og­nized a loss on assets of sev­eral bil­lion and a gain on re-​valuing/​devaluing lia­bil­i­ties of a larger amount, which nets to the $1.5 bil­lion or so. We ask: if that were the case, would the dear reader think bet­ter or worse of that par­tic­u­lar bank?

Our hunch, based upon these few obser­va­tions, is that bank stock prices would have decreased if these unre­al­ized gains would have been reported explic­itly for what they were/​are. Gen­er­ally, we’re agnos­tic about the ben­e­fits of trans­parency; how­ever, this is one time when we wish that there was a bit more of it. (See our post, Gos­samery Argu­ments for Trans­parency and Our Reply, from last Novem­ber for why more trans­parency isn’t nec­es­sar­ily better.)

Is that Really the Worst-​Case?

Today’s front-​page arti­cle in the The Wall Street Jour­nal, Fed Sees Up to $599 Bil­lion in Bank Losses, is sub­ti­tled “Worst-​Case Cap­i­tal Short­fall of $75 Bil­lion at 10 Banks Is Less Than Many Feared; Some Shares Rise on Hopes Cri­sis Is Easing.”

While it is the worst of the two cases ana­lyzed by the reg­u­la­tors, it is not the worst, rea­son­able case that could be imag­ined. Per­haps that’s why the short­fall was “Less Than Many Feared.”

• It’s rea­son­ably pos­si­ble for the down­turn to be deeper and/​or longer than con­sid­ered. In fact, one could assign a rea­son­able, non-​trivial prob­a­bil­ity to it.
• It’s pos­si­ble – maybe even rea­son­ably prob­a­ble – that given the sce­nar­ios used, the banks (and the reg­u­la­tors) pos­i­tively biased the val­u­a­tion results. (Con­vert­ing macro-​economic assump­tions into asset val­ues is a highly spec­u­la­tive and sub­jec­tive busi­ness – regard­less of the num­ber of cal­cu­la­tions per­formed to gen­er­ate those values.)
• It’s quite pos­si­ble that a man-​made or nat­ural dis­as­ter could com­pound the economy’s prob­lems and shave sev­eral addi­tional per­cent­age points off of GDP dur­ing the next two years. For exam­ple, we’ve writ­ten sev­eral times in recent weeks about the need for sce­nar­ios that include the effects of swine-​flu pan­demics, but large earth­quakes in Cal­i­for­nia, severe drought in the Mid­west, and mas­sive hur­ri­canes and floods in the South­east could be just as dev­as­tat­ing. While none of them is likely, they’re all pos­si­ble – even rea­son­ably possible.

So, we ask, is that sec­ond case really the worst-​case?

The Journal’s Nar­ra­tive Fallacy

While we take issue with the sub­ti­tle of the above arti­cle, there’s another arti­cle in today’s The Wall Street Jour­nal, How the Stress Tests Stopped the Mar­ket Bleed­ing, that’s even more dubi­ous. In fact, the entire premise of it is flawed.

Does any­one other than the two cred­u­lous reporters believe the title to be the case? Geithner’s promise that none of the 19 would be allowed to fail may have had a big­ger effect, but the stress tests them­selves? The evi­dence for that is shame­fully inad­e­quate. So we ask: who are they try­ing to fool?

From our per­spec­tive, there’s noth­ing in the arti­cle to jus­tify the title’s con­clu­sion. In fact, our ref­er­ence to it as a “Nar­ra­tive Fal­lacy” is too gen­er­ous, because if it were, there would be a sequence or set of facts that could be con­cocted to tell such a tale, but there doesn’t seem to be such a set, here. Instead, it seems more like a coin­ci­dence, i.e., it seems that one could eas­ily argue that North Car­olina win­ning the NCAA tour­na­ment had more of an effect or that the mar­ket decreased as tem­per­a­tures cooled in the north­ern hemi­sphere and has begun to rise with the arrival of Spring’s warmer weather. Both of those “expla­na­tions” seem just as compelling.

As Nas­sim Nicholas Taleb has pointed out many, many times, such fal­la­cious story-​telling is all too com­mon in the busi­ness press, where reporters con­stantly ascribe causes and rea­sons to daily (and hourly) changes in prices and indices.

