[HN Gopher] A quantum walk down Wall Street
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A quantum walk down Wall Street
Author : helsinkiandrew
Score : 80 points
Date : 2021-11-07 07:02 UTC (1 days ago)
(HTM) web link (www.economist.com)
(TXT) w3m dump (www.economist.com)
| andreareina wrote:
| This sounds like something to be solved by agent-based
| simulations that don't need any quantum woo. What am I missing?
| snthpy wrote:
| The end of the article talks about valuing call options. I took a
| graduate course on Path Integrals for Derivatives Pricing in 2001
| or 2002 so nothing new there. Since I didn't become a bank quant
| I never had any use for it. Linear models are much used on the
| buy side. Agree with the Nick Patterson quote below which says
| the same.
|
| Hard to tell what the book is about. Sounds a bit like a Deepak
| Chopra take on economics. Throw a few mentions of "quantum" in
| there to sell books.
| Ice_cream_suit wrote:
| Renaissance Technologies is rumoured to use methods from
| topological quantum field theory.
|
| They are fiercely and aggressively secretive, so no one really
| know for sure.
|
| However, their founder worked in that field before moving to
| business:
| https://en.wikipedia.org/wiki/Chern%E2%80%93Simons_theory
|
| Famously, he was sacked by the NSA for giving an interview
| opposing US involvement in the Vietnam war.
| tubby12345 wrote:
| >topological quantum field theory
|
| lolol. i will bet all of my 401k that they absolutely do not.
|
| i've interviewed at a couple of hedge funds and have lots of
| friends at various prop shops/hft firms/etc. most of them are
| using linear models. the ones that have market maker businesses
| deploy those linear models to fpgas.
|
| people act like these places are spooky magic cauldrons of
| physics + math + computer science. they're not (but it's
| definitely in their interest to promote such rumors). what they
| do have is very very robust data collection/aggregation
| infrastructure and backtesting systems. the rest is just
| correctness of execution of strats.
| lordnacho wrote:
| I'll second that. I've done options trading, trend following,
| and HFT. Often you need smart people to do simple things, but
| they are still simple things. Gotta remember there's a lot of
| noise in financial data, and you don't actually have as much
| of it as people think. Even all the ticks on all the
| exchanges fit in a few GB of binary per day.
|
| RenTech is especially good at acting like they're from
| another planet, which I'm sure helps them attract those
| stellar mathematicians.
| pgwhalen wrote:
| > Even all the ticks on all the exchanges fit in a few GB
| of binary per day.
|
| This isn't true once you include equity options, which have
| several orders of magnitude more data.
|
| However your general point still stands, because most
| options trading strategies don't need such extreme
| granularity of data. Much of it can be ignored, or close to
| it.
| dave_sullivan wrote:
| That's actually been surprising to me but makes sense: "the
| entire history of the stock market" is not that big in
| terms of data, and the dynamics change frequently enough to
| where things that happened in 2000 are almost useless from
| a machine learning standpoint, my models perform best when
| trained on a much more selective subset (I believe because
| the reasons for trades and market participants keep
| changing, so the dynamics change enough to where old rules
| don't apply anymore).
| helsinki wrote:
| Correct. You can make money using only yesterday's data
| for training purposes.
| mellavora wrote:
| Your especially right about the noise in financial data.
| Nice thing about linear models (vs i.e. random forest, or
| even worse deep learning) is that they are limited in how
| they can overfit the noise. They only fit a known function
| to known regressors.
| xapata wrote:
| And, even more important, they aren't susceptible to
| adversarial activity like a deep net could be.
| WanderPanda wrote:
| Can you distinguish noise from non-linear correlations? I
| feel like you can never prove the absence of non-linear
| correlation, but only showing it's presence once
| modelled/detected
| njarboe wrote:
| RenTech is also basically the only largest hedge fund that
| has beat the market by a wide margin for decades. An
| average 66% annual return in their Medallion Fund since
| 1988 according to wikipedia. That is pretty much insane and
| seems to be something only space aliens could do. If anyone
| is using quantum computers to help trade, it is probably
| them.
| kasey_junk wrote:
| Worth noting that their public funds don't return
| anything like the rumored Medallion fund returns (though
| they are generally pretty good).
| selectodude wrote:
| Medallion is also kept very small because I would guess
| the tricks that they use to keep those returns so high
| (maybe even some sort of topological quantum field
| theory!) don't scale well to larger investments.
| njarboe wrote:
| Not sure if I would call ~$10 billion very small and
| making $6-7 billion per year is good chunk of money. But,
| yea, I'm sure that would get bigger if they thought they
| could keep their returns high.
| wolverine876 wrote:
| > An average 66% annual return in their Medallion Fund
| since 1988 according to wikipedia.
