George Carlin – It’s a Big Club and You Ain’t In It! The American Dream

The Real Owners of this Country don’t want a population of citizens capable of critical thinking. They don’t want well informed, well educated people capable of critical thinking. They want OBEDIENT WORKERS, OBEDIENT WORKERS.

A Shocking New Look at the 2008 Housing Crisis | Amanpour and Company

Aaron Glantz’s award-winning investigative journalism has sparked over a dozen congressional hearings and criminal probes. His latest book, “Homewreckers,” takes a shocking new look at America’s 2008 housing crisis. It’s a tale of greed and corruption, as Glantz pulls back the curtain on a group of Wall Street magnates who he says took advantage of a rigged system. Moreover, as Glantz tells Hari Sreenivasan, these “homewreckers” include key members of President Trump’s inner circle.

Michael Lewis: Nobody Understands the Stock Market

April 2 (Bloomberg) — “Flash Boys: A Wall Street Revolt” Author Michael Lewis discusses his book, trading and the stock market on Bloomberg Television’s “Market Makers.” (Source: Bloomberg)

— Subscribe to Bloomberg on YouTube: http://www.youtube.com/Bloomberg

Bloomberg Television offers extensive coverage and analysis of international business news and stories of global importance. It is available in more than 310 million households worldwide and reaches the most affluent and influential viewers in terms of household income, asset value and education levels. With production hubs in London, New York and Hong Kong, the network provides 24-hour continuous coverage of the people, companies and ideas that move the markets.

The Bizarre Economics of Tax Havens and Pirate Banking: James S. Henry at TEDxRadboudU 2013

James S. Henry introduces a hot topic: offshore banking. The G8 and G20 are planning meetings to discuss it. Even the Netherlands is a tax haven for certain types of companies. The huge amount of numbers and graphs tells us that we are confronted with nothing less than a global tax haven industry. For example, Apple makes 100 billion dollars a year of tax free profits because of the games private bankers know how to play.

In medieval times people couldn’t hide their wealth when tax collectors came to inventory it. Nowadays they can. It is said that 64 percent of the global profits are parked offshore, for an important part by multinationals from the first world.

The third world is the victim of this practise. An example from the banana industry: exporting a banana from the Cayman Islands costs 13 pence. When it arrives in the UK to be consumed, the costs have grown to 60 pence. All of this money goes to other parties than the Cayman Islands.

Because of the tax havens, countries from the Third World are not able to receive the tax incomes they are entitled to. Henry even concludes that the debt problem of the third world is not a debt problem, but a tax problem. Both amount to almost the same.

About TEDx
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)