For­tu­nately, the Paper Is Schizophrenic

By that we mean that unlike the report­ing staff, the edi­to­r­ial page writ­ers are a bit more skep­ti­cal about the ben­e­fits of the stress tests, in par­tic­u­lar, and gov­ern­ment involve­ment in the finan­cial sec­tor, in gen­eral. In their top Review and Out­look col­umn today, Stress for Suc­cess?, they con­clude: “The best that can be said about the stress tests is that they’re over.”

We think that’s a bit too harsh, but not by much. See our var­i­ous posts about the stress tests. The next post lists a new complaint.

Or, Is It the Naïve Government’s Stress Test­ing Exercise?

More Lack of Plan­ning and Insight from Our Reg­u­la­tors and Gov­ern­ment Officials

About one month ago – on April 7, to be pre­cise – we asked, Where Will the Bank Stress Test­ing Exer­cise Lead?

In that post, we wrote that the tests could be designed one of three ways: (1) with a pos­i­tive bias to ensure that all or almost all of the banks could pass the tests, (2) with no bias to get a hon­est — though not nec­es­sar­ily accu­rate — assess­ment of each bank’s finan­cial con­di­tion (with accu­racy con­strained by the implicit and explicit assump­tions built into the exer­cise), or (3) with a neg­a­tive bias to ensure that most or all banks fail the test.

Given the var­i­ous news reports that four­teen of the 19 banks may have “failed” the tests and that the four­teen have since been nego­ti­ated down to ten that may “require cap­i­tal,” it doesn’t seem that the tests were designed or biased to gen­er­ate pos­i­tive results. In ret­ro­spect, it doesn’t seem that the eco­nomic assump­tions were par­tic­u­larly neg­a­tive – see We Can’t Sub­si­dize the Banks For­ever in today’s edi­tion of The Wall Street Jour­nal for evi­dence that first quar­ter eco­nomic activ­ity and sta­tis­tics were worse than pro­jected in the exer­cise. Note, how­ever, that if they were designed with a pos­i­tive or opti­mistic bias, then the reg­u­la­tors who designed the Super­vi­sory Cap­i­tal Assess­ment Pro­gram (SCAP) wre/​are hor­ren­dously clue­less and incom­pe­tent, and that’s not out­side the realm of possibility.

As we wrote last month, we can’t imag­ine any­one design­ing a neg­a­tive bias into the tests; so, that means that, most likely, the gov­ern­ment sought an “hon­est” though not nec­es­sar­ily accu­rate assess­ment of each bank’s abil­ity to absorb addi­tional losses.

That was and is prob­lem­atic given the amount of pub­lic­ity gen­er­ated about the pro­gram. It would have been much bet­ter to per­form the tests in total secrecy – in what appeared to be a dis­jointed, dis­or­ga­nized, ad hoc, and unsys­tem­atic man­ner to belie any sense that a thor­ough inves­ti­ga­tion or com­pre­hen­sive and national approach was being under­taken. (They should have been stan­dard­ized but secret tests with no pub­lic­ity or acknowl­edge­ments of their existence.)

The three-​day delay in announc­ing their find­ings shows that the reg­u­la­tors – the Fed, the OCC, etc – were unpre­pared for the results. As we wrote back then, there was no sce­nario analy­ses of the stress test out­comes. For exam­ples, what will we do if four­teen banks require more cap­i­tal, all nine­teen, what about two giant ones, etc?

It’s another exam­ple of gov­ern­ment offi­cials being too rash and not thought­ful enough for their own – and the economy’s – sake. That’s why the road to hell is paved with good intentions.

When we find the time, we’ll expand this post later today or tomor­row, but the events of this week show that the government’s response to the Liq­uid­ity Cri­sis, which is, in fact, a cri­sis in con­fi­dence in finan­cial inter­me­di­aries, is no more thought­ful than its reac­tion to the Mort­gage Débâ­cle, and that pan­icked and over-​publicized response cre­ated the Liq­uid­ity Cri­sis in the first place.

Please, folks, first “do no harm,” which means that you have to think before act­ing or cal­cu­lat­ing. Now where have you seen that before?

Last week we wrote two related posts: A New Influenza Stress Test and Influenza Pan­demic Stress Test, Part II. Both posts dis­cuss the need for banks to per­form stress tests/​scenario analy­ses that incor­po­rate the pos­si­ble neg­a­tive eco­nomic effects of a flu pan­demic in addi­tional to con­sid­er­a­tion of pos­si­ble addi­tional struc­tural weak­nesses (and shrink­age) in the economy.