|
| The claim, the secondary (tertiary?) source, and the
| primary source make that all hard to not smile at.
|
| 66% annualized returns are more likely to be pyramid
| schemes - but that couldn't happen, could it?
| H8crilA wrote:
| That's because it's not 66% but instead $6B. If they had
| twice as much capital it would be 33%, and if they had
| ten times as much capital it would be 6.6%. I'm
| simplifying to show the main point.
| RationPhantoms wrote:
| The Medallion Fund has already reached their max
| investment amount so while it's ground-breaking, no new
| RenTech employees can take advantage of it.
| amelius wrote:
| Linear models, so not even deep learning models?
| tubby12345 wrote:
| i interviewed at DE Shaw not less than two weeks ago. my
| research area is GPUs and etc. they don't have a GPUs team.
| i passed on the offer.
| quantumofalpha wrote:
| Why not both? Linear models for absolute lowest tick-to-
| trade latency doesn't preclude you from using fancier stuff
| at earlier modelling steps. Final linear models you ship to
| fpga can be mere distillations/triggers
| short_sells_poo wrote:
| No. Most "advanced" ML methods are extremely difficult to
| get to work in finance. You have a limited dataset that is
| low signal to noise ratio, highly non-normal and
| heteroscedastic. Crucially, you can't easily make more data
| (and no, synthetizing new price data is not an option in
| most cases). This makes the upfront costs very high, and
| you then have to prove that you can beat the performance of
| simple models, and not just by a little. A complicated ML
| model that offers a 10% better risk/reward ratio (e.g. 2.2
| Sharpe instead of 2) is a complete failure, because you
| traded a simple model that is easy to reason about
| intuitively for a total blackbox that is very difficult to
| understand.
|
| Sure, you've got the quintessential marketing induced ML
| overlay that many firms do, but in all cases I've seen so
| far it's completely defanged and really there only so that
| it can serve as a marketing move.
| quantumofalpha wrote:
| Really depends on time horizon you're talking about. They
| actually work pretty well for HFT, there's plenty of data
| around, and most of the information is just in market
| data - no nasty low frequency stuff to deal with like
| news, earnings, alternative data, insider trading,
| butterflies flapping wings in china etc. But the problem
| is by the time your GPU spits out a datapoint somebody
| else can go in and trade a few thousand times in the
| meantime. State of the art on the most heavy competed
| exchanges is that your fpga (or even asic) with a fiber
| connected directly to the exchange needs to start sending
| ethernet/ip headers even before it made up its mind what
| it wants to send in the payload.
|
| At lower frequencies when the data gets thin and
| noise/overfitting is a major problem, yeah it makes sense
| to use simpler models. Bias/variance tradeoff in action.
| bagels wrote:
| This sounds a lot more plausible. Being able to extract
| signals faster or that others cannot seems a much more likely
| strategy.
| dahak27 wrote:
| You're right overall that most of these places are a lot less
| flashy on the inside (have worked at a couple). Linear models
| everywhere as you said
|
| However I think you're underestimating RenTech here. They're
| genuinely just in another league compared to what most people
| consider the "elite" quant shops. You're not getting in
| unless you're an actually impressive academic with a track-
| record, so I wouldn't be surprised if they're trying some
| weird stuff that other shops can't even understand (although
| I would imagine in small size vs. more vanilla stuff).
|
| IMO places like JS/CitSec do a really good job of bombarding
| campuses to inculcate this idea they're the absolute apex of
| mathematical wizardry, but the places that are really doing
| some dark magic shit aren't trying to get undergrads to apply
| to them. Ofc maybe I'm falling for the same kind of
| propaganda for RenTech
| DebtDeflation wrote:
| >However I think you're underestimating RenTech here.
| They're genuinely just in another league compared to what
| most people consider the "elite" quant shops.
|
| People said the same thing about LTCM. They had multiple
| Nobel Prize winners on staff, literally the people who
| wrote the Economics and Finance textbooks.
|
| Then a decade later, history repeated with all of the prop
| trading outfits doing securitization.
|
| It's always the same ingredients: 1) a theoretically sound
| strategy for taking advantage of some arbitrage opportunity
| 2) the assumption that positions can actually be liquidated
| on demand at the prevailing price and 3) enormous amounts
| of leverage. Then something happens that wasn't accounted
| for (e.g., sovereign default, counterparty default, etc.)
| and suddenly the strategy is no longer sound ("in a crisis
| all correlations go to one"), the liquidity assumption is
| no longer true ("where are all the buyers?"), and the
| leverage puts you out of business ("the market can stay
| irrational longer than you can stay solvent"). People never
| learn.