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
18:10
and everybody wanted that you know I
18:12
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
18:17
was the goal of everyone it appeared to
18:19
me huh this is money okay and Aspen’s
18:27
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
18:33
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
18:44
hedge fund that does this every year
18:47
they’re taking a percentage they’re
18:50
taking some of that as profit as their
18:52
bonus effectively so they make some of
18:54
that they make some more they make some
18:56
more all of this money they’re putting
18:58
into their own bank account and then
19:01
when they lose money that’s their
19:03
clients money that’s a lot it’s not
19:04
their money so you’ve got you can so you
19:06
can see why it’s very easy for people to
19:08
abuse this kind of thing I think it’s
19:12
fantastic the people who take risk
19:15
should be compensated for taking risk
19:19
but only if they are actually taking
19:22
risk themselves taking risk with other
19:24
people’s money you should not get
19:26
compensated for I’m sorry I did that the
19:29
Donald where that fits into economic
19:32
theory but taking risk with other
19:33
people’s money does not get rewarded
19:34
sadly though it does in this business
19:38
no but now
19:46
there was a moment when I thought when I
19:50
questioned why I was ever involved in
19:53
Wall Street goodbye I need it right now
19:56
on the double
19:57
hi that’s something I thought that
20:01
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
20:08
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
20:15
yes people used it but you know if
20:18
people had used it and put good
20:20
mortgages into it who never would have
20:21
caused a problem at all but when you put
20:24
you know mortgages that you have a
20:26
fairly high certainty that people cannot
20:29
repay and then half of all the mortgages
20:32
issued in a given year that type of
20:33
mortgages yes the industry has gotten
20:36
out of control
20:39
trillions of dollars a year basically
20:41
went through that model these bonds
20:46
within two and three years of being
20:47
issued went from triple-a to
20:50
unwrite I mean just catastrophic
20:51
collapse a lot of trading firms that
20:55
kept these the riskier pieces in their
20:58
portfolio saw them drop to next to
21:00
nothing and given the leverages the
21:02
amount of leverage under the amount that
21:03
the banks had borrowed they were
21:05
suddenly in a financial panic
21:14
Saturday after midnight still studying
21:17
I know long hours will not stop when I
21:20
enter a future job as a client
21:27
because I was primarily a technologist I
21:30
did not fully understand what was going
21:32
on I think part of my motivation
21:34
post-crash for becoming a quant is to
21:37
gain that understanding having been
21:39
through the personal experience of
21:41
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
22:13
people that are in the business right
22:15
now probably refuse to talk to the
22:17
public if they were to talk to the press
22:18
they would be fired
22:19
so only limited few people in the
22:22
business have the option of talking to
22:24
the press once you’re in the world right
22:28
I mean your phones are ringing you know
22:31
from the moment I woke up in the morning
22:32
and I remembered you know a lot of these
22:34
guys I do quite well they try to wake me
22:37
up 6 o’clock oh I thought you were
22:39
asleep you know can you be up till 11
22:41
o’clock
22:44
you have to be wired you have to be
22:47
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
22:54
the software fails people lose millions
22:57
or billions can’t happen you can’t you
23:00
can’t be wrong you have to be perfect it
23:01
says it’s a lot of stress my wife was in
23:07
the business with me
23:08
we both would wake up in the morning and
23:10
describe similar nightmares phones were
23:13
ringing we couldn’t answer them and then
23:15
we sort of grew out of that and we both
23:18
realized that we didn’t know what day of
23:21
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
23:43
stirs
23:50
banking is completely lost touch with
23:53
its purpose its original purpose and is
23:56
now becoming dangerous
23:57
it used to be that when some of these
23:59
derivatives were first invented they
24:01
were to help your farmer for example
24:03
hedge the value of his crop so he was he
24:06
wasn’t speculating on the price of wheat
24:08
he was busy growing it now there are
24:12
more people trading these these
24:14
commodity derivatives and then are
24:15
actually involved in the production of
24:17
the commodity so which is completely
24:20
bizarre I know a lot and quite a lot of
24:24
people in this business who are feeling
24:27
a bit jaded now people are starting to
24:31
ask questions my nice friends I started
24:35
to ask questions about the role in
24:36
society you may be making lots of money
24:38
but are you is it something to tell your
24:40
grandchildren oh yeah I was a banker I
24:42
was there when I caused the the
24:46
2008-2009 crisis etc what are they
24:50
actually doing with their lives or their
24:52
or just moving this money around this
24:54
isn’t necessary such a business to be
24:56
proud of I think that’s probably
25:03
planning 30 35 pounds responsibility is
25:07
just not a one-way street when it’s
25:09
successful you’re responsible well you
25:10
can’t be unresponsible when the same
25:12
same item is is a failure you have to
25:15
have some type of responsibility and I
25:17
could say I wasn’t but I was involved I
25:21
made a comfortable very comfortable
25:23
living and and I was proud of what I had
25:28
done I never I myself never saw this
25:32
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
25:46
inside different color a chef and the
25:50
city loves this wild taste I only do it
25:54
for one chef because if I did too many
25:56
there wouldn’t be enough you know the
25:59
model is Hippocratic oath I will
26:02
remember that I didn’t make the world
26:04
and it doesn’t satisfy my equations
26:06
that’s obviously that’s it that’s about
26:09
having a a mature appreciation that
26:13
whatever you do that the models are
26:15
never going to be perfect
26:16
I will never sacrifice reality for
26:18
elegance without explaining why I have
26:21
done so so it’s again it’s a competition
26:24
between the real world and the elegant
26:27
world of mathematics and sometimes the
26:28
real world is just dirty
26:31
nor will I give the people who use my
26:34
model false comfort about its accuracy
26:36
instead I will make explicit its
26:38
assumptions and oversights quanta are
26:41
asked the following by some trader they
26:43
say well look you’ve just measured the
26:45
risk in this portfolio it’s too big okay
26:48
to quant back to the drawing board
26:50
I want you redoing numbers and come up
26:52
with a smaller risk it doesn’t mean
26:55
change the portfolio it means change the
26:57
maths to make it look less risky people
27:00
can use the models to hide risk though I
27:06
will use models boldly to estimate value
27:08
I will not be overly impressed by
27:10
mathematics people make finance too
27:14
mathematical so mathematical that many
27:17
people who have to implement the models
27:19
don’t understand what’s going on and
27:21
once you have too much mathematics it’s
27:23
difficult to see where the mistakes are
27:25
I understand that my work may have
27:27
enormous effects on society and the
27:29
economy many of them beyond my
27:31
comprehension so this is a serious
27:34
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
27:42
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
28:01
of the book of me and Emanuel Derman
28:06
with our with our Karl Marx beards on
28:08
because obviously it’s it’s basically
28:11
that the inspiration was a kind of
28:12
communist manifesto you take the
28:15
combined the communist manifesto with
28:17
the Hippocratic oath and this is what
28:19
you’ve got when I first came to the
28:21
field I was sort of optimistic about
28:23
using quantitative methods on the
28:24
financial markets and I don’t think
28:26
they’re useless but them but I’m trying
28:31
to think how to say it I don’t think you
28:32
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
28:42
be God’s true for most you know even if
28:44
they’re they’re not 100 percent accurate
28:45
and I’m I don’t think that’s possible in
28:48
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
28:57
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
29:02
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
29:09
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
29:20
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
29:27
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
30:01
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
31:02
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
31:28
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