In the sec­ond post, we men­tioned a gov­ern­ment study from a few years ago that esti­mated a five per­cent con­trac­tion in GDP if the USA faced a severe pan­demic. (In our best Jack Nicholson/​A Few Good Men courtroom-​scene imper­son­ation, we ask: is there any other kind of pan­demic, Danny?)

In today’s edi­tion of The Wall Street Jour­nal, Robert J. Barro and Jose F. Ursula pro­vide addi­tional evi­dence of the pos­si­ble neg­a­tive effects of a pan­demic in Pan­demics and Depres­sions. In it they pro­vide esti­mates of the his­tor­i­cal costs of such out­breaks. Well worth reading.

We’ll have more to say about the stress tests in our next post. The past week’s events pro­vide evi­dence to con­firm one of our hypothe­ses from a post one month ago when we asked Where Will the Bank Stress Test­ing Exer­cise Lead?

What Should It Mean to Earn a Master’s Degree?

We don’t answer that ques­tion here, but shouldn’t one be required to mas­ter something?

It Was a Mat­ter of Time

Since early Octo­ber, we’ve won­dered when we’d see the first edi­to­r­ial crit­i­ciz­ing MBAs and busi­ness schools for their role in the ongo­ing finan­cial cri­sis.¹ In our mind, much of the blame should be shared between busi­ness types, i.e., MBAs, and so-​called “quants,” with the major­ity of the blame placed on senior man­agers who per­mit­ted lax con­trols and mis­aligned incen­tives to exist.

We didn’t write about it when the thought orig­i­nally occurred to us nor dur­ing the inter­ven­ing six months-​or-​so, but we’ve been tempted to write on any num­ber of occasions.

Two events occurred last week that moti­vated us to write today. First, our excel­lent, for­mer TA, Brid­get Ardoyno, wrote to us that she has been blog­ging at http://​econ​mom​.blogspot​.com, and that reminded us of teach­ing MBAs (but in a good way).

The Main Shortcoming

The other event was the appear­ance of an excel­lent opin­ion col­umn, How Busi­ness Schools Have Failed Busi­ness, in last Friday’s edi­tion of The Wall Street Jour­nal. The col­umn, by Michael Jacobs, lists three main fail­ings of busi­ness schools with respect to the teach­ing and the cri­sis, but in fact, his three are all exam­ples of the lack of the qual­ity instruc­tion regard­ing con­trol and incen­tives.² Basi­cally, incen­tive issues are a type of con­trol prob­lem that arise in decen­tral­ized orga­ni­za­tion, where sub­or­di­nates are per­mit­ted a degree of auton­omy to act as they see fit.

The Root Causes

There is much to like about Mr. Jacobs’s crit­i­cism of busi­ness schools. How­ever, while we real­ize that edi­to­r­ial space is limited, he ignores the two main causes of the prob­lems that he iden­ti­fies: (1) poorly-​prepared stu­dents, and (2) an over-​emphasis on enter­tain­ment and teach­ing rat­ings that moti­vates instruc­tors to offer sim­plis­tic lessons at the expense of sub­stan­tive learn­ing. The first is related to the pathetic under­grad­u­ate edu­ca­tions most folks receive and the sec­ond is, well, an exam­ple of an incen­tive prob­lem. (We’ll get back to both of these below.)

Incen­tive Prob­lems Are Easy to Iden­tify, but Dif­fi­cult to Solve

Incen­tives prob­lems are as nat­ural and as old as recorded his­tory: every­body wants what they want. In the Old Tes­ta­ment, were Adam and Eve any­thing if not incen­tive prob­lems? Cain? We could go, but there’s no rea­son. All of the indi­vid­u­als were free to act in a decen­tral­ized set­ting, and failed to live up to their responsibilities.

In the New Tes­ta­ment, Jesus dis­cusses incen­tive prob­lems on any num­ber of occa­sions. Two of our favorites: (1) the para­ble of the faith­ful and unfaith­ful ser­vants (Luke 12:41 — 48) and (2) the para­ble of the good shep­herd, (John 10:11 — 13). All con­sider the fallen nature of man and his (com­pletely nat­ural) self­ish behavior.

