
Why do traders in investment banks feel their jobs are immune from AI, etc? - aburan28
https://www.quora.com/Why-do-traders-in-investment-banks-feel-their-jobs-are-immune-from-AI-automation-and-deep-learning
======
vegabook
because traders are used to seeing such predictions fail.

Reuters was trading FX electronically since the early 1990s. At the tier one
IB I worked for the IT budget was 500m USD a year (across products), and that
was in 1997! Huge resources were thrown at automation. However, to this day,
large trades in FX (> 10m USD notional) are still almost exclusively performed
by humans over a telephone or over the bloomberg messaging system.

That's because, no matter how much you automate stuff, there is still the 1%
"edge case" scenario where something goes wrong, and when that happens, you
most definitely want a human that you can "look in the eye", when you have
that sort of execution risk. Remember that markets move really fast and there
is a lot of risk in big trades that "go wrong" because unwinding said trade
will almost certainly cost one of the sides a fortune.

Also, high finance is not just about what you know. It's inevitably about
_who_ you know, about "illogical" factors such as salesperson charisma,
entertainment, and most importantly, a credible personality type that
understands the edge case risks. These things are very hard to replicate with
a machine. You'll say they should be, that these things are unfair, but they
remain a fact after many attempts at removing them have failed.

As for AI, let's for now call it what it is: machine learning. Learning from
the past. That's fine for recognising stop signs at different distances,
angles and degrees of noise. But in finance, the past is often misleading.
Sure there's trend, but there are also very big instabilities in the
historical correlation matrix. Paradigms shift without you even realising it.
The constant is change. AI is not good enough at that, _yet_.

BTW, that's not to say machines are not making inroads. It's becoming almost
impossible to get a decent trading job now with knowing at least R and Python
to a comfortable degree, and good quant programmers cost a fortune. There's
massive demand.

~~~
dougabug
Machine learning is "learning from data." It is not the assumption that there
are no dynamics, and that the future will simply be a repetition of the past.
To the extent that the future is predictable, learning from data is the best
that can be done.

The reality is that speech recognition, language translation, face
recognition, object classification and detection, semantic segmentation,
speech and image synthesis have improved by extraordinary leaps and bounds in
recent years. If we used the logic that past failures inform a confident
belief that future success in a challenge will inevitably fail, then we
should've bet heavily against Alpha Go defeating one of the most accomplished
human Go champions in the world. Self driving cars seem like a sci-fi fantasy
until they become a mundane reality.

There's an irrational arrogance to human beings in general, and Wall Street
types in particular, regarding the specialness / non-reproducibility of their
intelligence. It's not unlike the belief that people had that organic
molecules were somehow special, "vital," and not synthesizable from base
elements.

Certainly, there's a long way to go to replicate the capabilities of a human
brain, but I don't think we should exaggerate or fetishisize the human power
to estimate and mitigate risk. We've seen many spectacular failures of that in
recent years.

~~~
vegabook
The difference is that chess, go, etc are all essentially rules based. Finance
has very few rules that do not break over time. Just look at QE. Arguably the
financial market represents the collective intelligence of a huge amount of
very clever people. Machines are only just starting to challenge a single
human at a rules-based activity. We're very far from beating a brutally
darwinian, impressively adaptive, human hive-mind whose main skill is figuring
out when rules are about to get broken.

~~~
dougabug
What are the rules for image / video captioning? For natural sounding speech
synthesis? For realistic image generation? For semantic segmentation? For
determining perceptual visual similarity between images?

Frankly, rules based AI is basically a bust compared to learning from data
approaches.

The hive was pretty amazing at destabilizing the entire global economy within
a brief span following fundamental financial de-regulation.

People flatter themselves in ways which satisfies their egos and self-
interest. Of course they want to believe in, and have everyone else credit,
their magical superpowers. No government (backstop) wires necessary.

~~~
dilemma
Automatic image and video captioning is in a very sorry state. Machines can't
do it.

Machine learning is rule based. The difference is just that it creates many
more rules for more and more granular cases. But it will never be intelligent,
it will always be a dumb digital bureaucrat.

~~~
yjftsjthsd-h
Given results from ex. neural networks, ML "rules" appear to be granular and
flexible enough that I'm not sure they usefully count as being rules anymore.

~~~
pyrale
There are rules in that you're able to create an exhaustive labeled training
dataset. The rules may not be generic, but they exist through a specification
by example.

Beating a human when there is no discoverability to the problem, and when
building an exhaustive dataset is a problem in itself is not on the horizon
yet.

------
mathattack
A lot of traders are losing their jobs, and many fear this.

As other mention, though, Wall Street makes a lot of money trading the edge
cases. For instance, many people thought derivatives traders would become
obsolete when the Black Scholes formula arrived. In reality, the model grew
the size of the derivatives market, and traders made money knowing where the
model was wrong. (Example: It assumes constant volatility)

Similarly, many investors use an OAS (Option Adjusted Spread) model to justify
prices on one-off Mortgage Backed Securities. This also helps grow the market,
as there's more transparent pricing. But traders know where the models are
wrong, and make money off of them.

When technology enabled FX trade spreads to be less than a penny, people
thought traders were done. But this increased the volume of trading (more
hedging became cost-efficient) so while the % skimmed by traders decreased,
the absolute $s increased.

Net, as long as the financial pie grows, traders can find ways to siphon money
off. That amount may grow or shrink, but generally the story is more
technology has helped them.

Perhaps the best analogy is a chess expert paired with a computer can beat
either the computer or the expert alone.

~~~
21
> Perhaps the best analogy is a chess expert paired with a computer can beat
> either the computer or the expert alone.

This has stopped being true for a number of years. Computers play chess so
much better now, that a human will actually impede it.

Think this way: could a 12 year old (the human) help a math graduate (the
computer) on some problem? Or more likely he will just be a distraction?

More elaborations on this from gwern: [https://www.gwern.net/Notes#advanced-
chess-obituary](https://www.gwern.net/Notes#advanced-chess-obituary)

~~~
philipov
A better analogy would be computer-assisted poker. The computer can keep track
of the cards and provide probabilities, while the human provides the social
computations (figuring out exploits by modelling the opponent's mental state).
Computers have been very successful at pure optimization problems like chess,
but still lag behind on games of assymetrical information.

