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Open Source Ratings Model?
A couple of days ago I got this comment from a reader, which got me super excited.
His proposal is that we could start an open source ratings model to compete with S&P and Moody’s and Fitch ratings. I have made a few relevant lists which I want to share with you to address this idea.
Reasons to have an open source ratings model:
- The current rating agencies have a reputation for bad modeling; in particular, their models, upon examination, often have extremely unrealistic underlying assumptions. This could be rooted out and modified if a community of modelers and traders did their honest best to realistically model default.
- The current ratings agencies also have enormous power, as exemplified in the past few days of crazy volatile trading after S&P downgraded the debt of the U.S. (although the European debt problems are just as much to blame for that I believe). An alternative credit model, if it was well-known and trusted, would dilute their power.
- Although the rating agency shared descriptions of their models with their clients, they weren’t in fact open-source, and indeed the level of exchange probably served only to allow the clients to game the models. One of the goals of an open-source ratings model would be to avoid easy gaming.
- Just to show you how not open source S&P is currently, check out this article where they argue that they shouldn’t have to admit their mistakes. When you combine the power they wield, their reputation for sloppy reasoning, and their insistence on being protected from their mistakes, it is a pretty idiotic system.
- The ratings agencies also have a virtual lock on their industry- it is in fact incredibly difficult to open a new ratings agency, as I know from my experience at Riskmetrics, where we looked into doing so. By starting an open source ratings model, we can (hopefully) avoid issues like permits or whatever the problem was by not charging money and just listing free opinions.
Obstructions to starting an open source ratings model:
- It’s a lot of work, and we would need to set it up in some kind of wiki way so people could contribute to it. In fact it would have to me more Linux style, where some person or people maintain the model and the suggestions. Again, lots of work.
- Data! A good model requires lots of good data. Altman’s Z-score default model, which friends of mine worked on with him at Riskmetrics and then MSCI, could be the basis of an open source model, since it is being published. But the data that trains the model isn’t altogether publicly available. I’m working on this, would love to hear readers’ comments.
What is an open source model?
- The model itself is written in an open source language such as python or R and is publicly available for download.
- The data is also publicly available, and together with the above, this means people can download the data and model and change the parameters of the model to test for robustness- they can also change or tweak the model themselves.
- There is good documentation of the model describing how it was created.
- There is an account kept of how often different models are tried on the in-sample data. This prevents a kind of data fitting that people generally don’t think about enough, namely trying so many different models on one data set that eventually some model will look really good.
Wall Street versus us
There have been two articles in the past few days which address the mentality of people working on Wall Street versus the rest of us.
First, we have this article from William Cohen, posted on Bloomberg.com, which is the first part of a series entitled, “Ending the Moral Rot on Wall Street.” This first part doesn’t contain much new; it goes over just how obnoxious and easy to hate the various Goldman Sachs assholes were when they packaged and sold mortgage debris and then emailed their friends about how much money they stood to make. And the second (and perhaps further) parts promise to explain how we are going to address the corruption and greed. My complaint, which is totally unfounded since I haven’t read the next parts, is that this guy is not disagreeing well. In other words, he’s setting up the guys on Wall Street to be monstrous and ethically vapid. This attitude is not going to help really understand the situation, nor will it lend itself to satisfying solutions. Here’s an example of the kind of “they are monsters” prose that probably won’t help:
These crimes are being committed, he said, by people who “have already made more money than could ever be spent in one lifetime and achieved more impressive success than could ever be chronicled in one obituary. And it begs the question, is corporate culture becoming increasingly corrupt?”
Yes, it certainly does raise that question.
Second, we have this blog post by Mark Cuban, which was originally posted in 2010 but is still relevant. In it, an effort is made to understand the actual mentality of the traders on Wall Street. Namely, they are framed as hackers:
Just as hackers search for and exploit operating system and application shortcomings, traders do the same thing. A hacker wants to jump in front of your shopping cart and grab your credit card and then sell it. A high frequency trader wants to jump in front of your trade and then sell that stock to you. A hacker will tell you that they are serving a purpose by identifying the weak links in your system. A trader will tell you they deserve the pennies they are making on the trade because they provide liquidity to the market.
I recognize that one is illegal, the other is not. That isn’t the important issue.
I agree with this characterization, and moreover I applaud the effort to understand the culture. These guys actually do think they are playing fairly within the context of their “game” (and they do care that it’s legal). To change their mindset we need to actually change the rules of the game, not just complain that they are corrupt, because, like in a religious disagreement, they can easily dismiss such talk as irrelevant to their lives.
Going back to the first article, it says:
That Wall Street executives have been able to avoid any shred of responsibility for their actions in the years leading up to the crisis speaks volumes not only about an abject ethical deterioration but also about the unhealthy alliance that exists between the powerful in Washington and their patrons in New York. Our collective failure to demand redress against a Wall Street culture that remains out of control is one of the more troubling facts of life in America today.
I agree that we do need to demand redress, but not against a culture’s ethical deterioration, which is just far too vague, but rather against individual corrupt actions. In other words we need to make the punishments for well-defined evil deeds clear and we need to follow through with the consequences. In order to do this we need to demand transparency so we can start to even define evil deeds. This means some system of understanding the models that are being used, and the risks being taken, and a market consensus that the models are sufficient. It means the actual threat of losing actual money, or even going to jail, if the models being used are crappy or if it turns out you were lying about the risks you were taking – or even if you were ignorant of them.
Cool example of Bayesian methods applied to education
My friend Matt DeLand teamed up recently with Jared Chung to enter a data mining hacking contest sponsored by Donors Choose, which is a well-known online charity connecting low-income classrooms across the country to donors who get to choose which projects to support.
Their goal was to figure out how many of the thousands of projects up for funding were directly related to career preparation, and they performed a nifty Bayesian analysis to do it. Turns out it’s less than 1%!
Here’s their report. It’s really well explained in the 5-page pdf, if you have a few minutes.
