Quants | The Alchemists of Wall Street | VPRO documentary

yeah nobody I mean these are huge
18:03
numbers to make millions 5 million 10
18:06
million oh that’s a lifetime’s worth of
18:07
money you don’t ever need to work again
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and everybody wanted that you know I
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could quit working this year I made
18:14
enough money in one year I’ll never have
18:15
to work for the rest of my life and that
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was the goal of everyone it appeared to
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me huh this is money okay and Aspen’s
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talking about making money making money
18:29
making money every year you’re making
18:31
money and then one year you blow up now
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the difference between this being your
18:35
money and being a hedge fund is if this
18:38
is your money fantastic you’re making
18:40
money you’re down here you’re bankrupt
18:42
if it is somebody else’s money if it’s a
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hedge fund that does this every year
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they’re taking a percentage they’re
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taking some of that as profit as their
18:52
bonus effectively so they make some of
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that they make some more they make some
18:56
more all of this money they’re putting
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into their own bank account and then
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when they lose money that’s their
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clients money that’s a lot it’s not
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their money so you’ve got you can so you
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can see why it’s very easy for people to
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abuse this kind of thing I think it’s
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fantastic the people who take risk
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should be compensated for taking risk
19:19
but only if they are actually taking
19:22
risk themselves taking risk with other
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people’s money you should not get
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compensated for I’m sorry I did that the
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Donald where that fits into economic
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theory but taking risk with other
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people’s money does not get rewarded
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sadly though it does in this business
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no but now
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there was a moment when I thought when I
19:50
questioned why I was ever involved in
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Wall Street goodbye I need it right now
19:56
on the double
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hi that’s something I thought that
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people would be more judicious and more
20:04
conservative in their lending and I was
20:06
involved in it and I thought well wait a
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second these guys are out of control
20:09
totally the piece of software per se you
20:13
know that’s a sort of inanimate object
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yes people used it but you know if
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people had used it and put good
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mortgages into it who never would have
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caused a problem at all but when you put
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you know mortgages that you have a
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fairly high certainty that people cannot
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repay and then half of all the mortgages
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issued in a given year that type of
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mortgages yes the industry has gotten
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out of control
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trillions of dollars a year basically
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went through that model these bonds
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within two and three years of being
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issued went from triple-a to
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unwrite I mean just catastrophic
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collapse a lot of trading firms that
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kept these the riskier pieces in their
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portfolio saw them drop to next to
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nothing and given the leverages the
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amount of leverage under the amount that
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the banks had borrowed they were
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suddenly in a financial panic
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Saturday after midnight still studying
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I know long hours will not stop when I
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enter a future job as a client
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because I was primarily a technologist I
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did not fully understand what was going