The stock market is more like poker than like chess, because it is the correct
application of theory of mind (Can a computer bluff? Can a computer cheat?)
that elevates it above a game of chance.

------
bboreham
For around eight years my primary job function was to put investment bank
traders out of a job, by automating what they did.

There were still humans in charge of the algorithms, but they moved more
towards Python programmers than market traders.

Many of the "old-style" traders bitched about what we did, and most moved jobs
to banks that were less advanced.

(I was in the interest rates line; typical trade size is $10M)

~~~
2sk21
I am curious about how the old-style traders actually did their jobs. Did they
base their trading decisions on data or instinct?

~~~
cm2187
Trading illiquid products is all about knowing your market, and having a good
idea of who you will be able to sell something when you accept to buy it (you
are not in the business of taking a position you cannot get out of). Having a
good understanding of the flows, who is buying, who is selling, who still has
room for this exposure, etc.

This is achieved by discussing with sales people, who themselves discuss with
investors, as well as traders at other banks (through brokers).

Now the definition of illiquid varies. Many products that used to be illiquid
are now pretty liquid (interest rate derivatives) while many other are liquid
only for small trade size (certain bonds). FX is an interesting example. It is
very liquid but it is also a market where many clients need to make jumbo
transactions on the spot, and these would be market moving if not carefully
managed. That's something that could be probably automated.

I find the article very poorly written. "Investment bankers" is extremely
vague and the breadth of very different product in different markets traded by
investment banks makes this sort of generalization a bit absurd.

The other reason why I think the article doesn't make sense is that investment
banks cater for certain giant markets (equity, FX, treasuries, etc) but also
for a huge variety of niche markets, in which only a handful of banks and
traders are active. If you add the salaries of the couple of traders in each
of the active banks on one particular market, the savings you would do
automating the market wouldn't justify the years of IT development to train
and fine tune an algo, which would still need to be maintained as the market
evolves (and then you end up overpaying an AI expert instead of overpaying a
couple of traders...).

I think AI will shine at solving wide problems that affect a large number of
people. Self driving cars. Butler robots. Building a house. Manufacturing
something common. These markets have the scale to justify large investments.

I very much doubt that AI will replace every single complex task done by a man
today, for the very same reason that software hasn't replaced every single
manual task done by a man today: the cost of developing and maintaining
software can easily exceed the salary of the few guys you are trying to
replace. To overcome that with software, we need to dramatically reduce the
cost of developing software, enabling ordinary employees to develop their own
software. But even today we are very far from that. What's the % of a
generation who can actually code out of college today? How easy and useful are
the main programming languages? I'd argue we are now going into the opposite
direction. Microsoft is poised to take VBA out of office. All major OS are
evolving toward the iOS-style locked down platform where you can only run
Apple/Microsoft approved software. Corporate IT is ever more locking down
platforms with software whitelisting, etc. I wonder if the golden age of
productivity improvement through software has not peaked.

~~~
kpil
>To overcome that with software, we need to dramatically reduce the cost of
developing software, enabling ordinary employees to develop their own
software.

I think this is the key to running an effective organisation.

It requires that most people know how to program, or at least know enough to
understand what is possible to program.

I also don't see this coming, partly because the education systems are not
really up to par, but also because it's really hard to develop complex
systems.

I'd argue that the languages are not really the issue here even if the trends
seems to go towards even crappier languages (like js, php) to really mess up
the heads of beginners.

But even with a hypothetical "perfect language" the main problems is the huge
amount of time and effort it takes to learn any programming language at all,
plus the even more enormous amount of time it takes to write something useful
even for a really experienced developer.

But sure. It's perhaps time for a new cycle of tearing down the "mainframes"
(in someone else's basement this time) and reinvent personal computing for the
2nd or 3rd time...

------
Irishsteve
There seems to be some confusion going on about investment bankers and traders
in the discussion.

Trading has been changing significantly since the 'big bang' when trading went
from pits to electronic. From there on in you see the evolution of algorithm /
program trading. This area has been using quants for decades at this point.
There are a good few big names brands out there that are known for being
'algorithmic heavy', Man, Citadel, DE Shaw come to mind (I"m a few years out
of date). That whole field has been open to introducing automation /
algorithms to create a business edge and will probably continue to advance
because its good for business. The profile of traders has also changed (Barrow
boys versus PhDs)

Then I guess on the other side is investment banking such as m&a, equity and
debt capital markets. Generally there its relationship based , juniors work on
pitch books which from what I saw / heard were generally overlooked. This is
potentially a lot harder to automate away. Then the bank would try to pull in
some rain makers or grow them internally to land big deals. Usually these
opportunities open up because their clients (Other companies) have learnt to
trust the organization or at the least learn to expect a certain behavriour
when enlisting their services.

~~~
cm2187
Agree. But even the trading you are referring to is the trading of liquid
products (essentially equity). A lot of OTC trading is still very illiquid and
will likely not move to electronic platforms for the foreseeable future.

------
lordnacho
I've got a story that connects the new and the old way of trading.

When I joined the industry just after the millenium, I joined a firm of guys
who used to be floor traders. Basically the guys from "Trading Places" with
Eddie Murphy: coloured coats, loud shouting, eating contests. As London got
automated, they moved "upstairs", which basically meant holding the eating
contests in a room of screens and squawk boxes. It was a fun time (but not for
everyone; old school also means macho culture and sexual harassment lawsuits).
One day I thought to myself "in what other job in the world would you find
your boss breakdancing?"

I checked up on that breakdancing guy the other day. He's continued along the
way of old school market makers, taking calls from brokers and manually
entring them into a system. He literally said "Nacho, I'm a dinosaur. I can't
code, but I have 25 years of experience trading. And trading changed.
Everything is eaten by the computers, and on top of that we have free money
keeping the market from having more than one opinion."

We talked about a guy who used to work in the firm we were at. He'd gone the
other way, and caught the start of the HFT boom. Now he's a billionaire. It's
amazing that someone could go from the pit to trading several percent of
global daily volume each day.

But basically, the old school traders are well aware of what the computers can
do. They aren't stupid, the ones who can't code know they can't, and they can
see the writing on the walls.

