earnings

  • 12 Apr 2013 at 2:48 PM
  • Banks

J.P. Morgan Isn’t Doing This For Fun You Know

Yesterday JPMorgan research released a 328 page report arguing that global tier 1 investment banks were “un-investable,” and today JPMorgan reported record first-quarter earnings of $1.59 per share versus $1.40 consensus, so I guess it sort of looks like there’s a disconnect. But not really? Here are the analysts on banking regulation:

We believe Tier I IBs are un-investable at the moment and the right time to make a switch into Tier I IBs would be if we get more clarity on regulations providing us comfort around the ROE potential of Tier I IBs or we see IBs having to spin-off their businesses leading to capital return to shareholders. We believe Tier I IBs will continue to remain more exposed to the IB regulatory changes as they try to “defend their turf” while Tier II IBs have the option to step back more aggressively.

Jamie Dimon, meanwhile, responded to analyst questions this morning by more or less begging the analysts themselves to call their congresspeople and defend JPMorgan’s turf, arguing that banks are safer than ever, that JPMorgan’s size and scale and universality provides services that clients want and is good for the world, and that “I hope at one point we declare victory and stop eating our young.”1

The analyst report is a fascinating bit of business. The claim is that global investment banking – by which they mean of course FICC trading – will see market share move toward top-tier banks, driven mainly by the commoditization of the FICC business with clearing and greater price transparency around derivatives, as well as higher capital requirements and more complex and Balkanized regulation around trading activities. The result: Read more »

Remember Deutsche Bank’s rather poor earnings report a couple of months ago? Well, it turns out that things have gotten worse, because people and regulators continue to sue Frankfurt’s most downtrodden bank. Read more »

  • 31 Jan 2013 at 2:04 PM
  • Banks

Deutsche Bank Improved Its Balance Sheet By Losing A Lot Of Money

Bank earnings season is always a little surreal, I guess because there’s an inherent surrealism about banking. Deutsche Bank reported earnings today,1 and those earnings had an up-is-down quality that Bloomberg’s summary captured in this amazing sentence:2

Deutsche Bank AG, Europe’s biggest bank by assets, exceeded a goal for raising capital levels as co-Chief Executive Officer Anshu Jain focused on bolstering the firm’s finances rather than limiting losses.

So there’s one way of running a business where you bolster your finances by making money. And then there is global banking. Here is another, possibly even more astonishing line from the same article:

Deutsche Bank “took pain” in the quarter by booking a loss to boost its capital ratio without selling shares, Jain said.

Booking a loss to boost its capital ratio. Losing money, in the regular universe, should reduce your capital: capital is mostly retained earnings. Everything here is backwards.

Here is how Deutsche Bank boosted its capital ratios without (1) raising capital from the market or (2) making money: Read more »

  • 16 Jan 2013 at 5:54 PM

Goldman Welcomed New CFO With A Nice Earnings Beat

If you read a lot of media coverage of Goldman Sachs earnings you get the sense that the most important number the firm reports is average compensation per employee, which this year was a nice oh-so-close-to-round $399,506. I CONCUR, of course.1 Also of interest is the comp ratio, which was only 39% this year, as less of the spoils of Goldman’s labors go to the people in the building doing the labors, and more go to the people providing the capital. Progress!

The analysts on the earnings call were not all that focused on comp, which I attribute to jealousy, but there were some exceptions. Like JPMorgan’s Kian Abouhossein, who pressed the Viniar/Schwartz CFO tag-team about expenses and headcount in Investing & Lending, playing an enjoyable guessing game with the twin CFOs about staffing levels in Investing & Lending:2

I mean, there are only few hundred — I assume there are only a few hundred people running in this division. I can’t believe there’s thousands of — I would be even surprised if it’s 1,000 people. So I’m just wondering why you’re having $2 billion to $3 billion of expenses. Is it interest expenses or is it something else? I just don’t understand why there’s such a big expense level.

Because the few hundred people are paid really well? Other? Dunno. You can guess why Schwiniar might have stalled here (and on a later question about I&L Basel III RWAs); the Investing & Lending business model has gotten some negative attention recently. The problem is basically that it does things like investing and lending, which almost violate the Volcker Rule, or would if it existed, which it doesn’t, yet.