Speaking of Donors Choose, it was featured at a HackNY Summer Fellows event I went to last week. The Summer Fellows is essentially like the math camp I taught at for high school students except it’s a computer camp for college students – same level of nerdy loveliness though. The event was a showcase for the fantastically nerdy student hackers, and there were some very impressive exhibits.
The hack involving Donors Choose shows a movie of how the donations are being given from some location to the classroom that’s benefitting on a big map of the country, and shown quickly from 2005 or so really exhibits how quickly the concept grew. It’s not unlike this visualization of the history of the world through the lens of Wikipedia.
Why didn’t anybody invite me!?
There was an attempt yesterday morning to increase transparency on Wall St.
Three strikes against the mortgage industry
There’s a great example here of mortgage lenders lying through their teeth with statistics. Felix Salmon uncovers a ridiculous attempt to make loans look safe by cutting up the pile of mortgages in a tricky way- sound familiar at all?
And there’s a great article here about why they are lying. Namely, there is proposed legislation that would require the banks to keep 5% of the packaged mortgages on their books.
And finally here’s a great description of why they should know better. A breakdown of what banks are currently doing to avoid marking down their mortgage book.
Elizabeth Warren: Moses and the Promised Land
This is a guest post by FogOfWar
In Biblical style, Elizabeth Warren (EW) was not nominated to head the CFPB (Consumer Financial Protection Bureau). Having spearheaded the movement to create the institution, pushed to make it part of the otherwise-generally-useless* Dodd Frank “Financial Reform” Bill, and spent the better part of the last two years staffing the actual CFPB and moving it into gear, she has now been deemed too controversial by what passes for a President these days.
One of my favorite EW quotes: “My first choice is a strong consumer agency. My second choice is no agency at all and plenty of blood and teeth left on the floor.” This still remains to be seen, as opposition to the CPFB (and filibuster threats to any appointment to head the Bureau) remains in the face of nominee Richard Cordray. In fact, if one were inclined to be an Obama apologist (I gave up apologizing for Obama right about here), one might view the Warren-Cordray switch as a potentially brilliant tactical maneuver, with the emphasis on “potentially”. If the opposition to the CPFB took its persona in EW, then sidestepping her personally to get the agency up and running would be worthwhile, particularly as Cordray seems at least as assertively pro-consumer as EW (a bank lobbyist described him as “Elizabeth Warren without the charm”).
Barney Frank believes gender bias played a role. Maybe yes, maybe no and the Cordray confirmation will give some evidence to that question. I suspect the Republican opposition isn’t stupid and knows that Cordray will run a good agency. If that’s right then passing over EW doesn’t really serve any purpose.
Hard to tell what a public figure is really like, but my sense is EW doesn’t have any ego attached to running the agency personally. And what she does next is really up to her, I mean who really cares what we think she should do?
Wait—this is a blog! Our Raison d’être is practically making suggestions that no one will listen to, so let’s go…
1. Run for Congress
The biggest idea floated around. Yves Smith thinks it’s a terrible idea. I’m not entirely convinced—there are many ways to make a difference in this world, and being one minority member of a large and powerful body, and thus moving the body incrementally in the right direction can be a very good thing.
Two questions though: can she win (a few early stage polls seemed to indicate no, but do early stage polls really have much predictive value on final election results? Cathy? Fivethirtyeight?), and on which party platform would she run (I vote for running as an Independent)? Any thoughts from the ground from our MA-registered voters?
2. The “Al Gore” option
EW could continue to advocate, lecture and write outside of political office. She’s good television and would be free to speak without the gag order of elected office. Definitely something to be said for this option. Just realized pulling links for this post that EW was the person from the movie “Maxed Out”. Part of me thinks “damn that was effective and she should do more of that because it was so effective” and part of me thinks “wait, that movie came out in 2006 and no one listened and no one will listen”, and then the other part goes “but it can happen—you’ve actually seen social perceptions change in the wake of Al Gore (and yes, lots and lots of other people, but sparks do matter) with real and deep impacts.”
3. The “Colin Powell” option
Y’now, being in the public light kinda sucks ass. Colin Powell passed up a run for President, and largely retired to private life, and doesn’t seem to have any complaints about it. One legitimate option is to say “I did my part, you guys fight the good fight & I’m going to hang out with my grandkids on the beach.”
Any other suggestions?
*-Paul Volker deserves a parallel post of equal length for pushing the Volker Rule through this legislation and similarly receiving the thanks of being sidelined by the TBTF bank-capital-must-increase-even-if-the-peasants-have-to-eat-cake crowd.
Quit your job and become a data miner!?
Today my friend sent me this link, which is a pretty interesting and inspiring video of a talk from a guy from Google named Steve Yegge talking at an O’Reilly conference about how he’s sick of working on uninspiring projects involving social media and cat pictures, and wants to devote himself (and wants you to devote yourself) to more important questions about the nature of human existence. And he things the way to go about this is to become a data miner. I dig it! Of course he’s preaching to the choir at that conference. I wonder what other people will make of his appeal. Can one nerd change an entire culture of endless cat pic collections?
And lest you think that data mining is the answer to everything, here’s an article about how much data mining (in the form of “Value-added modeling”) can screw up other peoples’ lives when it’s misdirected. It’s written by John Ewing, who is the fabulous president of MfA, an organization that trains and mentors excellent college math majors to become effective math teachers in the New York Public School system and beyond- the “beyond” part is partly due to the crazy state of the budgets for new teachers here in NYC- we now have access to these wonderful MfA graduates but have hiring freezes so we can’t hire them. Also, my good friend Japheth Wood, a.k.a. the Math Wizard, is one of the MfA mentors.
I’m planning to post more soon on how crappy the value-added modeling (VAM) system is and how’s it’s a perfect example of mathematics being used to make things seem magical and therefore inaccessible, the exact opposite of what should be going on.