As far as I can tell, there's only one area of trading that's relatively
immune to the machines. And even that isn't completely immune. It's special
situations. That's where you're looking at corporate events like mergers,
rights issues, and so on. It's somewhat hard to automate because there's just
not that many things to make bets on. One guy can sit and read through a bunch
of events and put on big bets, and there aren't that many people who have the
specifics of how to make the decisions. So the benefits of automating it are
not as huge as with most other types of trading.

------
vii
The question is a logical fallacy. I worked at an IB and even in 2011 traders
were acutely aware of the benefits of technology and eager to invest in it and
embrace it. Many of the answers here are regurgitations of techno-utopian
talking points that do not take into account three issues

1\. Traders generally exert an advisory/supervisory role on the set of prices
that the bank offers, prices which are based on a formula or other fairly
automatic means, with an added human adjustment. They already extensively use
technology.

2\. Traders are therefore most involved where profit can be made but simple
algorithms don't work. For example, pricing big deals in illiquid markets,
like when a company issues a large complex bond. As this contract is by
definition not traded yet and not the same as others, there is necessarily
limited applicable training data, so that there is no way to learn by example
- i.e., use deep learning techniques (what I assume the question is asking
about). In this case, trust and relationships are extremely important as both
sides of the deal have limited information.

3\. Markets change dynamics, often very rapidly. Traders have to react
intelligently to events: like interest rates hitting the zero lower bound,
wars breaking out or industrial accidents. They need to anticipate the actual
consequence to future cash flows and also to sense the appetite of the market
after the event. Publicly announced AI techniques are very far away from this
kind of complex general reasoning.

The days of manual trading are long gone: of open outcry traders, yelling in
bullpits and making handsignals, when banks would hire big imposing ex-
football players. The question is a "why do you feel you can get away with
beating your wife"?

------
earthly10x
The last few minutes of this documentary on Long Term Capital Management and
its algorithmic failure will tell you why:
[https://vimeo.com/28554862](https://vimeo.com/28554862)

~~~
smhost
The complete lack of any sign of remorse on their faces about having burned a
trillion dollars made the hair on the back of my neck stand up. I've never
seen such a blatant display of psychopathy.

------
ericjang
Due diligence on the financials of a company (what investment bankers are
supposed to do) is actually really hard to get right with the algorithms we
have today. Much of the data and insight compiled by an I-banker today does
not exist in an easily parse-able form for automated algorithms, and a
substantial amount of the computation relies on common sense knowledge.

~~~
JumpCrisscross
> _Due diligence on the financials of a company (what investment bankers are
> supposed to do) is actually really hard to get right_

Diligence is automatable, in the long run. There is a human element to it, but
it is small in most contexts.

Bankers solve trust problems. An AI would need to be trustworthy in a personal
way to replace bankers--this only happens with AGI. For a long time, as long
as humans control capital, there will be other humans interfacing those humans
with each other.

~~~
marcosdumay
> An AI would need to be trustworthy in a personal way to replace bankers--
> this only happens with AGI.

This happens with an unbeatable public track record. We trust AIs in lots of
tasks already, and that is not because they smile and speech nicely.

------
anonu
I generally don't think that all traders believe their jobs are immune. Any
rational person that looks back at history will observe that the markets have
constantly been changing due to technology that speeds up a trade or makes it
more accurate. However, most of the significant changes have not been to due
to Artificial Intelligence innovations. Instead, those changes have been about
automating tasks that were once repetitive. I wouldn't necessarily call that
AI.

If you'll allow me to simplify the IB Trader's job: there are 2 types of
traders: agency and principal traders. Agency traders build relationships with
clients, accept orders from them, execute them in the market. They make money
on commissions. Principal traders will take risk. Sometimes on behalf of a
client - on the back of a client order - or sometimes purely for the bank's
own account.

The agency traders have seen their roles decimated by technology - because
much of their role (minus the relationship building part) was automatized. On
the risk-taking side, AI has crept into some places - albeit in very narrow
use-cases. For example, we've seen the rise of the robo-advisor, where an
"algorithm" comes in and automatically adjusts your portfolio to reduce risk
and increase alpha. Well, the risk reduction party is well-known (Markowitz
portfolio theory). But the increasing alpha part is the difficult thing. And
AI seems to be quite far off in its ability to be a stock picker - simply
because the passive approach is superior (ie, no intelligence needed at all).

------
argonaut
Because investment bankers are just salespeople? Nobody is suggesting AI will
replace salespeople in the near future. I could see there being fewer grunt
analysts in the future, though.

~~~
sirclueless
> Nobody is suggesting AI will replace salespeople in the near future.

They aren't? Because I see this happening all the time. Automated checkout
lines, E-Trade and online brokerages, etc. Low-value transactions are handled
more and more by electronic "salespeople". All it takes to reach high-value
transactions as well is for the clientele to decide they trust machines more
than humans, which is not all that unlikely given the many sources of human
error involved.

It's possible that humans will be involved in high-value transactions like
investment for a long time, since the marginal cost of human labor is low as
the numbers get bigger, but it's not impossible to replace; we already have
the technology.

~~~
supercon
I think that the term 'salespeople' here refer to those who proactively push
their products to the market and by doing so widen the market for the company
they represent.

The examples you give are indeed places where buying or selling happens, but
where does the incentive to do these transactions come from? It's still from
humans. Sure, we are bombarded left and right with ads that were carefully
targeted for us by complex algorithms, but I don't think I've ever bought
anything from Amazon without reading a review about the product from another
user, or bought stock without going through several opinions written by more-
or-less respected analysts.

------
konschubert
> "Would you trust purchasing a house from a seller, without meeting/talking
> to them, or a single person before and throughout the purchase?"

You mean I can get an unbiased look at a house in peace, compare the numbers,
look at the plans, measure the humidity and do my due diligence without a
sales person breathing down my neck?

Hell yea. I'd pay premium for that.

~~~
tatabska
This is the classical hn bias. Normal people would like to talk to humans. Hn
users would rather get info, plans, etc from houses and eventually buy them
and sign the contract using a REST API with a node.js client..

~~~
jaypaulynice
That's a rational buyer...what do you think the bank does? They run the
numbers to see if the person qualifies, has great credit, etc...do you think
they care how your day is going? Lol...

