www.localmeze.com

What's going on I don't know.

hn At machine.imap.cc

hn At machine.imap.cc

I hadn't yet heard of James Simons. The rumor I heard was that Simons liked to hire mathematical physicists from Russia.

I had no way to go to Wall Street and already know all about everything they they were doing. The martgingale convergence theorem, measurable selection, power spectral estimation, sure, all about Wall Street, no.

When I was in graduate school, people who understood both measure theory and martingales, Markov processes, etc. were like hen's teeth. Or, sure, essentially every pure math Ph.D. knows measure theory, but curiously, at least in the US, they rarely take a course in graduate probability. It's tough for me to believe that many physics students actually work at all carefully through measure theory. So, hen's teeth.

So, I thought that I had relatively good qualifications. And since I'd read E. Thorpe's book, Wall Street was one of my goals. But I couldn't get the time of day from Wall Street.

Finally, with the letter back from Fisher Black, I gave up. I mean, good grief, a lot of the interest is in the Brownian motion approach to the Dirichelet problem and Black-Scholes, and that was Fisher Black.

In a sense I can't fault Wall Street: A lot of people there are making a lot of money now, with, usually without, measure theory, etc., so clearly they don't need me.

Once again, over again, one more time, in the US the main way to make money is to own a business and make it valuable, not to work for someone else. So, I'm doing a start-up. Based on some mathematics, including measure theory? Yes. Having to do with Wall Street? No.

Right, LTCM: So, let's see, independent increments with the same distribution and not much more and satisfy the central limit theorem and, thus, get a Gaussian process, really, an approximation to Brownian motion. So, ..., and LTCM should have worked, right? Wrong! Those assumptions are only approximately correct, and moreover need some work on the rate of convergence to a Gaussian, with good attention to the tails, and, there, tilt. Boom. Someone kicks over a bucket of fish heads in Asia and ..., down goes LTCM.

Sure, would've been great to have met Simons. Heck, I never got around to working in differential geometry but at one time did get the notes of S. S. Chern! And once tried to understand a seminar of an A. Gleason student! But I did cover exterior algebra, from both Fleming and Spivak. Now I have Cartan's book, now in English!

I have no idea just what Simons did to make his $12 billion or so, but likely it had to do with algorithmic trading in some sense.

Once I did get an interview at Morgan-Stanley, showed them some work I'd done in mathematical statistics, I later published, and mentioned that I'd like to work in the applied math of trading but got no interest.

The people on Wall Street made plenty of money and didn't need me.

So, I decided to go where I could make money just by pleasing users/customers -- do a start-up, i.e., hire myself.

From headhunters, I got a lot of just hostility: The main reaction was that in looking for a job I was doing something wrong. For another, my resume said I'd been a professor. Right, I had been. So, the head hunter got all twisted out of shape suggesting that I claimed the title of Full Professor. Nope, I claimed no such thing. The headhunter was eager to be nasty. Bizarre. Dysfunctional. Destructive. Nonsense.

I don't know what Wall Street wanted; I have to doubt that much of Wall Street knew what Wall Street wanted; whatever they did or didn't want, they didn't want me.

It's a very old problem: If working very high up, then are almost certainly (Simons is a grand exception) are working for people who, net, don't know measure theory. Then a person actually making use of such math will have a huge interpersonal interface problem.

Quite broadly one of the main bottlenecks in getting value from technical work is the problem of the awkward, often bitter, interface between a good technical person and a less technical superior.

I have heard that the lawyers have a solution here: A working lawyer is supposed to report only to a qualified lawyer.

Really, then, a technical person with some valuable technical work should just start their own business.

Or, how many people on Wall Street working as applied mathematicians and not for themselves earn money enough to live in a nice Manhattan townhouse or apartment? My guess is, not many and that, instead, the big bucks, say, for a $20 million townhouse, are going to non-technical people, management, sales, IB, trading, firm ownership, etc.

Precisely. You've correctly identified the irrational non-technical prejudice the financial industry may have towards someone such as yourself. The only solution is to become their competitor. You'd be surprised how easy it is to beat incompetent corporations at their own game. If it can be done with multi-stage rockets, it can be done with hedge funds.

Hence why we're all united here as fans of PG's essays on HN. Welcome aboard, and god speed in your entrepreneurial ventures.

For me, it has been some fun math and software. I'm gathering some initial data and should go live soon. Then if people like the work, I'll be in good shape.

Just checked with my ISP: Can upgrade to 25 Mbps upload speed with a static IP address for $89 a month. That 25 Mbps is a lot: If users really like my work, enough to half fill that 24 x 7, it adds up to millions a year in revenue. Less expensive to start than a pizza carryout, and makes money even when I'm asleep.

I'm borrowing at least two of PG's points: (1) At first don't try to please 1 million users only a little but try to please 100 users a lot. Then they will tell others and will have 1000 users and 10,000 users. Then expand to another 100 users .... (2) Initially, don't be afraid to do work that does not scale. So, I'm following that: For the data, the 'business model' has that gathered, in a way that will scale, automatically as a by-product of the usage, but that will work well only with a lot of usage. In the meanwhile, I will will just insert good data by hand!

From the lectures in Sam Altman's course at Stanford, just completed, what I'm doing looks fine except I'm a solo founder, who's done all the work, thus, knows all the work, has no co-founder disputes, owns 100% of the business, and has meager burn rate. The burn rate is so low that by the time the business qualifies for equity funding, it will likely also be profitable enough for me to buy lots more servers, in a spare bedroom, upgrade my house circuit breaker to 200 A, put in a window A/C, get some UPS units, put my emergency electric generator on a pad in a small shack just out back and have it kick off when the UPS says so, get a new SUV and Corvette, and keep growing. Outsource bookkeeping, accounting, taxes, and legal, and grow. Maybe be like the Canadian romantic matchmaking service Plenty of Fish, long just one guy, two old Dell servers, ads just from Google, and $10 million a year in revenue.

Sure, if we were four co-founders, all married, with all four wives pregnant and wanting a new, two bath, three bedroom house, with a nice backyard, in a nice neighborhood, and a new SUV, for her, with a baby car seat, a play pen, a bassinet, a crib, a stroller, two washing machines, help with the housework, a GYN, OB, pediatrician, GP, dentist, dermatologist, optometrist, swimming instructor, etc., then, sure, we'd be desperate for equity funding! But, not me!

Looks fine so far.

$10 million a year is a lot for a mathematician on Wall Street.