That being said, there is not a more com­plex topic to address in busi­ness schools – or any type of school, for that mat­ter – than incen­tives. That’s because the topic involves social (or multi-​party) sit­u­a­tions where one needs to be able to pre­dict how another party will respond autonomously and freely to con­trol mech­a­nisms like com­pen­sa­tion schemes.

Many of our read­ers already know that deci­sions can be cat­e­go­rized as games against nature – single-​person decision-​theory – and games against oth­ers, i.e., game the­ory. Gen­er­ally – though not pre­cisely – one can think of the inves­ti­ga­tions in the nat­ural sci­ences as exam­ples of single-​person deci­sions and inves­ti­ga­tions in the social sci­ences as exam­ples of multi-​person deci­sions, e.g., how does one respond to a sur­vey so how should the researcher inter­pret that response?

Incen­tive or agency prob­lems – and infor­ma­tion eco­nom­ics prob­lems in gen­eral – can often be mod­eled math­e­mat­i­cally using game the­ory or sim­i­lar meth­ods. In many of these prob­lems of inter­est to busi­ness stu­dents, one decision-​maker – say, the supe­rior or prin­ci­pal – is attempt­ing to max­i­mize his own expected sat­is­fac­tion or prof­its while ensur­ing that (1) the other per­son – the sub­or­di­nate or agent – is will­ing to par­tic­i­pate with him (in the social set­ting like a firm or orga­ni­za­tion) and (2) with full knowl­edge that the sub­or­di­nate or agent will do what’s best for himself.

Those two con­di­tions – par­tic­i­pa­tion and incentive-​compatibility – con­strain the principal’s abil­ity to max­i­mize his own expected sat­is­fac­tion, and the lat­ter prob­lem is espe­cially vex­ing to solve because it means that one of principal’s con­straints is the other person’s opti­miza­tion prob­lem. How do you do what’s best for your­self while real­iz­ing that the other per­son is also behav­ing oppor­tunis­ti­cally (by doing what’s best for himself)?

Objec­tively mod­el­ing these issues as math­e­mat­i­cal prob­lems tends to require a rather high level of sophis­ti­ca­tion, and solv­ing the resul­tant prob­lem – or even know­ing when a math­e­mat­i­cal solu­tion exists – requires an even greater under­stand­ing of advanced cal­cu­lus, opti­miza­tion, real analy­sis, and other math­et­i­cal the­o­ries and tech­niques.³

Very few MBA stu­dents are pre­pared to tackle those top­ics (and their appli­ca­tions) at that level of understanding.

Our Root Causes, Again

A larger set of stu­dents can han­dle sim­pli­fied illus­tra­tions and exam­ples of prob­lems that tend to be more numer­i­cal in nature. Often, when taught in con­junc­tion with a math soft­ware pro­gram, they can gain a keen under­stand­ing of the sub­tle issues that arise in the study of incen­tives, e.g., pay­ing more for more out­put isn’t nec­es­sar­ily opti­mal nor incentive-​compatible.⁴

Unfor­tu­nately, the root causes that we iden­ti­fied above – igno­rance and selfishness/​greed – make it dif­fi­cult for most instruc­tors to offer and suc­cess­fully teach such a course to MBA students.

We’ll empha­size the stu­dents’ igno­rance and not the instruc­tors’; instead, we’ll focus on their selfishness.

Most MBA stu­dents are poorly pre­pared to think clearly, abstractly, and quan­ti­ta­tively, and that makes it a chal­lenge to teach them either (1) quan­ti­ta­tive sub­jects or (2) top­ics that can be effec­tively mod­eled, illus­trated, or explained in a quan­ti­ta­tive manner.

Incen­tive prob­lems fall into the lat­ter cat­e­gory. (What we’d call) sim­ple math­e­mat­i­cal or numer­i­cal mod­els pro­vide (by def­i­n­i­tion) abstract illus­tra­tions of par­tic­u­lar phe­nom­ena and behav­iors. They’re rarely solu­tions to real world problems.

Most MBA stu­dents are not sophis­ti­cated enough to han­dle that dis­tinc­tion; they want recipes, not thought processes, and recipes are eas­ier to teach and grade. It’s not because the stu­dents are stu­pid, but it often is because they were poorly-​trained as under­grad­u­ates and in require, core classes. Per Mr. Jacobs’s essay, there’s gen­er­ally not much evi­dence of profs teach­ing compensation-​related recipes in busi­ness schools because of the lack of rel­e­vant incentive-​related courses. Thatt’s evi­dence of absence (of the courses), rather than an absence of evidence.