~~~
tatabska
Of course they don't... But they are not the client... It's the client who
needs honeyed words, and that an AI can't do..

------
portent
In an investment bank a trader has a high ratio of support staff around them:
legal, compliance, IT, operations, quants, finance/tax, risk. These 'support'
jobs are a significant fraction of the real cost of a trading seat - not just
the trader's salary.

Automation has happened incrementally in the industry for years, like many
others - starting with the easiest stuff (low hanging fruit) like some
operations tasks and mechanical trading tasks, and leaving the more complex
tasks for humans - or letting a human scale to do more.

The more complex tasks that are left typically require non-trivial
intelligence, e.g. understanding why the new product brought to market by your
competitor or counterparty is slightly different to what you are trading
today, and deciding if you can/should transact in it. Understanding what
impact the upcoming compliance rule changes have on your market and activities
(there are always regulatory rule changes). Understanding what the limits of
your trading are, to avoid concentrating too much exposure in one area.
Understanding why your counterparty is upset about some aspect of the
transaction. etc.

------
IIIIIIII
Famous last words for a lot of businesses:

>When it comes to AI/Machine Learning: the nature of ____ and markets are
drastically different to other fields that AI/ML have previously excelled in.
The main reason being what are the laws and rules that govern how an AI/ML
should view a field?

>Since the very nature of a market is… a constant change respecting an
infinite and broad amount of variables (____), a complex system (repeating
exact past actions, will not give you the same results) and a social
interaction/conflict regarding an ambiguous ____, it becomes incredibly
difficult to determine those laws and rules.

>In physics, mathematics, computer programming, you will always have a safe
level of predictability when it comes to certain functions and how they
interact to give you a reliable solution. With ____, instead of this safe
level, there is just irrationality beliefs; something you cannot model with
accurate certainty (just look at how AI/ML would handle predictions for Brexit
and Trump, and then, how it would cope with the aftermath).

~~~
user5994461
Markets predictions were at 20% of Brexit and Trump the day before the vote.
And moving from 15 to 50% during the week before that. Noting they followed
similar patterns.

They assessed the risk fine.

------
ynniv
_a constant change respecting an infinite and broad amount of variables
(macroeconomic), a complex system (repeating exact past actions, will not give
you the same results) and a social interaction /conflict regarding an
ambiguous valuation of a price, it becomes incredibly difficult to determine
those laws and rules._

Just like driving a car.

~~~
dsacco
Well, no, not really. Ideally a car has a definable spec, such as a road with
consistent markers. Steering within a consistent set of lines and reacting to
other cars on the road is difficult enough, especially if you try to account
for random behavior from other drivers.

Modeling and forecasting a security's price mathematically, or a set of
security prices, is complex in a different sort of way. A better analogy would
be like trying to program a car to deal with a meteorite that suddenly hits
the road in a random spot, or a bomb that goes off 100 feet in front of the
car as it's cruising on the road. There are far fewer rules with which to
start a foundation, and the entire macroeconomic structure is far more
delicate and in constant flux from news, other traders competing against you,
information closed to the market, etc. With cars, you at least get a road, and
add randomness in with other drivers. With security prices, you _might_ have a
lower bound of potential losses, if you're buying long. It's just a different
animal.

------
wobbleblob
Maybe with their work, labor costs are a relatively small portion of the
product price?

~~~
gaius
Look up the comp ratios of some of the major investment banks. It can easily
be 50%. As with all professional services firms, the biggest costs are people
and real estate.

~~~
btian
I think he's saying the money client pay to investment banks is a small
compared to size of the deals bankers advice / underwrite etc.

~~~
gaius
But it is large compared to what the shareholders earn, and they are the ones
ultimately pulling the strings. The days of the white-shoe partnership are
long gone...

------
beefield
If traders have managed to persuade people that they are able to beat the
market against all evidence[1], why would they not be able to convince people
that they are better than AI?

[1] Of course, there are anecdotal evidence of the opposite, but there
_should_ be those if the performance of a trader is a random process.

~~~
dsacco
Do you consider several hedge funds consistently beating the market with
significant margins for over 20 years to be "anecdotal" evidence?

The evidence shows that it is very difficult for traders to consistently beat
the market. The evidence does not show that their performance, as a
profession, is random.

~~~
beefield
Yes, I consider them anecdotal. If you have a billion people flipping coins, a
few are for sure getting 20 tails in row, but that is no evidence that they
would be better coin flippers than the others.

> The evidence does not show that their performance, as a profession, is
> random.

I think you are right, if I recall correctly, the evidence points to a
conclusion that the performance of their profession is _worse_ than random
when you take fees into account...

~~~
dsacco
Yes, that's the classical coin flipping example from the strong position on
Fama's Efficient Market Hypothesis. There are several problems with the coin-
flipping analogy:

1\. As stated, it's not falsifiable. So you start with a conception of the
market as entirely random, and you observe that participants are consistently
beating this market. Each time you observe someone beating the market, you
chalk it up to the probability distribution. _" Well, that's just a two-sigma
event._" Then you see it happen again. _" Well, that's just a three-sigma
event._" Then again, and again, and again. How many sigmas from the average
market performance are you willing to accept before you agree that someone is
legitimately and purposely beating the market with a skill-based mechanism,
not a chance-based mechanism?

Furthermore, do you have the numbers to turn this into a falsifiable claim?
What is your time interval? Daily, weekly, monthly or annually? How many
correct forecasts do they have to make ("how many sigmas from the average"),
compared to the chance expectation of coin flipping over the same timescale?
If you don't have these numbers handy, then it's purely a thought experiment.
Subsequently, the observation that funds like Berkshire Hathaway, Bridgewater,
Renaissance Technologies, Baupost Group, Citadel, DE Shaw, etc. consistently
beat the market for at least 20% _net of fees_ over 20-30 years suggests that,
per Occam's Razor, people can beat the market due to skill.

2\. The analogy is not comparable to active trading. You don't need to hit 20
heads in a row to beat the market consistently, you just need to hit a p-value
number of _x_ heads correct for _y_ coin flips greater than chance would
suggest. We don't assume that basketball is a game of chance if the players
can't make all their shots in a row; nor do we assume that baseball players
with a 0.3 batting average aren't clearly better than the average high school
dugout. If your trading interval is weekly or monthly, and you're consistently
up over the market (even net of fees!) for 240 months or 360 months, it
doesn't matter if every single month was a winner.