THE MONEY GAME, CHEATERS EDITION

The coronavirus has thrown us into truly unprecedented times. Most countries have enforced a lockdown, and global travel has ground to a halt, and this, in turn, has had an enormous impact on the economy.

Stock markets all over the world experienced huge volatility. Wall Street suffered its worst day since ‘Black Monday’, oil prices went negative for the first time in history and governments all over the world have been implementing extreme fiscal and monetary policies.

Many analysts have suggested that rather than coronavirus being the cause of this economic downturn, instead, it was merely the pin that popped the bubble and the enormous debts that have been amounting since long before the 2008 global financial crisis was a disaster waiting to happen.

So, how do we get out of this mess? Who stands to benefit from government money printing? Who has to pay this money back? And, why the fuck is Steve Mnuchin, the Secretary of the Treasury?

To answer these questions and more, I am joined by leading finance experts: Andrea Ferrero, Andreas M. Antonopoulos, Caitlin Long, Ben Hunt & Raoul Pal. We look at the corruption and mismanagement of the economy by central banks and governments.

Technology and Politics (Exponent Podcast)

In 2014, Ben and James were talking about the system being “rigged”, anticipating political developments slightly more than 1 year later.

 

Are the recent debates on net neutrality, the protests of Google buses, even SOPA a sign of things to come? Building on Ben’s article The Net Neutrality Wake-up Call Ben and James discuss the intersection of technology and politics.

  • Why do people in technology tend to dislike politics?
  • Is net neutrality really that important and understanding open loop unbundling
  • The tech industry and creative destruction: is it good for society when companies go out of business?
  • The impact of money on politics
  • Why tech and politics are on a collision course
  • What we can do to effect change on an individual basis

Links: