Do you want to invest like Warren Buffett? Sure you do. You know who will tell you how? Strangely, some guys at AQR:*
[W]e create a portfolio that tracks Buffett’s market exposure and active stock-selection themes, leveraged to the same active risk as Berkshire. We find that this systematic Buffett-style portfolio performs comparably to Berkshire Hathaway.
They acknowledge that Robo-Buffett doesn’t incur transaction costs that flesh-Buffett does (because R.-B. is as of yet just a simulation) but, that aside, “comparably” is an understatement:
Whee! Go Robo-Buffett! Who, intriguingly, looks a lot like … AQR: Read more »
Mutual funds are kind of weird in that they basically aren’t allowed to get paid for performance, so they charge investors a flat percentage of assets under management, so for mutual fund managers looking dapper on CNBC is often more profitable than sitting in your office researching stocks. Still – and perhaps perversely – performance does seem to attract assets, so if you run a mutual fund company there is quite a bit of value in trying to get your portfolio managers to pick the right stocks. There are various ways to do that: you could, for instance, ask them politely to do a good job, or yell at them when they don’t, or build them a treehouse. But, who are we kidding, basically there’s money: if you give them more money for picking good stocks, and less money for picking bad stocks, then you will probably attract good stock-pickers and encourage them to pick good stocks.
I enjoyed this paper immoderately: Read more »
We’ve talked a bit before about how there’s a booming academic business in papers finding that investment managers do or do not add value versus non-managed alternatives like passive indexing or keeping your money under your pillow and just burning a constant percentage of it every month. Part of why that’s a thing is that the data can be prodded, smooshed, or cherry-picked to say many different things, and so they are. I enjoyed this paper about mutual funds by Stanford GSB profs Jonathan Berk and Jules Van Binsbergen (NBER today here, SSRN in April here) in part for its discussion of data problems, which starts with the fact that they used the industry-standard (in the academic-papers-about-mutual-funds industry) CRSP database and compared it to Morningstar data because “even a casual perusal of the returns on CRSP is enough to reveal that some of the reported returns are suspect.” Suspect like:
We then compared the returns reported on CRSP to what was reported on Morningstar. Somewhat surprisingly, 3.3% of return observations differed. Even if we restrict attention to returns that differ by more than 10 b.p., 1.3% of the data is inconsistent. An example of this is when a 10% return is accidentally reported as “10.0″ instead of “0.10″.
That is one way to get alpha. Anyway they look at the data using a (strangely) unusual metric of dollar value added, which is roughly alpha (gross excess return over some investable benchmark, in this case a Vanguard index fund) and multiplying it by assets under management, the intuition being that making 1% excess return on a $10bn portfolio is more impressive than doubling your $10 bet at the craps table. And they find that mutual fund managers are better than controlled money burning by the thinnest of margins: Read more »
One of the more fertile areas of academic finance is explaining why M&A is so bad – mergers seem to be on average value destructive, so why do they keep happening? Are CEOs just stupid? Are bankers just evil and persuasive? Here’s one answer that may be worth considering, which is that it looks like a good idea to acquire a successful company run by a talented and dedicated founder-CEO, but then things go pear-shaped because that founder-CEO either (1) departs, voluntarily or otherwise, with his giant bags of loot, or (2) suddenly loses interest in running his or her company when it’s owned by someone else and that someone else is now the founder-CEO’s boss:
Bidder gains are lower for acquisitions that involve targets with a founder CEO than for acquisitions of targets without a founder. The difference in bidder gains between takeovers of targets with founder CEOs and those without a founder is statistically significant, economically material, and robust to several model specifications that include a wide variety of deal- and firm-level control variables, like form of payment, competition, relative size, as well as some characteristics of the target CEO, such as his cash flow and voting stakes, age, and tenure.
That’s from this paper by Nandu J. Nagarajan, Frederik P. Schlingemann, Marieke van der Poel and Mehmet F. Yalin. It doesn’t clear up the whole mystery – non-founder mergers have also destroyed some value here and there, though I guess statistically less so – but I found it kind of fun. Read more »
A stylized picture of a credit default swap is that it’s a way for a bank to offload to the market the credit risk of loans that it makes, while still funding those loans and making a profit on them. If you start from that stylized picture, you must at some point get comfortable with the stylized fact that this market is probably rife with insider trading. Turns out it is! Part of the reason for that is that it’s maybe legal,* part of it is just the general run of market-participant scumminess,** but there’s also the fact that the basic model sort of requires it. Here is the basic model:
- private side bank employees evaluate a company for a loan, using lender materials that contain nonpublic information and banker relationships that are all about nonpublic information,***
- private side bank employees negotiate and fund that loan with a company,
- [magic happens], and
- public side bank employees buy CDS on some but not all of the companies that the bank lends to in sizes that vary among companies.
So, I mean, I generally trust that most banks are over-compliant on this point and the magic happens behind a Chinese wall and so forth, but still, that sequence of events should make you a tiny bit suspicious if you’re anti insider trading in CDS.
Anyway, if you continue on with that stylized picture you’ll notice that, while the existence of traded CDS allows for a two-sided market of public-market speculators who buy CDS to bet against companies that they don’t lend to (or that they lend to only in public bond form), the origin of and net demand for single-name corporate credit protection comes largely from banks who do private-side lending and are probably hedging that lending. This is basically true.
That sucks for the CDS writer, doesn’t it? Read more »
Oh am I a sucker for this sort of thing:
This paper proposes a theoretically sound and easy-to-implement way to measure the systemic risk of financial institutions using publicly available accounting and stock market data. The measure models credit risk of banks as a put option on bank assets, a tradition that originated with Merton (1974). We extend his contribution by expressing the value of banking-sector losses from systemic default risk as the value of a put option written on a portfolio of aggregate bank assets whose exercise price equals the face value of aggregate bank debt. We conceive of an individual bank’s systemic risk as its contribution to the value of this potential sector-wide put on the financial safety net. To track the interaction of private and governmental sources of systemic risk during and in advance of successive business-cycle contractions, we apply our model to quarterly data over the period 1974-2010. Results indicate that systemic risk reached unprecedented highs during the years 2008-2010, and that bank size, leverage, and asset risk are key drivers of systemic risk.
A “theoretically sound and easy-to-implement way to measure the systemic risk of financial institutions” sounds pretty good! Is it easy to implement? Well let’s implement it to find out. [Pounds head against Google Spreadsheets.] Umm. Okay, I guess it was easy? I don’t know, I can’t fully replicate their numbers; tell me where I’m wrong in the comments. Or don’t. Read more »
There are probably some things that bankers could advise companies to do that are unequivocally bad. Obviously if I were Bank X’s Executive Director and Global Head of Lighting Money on Fire, and I went around showing companies a pitch book that was all “signalling benefits of lighting money on fire,” and I got a bunch of companies to do it, and it became a thing, and academics and industry groups did studies on it, I suspect that they would consistently report that the trade was NPV negative at a 1% level of significance. But maybe not, because, industry groups. Anyway though you can probably imagine some of these things existing outside of silly stylized examples – in hindsight, CDOs of mezz ABS look pretty close to lighting money on fire – but not too many of them. Because if a thing is always bad through the cycle then you’d quickly run out of people to do it, for some value of “quickly.”
Is it possible that mergers are such a thing?
No, it is not!
There, that was easy. Nor, obviously, are they the sort of thing that is unequivocally good – I suppose there are such things?* Instead, mergers are like, I dunno, hedge funds. You can ask the specific question of “will this merger be good for this company?,” and the answer will mostly be “maybe” but said with DCFs and stuff. Or you can ask the general question of “are mergers mostly good or mostly bad?” and the answer will be entertainingly indeterminate. Thus mergers are unequivocally good for academics, QED. Anyway this is a strange paper: Read more »
The beginning of April brings with it, among other things, a new batch of NBER papers, and here is one that is mildly amusing but probably not an April Fool’s prank, although it is called “Tailspotting: How Disclosure, Stock Prices and Volatility Change When CEOs Fly to Their Vacation Homes,” so, y’know, maybe. Anyway it’s by Stern professor David Yermack and … if it is fake, it’s still probably correct:
Companies disclose favorable news just before CEOs leave for vacation and delay subsequent announcements until CEOs return, releasing news at an unusually high rate on the CEO’s first day back. When CEOs are away, companies announce less news than usual and stock prices exhibit sharply lower volatility. Volatility increases immediately when CEOs return to work. CEOs spend fewer days out of the office when their ownership is high and when the weather at their vacation homes is cold or rainy.
Except their ski chalets? I don’t know. Also this sentence should win some sort of award: “However, a bivariate probit model presented below indicates that news disclosures appear to be linked to CEOs’ vacations even after using weather variables to control for endogeneity of the vacation schedule.”*
The basic result is not that surprising; if I learned one thing from this paper it’s less “CEO activities are an important part of the short-term news relating to a stock” and more “it is possible to use vacation home property records and FAA databases to find out when CEOs visit their vacation homes, and that that is what your Stern tuition is paying for, which, okay!” Still here are two passages to maybe think about: Read more »
The Federal Reserve has this new paper out about TARP that does a bit of highly suggestive eyebrow raising about some banks that shall remain nameless. They start from the awkward fact that TARP wanted everything in one bag but didn’t want the bag to be heavy, or as they put it:
The conflicted nature of the TARP objectives reflects the tension between different approaches to the financial crisis. While recapitalization was directed at returning banks to a position of financial stability, these banks were also expected to provide macro-stabilization by converting their new cash into risky loans. TARP was a use of public tax-payer funds and some public opinion argued that the funds should be used to make loans, so that the benefit of the funds would be passed through directly to consumers and businesses.
So you might reasonably ask: were TARP funds locked in the vault to return the recipient banks to financial health, or blown on loans to risky ventures, or other? Well, here is Figure 1 (aggregate commercial and industrial loans from commercial banks in the U.S.):
So … not loaned then. But that’s not important! The authors are actually looking not primarily at aggregate amounts of loans but at riskiness of loans and here’s what they get: Read more »