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on I think part of my motivation
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post-crash for becoming a quant is to
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gain that understanding having been
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through the personal experience of
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seeing the destruction of my firm looked
21:45
again at my resume that I put out there
21:48
the same headhunter called again today
21:51
to see if I would like to take a job in
21:53
my former field as a financial
21:55
technologist I declined again of course
22:01
no invitation for a quanzhou Piett
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people that are in the business right
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now probably refuse to talk to the
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public if they were to talk to the press
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they would be fired
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so only limited few people in the
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business have the option of talking to
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the press once you’re in the world right
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I mean your phones are ringing you know
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from the moment I woke up in the morning
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and I remembered you know a lot of these
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guys I do quite well they try to wake me
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up 6 o’clock oh I thought you were
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asleep you know can you be up till 11
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o’clock
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you have to be wired you have to be
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alert every second you have to be
22:49
engaged and and you have to be perfect
22:52
and you have to be right all the time
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the software fails people lose millions
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or billions can’t happen you can’t you
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can’t be wrong you have to be perfect it
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says it’s a lot of stress my wife was in
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the business with me
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we both would wake up in the morning and
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describe similar nightmares phones were
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ringing we couldn’t answer them and then
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we sort of grew out of that and we both
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realized that we didn’t know what day of
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the week was that’s right boy there’s
23:24
always videos person departures Barclays
23:27
dangerously Pleasant read the planet
23:30
record is brought to you by the Deaf
23:31
1.6% it wonder the up 1.2 percent
23:35
so is the CAC in Paris hey Joel boy
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stirs
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banking is completely lost touch with
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its purpose its original purpose and is
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now becoming dangerous
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it used to be that when some of these
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derivatives were first invented they
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were to help your farmer for example
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hedge the value of his crop so he was he
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wasn’t speculating on the price of wheat
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he was busy growing it now there are
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more people trading these these
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commodity derivatives and then are
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actually involved in the production of
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the commodity so which is completely
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bizarre I know a lot and quite a lot of
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people in this business who are feeling
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a bit jaded now people are starting to
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ask questions my nice friends I started
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to ask questions about the role in
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society you may be making lots of money
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but are you is it something to tell your
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grandchildren oh yeah I was a banker I
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was there when I caused the the
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2008-2009 crisis etc what are they
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actually doing with their lives or their
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or just moving this money around this
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isn’t necessary such a business to be
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proud of I think that’s probably
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planning 30 35 pounds responsibility is
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just not a one-way street when it’s
