When you hate on certain people and things as long as I’ve hated on the banking system and Tim Geithner, you start to notice certain things. Patterns.
I read Tim Geithner’s book Stress Test last week, and instead of going through and sharing all the pains of reading it, which were many, I’m going to make one single point.
Namely, Tim was unqualified for his jobs and head of the NY Fed, during the crisis, and then as Obama’s Treasury Secretary. He says so a bunch of times and I believe him. You should too.
He even is forced at some point to admit he had no idea what banks really did, and since he needed someone or something to blame for his deep ignorance, he somehow manages to say that Brooksley Born was right, that derivatives should have been regulated, but that since she was at the CFTC everybody (read: Geithner’s heroes Larry Summers and Robert Rubin) dismissed her out of hand, and that as a result he had no ability to look into the proliferating shadow banking or stuff going on at all the investment banks and hedge funds. So it was kind of her fault that he wasn’t forced to understand stuff, even though she warned people, and when shit got real, all he could do was preserve the system because the alternative would be chaos. And people should fucking thank him. That’s his 600 page book in a nutshell.
Let’s put aside Tim Geithner’s mistakes and his narrow outlook on what could have been done better, and even what Dodd-Frank should accomplish, for a moment. It’s hard to resist complaining about those things, but I’ll do my best.
The truth is, Tim Geithner was a perfect product of the system. He was an effect, not a cause.
When I dwell on the fact that he got the NY Fed job with no in-the-weeds knowledge or experience on how banks operate, there’s no reason, not one single reason, to think it’s not going to happen again.
What’s going to prevent the next NY Fed bank head from being as unqualified as Tim Geithner?
Put it another way: how could we possibly expect the people running the regulators and the Treasury and the Fed to actually understand the system, when they are appointed the way they are? In case you missed it, the process currently is their ability to get along with Larry Summers and Robert Rubin and to look like a banker.
Before you go telling me I’m asking for a Goldman Sachs crony to take over all these positions, I’m not. It’s actually not impossible to understand this system for a curious, smart, skeptical, and patient person who asks good questions and has the power to make meetings with heads of trading floors. And you don’t have to become captured when you do that. You can remember that it’s your job to understand and regulate the system, that it’s actually a perfectly reasonable way to protect the country. From bankers.
Here’s a scary thought, which would be going in the exact wrong direction: we have Hillary Clinton as president and she brings in all the usual suspects to be in charge of this stuff, just like Obama did. Ugh.
I feel like a questionnaire is in order for anyone being considered for one of these jobs. Things like, how does overnight lending work, and what is being used for collateral, and what have other countries done in moments of financial crisis, and how did that work out for them, and what is a collateralized debt obligation and how does one assess the associated risks and who does that and why. Please suggest more.
I don’t want to say too much because I’m not even halfway through but here’s one thing: Geithner is surprisingly honest about certain things and predictably dishonest, or at least misleading, about other things.
And although at first I thought it would be purely painful to read this book, since I don’t have any respect for the guy, now I’m glad I’m doing it, because it exposes so much about how the old boys network operates. It’s material.
It’s unusual that I find myself in the position of defending Wall Street activities, but here goes.
I just don’t think HFT is that big of a deal relative to other Wall Street evils. I have written a couple of times about HFT and I’m not a huge fan, and I don’t buy the “liquidity is good and more liquidity is better” argument: at some point enough is enough. I do think that day-to-day investors have largely benefitted from it but that people whose money is in massive funds which are regularly traded have seen their money get skimmed every month. Overall it’s a smallish negative tax on the average person, I’d expect.
Here’s why HFT deserves some of our hatred: there’s way too much human resources going into this stuff and it’s embarrassing, what with the laying of cables and blasting through mountains and such. And it’s a great sociological look into the absolutely greed-led mindset of the Wall Street trader, but honestly I think we already had that. It’s really business as usual at a microscopic scale, and nobody should really be surprised to learn that people will do anything to make money that’s technically possible and technically legal, and that they will brag about how they’re making the world a better place while they do it. Same old same old.
So I’m not saying HFT is awesome and we should encourage more of it. I’m all for thinking about how to slow down trading to once a second and make it “more fair” for more players (although that’s hard to do even as a thought experiment), or taxing transaction to make things slow down by themselves, which would be easy.
But here’s the thing, it’s not some huge awful thing we should focus on, even though Michael Lewis is a really good and engaging writer.
You wanna focus on something? Let’s talk about money laundering in HSBC and now Citi that is not under control. Let’s talk about ongoing mortgage fraud and robo-signing and the ongoing bailout/ taxpayer subsidy and people still losing their homes, and the poor still being the targets of illegal and predatory loans, and Too-Big-To-Fail getting worse, and the direct line between the bailout and the broken pension promises for civil servants and the overall price list for fraud that has been built.
Let’s talk about the people who created the underlying fraud still at work in places like Bank of America, and how few masterminds have gone to jail and how the SEC and the Obama administration has made that happen through inaction and passivity and how Congress is sitting on its hands because of the money coming in from lobbyists. Let’s talk about the increasing distance between the justice system for the poor and the justice system for the rich in this country.