Here is the FT’s Tracy Alloway on Goldman’s earnings: Read more »

  • 11 Jan 2013 at 1:32 PM
  • Banks

Wells Fargo Mostly Putting Deposits Into Gold Ingots These Days

Bank earnings season kicked off today with Wells Fargo’s announcement, and since I have nothing really to say about Wells Fargo earnings I figured the least I could do was put up some charts instead. Not on earnings – they’re up! net interest margin is down! on balance, gnash your teeth a little! – but on what Wells Fargo is doing with all the money it’s got.

This seems like a popular question to ponder, since it’s got rather a lot of money. So today brings the Journal‘s vividly headlined “Wads of Cash Squeeze Bank Margins”, and earlier we had Frank Partnoy and Jesse Eisinger’s attempt to find out where Wells is hiding all its fraud. The main thing is:

  • Banks have lots of deposits because everybody’s scared of everything so they put their money in the bank.1
  • Banks aren’t making lots of loans for some reason, with the reason ranging from “banks are a bunch of scumbags” to “you’re all a bunch of deadbeats.”
  • So they have money left over.
  • So they put it somewhere.

A natural question is “where is the somewhere?” and here is where Wells puts it:

That’s just various bits as a percentage of total deposits. You can see loans have decreased as a percentage of deposits since the crisis; other risky-type assets – trading assets and available-for-sale corporate and mortgage bonds, etc. – have increased a bit but not enough to make up for that drop: Read more »

  • 25 Oct 2012 at 4:28 PM
  • Banks

Banking Boring Again Even At Credit Suisse

One way to make a lot of money in banking is just to be really good at it. But this is not a very good way! There are lots of people who want to make a lot of money in banking, and all of them1 have at least considered the approach of “just be good at it,” so you have no real competitive edge if that’s your strategy. You need to be creative and think outside the box, as you might say, if you were not very good at banking, as the law of large numbers says you are not.

I love me some Credit Suisse; they think outside the box. Then they sell the box to themselves in a roundabout fashion that magically removes it from their balance sheet. So when I saw this

“As we continue to reduce costs, continue to optimize our capital and we continue to have momentum on the client side we think we will be able to improve our return on equity toward that 15 percent target,” Dougan said in an interview with Bloomberg Television. “That’s something that’s achievable.”

I had so much hope! I mean, “reduce costs” is boring and sad, and “momentum on the client side” is just like “be good bankers” which whatever, but “optimize our capital” could mean all sorts of devious things.

It probably does but I couldn’t find them. I mean, other than the usual devious things, which start with “Basel II.5 core tier 1 ratio increased by 2.2 percentage points to 14.7%, total capital ratio increased by 1.0 percentage point to 21.2″ and segue right along into this funding stack: Read more »

  • 18 Oct 2012 at 1:15 PM
  • Banks

Morgan Stanley Now 23% Safer

A value-at-risk model basically works like this. You have some stuff, which is worth X today. Tomorrow it will be worth X + Y, where Y ranges from more or less negative infinity to positive infinity. Y is a function of a bunch of correlated random variables, rates and credit and stock prices and general whatnot. You look at a distribution of moves in those variables and take (usually) a 2-standard deviation daily move; if 95% of the time rates move by -10 to +10 basis points, your VaR model will assume a -10bp or +10bp move, whichever is bad for you. You take the 95%-worst-case, taking into account correlation etc., and tot up how much you’d lose in that case. Then you write that number down and feel a bit better, since you’ve sort of implicitly replaced “we have $X today and will have some number between negative and positive infinity tomorrow” with “we have $X today and will have some number between ($X – VaR) and positive infinity tomorrow,” though of course the first statement is true but unhelpful and the second is not true and also unhelpful.

But that aside! You get your VaR from a distribution of your variables, but the obvious question is what distribution. A good answer would be like “the distribution of those variables over the next three months,” say, for quarterly reporting, but of course that is only a good answer because it begs the question; if you knew what would happen over the next three months you would, one assume, always end those three months with more than $X and this VaR thing would be moot or moot-ish.1

So instead you look at things that you think will allow you to predict that future distribution as accurately as possible, which is epistemically troubling since VaR is a measure of how inaccurate your predictions might turn out to be. Anyway! You pick a distribution of variables based on the sort of stuff that you always use to estimate future distributions in your future-distribution-estimating business, which could mean distributions implied by market prices (e.g. option implied vol) but which seems to mostly mean historical distributions. You look at the last N days of data and assume that the world will be similarly distributed in the following M days, because really what else is there to do.

Picking the number of days to use is hard because, one, this is in some strict sense a nonsense endeavor, but also two, the world changes over time, so looking back one year is for instance rather different from looking back four years. Here is how different: Read more »