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successful you’re responsible well you
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can’t be unresponsible when the same
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same item is is a failure you have to
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have some type of responsibility and I
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could say I wasn’t but I was involved I
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made a comfortable very comfortable
25:23
living and and I was proud of what I had
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done I never I myself never saw this
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kind of debacle
25:38
pretty big muscle to see a little Wilder
25:43
this is a you know they’re yellow on the
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inside different color a chef and the
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city loves this wild taste I only do it
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for one chef because if I did too many
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there wouldn’t be enough you know the
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model is Hippocratic oath I will
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remember that I didn’t make the world
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and it doesn’t satisfy my equations
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that’s obviously that’s it that’s about
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having a a mature appreciation that
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whatever you do that the models are
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never going to be perfect
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I will never sacrifice reality for
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elegance without explaining why I have
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done so so it’s again it’s a competition
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between the real world and the elegant
26:27
world of mathematics and sometimes the
26:28
real world is just dirty
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nor will I give the people who use my
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model false comfort about its accuracy
26:36
instead I will make explicit its
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assumptions and oversights quanta are
26:41
asked the following by some trader they
26:43
say well look you’ve just measured the
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risk in this portfolio it’s too big okay
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to quant back to the drawing board
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I want you redoing numbers and come up
26:52
with a smaller risk it doesn’t mean
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change the portfolio it means change the
26:57
maths to make it look less risky people
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can use the models to hide risk though I
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will use models boldly to estimate value
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I will not be overly impressed by
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mathematics people make finance too
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mathematical so mathematical that many
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people who have to implement the models
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don’t understand what’s going on and
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once you have too much mathematics it’s
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difficult to see where the mistakes are
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I understand that my work may have
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enormous effects on society and the
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economy many of them beyond my
27:31
comprehension so this is a serious
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business it’s what it’s saying the
27:37
quantitative finance banking has become
27:39
so enormous it’s it’s outstripped all
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other all other businesses and really it
27:44
should just be a service for these other
27:46
businesses rather than we are everybody
27:49
is now working to
27:51
she service the banks move is what it
27:53
feels like it’s it’s completely changed
27:56
the nature of the world always banking
27:59
again so there’s a nice little picture
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of the book of me and Emanuel Derman
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with our with our Karl Marx beards on
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because obviously it’s it’s basically
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that the inspiration was a kind of
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communist manifesto you take the
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combined the communist manifesto with
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the Hippocratic oath and this is what
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you’ve got when I first came to the
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field I was sort of optimistic about
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using quantitative methods on the
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financial markets and I don’t think
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they’re useless but them but I’m trying
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to think how to say it I don’t think you
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can use quantitative methods to explain