Tell me what I missed.
The HFT noise is misplaced and a distraction from the ongoing real story.
Before I begin this morning’s rant, I need to mention that, as I’ve taken on a new job recently and I’m still trying to write a book, I’m expecting to not be able to blog as regularly as I have been. It pains me to say it but my posts will become more intermittent until this book is finished. I’ll miss you more than you’ll miss me!
On to today’s bullshit modeling idea, which was sent to me by both Linda Brown and Michael Crimmins. It’s a new model built in part by the former chief economist for the Commodity Futures Trading Commission (CFTC) Andrei Kirilenko, who is now a finance professor at Sloan. In case you don’t know, the CFTC is the regulator in charge of futures and swaps.
I’ll excerpt this New York Times article which describes the model:
The algorithm, he says, uncovers key word clusters to measure “regulatory sentiment” as pro-regulation, anti-regulation or neutral, on a scale from -1 to +1, with zero being neutral.
If the number assigned to a final rule is different from the proposed one and closer to the number assigned to all the public comments, then it can be inferred that the agency has taken the public’s views into account, he says.
- I know really smart people that use similar sentiment algorithms on word clusters. I have no beef with the underlying NLP algorithm.
- What I do have a problem with is the apparent assumption that the “the number assigned to all the public comments” makes any sense, and in particular whether it takes into account “the public’s view”.
- It sounds like the algorithm dumps all the public comment letters into a pot and mixes it together to get an overall score. The problem with this is that the industry insiders and their lobbyists overwhelm public commenting systems.
- For example, go take a look at the list of public letters for the Volcker Rule. It’s not unlike this graphic on the meetings of the regulators on the Volcker Rule:
- Besides dominating the sheer number of letters, I’ll bet the length of each letter is also much longer on average for such parties with very fancy lawyers.
- Now think about how the NLP algorithm will deal with this in a big pot: it will be dominated by the language of the pro-industry insiders.
- Moreover, if such a model were to be directly used, say to check that public commenting letters were written in a given case, lobbyists would have even more reason to overwhelm public commenting systems.
The take-away is that this is an amazing example of a so-called objective mathematical model set up to legitimize the watering down of financial regulation by lobbyists.
Update: I’m willing to admit I might have spoken too soon. I look forward to reading the paper on this algorithm and taking a deeper look instead of relying on a newspaper.
Here are two things you might have some trouble believing if you read the papers regularly and find yourself convinced we are in a housing recovery. First, there are still huge numbers of homeowners on the brink of, or just starting to enter, foreclosure. Second, many of the banks foreclosing on those properties do not have clear legal ownership over the mortgages in question.
Obama should have addressed the first problem through TARP way back in 2008. In fact mortgage modification was an intention of TARP that was promised Congress when it passed the second half of the money but it never happened. Instead Obama came up with the garbage called HAMP, which has been dreadfully implemented and possibly a net harmful program.
Even without Obama, we should have seen a willingness to renegotiate debt. After all, we can negotiate credit card debt, and businesses routinely renegotiate their mortgages. Why are private home mortgages kept airtight? I guess the banks see it as in their interest not to allow negotiations, and whatever the banks want, the banks seem to get.
The second problem, which is essentially one of botched paperwork (explained here), is probably technically the job of some regulator to deal with, but nobody wants to “blow up the system” so nobody is dealing with it. This is especially ironic considering how often we hear about the so-called sanctity of the contract.
The result of these huge looming problems is that banks got bailed out and the system never got cleared of its actual debt and paperwork problems,.
Enter the concept of using eminent domain to force these two issues. Strike Debt, an offshoot of Occupy Wall Street, is pushing this in a few nationwide court cases, for example in Richmond, California.
More recently, and what inspired this post this morning, is a plan cooked up by Strike Debt using eminent domain to force courts to clear up broken chains of title, written by Hannah Appel and JP Massar.
This idea is on its face unappealing, given the history of that crude tool eminent domain. Everyone I meet has their own stories, but start here for a short list of eminent domain abuses.
And it might not work, either. A district judge might not want to deal with the complexity of the issue and might just let the bad paperwork through.
For that matter, many concerns have been voiced about the practicality of this approach, and one that deeply resonates with me is the idea of using it against current mortgages – i.e. mortgages where the homeowner is up-to-date with payment. Using eminent domain in such a case could set a precedent whereby, even though someone has been taking care of their property, the city uses eminent domain to condemn it based on historical data which implies the owner is likely to neglect their property. That would not be good enough. As far as I know the current plan only uses mortgages where there have been missed payments, though.
The bottomline is this: we’re in a situation where all these homeowners are being crushed with unreasonable monthly payments, and hugely inflated principals, where the legal ownership of the mortgage itself is under question, and nobody seems to want to do squat about it. Maybe it’s time a crude tool is used against a cruel enemy.