The Bad Food Tax
There’s an interesting op-ed article in today’s New York Times. The author, Mark Bittman, is proposing that we tax bad foods to the point where people will naturally select healthy food because they will be subsidized and cheap.
He has lots of statistics to back him up, and if you’re someone like me who reads this kind of thing widely, nothing surprised me. Of course Americans eat crappy food and it’s terrible for our bodies. We know that, it’s old news.
And we all want to know how to fix this- clearly education about nutrition isn’t doing the trick by itself. And I’m the first person who would love to use quantitative methods to solve a really important, big problem. Moreover, if we start to get rid of the evil farm subsidies that are currently creating a ridiculous market for corn sugar (a major reason we have some much soda on the shelves at such low prices to begin with) as well as screwing up the farmers in Africa and other places, that will be a good thing.
Unfortunately, I really think his tax plan stinks. The main problem is something he actually brings up and dismisses- namely:
Some advocates for the poor say taxes like these are unfair because low-income people pay a higher percentage of their income for food and would find it more difficult to buy soda or junk. But since poor people suffer disproportionately from the cost of high-quality, fresh foods, subsidizing those foods would be particularly beneficial to them.
Yes they would, if they could actually buy them in their neighborhood! If he has the idea that the reason poor people buy crappy food is because they go into their neighborhood grocery store with a museum-like display of fresh fruits and vegetables, bypass those foods (because they are too expensive) to go straight to the back and find junk, then I guess his plan would make sense. Unfortunately the truth is, there is no fresh fruit at most of the food stores in poor urban areas – they are typically small and carry long-lasting packaged goods and groceries, from canned evaporated milk to diapers, and don’t have extra space. Moreover, I don’t think a pure price comparison is going to convince them to carry fruit, because it’s not just the higher prices that makes bodegas carry no fruit- it’s also the convenience of packages that don’t go bad. In fact it’s an entirely different business model, which is unfortunately a pretty tough nut to crack, but is essential in this discussion.
In other words, the result of this tax plan would be, for poor people, even higher prices for crappy food, not access to fresh cheap food. Unless the plan has worked out a system for how to get fresh fruit into poor areas, it really is missing the very audience it wishes to target.
_Love_ you people
I’d like to make a shout-out today to a bunch of people.
First, my readers, who are gorgeous, sexy, and brilliant people. Thanks for reading.
Second, my commenters, who are thoughtful, gorgeous, sexy, and brilliant people, especially when they back me the fuck up. Go, you people! I’m nearly at a 3-to-1 comment-to-post ratio, which makes me feel pretty awesome. I’ve learned a whole bunch and met some pretty amazing people recently through their comments. I’ve actually been please to discover that I really enjoy being disagreed with and argued with- it makes it so much faster to learn. So keep the (constructive) criticisms coming!
Next, I’d like to throw out a bunch of links to blogs which I really like. Actually I recently created a blog roll so there’s that. But in particular I’d like you to check out some of my favorites:
- My good friend Jordan Ellenberg has a wonderful blog entitled “Quomodocumque“, whatever that means (oh wait! it means “whatever” in Latin; I wonder if that is meant sarcastically), in which he muses about math (Rubik’s cubes included!) and… whatever.
- Just in case you’ve somehow missed the whole String Theory Debate, please inform yourself at Peter Woit’s blog called “Not Even Wrong”. When I taught at the Columbia math department, as a Barnard math professor, I used to eat lunch with Peter every day at the Mill Korean on Broadway and 112th. What was adorable about Peter is that every frigging day, and I mean every day, he’d read the menu, look a bit confused, and then order beef fried rice. And then he’d give me his Chiclets at the end of the meal. I’m not sure why this story would recommend his blog to you but it certainly endears him to me. His blog rocks btw.
- Andrew Gelman’s blog titled Statistical Modeling, Causal Inference, and Social Science has a pretty awesome post today about economists (who doesn’t love hating on economists?!).
- I just found this blog, Quantivity, which contains impressively informed finance stuff, and is more technical than what I’m going for.
- Check out a new game theory blog, called Nuclear Chicken Collusion, which comes up with very readable, fun versions of fancy ideas. Their most recent post talks about the probability of there being a god and what it means for you.
High frequency trading: Update
I’d like to make an update to my earlier rant about high frequency trading. I got an awesome comment from someone in finance that explains that my main point is invalid, namely:
…the statement that high frequency traders tend to back away when the market gets volatile may be true, but it is demonstrably true that other, non-electronic, non-high-frequency, market makers do and have done exactly the same thing historically (numerous examples included 1987, 1998, various times in the mortgage crisis, and just the other morning in Italian government bonds when they traded 3 points wide for I believe over an hour). While there is an obligation to make markets, in general one is not obliged to make markets at any particular width; and if there were such an obligation, the economics of being a marketmaker would be really terrible, because you would be saying that at certain junctures you are obliged to be picked off (typically exactly when that has the greatest chance of bankrupting your enterprise).
My conclusion is that it’s not a clear but case that high-frequency traders actually increase the risk.
By the way, just in case it’s not clear: one of the main reasons I am blogging in the first place is so that people will set me straight if I’m wrong about the facts. So please do comment if you think I’m getting things wrong.
High frequency trading
This morning there was an article in the New York Times describing high frequency traders- what they do and how they want people to like them. I’m of the mind that there’s not much to like.
NOTE: Please see update!
High frequency traders are basic, old-fashioned opportunists. They buy somewhere and try to sell somewhere else cheaper. They have expensive technology and colocate next to exchanges to deal with speed-of-light issues to shave off tiny fractions of seconds for their trades. They notice a currency change in Brazil and trade on it in the US before anyone else notices. That kind of thing.
They will tell you that they are useful to the market, because they have set the bid-ask spread smaller than it used to be. Back in the day, there were official “market makers” who would maintain a book of certain instruments, and would be the go-to person for anyone who wanted to buy or sell. In return for the service they would charge a fee, which would be this so-called spread. Moreover, they were required to offer to buy and to sell in all kinds of trading environments (the spreads could get pretty wide of course).