3\. Have you ever read Warren Buffet's response to the EMH assertion, as
postulated by Fama?[1] He outlined an excellent rebuttal in his 1984 _The
Superinvestors of Graham and Doddsville._ Essentially, if you assume that the
coin flipping analogy _does_ map to trading, then you should expect to see a
normal distribution of the winners, given that the market is inherently random
and no one is achieving superior coin flips through skill. However, if you
observe that the winning coin-flippers consistently hail from a small village
with standard coin-flipping training, then it is more reasonable to assume
that there is something unique about those particular flippers. This is what
we see in reality - yes, most amateur traders fail miserably, and yes, most
hedge funds underperform the market over time. But there is a relatively small
concentration of extremely successful funds and traders in an uneven
distribution.

4\. Even Fama has walked back on Efficient Market Hypothesis, and no longer
espouses the view that the market is inherently random. It is deeply complex,
yes, but it is not efficient, nor entirely random. Several studies have been
conducted to empirically examine EMH, and the results in favor of the
hypothesis are dubious.[2][3][4] A much more charitable retelling of EMH is
the weak position, which essentially states that any _obvious_ alpha will be
quickly arb'd out of real utility, but that _non-obvious_ alpha, or alpha
which is technically public but not easily _accessible_ will retain utility
until it becomes obvious. This also maps more cleanly to reality, in which
trading on e.g. news reports is mostly unprofitable (everyone can get a news
report at around the same time, for the same level of skill) whereas
mathematically modeling pricing relationships can be extremely profitable
(doing so accurately requires public, but mostly unclean data and a great deal
of skill).

_______________________________________

1\. _The Superinvestors of Graham and Doddsville_ \-
[http://www8.gsb.columbia.edu/rtfiles/cbs/hermes/Buffett1984....](http://www8.gsb.columbia.edu/rtfiles/cbs/hermes/Buffett1984.pdf)

2\. _Investment Performance of Common Stocks in Relation to Their Price-
Earning Ratios: A Test of the Efficient Market Hypothesis_ \-
[http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1977....](http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1977.tb01979.x/abstract;jsessionid=93367F17F01A240FFD25E0CB0BF66FB8.f03t04)

3\. _The Cross-Section of Expected Stock Returns_ \-
[http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1992....](http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1992.tb04398.x/abstract)

4\. _International Stock Market Efficiency and Integration: A Study of 18
Nations_ \-
[http://onlinelibrary.wiley.com/doi/10.1111/1468-5957.00134/a...](http://onlinelibrary.wiley.com/doi/10.1111/1468-5957.00134/abstract)

~~~
beefield
My belief in some of the weaker forms of EMH does not stem from the idea that
markets would be somehow correct, but vice versa. Markets are (almost[1])
always incorrect, and nobody can know how much they are incorrect tomorrow[2].
Thus nobody can beat the markets, other than the random coin tosser.

Now, I fully agree that there have been certain anomalies (value premium
anomaly in case of Buffett) that pretty much align with the strategies of
these long term successful investors. Question is, has it been their skill to
pick right anomaly as a basis for their strategy, or luck? Again, in the world
of investment strategies, there for sure is _someone_ trying almost anything.
And if that anomaly disappears[3], do they have the skill to change their
strategy?

But we are a bit off topic here. The original question was "Why do traders in
investment banks..." that is a different species from the warrenbuffetts.

[1] Asset markets can be right somewhat like a clock that has stopped is right
twice a day.

[2] Yes, Keynes said "The market can stay irrational longer than you can stay
solvent."

[3] I have actually bet my money that the value premium anomaly is not
disappearing, but that anomaly is not something investment bank traders can
enjoy, as the anomaly is far too long term anomaly for them.

------
bnmfsd
Is there a fallacy name for this? i.e., asking a question that suggests
something ("investment bankers have this feeling") as a premise, that may be
not true.

~~~
amelius
It isn't a fallacy to ask a question :)

~~~
pestaa
Indeed it can be:
[https://en.wikipedia.org/wiki/Loaded_question](https://en.wikipedia.org/wiki/Loaded_question)

------
jahnu
For similar reasons that spreadsheets didn't put accountants out of work.

------
bamurphymac1
Honestly, maybe they just don't care? Rather, what should they do about it,
what would we expect people with such huge earning potential _right now_ to do
other than push forward with the plan that works under the status quo.

Answering my own question: I'd expect bankers to save more (of their own
money) in anticipation of the good times not lasting as long. More
conservative types will weather the storm and spendthrifts will get wiped out.

In other words: business as usual, up until the very moment it isn't.

------
yazaddaruvala
Everybody feels _their job_ is safe from automation. Its the same way planes
crash but _not mine_.

Believing "I am special", is just built into us.

~~~
314
Not only do I believe that my job can be automated - I've spent years trying
to do just that.

Of course, I wouldn't be giving the scripts to my employer, just spending more
time doing other things...

~~~
yazaddaruvala
I think the difference here is "task" !== "job". You're automating tasks. Your
job is to keep the system running as effectively as possible (I don't know
what you actually do). Meanwhile, I do get that you're not actively trying to
lose the responsibility of these tasks, i.e. "I wouldn't be giving the scripts
to my employer", but that is because you're trying to hold onto the relaxed
transition phase between tasks X, Y, Z to tasks 1, 2, 3. If you really had job
security issues, you would not have written those scripts.

Are you sure you haven't perhaps fallen prey to too much job security? Such a
large sense of job security that you don't care about automating X part of it
away. You, like me, like other "rockstar" software developers, (perhaps[0])
believe it doesn't matter if you automate X, Y, Z, because you're so good,
that when you're out of responsibilities you will be offered the
followup/orthogonal tasks 1, 2, 3.

Anyways, I'm just trying to highlight that you too, perhaps subconsciously,
think "I am special, it wont happen to me", because at least I who also don't
care about automation feel this way.

[0] I know for me, this is the truth. This overconfidence is why I don't care
about automating my tasks away. Honestly, even giving the scripts to my
employer makes little difference to me.