There’s much more evi­dence of that behav­ior in finance classes, where stu­dents want recipes for val­u­a­tion. They’ll take abstract mod­els, with either unre­al­is­tic assump­tions or very, very spe­cial­ized assump­tions and unwit­tingly (and unknow­ingly) treat them as very prac­ti­cal and pre­cise meth­ods that cal­cu­late the one true value of the thing.

Unfor­tu­nately, they’re often encour­aged to do so by their pro­fes­sors because it’s much eas­ier to teach numer­i­cal – though irrel­e­vant or mis-​specified – recipes than it is to teach (and grade) thought processes.

In fact, that ten­dency to dumb-​down teach­ing even extends to some fac­ulty mem­bers’ research agen­das. Dur­ing our aca­d­e­mic career, we attended any num­ber of sem­i­nars where we heard the pre­sen­ter jus­tify his or her overly-​simplistic and vac­u­ous model by argu­ing that “we want to be able to explain it to MBA students.”

Imag­ine if med­ical research were con­ducted in the same man­ner? Or any seri­ous field of inquiry for that matter?

From our per­spec­tive, it’s com­pletely ass-​backwards (and, in fact, its pres­ence goes par­tially to explain why we’re in the pri­vate sec­tor, today).

In an ideal words, the ped­a­gog­i­cal empha­sis would be on edu­cat­ing the stu­dents by attempt­ing to pull-​them-​up to a level that they had not antic­i­pated nor even known existed, and not pre­sent­ing dumb-​downed “research” papers for enter­tain­ment or pre­tense, but, hey, the lat­ter alter­na­tive is easy, and one can gen­er­ally gar­ner higher teach­ing rat­ings by not chal­leng­ing the stu­dents, espe­cially if that per­spec­tive and tech­nique is per­va­sive within the school. (We knew any num­ber of fac­ulty mem­bers at very expen­sive and seem­ingly pres­ti­gious insti­tu­tions who would pro­vide “sam­ple” or “prac­tice” exams before test dates – the actual exams would have slightly-​changed num­bers; who would sched­ule fre­quent guest speak­ers because “the stu­dents like it (and we don’t have to pre­pare);” and would show videos of fac­to­ries or what­ever once per week because, again, “the stu­dents like it (and we don’t have to pre­pare).” (Geez, it’s almost enough to make one cynical.)

Any­way, that com­bi­na­tion of poor prepa­ra­tion of most stu­dents and the mis­aligned incen­tives of b-​school pro­fes­sors make true learn­ing about these thorny and dif­fi­cult (social) prob­lems, which all firms and orga­ni­za­tions face, nearly impos­si­ble to achieve.

Why It’s Dif­fi­cult to Teach about Incen­tives Issues

It’s not just the math­e­mat­i­cal nature of the most com­pelling mod­els of incen­tives that makes teach­ing dif­fi­cult. It’s also because the prob­lems are not par­tic­u­larly robust. By that we mean, illus­tra­tions and exam­ples must be care­fully (and empa­thet­i­cally) con­structed, or they’re either (1) extremely stu­pid and un-​insightful, or (2) extremely spe­cial­ized, detailed, and so qual­i­fied (by assump­tions) that they need a very high degree of math­e­mat­i­cal under­stand­ing to com­pre­hend and solve (and they end-​up say­ing very lit­tle, anyway).

The fer­tile mid­dle ground requires instruc­tors and stu­dents to pos­sess a rather high level of eco­nomic rea­son­ing and strong math skills. We’ll avoid crit­i­ciz­ing instruc­tors, here, but unfor­tu­nately, many MBA pro­grams have de-​emphasized, elim­i­nated, or con­sol­i­dated micro­eco­nom­ics courses, and those courses are (or were) the best place to develop the req­ui­site level of eco­nomic rea­son­ing. In those courses and well-​designed incen­tives courses, there is no sub­sti­tute for a lot of hard work.

By the way, we unsuc­cess­fully tried to estab­lish just such a Con­trol & Incen­tives course at our last aca­d­e­mic employer, but there were no required econ courses and only a few very moti­vated, very curi­ous, or previously-​trained stu­dents would enroll in the elec­tive. (Too much work!) As a pub­lic ser­vice, we’ll attempt to put that course mate­r­ial on-​line in the near future.