It’s true that those spreads have gotten smaller since high-frequency traders have come to dominate. They have substantially replaced the old-school market makers and claim to be doing a better job. However, it’s also true that high-frequency traders aren’t required to be there. So when the going gets tough they completely vanish. This happens in moments of panic, and it can easily be true that their ability to vanish at will can also create more panics more often (I’d love some evidence to support or deny this theory), since from their perspective, at the first sign of weirdness, they may as well pull out until the dust settles.
The analogy I like to come up with is a little story about chores. Suppose you have someone who comes and helps you with your cleaning, mostly dishes, every day, for a small fee. Since you have kids and a job, the small fee seems to be worth it. After a while someone else comes along and offers to do your dishes every day! for free!! What a deal! You can’t resist. However, it turns out that, if the kitchen actually gets really dirty and needs to be mopped up or seriously cleaned, the free-dishes guy is nowhere to be found and you’re on your own, just when all the kids are sick and there’s a product release at work. Maybe not such a great deal after all.
What is an earnings surprise?
One of my goals for this blog is to provide a minimally watered-down resource for technical but common financial terms. It annoys me when I see technical jargon thrown around in articles without any references.
My audience for a post like this is someone who is somewhat mathematically trained, but not necessarily mathematically sophisticated, and certainly not knowledgeable about finance. I already wrote a similar post about what it means for a statistic to be seasonally adjusted here.
By way of very basic background, publicly traded companies (i.e. companies you can buy stock on) announce their earnings once a quarter. They each have a different schedule for this, and their stock price often has drastic movements after the announcement, depending on if it’s good news or bad news. They usually make their announcement before or after trading hours so that it’s more difficult for news to leak and affect the price in weird ways minutes before and after the announcement, but even so most insider trading is centered around knowing and trading on earnings announcements before the official announcement. (Don’t do this. It’s really easy to trace. There are plenty of other ways to illegally make money on Wall Street that are harder to trace.)
In fact, there’s so much money at stake that there’s a whole squad of “analysts” whose job it is to anticipate earnings announcements. They are supposed to learn lots of qualitative information about the industry and the company and how it’s managed etc. Even so most analysts are pretty bad at forecasting earnings. For that reason, instead of listening to a specific analyst, people sometimes take an average of a bunch of analysts’ opinions in an effort to harness the wisdom of crowds. Unfortunately the opinions of analysts are probably not independent, so it’s not clear how much averaging is really going on.
The bottomline of the above discussion is that the concept of an earnings surprise is really only borderline technical, because it’s possible to define it in a super naive, model-free way, namely as the difference between the “consensus among experts” and the actual earnings announcement. However, there’s also a way to quantitatively model it, and the model will probably be as good or better than most analysts’ predictions. I will discuss this model now.
[As an aside, if this model works as well or better as most analysts’ opinions, why don’t analysts just use this model? One possible answer is that, as an analyst, you only get big payoffs if you make a big, unexpected prediction which turns out to be true; you don’t get much credit for being pretty close to right most of the time. In other words you have an incentive to make brash forecasts. One example of this is Meredith Whitney, who got famous for saying in October 2007 that Citigroup would get hosed. Of course it could also be that she’s really pretty good at learning about companies.]
An earnings surprise is the difference between the actual earnings, known on day t, and a forecast of the earnings, known on day t-1. So how do we forecast earnings? A simple and reasonable way to start is to use an autoregressive model, which is a fancy way of saying do a regression to tell you how past earnings announcements can be used as signals to predict future earnings announcements. For example, at first blush we may use last earning’s announcement as a best guess of this coming one. But then we may realize that companies tend to drift in the same direction for some number of quarters (we would find this kind of thing out by pooling data over lots of companies over lots of time), so we would actually care not just about what the last earnings announcement was but also the previous one or two or three. [By the way, this is essentially the same first step I want to use in the diabetes glucose level model, when I use past log levels to predict future log levels.]
The difference between two quarters ago and last quarter gives you a sense of the derivative of the earnings curve, and if you take an alternating sum over the past three you get a sense of the curvature or acceleration of the earnings curve.
It’s even possible you’d want to use more than three past data points, but in that case, since the number of coefficients you are regressing is getting big, you’d probably want to place a strong prior on those coefficients in order to reduce the degrees of freedom; otherwise we would be be fitting the coefficients to the data too much and we’d expect it to lose predictive power. I will devote another post to describing how to put a prior on this kind of thing.
Once we have as good a forecast of the earnings knowing past earnings as we can get, we can try adding macroeconomic or industry-specific signals to the model and see if we get better forecasts – such signals would bring up or bring down the earnings for the whole industry. For example, there may be some manufacturing index we could use as a proxy to the economic environment, or we could use the NASDAQ index for the tech environment.
Since there is never enough data for this kind of model, we would pool all the data we had, for all the quarters and all the companies, and run a causal regression to estimate our coefficients. Then we would calculate a earnings forecast for a specific company by plugging in the past few quarterly results of earnings for that company.
Bank accounting link
I wanted to share this link with you; it is both interesting and relevant to another post I’m working on (a follow up to this one) that will describe two ideas I’m contemplating regarding how to systematically change the way big banks are motivated to behave in the presence of the “too big to fail” guarantee.
Its goal is to describe how banks will behave in a given situation with a mortgage, but the thought process generalizes quite well to how banks behave in general, and in particular how accounting considerations trump utility to the depositors and even the long-term shareholders. It also explains, to those of us who were wondering, why Obama’s mortgage modification plan was never going to work.
Weekend Reading
FogOfWar and I have compiled a short list of weekend reading for you that you may enjoy:
- What’s the right way to think about China’s economy?
- Is Japan’s “lost decades” a media myth?