28:34
markets either people like borer
28:37
Einstein or Schrodinger or Fineman
28:39
discovered things that um that seem to
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be God’s true for most you know even if
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they’re they’re not 100 percent accurate
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and I’m I don’t think that’s possible in
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finance I sort of think it’s an illusion
28:50
it’s the world the financial world and
28:53
their world of people is changing the
28:54
whole time history doesn’t repeat itself
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whereas in physics history repeats
28:58
itself all the time you can do the same
29:00
experiment over and over again so I
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don’t know somewhere somewhere somewhere
29:03
after five or six years in the field I
29:05
began to realize that it wasn’t the same
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thing as doing physics in physics if you
29:11
wake up in the morning and think of an
29:13
equation or think of some theory you
29:16
actually have a small hope in hell that
29:18
you might actually be right but in
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finance if you write down some set of
29:21
assumptions and you look at yourself
29:22
honestly it may be useful but you know
29:25
it’s not going to be right in some
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absolute sense
29:30
because you’re dealing with people and
29:31
and people don’t work that way
29:43
another weekend trying to remember all
29:46
the parts of the city I haven’t seen
29:48
since I started the course longing to
29:51
visit art galleries eat out every night
29:53
to live the day at the library seem to
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have more hours than the normal 12
30:06
studying alone with other people doing
30:08
the same thing I feel like a monk in a
30:11
monastery it’s peaceful the library is
30:14
quite old sometimes we have to cover the
30:17
air-conditioner with old Soviet
30:19
mathematical journals from the 60s
30:37
once I dreamt of doing pure science
30:40
working on rocket ships working at a
30:42
small start-up company
30:47
there has to be a way to be creative as
30:49
a quant – like designing new financial
30:51
products and the math to price them
30:59
do you think it’s always possible for
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people to express a worry they have
31:05
about the things they’re building or
31:07
writing it’s possible people may not
31:09
listen to them in the end most of these
31:11
people are employees people don’t always
31:14
listen to you but yeah it’s possible to
31:16
do it and I think people should do it
31:17
and I think people who use the model
31:19
should should understand that but I
31:22
don’t honestly believe that the models
31:25
are responsible for what happened in the
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world I think what’s just one for what
31:29
happened in the world is that they’ve
31:30
been an increasing number of they’ve
31:35
been an increasing number of crises
31:36
since 1990 financial crises in the world
31:38
since 1994 and every time people are
31:41
used to people are used to constant
31:44
growth and acceleration and every time
31:46
it slowed down the government stepped in
31:49
and tried to stimulate it again by
31:51
lowering interest rates just like
31:52
they’re doing now and so you get these
31:55
sort of a rise and a collapse and then
31:56
people don’t like the collapse so they
31:58
lend money cheaply enforcer’ rise again
32:00
and each time the oscillations get
32:02
bigger and bigger and they doing exactly
32:04
the same I have no idea what’s the right
32:06
thing to do but they’re doing exactly
32:07
the same thing now which is trying to
32:09
stimulate the economy every time it
32:11
looks like it stops growing fast
32:17
it shocks me that as a person who runs
32:20
many businesses that we can talk about
32:23
an economy shrinking by 1% is also
32:27
growing by 1% is fantastic this
32:31
difference of 2% how can that difference
32:34
in 2% have such a big impact on the
32:36
world around us 1% plus or minus in my
32:40
businesses I won’t notice the economist
32:42
sir they think that they’re scientists
32:45
so they come up with these what they
32:47
call laws they’re not laws laws of
32:51
gravity that’s a law anything that Isaac
32:54
Newton comes up with it is a law but
32:56
when the Economist comes up it’s just a
32:58
framework an idea it may work it may not
33:01
sometimes it’s that’s not a law but they
33:03
think their laws and so they build up
33:05
this whole edifice of theory based upon
33:09
this very shaky foundations and they get
33:11
all sorts of nonsense coming out of it
33:20
let’s ease off
33:25
I think that the natural world is
33:29
something you learn to appreciate
33:32
through a struggle in the financial
33:36
world
33:36
you know money is a man-made phenomenon
33:39
right it’s like a game right where you
33:41
make the rules well money is a game that
33:43
people make the rules for but out there
33:46
the day-to-day activity is not about
33:48
making money the day-to-day activity
33:50
trying to grow an animal a healthy
33:53
animal or a group of healthy atoms
33:55
that’s a big difference
34:04
that is beautiful
34:06
believe it or not that is beautiful the
34:08
beautiful thing about this is it says
34:09
that in the risk-neutral
34:11
I’ve got to keep emphasizing this is the
34:14
risk-neutral version when mu equals R if
34:18
it was the real world if this was the
34:20
real version it would have some dim UD
34:23
T’s in it
34:23
now let’s do some manipulations now some
34:25
of these manipulations are
34:26
straightforward six over zet in which
34:29
case there are no Zed’s in there at all
34:30
if you say to me the d by d big t
34:33
version because we want them we are
34:35