But Dif­fi­culty Is Really No Excuse

It’s up to trustees and deans to ensure that schools and pro­fes­sors edu­cate MBAs, rather than attempt to be “pop­u­lar.” That’s true at both the indi­vid­ual level and the sum of the indi­vid­ual lev­els, i.e., the school level, where administration’s allow them­selves to be sub­jected to the whims of Busi­ness Week writ­ers and sur­vey respon­dents. As a fac­ulty mem­ber, we won our share of teach­ing awards while try­ing to do the right thing; so, there’s no sour grapes here, and we know that it can be done; how­ever, we sus­pect that the short-​term empha­sis will not change. There’s too much iner­tia and very lit­tle confidence.

From our self­ish per­spec­tive, it’s not as bad as it seems because that gen­eral fail­ure to learn and teach presents many oppor­tu­ni­ties for con­sul­tants who under­stand both incen­tives and risk – peo­ple like our­selves. (We’ve writ­ten exten­sively about both issues, espe­cially as they per­tain to the cur­rent finan­cial cri­sis. Please search the archives if you’re inter­ested. Our Illus­tra­tions dis­cuss many of these issues, too.)

Are you sure that your firm or orga­ni­za­tion isn’t about to do some­thing stu­pid with incen­tive pay or claw­backs or whatever?

We’ll likely con­tinue to revise and edit this post in the near future. (It’s long and there’s prob­a­bly a few typos, but then TQM is rarely optimal.)

Copy­right © 2009 Spero Consulting.

Foot­notes:

Update: We have sev­eral newer posts on this topic, includ­ing a few on the need to include the effects of a poten­tial swine flu epi­demic on GDP in the sce­nario analy­ses and this one: SCAP, The Government’s Naïve Stress Test­ing Exer­cise.

We read the SCAP doc­u­ment pub­lished on the Fed­eral Reserve web site. It describes the government’s stress test­ing régime for the nation’s 19 largest banks. It’s all very inter­est­ing. (Well, not really.)

How­ever, we thought the most inter­est­ing sen­tence in the doc­u­ment was this one from the sec­ond para­graph on the first page: “A need for addi­tional cap­i­tal or a change in com­po­si­tion of cap­i­tal to build a buffer under an eco­nomic sce­nario that is more adverse than expected is not a mea­sure of the cur­rent sol­vency or via­bil­ity of the firm.” (We added the italics.)

Uhh, do you think it would have been nice for the reg­u­la­tors to have requested con­fi­den­tial, pri­vate liq­uid­ity and solvency-​related stress tests to start with? (Maybe they did, and they’re not telling anyone.)

So, we ask, exactly what is the point of the SCAP exer­cise? (We’ve asked that before.)

The notion of cap­i­tal being any kind of buffer only makes sense in a trad­ing port­fo­lio with com­pletely liq­uid assets, i.e., take your upfront cash (cap­i­tal), buy Trea­suries, repo them, take the pro­ceeds, buy more Trea­suries, repo them, and con­tinue lever­ag­ing as long as you can… Even in that case, the cap­i­tal isn’t quite a buffer for cred­i­tors, espe­cially as the lever­age increases.

With typ­i­cal illiq­uid bank loans and other such unmar­ketable invest­ments, the notion that the level of book value of com­mon equity pro­vides a “buffer” or “cush­ion” is vacant, i.e., that it is some mea­sure of liq­ui­da­tion value if the firm’s sol­vency is ques­tioned. (Even with liq­uid assets, if other traders know that a port­fo­lio must be liq­ui­dated, then the amount of cap­i­tal invested is then the max­i­mum, limited-​liability loss dur­ing the feed­ing frenzy, and is not the net liq­ui­da­tion value.)

For new read­ers, it’s worth not­ing that we’ve writ­ten about the government’s stress test on a few occa­sions – most recently on April 7 in Where Will the Bank Stress Test­ing Exer­cise Lead? (If you read that post, you’ll under­stand why we rec­om­mend con­fi­den­tial, pri­vate (seem­ingly) ran­dom or ad hoc requests by reg­u­la­tors for liq­uid­ity and sol­vency stress tests – noth­ing for­mal, stan­dard­ized, or com­pre­hen­sive that would indi­cate such a pol­icy or inves­ti­ga­tion actu­ally existed. There’s no rea­son to raise need­lessly sus­pi­cions by announc­ing such a program.)