- Can I hear a FUCK YEAH for Elizabeth Warren? I feel a follow-up post coming on how much she rocks.
- Get ready to be depressed by how few natural resources there really are.
- This essay really pins Robert Rubin to the wall in a totally awesome way. I will add more in another post.
- The Republicans are holding the entire nation for ransom over the possibility of default. Is it all political posturing? Or is it for the sake of the insanely shitty idea of a tax repatriation holiday? Here’s another article about this crappy idea; when Bloomberg makes you out as a selfish bastard then you know you’re a truly selfish bastard. I’m convinced that the politicians (and union leaders) arguing for this are just counting on the average person not understanding the actual issues well enough to know how evil it is (and how much kickback they must be getting). Another example of asymmetric information that really gets my goat.
- I think it’s fair to say we all need a little more of this in our lives.
Cookies
About three months ago I started working at an internet company which hosts advertising platforms. It’s a great place to work, with a bunch of fantastically optimistic, smart people who care about their quality of life. I’m on the tech team along with the team of developers which is led by this super smart, cool guy who looks like Keanu Reeves from the Matrix.
I’ve learned a few things about how the internet works and how information is collected about people who are surfing the web, and the bottom line is I clear my cookies now after every session of browsing. Now that I know the ways information travels the risks of retaining cookies seem to outweigh the benefits. First I’ll explain how the system works and then I’ll try to make a case for why it’s creepy, and finally, why you may not care at all.
Basically you should think of yourself, when you surf the web, as analogous to someone on the subway coming home from Macy’s with those enormous red and white shopping bags. You are a walking advertisement for your past, your consumer tastes, and your style, not to mention your willingness to purchase. Moreover, beyond that, you are also carrying around information about your political beliefs, religious beliefs, and temperament. The longer you browse between cookie cleanings, the more precise a picture you’ve painted of yourself for the sites you visit and for third parties (explained below) who get their hands on your information.
Just to give you a flavor of what I’m talking about, you probably are already aware that when you go to a site like, say, Amazon, the site assigns you a cookie to recognize you as a guest; when you return a week later it knows you and says, “Hi, Catherine!”. That’s on the low end of creepy since you have an account with Amazon and it’s convenient for the site to not ask you who you are every time you visit.
However, you may not be aware that Amazon can also see and parce the cookies that other sites, like Google (correction: a reader has pointed out to me that Google doesn’t let this happen, sorry. I was getting confused between the cookie and the “referring url”, which tells a site where the user has come from when they first get to the site. That does contain Google search terms), places on your web signature. In other words Amazon, or any other site that knows how to look, can figure out what other sites’ label of you says. Some cookies are encrypted but not all of them, and I think the general rule is to not encrypt- after all, the people who have the tools to read the cookies all benefit from that information being easy to read. From the perspective of Google, moreover, this information is helping improve your user experience. It should be added that Google and many other companies give you the option of opting out of receiving cookies, but to do so you have to figure out it’s happening and then how to opt out (which isn’t hard).
One last layer of cookie collection is this: there are other companies which lurk on websites (like Amazon, although I’m not an expert on exactly when and where this happens) which can also see your cookies and tag you with additional cookies, or even change your existing cookies (this is considered rude but not prevented). This is where, for me, the creep factor gets going. Those third parties certainly have less riding on their brand, since of course you don’t even see them, so they have less motivation to act honorably with the information they collect about you. For the most part, though, they are just looking to see what kind of advertisement you may be weak for and, once they figure it out, they show you exactly that model of showerhead that you searched for three weeks ago but decided was too expensive to buy. If you want to stop seeing that freaking showerhead popping up everywhere, clear thy cookies.
Here’s why I don’t like this; it’s not about the ubiquitous showerhead, which is just annoying. Think about rich people and how they experience their lives. I touched on this in a previous post about working at D.E. Shaw, but to summarize, rich people think they are always right, and that’s a pretty universal rule, which is to say anyone who becomes rich will probably succumb to that pretty quickly. Why, though? My guess is that everyone around them is aware of their money and is always trying to make them happy in the hope that they at some point could have some of that money. So they effectively live in a cocoon of rightness, which after a while seems perfectly logical and normal.
How that concept manifests itself in this conversation about cookies is that, in a small but meaningful way, that’s exactly what happens to the user when he or she is browsing the web with lots of cookies. Every time Joe encounters a site, the site and all third-party advertisers have the ability to see that Joe is a Republican gun-owner, and the ads shown to Joe will be absolutely in line with that part of the world. Similarly the cookies could expose Dan as a liberal vegetarian and he sees ads that never shake his foundations. It’s like we are funneled into a smaller and smaller world and we see less and less that could challenge our assumptions. This is an isolating thought, and it’s really happening.
At the same time, people sometimes want to be coddled, and I’m one of those people. Sometimes I enjoy it when my favorite yarn store advertises absolutely gorgeous silk-cashmere blends at me, or shows me to a rant against greedy bankers, and no I’d rather not replace them with Viagra ads. So it’s also a question of how much does this matter. For me it matters, but I also like New York City because it is dirty and gritty and all these people from all over the world live there and sweat on each other on the subway and it makes me feel like part of a larger community- I like to mix it up and have it mixed up.
I’d also like to mention another kind of reason you may want to clear your cookies: you get better deals. A general rule of internet advertising is that you don’t need to show good deals to loyalists. So if you don’t have cookies proving you have an account on Netflix, you may get an advertisement offering you three free months of membership. Or if you want to get more free articles on the New York Times website, clear your cookies and the site will have no idea who you are. There are many such examples like this.
Lastly, I’d like to point out that you probably don’t need to worry about this. After all, many browsers will clear your cookies but also clear your usernames and passwords, and you may never be able to get some of those back. And maybe you don’t mind being coddled while online. Maybe it’s the one place where you get to feel understood. Why question that?