trying to find the stochastic
34:36
differential equation not for log said
34:39
so you’re going to end up with new minus
34:40
1/2 Sigma squared let me backtrack it a
34:43
wee bit here and we have a stochastic
34:47
differential equation for Z then we can
34:51
also write down stochastic differential
34:52
equation for F there was a very very
34:57
short period of time when conser in the
35:00
doghouse so to speak the people were
35:01
saying but all banking is changed
35:03
forever a Kwan serveth I’ve finished
35:06
there’ll be no more these credit
35:08
instruments and I said you know second
35:10
guys you really don’t know your history
35:11
you don’t know human nature this will
35:14
all blow over you know in a matter of
35:16
months because we’re back to the big
35:17
bonus is everything goes back to as it
35:21
was if people don’t complain now then it
35:25
serves them right when the next
35:26
financial crisis happens
35:31
twelve hours to go before the evening
35:33
classes start
35:35
I feel United with my classmates but the
35:38
enormous workload it’s actually the fees
35:42
that we’re trying to maximize right of
35:44
course we have to maximize returns we
35:47
have to do a good job in managing their
35:49
money otherwise where we’re going to do
35:51
pretty poorly at collecting those fees I
35:54
wanted to feel challenged again and
35:56
enrolled in a quant program
35:58
it cost me $60,000 tuition which means
36:03
more debt that I now have to take on the
36:07
incentive fee structure basically means
36:10
that maximizing the twr is like
36:13
maximizing fees think about that that’s
36:16
kind of tricky
36:18
this course is a year and a half
36:20
full-time one and a half years no salary
36:24
expenses living in downtown Manhattan
36:26
plus paying full-time tuition so no
36:30
alcohol for me not a drop at least till
36:33
the end of the first semester I can’t
36:35
afford to lose a day to a hangover
36:37
hardly any social life for the time
36:39
being
36:43
most of the other students are Asian or
36:46
East Europeans math is their first
36:48
language and our common language we
36:51
Americans are the minority maximizing
36:55
the number of times that we’re going to
36:56
penetrate the previous high-water mark
36:59
we’re actually maximizing incentive so
37:02
you can see that this this type of
37:04
optimization is very hedge fund like
37:07
does everybody get it so far
37:12
used to be the physicists were splitting
37:14
the atom whose splitting the atom these
37:15
days building bridges who is people
37:18
building bridges everybody wants to move
37:19
into this field scientific creativity is
37:23
becoming financial creativity which is
37:25
all of the bogus
37:39
Kwan’s are essential to modern banking
37:41
because so much of it is based upon new
37:44
techniques like the latest thing is the
37:46
algorithmic trading that high-frequency
37:47
trading for what you need math skills it
37:52
used to be you know historically you
37:53
just have like floor traders and brokers
37:55
you know screaming and shouting down on
37:58
the floor of exchanges and trading
37:59
stocks you know and the order came down
38:01
and they would run up and they sort of a
38:03
muscle there he added we’re a different
38:05
color jackets you know the classic
38:06
pictures we’ve we’ve all seen Matthew
38:09
Goldstein almost obscene list for PES
38:12
below Reuters do same from the ears to
38:15
the Kefauver format high-frequency
38:16
trading on cotton the reality is so much
38:20
of this doesn’t even take place there I
38:22
mean that’s becoming such a lesser part
38:24
of trading in what goes on it goes on in
38:26
the back rooms and it goes on in these
38:27
these modeling’s where these programs
38:29
are put together by computer geeks
38:31
basically so high-frequency trading is
38:33
just about taking all this data
38:35
analyzing very very rapidly and then
38:37
putting on trays that may last
38:38
milliseconds what worries me the most is
38:42
I was disturbed to hear that some firms
38:45
get faster access to the markets than
38:50
other people I forget what they call it
38:52
now but people get like a tenth of a
38:55
second advantage big firms which i think
38:57
is unfair hedge funds try and get the
39:00
black boxes as close to an exchange as
39:02
possible because it takes time for the
39:06
signal to get from the black box to the
39:09
exchange to buy or to sell now of course
39:11
that is dictated by the speed of
39:13
lightning
39:14
now we’re talking about trading at the
39:16
speed of light
39:19
the classic crash was the 87 the 19th of
39:25
October 1987 crash that happened within
39:27
a day all that the big move the 20% fall
39:30
and S&P 500 was within a day the next
39:33
crash could be within minutes so what is
39:36
the black box a black box is just
39:39
something that has it has inside some
39:41
kind of formula
39:43
maybe secret or maybe not that takes in
39:45
lots of data and the data might be stock
39:50
prices and might be other information
39:51
and it tells you what to trade what to
39:54
buy and sell and my favorite is is
40:00
Google search terms trading based on
40:04
what people are searching for it’s not a
40:13
black box in the sense that um you know
40:16
if you if you saw the algorithms you
40:18
could fit what you want you and me might
40:20
not be able to figure it out but but
40:21
wiser minds maybe could and computers
40:23
can certainly read it so it’s a black
40:25
box in a sense that it’s almost hard for
40:26
the human mind to get their arms or you
40:29
know wrap themselves around to really
40:30
understand what’s going on
40:36
and you know people have said for years
40:38
that Goldman itself is a black box we
40:41
don’t really know how it makes all this
40:42
money in the billions of dollars and you
40:44
know the big bonuses we hear about the
40:46
New York Stock Exchange building is big
40:47
facility out in New Jersey which is you
40:49
know right near in New York and and
40:51
basically it’s being built for
40:52