A while back I was talking to some math people about how credit default swaps (CDSs), by their very nature, contain risk that is generally speaking undetectable with standard risk models like Value-at-Risk (VaR).
It occurred to me then that I could put it another way: that perhaps credit default swaps might have been deliberately created by someone who knew all about the standard risk models to game the system. VaR was commercialized in the mid 1990′s and CDSs existed around the same time, but didn’t take off for a decade or so until after VaR became super widespread, which makes it hard to prove without knowing the actors.
For that matter it is reasonable to assume something less deliberate occurred: that a bunch of weird instruments were created and those which hid risk the most thrived, kind of an evolutionary approach to the same theory.
I was reminded recently of this conspiracy theory when Joe Burns talked to my Occupy group last Sunday about his recent book, Reviving the Strike. He talked about the history of strikes as a tool of leverage, and how much less frequently we’ve seen large-scale strikes and industry-wide strikes. He made the point that the legality of strikes has historically been uncorrelated to the existence of strikes – that strikers cannot necessarily wait for the legal system to catch up with the needs of the worker. Sometimes strikers need to exert pressure on legislation.
Anyhoo, one question that came up in Q&A was how, in this world of subsidiaries and franchises, can workers strike against the upper management with control over the actual big money? After all, McDonalds workers work for franchisees who are often not well-off. The real money lives in the mother company but is legally isolated from the franchises.
Similarly, with Walmart, there are massive numbers of workers that don’t work directly for Walmart but do work in the massive supply chain network set up and run by Walmart. They would like to hold Walmart responsible for their working conditions. How does that work?
It seems like the same VaR/CDS story as above. Namely, the legal structure of McDonalds and Walmart almost seems deliberately set up to avoid legal responsibility from disgruntled workers. So maybe first you had the legal system, then lawyers set up the legal construction of the supply chain and workers such that striking workers could only strike against powerless figures, especially in the McDonalds case (since Walmart has plenty of workers working for the mother company as well).
Last couple of points. First, only long-term, powerful enterprises can go to the trouble of gaming such large systems. It’s an artifact of the age of the corporation.
And finally, I feel like it’s hard to combat. We could try to improve our risk or legal system but that makes them – probably – even more complicated, which in turn gives massive corporations more ways to game them. Not to be a cynic, but I don’t see a solution besides somehow separately sidestepping our personal risk exposure to these problems.
I am looking into the history of anti-discrimination laws like the Equal Credit Opportunity Act, (ECOA) and how it got passed, and hopefully find data to measure how well it’s worked since it got passed in 1974.
Putting aside the history of this legislation for now – although it is fascinating – I’d like to talk this morning about this paper from 1989 written by Gregory Elliehausen and Thomas Durkin from the Board of Governors of the Federal Reserve System, which discusses the abstract question of approaches to defining and regulation around discrimination.
This came up because when Congress passed ECOA, they left it to the regulators – in this case the Federal Reserve – to decide exactly how to write the rules, which pertain to credit decisions (think credit card offerings). From the article:
The term “discriminate against an applicant” was defined in Section 202. 2(n) as meaning “to treat an applicant less favorably than other applicants.” By itself, this rule does not offer an unquestionably unambiguous operational definition of socially unacceptable discrimination in a screening context where limited selections are constantly being made from a longer list of applicants.
The paper then goes on to list 3 separate regulatory approaches to anti-discrimination regulation. I have found these three definition really interesting and thought-provoking. I won’t even go into the rest of the paper on this post because I think just this list of three approaches is so interesting. Tell me if you agree.
1) The “effects-based” approach to regulation. This is the idea that, we don’t need to know how you actually make credit decisions, but if the effect is that no women or minorities ever get credit from you, then you’re doing something wrong. If you want to be really extreme in this category you get to things like quotas. if you want to be less extreme you think about studying applications that are similar except for one thing like race or gender, kind of like the the male vs. female science lab application test studied here. Needless to say, effects-based regulation is not in use, it’s considered too extreme.
2) The “intent-based” approach to regulation. This is where you have to prove intent to discriminate. It’s super rare that you can do that, because it’s super rare that people aiming to discriminate are dumb enough to make it obvious. Far easier to embed discrimination in a model where you can maintain plausible deniability. Although intent-based regulation is considered too extreme in the other direction, it seems to be what surfaces when there’s a legal case (although I’m not a legal expert).
3) The “practices-based” approach to regulation. This is where you make a list of acceptable or unacceptable practices in extending credit and hope you cover everything. So for example you aren’t allowed to explicitly use race or marital status or governmental assistance status in your credit models. This is what the Fed finally decided to use, and it makes sense in that it’s easy to implement, but of course the lists change over time, and that’s the key issue (for me anyway): we need to update those lists in the age of big data.
Tell me if you think there’s yet another approach not mentioned. And note these regulatory approaches correspond to different ways of thinking about or even defining discrimination, which is itself a great reason to list them comprehensively. I think my future discussions about what constitutes discrimination will be informed by which above approach will pick up on a given instance.