~~~
314
To some extent what you say is true, but only partly.

I'm not part of the cult of the "rockstar programmer". I do write a lot of
good code, and I tend to do it much faster than other programmers that I work
with. But programming is not actually my job description.

Without going into details - I do something else for living, that uses
computers quite heavily, and automating my job is more of a hobby. I have a
huge amount of flexibility in what I do, so there is an element of
substituting 1,2,3 for X,Y,Z because I find them more interesting. My boss
wouldn't care one way or another - he is more interested in whether or not the
tasks get finished, and maintaining a high quality level in the final product.

------
fpoling
A good trader can explain their trades, a good AI cannot _yet_. This is
important in many financial settings when some human must still be personally
responsible for the trades. For a manager it is much easier to approve
regression coefficients or a particular trading formula than to sign a neural
network into production.

~~~
webmaven
_> A good trader can explain their trades_

Yeah, but what are the odds that their explanation is just a post-hoc
rationalization (ie. "heads I get credit, tails I avoid blame")?

------
RockyMcNuts
what a strange question. technology has eliminated swathes of traders, open
outcry exchanges, equity execution traders. if you watch CNBC, you see almost
no one on the floor of the NYSE , because there is nothing worth doing there.
(except for a couple of exceptions due to exchange rules)

------
rbcgerard
Some vocabulary might be helpful here, generally there a few buckets most
traders can be put into:

1\. Proprietary trading (think hedge funds or the old bank prop desks, ranges
from the bass brothers to renaissance tech in terms of style)

2\. Execution or sales traders (often work for or are the counterparts to #1,
their goal is get the best price for their clients in the quantities and time
frames desired)

3\. Market making (essentially providing liquidity to both buyers and sellers)

4\. Sales - essentially layered on top of 2 & 3 to interact with 1

With that said, #3 has pretty much been automated in some markets and is the
easiest to automate, #2 has had a lot of automation for vanilla stuff, but
people are still involved in big, complicated things. #1 may be automated but
is largely strategy dependent, #4 is pretty hard to automate...

------
dbs
I don't agree with the question, especially if we are talking about de facto
traders. There is a high level of worry because commission margins and returns
per unit of risk are the lowest ever. I would say there is a high level of
calculated ignorance in the industry.

Truth is, most trader jobs have been gone in the last 15 years. First it was
the automation of order collection (phone orders being replaced by automatic
order routing processes), then automation of the execution process (from human
order management to algorithmic trading), then automation of the investment
management process (from discretionary processes to quantitative management),
and the last frontier will be the automation of the relationship with the
client.

Problems are different for different trader types.

Execution traders execute orders on behalf of clients. Today a lot of clients
execute directly using web terminals and APIs. And if you still execute on
behalf of others you spend a lot of time fighting against the machines (one
solution is to trade out of market, but this too is being automated). Very
very hard to come up with new execution algos.

For delta hedging traders the role has been reduced to monitoring, unless you
have allowance to take risk (which most banks don't since the 2008 crisis).

For alpha traders, whose job is to extract money from market, the risk is not
in being replaced by the machines, but one of overcrowding, i.e. everyone
following the same strategies is reducing returns and increasing risk (skew)
across the board.

Sales traders whose activity is to sell first, and trade last, still need to
manage relationships with customers. But this has been changing gradually,
with clients prefering digital interfaces, passive investment programs, and
now the rise of automated investment management programs.

I started working in the industry circa 1999. The head of trading I was
working with told me once machines will never be able to invest like a human.
He's still there doing a lot of money, but certain that it will end someday.
His strategy: "let's see if I can make it one more year"...

------
millstone
If the role of investment banking is to optimally allocate capital, then part
of that job is research. Think Andrew Left's exposing fraudulent Chinese tech
stocks, or the Lumber Liquidators controversy. Algorithms can augment this
work, but cannot replace it.

------
sverige
Well, an equally good question is why do programmers feel their jobs are
immune from AI, etc.?

~~~
qz_
Interesting, I never thought about that. It seems like something very far off,
though. Does anyone know about any research currently being done in this
field?

~~~
mike_hearn
That's what (supervised) machine learning and neural networks do, isn't it.
You specify the "what" and not the "how", they figure out the "how". Basically
techniques for automating the task of computer programming given requirements.

So any advance in AI/ML/NNs can be seen as advances in the field of automating
computer programmers. We don't tend to think of it like that because these
techniques have to be applied, currently, by computer programmers, and the
software the techniques "write" was generally infeasible to write by hand
anyway: it's been so far purely additive and solving problems that hand-
written software either couldn't do at all or where it sucked and progress was
very slow.

But watch out. The tech is getting better scarily fast. Neural networks have
been able to learn how to do basic algorithms like sorting given only
examples. The primary limit is still the amount of data they need to work
with, but R&D is driving that down too.

I can see a time when many tasks that today automatically require skilled
programmers are instead done by domain experts who simply shovel data into an
advanced neural network and discover it gets results that are good enough.
Perhaps hand-written software made by a skilled programmer would be better,
but the machine is a lot cheaper ...

[http://www.i-programmer.info/news/105-artificial-
intelligenc...](http://www.i-programmer.info/news/105-artificial-
intelligence/7923-neural-turing-machines-learn-their-algorithms.html)

------
wickedlogic
Traders will still be needed to justify bad decisions, or 'good' logic with
bad outcomes run by AI. ;)

Everytime I see a gameshow where you can 'bank' your current winnings, ... I
imagine the future of trading will include some strategy that has an AI
yelling those sorts of things to other ai agents acting in concert. The
strategies of the macro stock market positive outcomes, being applied to micro
stock actions. [https://www.t0.com](https://www.t0.com) is also going to be a
fun reality.

------
DrBazza
For one thing, traders have knowledge of multiple markets and real-world
events (hurricanes, elections, etc.) can infer correlation between those and
place trades accordingly. AI is completely unaware of these things and can
only train itself on the market data it trades against.

Also, not all trading is liquid, nor is it short term, both of which are
targets for automated algorithmic trading. Long terms investments are
typically human decisions.

------
zump
God I'm so fucking jealous of computer specialists who work in investment
banks. How do I get in without going to Harvard?