high-frequency traders so they can have
40:53
their equipment very close in a very can
40:56
you know tightly knit factory
40:58
essentially to do high-frequency trading
41:00
well who gets to have their server
41:02
where’s there going to be a lottery you
41:04
know you know does someone pay more to
41:06
get closer I mean it’s sort of a it’s
41:08
sort of absurd when you think about this
41:10
is what it’s come down to the
41:12
battleground is ultimately going to be
41:14
who has the most resources who can pay
41:17
the best salaries to hire the best
41:19
brains in reality we’re talking maybe
41:21
about a dozen or so really top players
41:22
you know and not everyone can be a
41:24
customer of goldman sachs not everyone
41:26
can be a customer of morgan stanley or
41:28
no berkeley also it does the the high
41:32
frequency trading means people more
41:33
concerned with the price of something
41:36
and not its value value means what it’s
41:39
really it’s really worth price is just
41:43
what people buy and sell for and if you
41:45
buy something now sell is second or two
41:49
later all you care about is the price
41:51
you sold it for is greater than the
41:52
price you bought it for it’s actual
41:54
value who cares it sort of flies in the
41:57
face of what we sort of think about what
41:59
what the what the markets are really
42:01
about the companies themselves almost
42:03
don’t matter what they do doesn’t matter
42:05
it’s just the fact which way their
42:07
stocks move is all that matters and
42:10
what’s sort of great thing about it that
42:13
I’ve I’ve seen from the standpoint is
42:15
the systemic risk that might be involved
42:16
it’s so much of this trading just takes
42:19
automatically and just takes place so
42:21
quickly that the the human element gets
42:24
more and more divorced from it I mean
42:25
the human beings are obviously
42:26
responsible for for writing the programs
42:29
but there’s no human being intercepting
42:31
between these trades and we saw this a
42:33
year ago with United Airlines there was
42:35
a false of bankruptcy rumor some wire
42:37
service inadvertently and transmitted an
42:40
old story about a UI
42:41
bankruptcy filing the problem is all
42:45
these news reading algorithms saw that
42:47
and immediately started sell sell sell
42:49
in a matter of minutes United Airlines
42:51
stock is cut in half that is clearly a
42:53
case where the computers have gone wild
42:59
banking is taking over the entire planet
43:01
and is having such a major impact on the
43:05
man in the street and it really should
43:07
not banking is supposed to be to take
43:09
money from people with too much to give
43:12
to people with too little who maybe want
43:14
to start a business if you’re a business
43:16
idea but that’s not what banking is
43:18
about anymore
43:19
banking is just about gambling on these
43:20
these numbers not realizing that behind
43:24
these numbers there are human beings
43:26
with jobs
43:34
there’s always been a joke about the New
43:37
York Stock Exchange becoming a museum at
43:38
some point and they’ll just have it for
43:40
like a show there and people running
43:42
around this is the way we used to trade
43:43
stocks you know isn’t it so quaint in
43:45
everything at the same time one can
43:58
argue though that if there’s this big
44:01
backlash in high-frequency trading
44:02
we may see revival to some form of human
44:05
element inside that people may say you
44:07
know as flawed as human beings are we
44:10
don’t want to give everything over to
44:11
the machines either
44:15
just walk past a crowded Wall Street
44:18
full of Chinese tourists asking me if
44:20
this was the actual stock exchange Wall
44:25
Street as a location is not any longer
44:28
what it was many banks moved their front
44:31
offices uptown and their back offices to
44:34
newer and cheaper spaces in New Jersey
44:37
now deutsche bank is the only major firm
44:40
left on Wall Street proper nearby is
44:43
Goldman Sachs
44:45
with no name on the door also about to
44:48
move there are almost no large firms
44:51
headquartered in the neighborhood that
44:53
was the cradle of American Finance only
44:56
the New York Stock Exchange remains its
44:59
facade one of the most iconic symbols of
45:01
global capitalism
45:19
I’m always trying to encourage young
45:21
people to do what I’m doing I mean it’s
45:23
a young person’s you know it’s pretty
45:25
some pretty physically intensive they
45:33
really haven’t grown that much I may not
45:39
make it to Christmas no I like a bigger
45:44
we sell a much we typically sell a much
45:46
bigger oyster right what do you find
45:48
more satisfying
45:50
well software is much more mental you
45:53
know the pleasure in the mental exertion
45:56
is pretty intense I get million lines of
45:58
software’s a lot – man you have it all
45:59
memorized right and there’s a pleasure
46:01
of like ask ruble Scrabble doing that
46:04
kind of word puzzle kind of thing uh
46:07
although it’s not that healthy you sit
46:09
in front of a machine you have the
46:10
terminal face effect you know it’s not
46:13
the same as this oh yeah this is pretty
46:15
uh not good I mean day like today pretty
46:19
idyllic right you’re just out in the
46:20
water a nice feeling bringing food and I
46:25
think we we still about 150,000 oysters
46:29
which is uh that’s $100,000 you know of
46:35
course I live off interest you know so I
46:39
don’t this is nice to have I make some
46:42
pocket money etc etc and the overhead
46:45
here is pretty small
46:49
you have to come to grips with nature
46:51
like I these these oysters should be
46:53
bigger every year the ones that I pick
46:55
in September and October are ready by
46:58
November why they aren’t I don’t know
47:00
and there’s nothing you can do about it
47:01
right we’re in software you can do
47:03
something about everything
47:04
you can modify you can get you can creat
47:07
make you know this virtual world you can
47:09
make what you want here you know you
47:12
have to live constrained by the real
47:16
world