In addi­tion, we have writ­ten about the silli­ness of cap­i­tal ratios a few times, also – in both last week’s aptly-​named post, More Cap­i­tal Ratio Silli­ness, and March Mad­ness: New Bank Cap­i­tal Require­ments from Saint Patrick’s Day. Other than pos­si­bly, ten­u­ously con­stru­ing the excepted sen­tence above from the SCAP doc­u­ment as an admis­sion of irrel­e­vancy (given what should be the true and impor­tant issue of inter­est dur­ing a liq­uid­ity cri­sis), we saw noth­ing in the SCAP doc­u­ment that notices or dis­cusses the test’s defi­cien­cies, par­tic­u­larly the short-​coming of empha­siz­ing book cap­i­tal at the expense of some­thing real. That might be a good thing – if the reg­u­la­tors under­stand the weak­nesses and con­sciously elim­i­nated that dis­cus­sion. How­ever, it’s a bad thing if they don’t under­stand or couldn’t iden­tify those short-​comings.

Oh, well. Let’s pray for good luck for these firms and the economy.

P.S. We may con­tinue to edit this post tomor­row or in the near future.

The Irrel­e­vance of Book Equity and Cap­i­tal Ratios

Last month we wrote March Mad­ness: New Bank Cap­i­tal Require­ments. In that, we stated: “We’ve always thought that such require­ments were stu­pid and pro­vided a false sense of secu­rity: kind of like duck­ing and cov­er­ing under one’s school desk as prac­tice and prepa­ra­tion for a nuclear explosion.”

We also pro­vided an exam­ple from an old merger of two rust belt firms. At the time of the merger, the firms had com­bined book val­ues of $2.0 bil­lion ($2,000 mil­lion) but com­bined mar­ket val­ues of about $300 mil­lion. At its the­o­ret­i­cal best, book value rep­re­sents net expected future ben­e­fits from past trans­ac­tions or events, whereas mar­ket value rep­re­sents net expected future ben­e­fits from all trans­ac­tions and events – both past and antic­i­pated. In the rust-​belt merger exam­ple, at the time, equity investors had con­cluded that the future would be bleak, and it turned out to be, but also at the time, no loan covenants were breached.

We think that’s worth restat­ing because on Mon­day, Bank of Amer­ica reported com­mon share­hold­ers’ equity of $166 bil­lion, yet finance​.google​.com reports that the mar­ket value of com­mon stock was about $50 bil­lion. Now, exactly how rel­e­vant is the book value of $166 bil­lion when investors value the firm at less than one-​third of it? We’d say, “not very.”

Think about it. Do you care if your house has a net book value of $166,000 if its net mar­ket value is $50,000. Or, ignor­ing tax-​planning impli­ca­tions, do you care if your lever­aged port­fo­lio has a book value of $166,000 if it can be liq­ui­dated for $50,000? Would you make deci­sions based upon the actual net equity of $50,000 or the reported net equity of $166,000? What do you think that, say, poten­tial cred­i­tors would con­sider when offer­ing financ­ing? More­over, what would you want them to con­sider if those cred­i­tors were act­ing as agents for you? There may be reg­u­la­tory impli­ca­tions to the book val­ues, but it seems that investors have con­cluded that those reg­u­la­tions (and all of the sub­si­dies) haven’t pro­vided enough sta­bil­ity or value to secure their resid­ual interests.

Also, real­ize that B of A’s net book value is greater because its lia­bil­i­ties are worth less than they were, which is not quite com­pletely worth­less. The prices for claims on the gross assets have declined. These are the silly, unre­al­ized account­ing gains are shown as result­ing from increases in credit spreads. In B of A’s case, they rec­og­nized at least $2.2 bil­lion of them in the first quar­ter although it was prob­a­bly more. (We wrote about this topic in Decem­ber in Mark­ing Debt to “Mar­ket” or Addi­tion Through Sub­trac­tion. 

By the way, and of course, B of A is not alone with its imbal­ance between its lower net mar­ket value and its much higher net account­ing value. In fact, Citi’s ratio of market-​to-​book equity ratio is sub­stan­tially smaller. And remem­ber, that’s despite the hun­dreds of bil­lions of dol­lars of guar­an­tees made by the U.S. gov­ern­ment on Citigroup’s behalf.