~~~
chillydawg
They are exactly what they claim to be: specialists. You need to become one in
some area that banks deem valuable. Current white-hot areas would be FPGA,
machine learning (but you'll also want a PhD in statistics, or at the very
least a good degree in it from a good uni) or be a badass systems developer
who can write absurdly low latency code in terms of allocation, cache
coherency, network sympathy and so on. To get this good, you need to have been
doing it for a decade or more, so start now. At the bottom. No one leaves
university and gets one of these jobs. They leave university, maybe get a PhD
or work for a decade and work up to them. You are jealous of people who have
put in thousands of hours of very hard work into their careers, but will you
do the same?

~~~
bboreham
Large IBs do hire dozens of new graduates every year into IT.

You have to be bright, articulate, interested.

~~~
zump
That tends to be Java CRUD not trading logic.

------
treehau5
> "Why do traders in investment banks feel their jobs are immune from AI,
> etc?"

Why do people need to have anxiety and fear about AI is the better question.
Let's solve those instead of this blindless ambition to automate everything,
and then somehow assume our benevolent government will give everyone UBI or
some other pipe dream.

------
wslh
I just think that if AI could beat them, they were already replaced. Any
innovation in trading is automatically implemented. May be this will be
possible in the future but it doesn't depend only on deep learning techniques
and having huge samples for learning because they have both.

~~~
saintPirelli
AFAIK the bulk of investment bankers are beaten just by chance as this article
suggests: [http://www.automaticfinances.com/monkey-stock-
picking/](http://www.automaticfinances.com/monkey-stock-picking/)

~~~
portent
The bulk of investment bankers are not picking stocks for funds. In the field
of fund management, there are some people doing this, and it is a very common
trend that passive indexes do better than the active funds - it is true.

In the field of investment banking trading (which is mostly market making) the
amount of automation varies by asset class: very automated for some asset
classes like fx, equities, much less for more illiquid asset classes like
credit, commodities, bespoke products.

As well, senior traders operate as the 'business' making more decisions than
pricing of products. They make the business decisions often judging legal,
compliance, accounting risks. (and not always correctly.).

e.g. do you accept to trade with a Dutch counterparty who wants to trade
against your German legal entity knowing that you can only hedge the position
in London? What is the risk between the two legal setups? What premium should
you charge for those risks?

Do you trade the very large size that the counterparty wants, knowing it takes
you over your balance sheet position limit - can you get approval for this
from your senior management? Can you offset the position in the market without
it moving against you? What premium do you charge for this?

------
edblarney
I don't think bankers are naive, they are seeing it happen.

If your job can be done overseas, it probably will be outsourced.

If your job is algorithmic, you'll be replaced by a computer.

A lot of M&A activity though doesn't fit that category.

------
blazespin
If it's true, it could be that there is more insider information being used
than is generally recognized. Computers can't get that info.

------
finman1
They don't. I work in in the trading department of a large bank - directly in
finance, not IT. Have been here 10 years.

Here's what I have seen. For more "liquid" markets - like delta-one blue chip
equities, IR swaps, spot FX - jobs ARE moving quickly. People are not
complacent. Competition comes from firms that are much faster in execution,
having automated most of the process - and presumably having lower hedging
costs by being able to move quickly. Or just basing their decisions "better"
on history.

Having said that, you have to remember that: a) Size of balance sheet matters.
A large bunch of clients of such firms trade with them due to "synergies".
Large shops are one-stop shops. They don't just sell you a swap. Its usually a
loan/funding + an option to hedge it + some tax advice thrown in. Its hard to
break it down into components and trade individually, as most other players
may not be even willing to face such counterparts. And shopping for each
component separately might mean larger time and friction costs. Here being a
large bank helps massively. Basically - capital is hard to be automated,
decision making is easier.

b) There are a large number of markets that cannot be automated anytime soon.
These are "illiquid" or "exotic" markets. The data on them is scarce and
trades happen in a lot less frequency, then say swaps or delta-one equity.
Throw in some options, and your model might say here's a price, but there's no
guarantee on it. Then you have to balance it compared to your book size, and
the price is not discoverable, or even same across firms (for good reason - my
cost of cash liquidity might be different to yours). Sometimes counterparts
will trade with you even if you have a worse price, because there's lower risk
of you falling down in 10 years on a 20 year cross currency trade or inflation
swap.

c) Good traders are very defensive and paranoid. They don't work under the
paradigm that history will repeat itself. They will try to look for risks that
might seem to have nothing to do with their market. I know some traders who
have been making good money every year in these exotic markets, regardless of
crisis or not. Some of the sharpest people I know - and they love their job.
Not just the money aspect. They just love the whole high pressure environment
and everything it entails. Now they are being drowned in regulation. Don't get
me wrong - regulation is good, but right now we have a mess. I won't try to
convince you - and unless you work in a bank, you will not agree with this.

d) Management is old. Might seem obvious, but most of the people at the top
have made their money the old-style way. After a certain amount of time, you
tend to trust your own instincts more than other things, especially if you've
been successful (which may have just been a random process to start with). So
they think this is just another fad and it will pass. These things have come
and gone - we're still here. This is a prime reason why some banks fail
suddenly. The top guys just didn't see it coming.

------
BigJeffeRonaldo
Because investment banking is a sales job.

------
allenleein
Investment bank business is all about conncetion. Connections lead to deal.
Machine can not replace that forever.

------
alexnewman
Because investment banks are run by sales. Only the people at the bottom
actually care about this stuff

------
gozur88
>No amount or greater sophistication of the algorithmic structures listed
above, can replace genuine human nuance, interaction and trust.

I don't think this is true. Not at all.

~~~
deepGem
Me neither. How much of the genuine human nuance is present in today's
financial services or any commission driven industry - next to nothing. Every
agent/broker is motivated by the highest commission he/she can make, nothing
more.

~~~
pyrale
I can reasonably say that you make this comment because you know nothing about
the business logic of trading desks.

A trader is not necessarily a sales or a broker, though. Nor is he a quant, or
a dev. People rarely imagine how many different jobs are involved in the
trading job, and how rich the business logic is. At my shop, traders are the
piece that connects all of the jobs in the value chain.

I believe, currently, the business logic can be improved locally by learning
systems (and it is), but there is no public example of an industrial learning
application encompassing a scope comparable to what the usual trading desk
handles. Sure, there are many inefficiencies ; traders work on heuristics,
afterall. But I don't believe we have the necessary horizon to aptly predict
the end of traders, because I don't see how we could make AIs with a better
efficiency.

~~~
deepGem
I'd say I know something about the business logic of trading desks. Some of my
friends worked at GS. I'm not implying traders are brokers. I do agree that
the trading business logic is very rich and that AI will be nowhere close to
replacing a trader in the next 15-20 years at least.

I do foresee a future in which a trader can accomplish a lot more than he/she
can today using AI. So in the future as the per trader efficiency increases,
the number of traders required will most probably decline, unless there is a
dramatic increase in trading volume that cannot be matched by the then state
of the art AI.

This is essentially what's happening today with X.ai, Facebook messenger and
the like. Sure the logic involved in booking air tickets for a group of 5 over
10 conversations isn't as complicated as the rich business logic of a trade,
but 5 years back Facebook messenger would've seemed almost impossible, just
like the trading business logic seems impossible to do with AI today.

~~~
pyrale
I have no doubt new technology will be leveraged to improve productivity, but
that's been quite common in the last decades.

On the other hand, the technology advances needed to transform the tools into
standalone actors are not merely a matter of scaling current technology.
Especially, the creation of training datasets is a problem for which we
currently have no solution, that's why we fall back on human trainers (mturk,
etc). That's why a solution to a problem with no clear, bounded model and no
easy dataset seems out of reach.

------
wickedlogic
Why do programmers think their jobs are immune from AI, hubris and history.

------
quickben
This post will get buried in this discussion, but I actually worked for a HFT
company trying to break into all sort of algorithmic trading (and made a small
fortune doing so).

The topic question is:

1\. Loaded question

2\. Uninformed question, look at a small subset of the electronic trading
_reality_.

3\. Overly broad: jobs are immune from AI, etc (what? depression? ancient
aliens?)

So, in order:

1\. Some traders will always get fired as they can't do their jobs (or are
just plain unlucky in the wrong time).

2\. The 'traders', or rather what people think of a 'trader' is a wrong image
in what I worked with. They were people configuring algorithms, linking
dependencies between tickers in various market segments, etc. These traders
did some rudimentary AI guiding of a sort. They used their brains, read
newspapers, tried to code engines to parse said newspapers with machine
learning long before it became media catchphrase, failed (badly), configured
various triggers. They weren't 'traders' in your ordinary sense of the word,
but struggled to make that work. It takes a _lot_ more in scope, than buy low
sell high' to make trading work in this millennia. Several magnitudes or more
work, if I'm to scope it. It's a corporate effort, not a singular one. Traders
do get fired but whole corporations go under also.

3\. The 'etc' part:

\- AI will never advance to the level to predict the future, as it will not
know the sum of human experiences driving that future. This is especially true
for the financial market as it is linked with the rest of all human activities
in a un-linkable fashion. I can take this as a philosophy thought experiment,
or as an economy fact, or from my limited experience, but, take it as you
will, AI is a 2017 buzzword to come. Take it with a grain of 100 shares worth
of salt.

\- There is a very _finite_ liquidity in the market, compared to the money
available. When you have to iceberg orders to not destroy a trading strategy
and move the gap for _everybody_ , it's really obvious that the money you can
make are _limited_. This was true in 2010, when most of the major banks
decided to also enter, and is more true today. So, connected with the previous
point. AI will never be _fast_ enough, to earn on the limited liquidity
compared to available players, considering we are capping off in silicon CPU
processing power right now. I'm open to arguing this point, as it was argued
to death among friends in the last decade, but I don't see this moving in any
direction unless processing power moves off silicon, and even then, for a
while. You can't scale atoms, and you still need 80 of them (or whatever is
the latest) for building anything, so that's the hard wall. [extra thoughts]
Given all of the above, humans have an edge, and humans with experience, have
a sharper edge than the AI. In trading, nothing will change, and AI wont
_replace_ traders. We can argue this point, feel free to reply.

\---

[extra thoughts] Purely my take on this, as future trends:

Javascript as popular web language will get capped off on performance soon
(few years?). Thus, as demand increases one of these will happen (or all three
of them):

\- Javascript will get threads, locks, and the rest of the circus and
Javascript programmers will have to learn a lot more on top of what they know
(in a language not quite friendly for writing threaded code in the first
place) and it will be super fun to be one for a while.

\- A new language will emerge to replace the web languages and get more
performance by simplifying the interaction with he browsers (Think CICS + IBM
+ inline assembly there)

\- The JavaScript+Browser Layers+OS+VM approach will get replaced with
something more lean in the next 5-10 years because people will want more
(whatever more is, nobody predicted it 100% so far).

Anyways, this post got unintentionally too long, I guess I had something to
say on the subject :)

------
chvid
Because what they are doing is really (an indirect form of) sales.

------
eva1984
A lot of them didn't understand technology.

------
progx
Insider trading can not be automated ;-)

------
Tycho
Reflexivity.

------
frankritchie
can AI discover insider info?

------
aresant
HN title is significantly different than the question the submission actually
asks which is "why do TRADERS in investment banks . . . " and should be
updated

~~~
nstj
In case the full title makes a difference it's "Why do traders in investment
banks feel their jobs are immune from AI, automation, and deep learning?"

cc @dang

~~~
huac
It looks like the question title was changed, in order to aggregate similar
questions/answers. Most of the answers answer the question in the current
title. I agree that trading and IB is a big distinction, and traders are 1.5
feet out the door already.

~~~
grzm
There's also a length limit to submission titles. I don't know what it is, but
I suspect the original title exceeds it.

~~~
nstj
> Please limit title to 80 characters [0]

[0]:
[https://news.ycombinator.com/submit](https://news.ycombinator.com/submit)

------
known
"Give me control of a nation's money supply, and I care not who makes its
laws." \--Rothschild, 1744

------
holri
Because Warran Buffet uses a computer - but only for bridge playing. But he
uses a pocket calculator for his investment decisions.

His philosophy is heavily based on soft facts. Appreciation of management and
understanding of the business model. This is not only based on logic and
numbers. Therefore a computer does not help.