Fair Foods
This post will only be indirectly quantitative, and not a rant, so I guess that means I will have to either apologize or change my mission statement. Sorry. Oh and by the way I do have lots of ideas for quantitative blogs coming up, topics to include:
- clear your cookies! how internet companies track your every click
- update on the diabetes model
- is being a mathematician just a crappy job?
- shout-outs to other nerd bloggers who are sending me readers
So yesterday I loaded up the (rental) car to the brim, with my mom, my two older sons, a guitar (for me) and an air conditioning unit (for my mom), and drove out to Amherst for the math program I’m teaching in for three weeks.
Before I left I visited my friend Nancy at Fair Foods in Dorchester.
I drove to her house early, getting there at maybe 8:30am. She wasn’t home- she had me meet her at a church near Codman Square, where she was making a drop. When I got there I helped her unload a van full of maybe 40 or so boxes of vegetables and fruit, with a few 50-pound bags of carrots and potatoes. She got on the van and handed me the boxes and I carried them over to a sidewalk, while the woman, Marie, who was accepting the drop, carried some smaller boxes into the basement. Nancy introduced me to Marie as her daughter, and introduced Marie to me as the beautiful, wise Haitian woman who was a professional cook and would turn all of these vegetables into a delicious feast for her congregation. Nancy and Marie talked about the church, and the fact that it was shared between two different congregations, one Haitian immigrant and one African-American, and how the church was run.
After a while it didn’t seem like Marie was going to get the help she was expecting to carry the larger boxes into the basement, so Nancy and I moved all of the boxes down there, temporarily rigging a window to be a de facto dumb waiter to avoid three corners and some stairs. There were tomatoes, white potatoes, red potatoes, carrots, ugli fruit, limes, lettuce, string beans, wax beans, and others I can’t remember. Almost all of these were in great condition, but some needed sorting before going into the feast. Marie asked for corn for the 4th of July- since the food that is collected is surplus, a given request may be hard to fill, especially around a holiday, which Nancy explained. But then she said that if we got corn we would call Marie right away.
After we finished unloading the van I was soaked in sweat; it reminded me of how incredibly strong I’d gotten working one summer for Nancy, unloading trucks all day (as well as loading them at the Chelsea Produce Market every morning at 7) and driving around the city in the big yellow truck making drops to churches, senior centers, and youth centers, and holding dollar-a-bag sites in vacant parking lots and sidestreets. That was in 1992; and Nancy, who was born in 1950, has been doing the program ever since, with various peoples’ help.
Nancy mentioned that before I’d gotten there she had gone into the church and listened to the singing and the praying of the Haitian congregation, and that it had been seriously beautiful. Marie insisted on us coming inside. We sat in the pews as the woman leading the small prayer group of about 8 people, mostly women, was talking to one woman who was clearly in distress. Perhaps she was in mourning. They were speaking in Creole, which I don’t understand (although I know some French so every now and then I can pick up a word or two), but it was viscerally moving how kindly the leader was speaking to the sad woman seated in front of her. After she allowed that woman to finish, she looked up and welcomed us in English and asked us our names. Marie explained in Creole something about us, probably that we had just brought in the food for the July 4th meal, and we were instantly welcomed by the entire group. After that they told us they were wrapping up their prayer session and would stand and have a group prayer.
Everyone stood, except for the mourning woman who was holding her head in her hands. And at once everyone started praying, but the interesting thing was they were all saying different prayers, and it was fascinating to watch and listen to how they could be both praying together and praying individually. I could make out a few words from Marie’s prayer, which near the beginning was quiet and included lots of words like “please” and “hope”, but which, like everyone else’s, became louder and more fervent and contained more words like “thank you” and “hallelujah”. It ended by everyone holding their hands up to the front of them and giving thanks. Everyone ended at exactly the same time.
After the prayer group ended, there were lots of hugs and hand shaking. Many of the women wanted to talk to Nancy and she probably ended up hugging and being hugged by everyone there. There was a deep human connection inside that little church, which is pretty different from my normal assumptions about piousness and rules-based religions. Connection and empathy.
After we left the church we went to a playground and sat and had coffee together, and Nancy laid something down that was pretty thick. She talked about her disillusionment with her generation- the hippy generation- how they made all these promises but then didn’t follow through- the words she uses is didn’t apply themselves. She talked about having faith in her generation up to the “We Are the World” moment, and then waiting, and seeing nothing come out of it, and how bitter that had made her feel, how disappointed. She said it took her years to get over that, and now she feels like those years of her life, until recently in fact, are in some sense unaccounted for, both because she’s been sick and because she was somewhat paralyzed with anger.
She went on to say that she’s in a new phase now, she’s accepted the lazy fact of life that the people she was counting on, if anything, have made the world a worse place, not a better one, but that she’s decided to love them and love the world anyway, and to continue to make human connections with individuals, because it makes her have faith in a different way, a more diffuse but a stronger faith that won’t be disappointed.
It’s interesting to me that Nancy would ever describe her life as unaccounted for or her feelings as bitter. When I met her in 1989, she had been diagnosed with MS and lived in a huge old house with very little working anything (and what was working she’d installed herself- wired the electricity and installed plumbing). She had a great Dane and a broken-down donated truck, and when I came to her we spent the whole night cleaning out and reorganizing the truck. Whenever the truck’s insurance was due, or the phone was about to be cut off, we’d get a check for $50 and it would be a miracle, and I always felt like if I was ever going to believe in something it would be because of her.
I fell in love with her and with her approach to problem solving- namely, do the right thing, and go figure how to with bare knuckles and sweat. Over the years she’s been better or worse off with her health, but she’s never given up and, to be honest, I never sensed bitterness from her. Maybe these are relative notions, that bitterness from her is like frustration from someone else. Unaccountability from the woman who moves tons of food a week, that will otherwise be thrown away, into the homes of impoverished, mostly immigrant households, who know her and appreciate her act of kindness and take part in that act, would mean… what? to other people. Hard to say.
Better risk modeling: motivating transparency
In a previous post, I wrote about what I see as the cowardice and small-mindedness of the U.S. government and in particular the regulators for not demanding daily portfolios of all large investors. Of course this goes for the governments in Europe as well, and especially right now. The Economist had a good article this past Friday which attempted to quantify the results of a Greek default, but there were major holes, especially in the realm of “who owns the CDS contracts on Greek bonds, and how many are there?”. This fear of the unknown is a root cause of the current political wrangling which will probably end in a postponement of resolving the Greek situation; the question is whether the borrowed time will be used properly or squandered.
It’s ridiculous that nobody knows where the risk lies, but as a friend of mine pointed out to me last week at lunch, it probably won’t be enough to demand the portfolios daily, even if you had the perfect quantitative risk model available to you to plug them into. Why? Because if “transparency” is what the regulators demand, then “transparency” is what they would get – in the form of obfuscated lawyered-up holding lists.
In other words, let’s say a bank has a huge pile of mortgage-backed securities of dubious value on their books, but doesn’t want to accept losses on them. If they knew they’d have to start giving their portfolio to the SEC daily instead of quarterly, it would change the rules of the game. They’d have to hide these holdings by pure obfuscation rather than short-term month- or quarter-end legal finagling. So for example, they could invest in company A, which invests in company B, which happens to have a bunch of mortgage-backed securities of dubious value, but which is too small to fall under the “daily reporting” rules. This is just an example but is probably an accurate portrayal of the kind of thing that would happen with enough lead time and enough lawyers.
What we actually want is to set up a system whereby banks and hedge funds are motivated to be transparent. Read this as: will lose money if they aren’t transparent, because that’s the only motivation that they respond to.
In some sense, as my friend reminded me, we don’t need to worry about hedge funds as much as about banks. This is because hedge funds do their trades through brokerages, which force margin calls on trades that they deem risky. In other words, they pay for their risk through margins on a trade-by-trade, daily basis. If you are thinking, “wait, what about LCTM? Isn’t that a hedge fund that got away with murder and almost blew up the system and didn’t seem to have large margins in place?” then the answer is, “yeah but brokers don’t get fooled (as much) by hedge funds anymore”. In other words, brokers, who are major players in the financial game, are the policemen of hedge funds.
There are two major limits to the above argument. Firstly, hedge funds purposefully use multiple brokers simultaneously so that nobody knows their entire book, so to the extent that risk of portfolio isn’t additive (it isn’t), this policing method isn’t complete. Secondly, it is only a local kind of risk issue- it doesn’t clarify risk given a catastrophic event (like a Greek default), but rather a more work-a-day “normal circumstances” market risk.
Even so, what about the banks? Are there any brokers measuring the risk of their activities and investments? Since the banks are the brokers, we have to look elsewhere… I guess that would have to be at the government, and the regulators themselves, maybe the FDIC… in any case, people decidedly not players in the financial game, not motivated by pay-off, and therefore not prone to delving into the asperger-inspiring details of complicated structured products to search out lies or liberal estimates.
The goal then is to create a new kind of market which allows insiders to bet on the validity of banks’ portfolios. You may be saying, “hey isn’t that just the stock price of the bank itself?”, and to answer that I’d refer you to this article which does a good job explaining how little information and power is actually being exercised by stockholders.
I will follow up this post with another more technical one where I will attempt to describe the new market and how it could (possibly, hopefully) function to motivate transparency of banks. But in the meantime, feel free to make suggestions!
Did someone say regulation?
FogOfWar has kindly offered the background below on the OTC market and an analogy with the bond market, inspired by this recent article describing the latest round of watering-down of derivatives regulations. The bottomline for me is that whenever you see people using the phrases “needlessly tying up capital that would otherwise be used to create jobs and grow the economy,” “would damage America,” or especially an emphasis on “U.S. firms,” it probably means they are trying to engender a local nationalistic fervor to camouflage a very basic greedy instinct. Here’s the background:
OTC derivatives, by definition, are not traded on an open exchange, but are entered into between two parties in a private transaction. We can use JPMorgan and United Airlines as a running example. United has some risk it has that it wants to hedge. Or maybe some banker has convinced United that they should be hedging a risk that they didn’t know they had until the banker showed up to tell them about it.
For some simple things, United could just go to an exchange (a stock market, but not limited to stocks). So, for example, United could buy a future on oil prices to lock in its cost of oil over the next year. The problem is that there actually aren’t that many different contracts traded on exchanges, and the risks don’t usually fit neatly into the contracts that are there to buy. There’s a whole chapter on how to get a best-possible hedge in this situation in Derivatives 101 (and probably a whole class after that and people who make a living doing it in real life). So you could ‘dirty hedge’ (do an imperfect hedge), or you could go to JPMorgan and ask for an exact hedge.
JPMorgan is happy to give you the hedge and either delta hedge out the risk and/or match against offsetting risk they have on their books (or even use the opportunity to take a speculative position they were thinking about anyway). The key point is that JPMorgan quotes you a price, but it isn’t a price on a transparent market–it’s just whatever price they think you’ll pay. If United is smart, they’ll farm out the hedging for a bunch of bids from different banks and try to get the best price, but they’ll never actually know if they got ripped off or not, because they don’t see how much it actually costs JPMorgan to cover that risk internally.
There are some areas where the hedges are common enough and enough people offer them OTC that the profit margins are pretty low (simple interest rate swaps are a good example). However, there is also a lot of money to be made from ripping off dumb customers like United when they wander outside of these areas into other areas where they get crap pricing. This is how derivatives trading desks make their bonus.
And that’s why JPMorgan cares about this legislation. They want to keep ripping off the United Airlines of the world, and if the government makes United go to an actual exchange with open prices, there’ll be competition and the profit margin will shrink. Adding a margin requirement is a bit more wonky, but at the end JPMorgan doesn’t like it because it might drive United to an exchange and away from an OTC derivatives trade with JPMorgan.
It may go without saying, but Jamie Dimon, JPMorgan, GS, BofA, etc. do not give a shit whatsoever about United, Shell, Alcoa, or any other corporate. They just want the profits from their OTC derivatives trading desk to keep rolling in–profits that come off the backs of their customers–and they’ll say whatever garbage they think Congress and the Agencies will swallow to keep the trades rolling.
Felix Salmon wrote all this up a ways back when Barney Frank was caving to the investment banks and putting the end-user exception into Dodd-Frank to begin with. That was around the time my opinion of Barney Frank went from “rock star” to “big fat pussy”. The history (Salmon honed in on this) tells the story in the world of bond trading–what follows is a very general overview from memory:
Once upon a time, if a corporate wanted to buy bonds, they went to their investment bank. They didn’t see exchange-listed prices, and maybe they got a few quotes to try to get good pricing, but at the end of the day, much like the OTC derivatives market described above, they either had to take a price offered by a bank or not.
Then the government came in and said bonds should be traded on open exchanges (with bid and ask prices available for participants to see). The banks said it would destroy the market, they said the corporates would suffer, they said the markets would move overseas, they probably said it would “hurt America” to do this. All of exactly the same horse shit Jamie Dimon and the banks are saying now about moving derivatives to exchanges.
Well, bond trading got moved to exchanges and exactly none of the things the banks warned about actually happened. Instead, the thing all of the banks were secretly fearing did happen: customers got good execution at lower prices and bank profit margins in the bond business slowly collapsed over time to a fraction of what they were back in the OTC-bond days. Go figure.
Data Without Borders
How freaking cool is this?! I signed up today and wrote to the founder, Jake Porway. He seems fantastic. I’m very excited about his project and how we (meaning you and me, kind reader) can help use our data scientist hats to help NGOs think about what data to collect and how to analyze it once they have it. Please consider signing up!
Guest post: Tax Repatriation Day
I’m delighted to have my first guest blogger!
“FogOfWar” (named after the documentary) is someone I’ve known for some time who comes from a mathy background, with a detour through accounting, tax & law winding up in banking (not as a quant). FOW & I have jammed finance policy many times and we tend to agree on a lot of things–I hope it will bring a “what really happens on the ground” perspective to thoughts about modeling as well as some useful insight into some of the technical rules (like accounting) that can matter a lot. Here’s his post:
The NYT ran an article on tax repatriation yesterday. Often, as someone in the industry, these articles can be infuriating for their lack of accuracy, misdirection or imprecision. In this case, however, my hat is off to the NYT for some damn fine traditional journalism. They’ve taken a fairly complicated issue (one I happen to know more than a little about), understood the core points in play and laid them out in an interesting, informative and readable article. Yes, it really is as bad as they make it out to be.
The “repatriation holiday” makes my vague-and-unofficial list of “10 worst tax ideas out there”. Unfortunately, every bad idea ultimately finds its way to Congress & this one is back for seconds. The NYT article lays out the case well, but here’s are two additional reasons on why this idea seems to have lasting appeal, which come in the form of catchy phrases:
“The money is trapped overseas”
We all know what “money”, “trapped” and “overseas” mean, and we can form an immediate idea of how this would be a bad thing, and how freeing that trapped money and bringing it back to the US would be good for the economy. Thus we get the inference: “The money is trapped overseas, and if we could bring it back it would create jobs.” Unfortunately, the second half of the second sentence is completely false. A more accurate sentence would be “The money is trapped overseas, and if we could bring it back corporations would pay slightly larger dividends this year, but not create any jobs or invest in any US plants that weren’t already in their strategic planning.” Doesn’t have quite the same ring to it…
“Structural subordination”
Not nearly as catchy as the first phrase, and uses two words for which most people don’t have a quick definition (at least not when paired together). Relevant, however, and a quick wonkish example with illustrate the thrust:
Let’s take a hypothetical US company, called (just to pick a name at random) “Lehman Holdings”. Lehman Holdings has assets claimed at $900 on its books and debt of $800. Lehman Holdings also owns 100% of another company, who we’ll call “Lehman UK”, which has assets claimed at $100 on its books and no debt. So, at first blush, one might think that Lehman has a 20% equity buffer: $1,000 of assets and $800 of debt (or a 4:1 debt ratio). This is nice easy math, which happens to be wrong in practice. The hidden assumption is that the people who loaned Lehman Holdings $800 can get access to all $1,000 of assets. They certainly can access the $900 of assets (or whatever they’re worth by the time bankruptcy hits), but the UK subsidiary is subject to UK bankruptcy rules, not US bankruptcy rules. Thus, when US creditors try to pull the $100 of assets out of the UK, they may find it’s more difficult than they anticipated (international bankruptcy gets sticky fast). Perhaps they could sell the stock of the subsidiary, but in real life that would involve untangling a whole host of interconnected contractual arrangements between Lehman Holdings and Lehman UK, which could take years. Not to mention the fact that to pull the $100 back, they’d have to pay ($35) in US taxes, so really there may be only $65 net to work with (other facts could zero out the tax bill). Probably in the end they can get the $100 of assets ($65 post taxes), but it can mean a significant time delay, and when you’re dealing with an imminent default, delay in action can translate to financial loss.
So, for all of these reasons, having $100 in a subsidiary isn’t worth quite the same thing as having $100 in the parent company. The fancy name for this is “structural subordination”, a term used by the credit rating agencies. So, if you’re a tech or pharma company with many billions of USD in your tax-shelter Irish/Dutch/Singapore subsidiaries, this can become a problem for your credit rating (which can impact your cost of borrowing). It’s probably not the primary reason for the lobbying efforts on tax repatriation, but it is definitely a factor, as the ($35) in tax is what’s preventing Holdings in the above example from pulling the $100 out of UK.
-FOW
mathbabe 