With Pri­vate Equity and other Illiq­uid Invest­ments, then most likely, Yes.

We’ve writ­ten about uni­ver­sity endow­ments on a few occa­sions, with Set an Exam­ple, Mr. Cohon! being the most recent. While we’re fond of just about every­thing we write, in this sub­set of posts, we par­tic­u­larly like our anal­ogy of invest­ing and bicy­cling in The Harvard-​Yale-​CALPERS Cycling Club. In fact, we’ll prob­a­bly extend it when we have the opportunity.

An arti­cle in this past Saturday’s Tribune-​Review, Carnegie Mel­lon loses $300 mil­lion in invest­ments, reminded us of an impor­tant fact that we haven’t men­tioned before, and that relates to the dif­fi­culty for investors of illiq­uid assets to esti­mate their losses in a timely fash­ion. Given the recent end of the first-​quarter, it seems like a worth­while time to men­tion this fact (although while the Carnegie Mel­lon arti­cle spurred us to write, we haven’t checked to see the size of CMU’s invest­ments in pri­vate equity.)

First, recall that many uni­ver­si­ties crowed that there endow­ments had lost less than the gen­eral “mar­kets” as of last June 30. Other than supe­rior invest­ing abil­ity or good for­tune, there is another pos­si­ble expla­na­tion for that phe­nom­e­non, which will likely now hurt them.

By now, just about every­one who would visit this page under­stands the issues related to mark-​to-​market account­ing – mainly that there are very few deep and liq­uid mar­kets with cur­rent, reli­able prices; so, the book value that is sup­posed to be a “mark-​to-​market price” is often an inter­nal mark-​to-​model cal­cu­la­tion or exter­nal quote from a friend. Those cal­cu­la­tions may or may not rep­re­sent any­thing other than the appli­ca­tion of a for­mula or algo­rithm, and a quote from a friend is just that – a friendly quote, but that’s not today’s topic.

Instead, con­sider one of the gross­est absur­di­ties of invest­ing life: a fre­quent account­ing treat­ment for pri­vate equity. By def­i­n­i­tion, if it’s pri­vate equity there is no mar­ket and no mar­ket price, yet often it must be “marked” to it.

While that’s prob­lem­atic – actu­ally it’s just plain stu­pid and con­tra­dic­tory – that’s not the larger prob­lem with which cer­tain endow­ments may now have face. The big­ger prob­lem is that the endow­ment may report the “val­ues” of cer­tain pri­vate equity funds on a three-​to-​six month lag – depend­ing upon when the reports are sent and when your invest­ment com­mit­tee meets to review and accept them.

So, imag­ine that you are an endow­ment invest­ment offi­cer and like many oth­ers, you’ve invested in a pri­vate equity fund or two or three, because, hey, at the time, there didn’t seem to be much risk and the his­tor­i­cal and pro­jected returns looked great. (Well, that’s what the sales­men and con­sul­tants said, and they’re alumni or their fathers are on the board of trustees or whatever.)

Some­time in May, as a fund investor, you’ll receive fund state­ments with val­ues as of Decem­ber 31 or even ear­lier, and you’ll have to re-​mark the endow­ment val­ues to those reported values.

Does the reader think that those pri­vate equity fund val­ues may show declines? Except in very rare cases, we’d think that val­ues would have had to decline – in some cases sub­stan­tial declines – espe­cially given those “as-​of” dates. Or, does the reader think that such deferred losses have been antic­i­pated and com­mu­ni­cated to fund investors? In our mind, that would be a very hope­ful out­look, espe­cially if the pri­vate equity fund man­ager had made cap­i­tal calls dur­ing in the interim, i.e., asked investors to fund their remain­ing con­trac­tual com­mit­ments. In that case, the fund man­agers would have had very lit­tle incen­tive to share addi­tional and pre­cise bad news with their investors.

So, given the lag, if such pro­jec­tions haven’t been pro­vided to endow­ments and accepted by them, then antic­i­pate endow­ments with pri­vate equity hold­ings to real­ize addi­tional losses in the very near future – most likely dur­ing the sec­ond quar­ter of 2009, which for many, is the last quar­ter of their fis­cal year. We doubt that other illiq­uid invest­ments fared much bet­ter or are marked more fre­quently; so, expect a rever­sal of last June’s (rel­a­tively) good fortune.