| bidirectional wrote:
| RenTech was founded years before LTCM and is still going
| strong. It's not repetition of history, they've outlasted
| or are older than most of the trading desks ever. They're
| basically a business providing a service to other market
| participants and executing that incredibly well, it's
| quite unlike the arbitrage LTCM was involved with.
| DebtDeflation wrote:
| And Bernie Madoff founded his firm two decades before Ren
| Tech, hell at one point he was the Chairman of NASDAQ.
| noduerme wrote:
| All of this wizardry operates under the premise that given
| just the right meta-meta-meta-formulae some tiny edge over
| randomness can be squeezed from the mountain of historical
| data by sheer willpower and brute force computation. _It
| cannot_. The sooner people accept this as an iron rule, the
| sooner they 'll stop falling for scams that promise to
| foretell the future.
| PascLeRasc wrote:
| Clarification: the data appears random to you.
| carnitine wrote:
| But it obviously can. The returns of Renaissance's
| Medallion fund cannot be explained by randomness. If
| every company in America was a hedge fund since 1776, the
| returns of Medallion would not arise by chance. They
| clearly have an edge (and don't even accept outsider
| money, so no need to falsify).
| ackbar03 wrote:
| I think your definitely idolizing them a bit too much.
| Maybe a bit ahead of the curve but not doing anything
| super fancy (although I guess those two statements are
| somewhat contradictory).
|
| Just from snippets I've sort of heard/read about, I think
| they were one of the earlier ones to move into HFT
| (although maybe not the super fast infrastructure heavy
| type these days). In some interview Simmons said they
| realized returns became more predictable they shorter the
| time frame they looked at and they pushed it to the
| extreme. I think there is also reason to suspect that
| they may have adopted some NLP strategies early on as
| well since Mercer was involved in that or something, and
| they initially hired a bulk of their team from IBMs NLP
| research team. Also they did not dodge 2008 completely,
| in some interview they said they lost close to / more
| than half their portfolio value in the market crash, but
| because they didn't have stupid leverage or outside
| investors or something like that, and also because they
| trusted their models, they didn't sell and held on. So
| maybe just slightly better execution but mostly the same.
|
| Anyways, I was reading about these guys back in 09 when
| quant trading wasn't so blown up. Now every kid whose
| decent at math seems to want to be the next renaissance,
| which just makes me feel like the best years for that are
| over.
| randomcarbloke wrote:
| fancy or not an edge is an edge.
| WanderPanda wrote:
| I'm not so sure the best years are over. The passive
| investing trend might work to the contrary and make the
| markets less efficient
| carnitine wrote:
| I'm not idolising them, I'm just framing their returns in
| the correct perspective. The probability of any of the
| top firms existing by chance is astronomically small,
| that's all I'm saying. Same is true of BlueCrest etc.
|
| As far as I know the NLP stuff is more to do with similar
| techniques being applied to market data, rather than
| actual speech recognition or whatever. Hidden Markov
| models and the like.
| evanpw wrote:
| Medallion distributes their earnings and stays a fixed
| size rather than compounding, so it's a category error to
| compare their returns to most hedge funds. (At 66% return
| for 30 years, they'd own everything in the world
| otherwise). They're more like an internal prop-trading
| firm, which makes their returns good but not insane.
| carnitine wrote:
| I'm well aware it's not compounded, it's still a
| worthwhile comparison. We're comparing ability to capture
| alpha, they're clearly among the best in the world at
| that. 66% is insane for 30 years as a prop desk even with
| a fixed capacity, what makes you say it's just good? Who
| is doing better?
| pfortuny wrote:
| They are the best at extracting information from publicly
| available data at fast speed, no more than that.
|
| If you hire very intelligent people to do just that, you
| are doing it right. But the info is out there for
| everybody to see. They just arrive earlier than others.
| How? That is the secret.
| throwaway198843 wrote:
| They are well known for insider trading and other market
| abuses. Of course they'd rather everyone believed it was
| all the PhDs they've hired, but it's just a smokescreen.
| carnitine wrote:
| The SEC will pay you a lot of money if you can
| substantiate those claims.
| pfortuny wrote:
| https://www.cityam.com/renaissance-hedge-fund-pay-5bn-
| back-t...
|
| That is one example.
| carnitine wrote:
| That's neither insider trading nor market abuse. They did
| something in a grey area regarding taxes, then decided to
| pay the bill rather than fighting in court to determine
| if it was or wasn't legal.
| santiagobasulto wrote:
| Where are Reinforcement Learning algorithms standing today in
| Finance? I remember ~3 years ago they were supposed to be the
| next big thing.
| RandomLensman wrote:
| Seconded. I think generally people give way too little weight
| to actually doing things well. There can be some clever
| mathematical ideas in there here and there, but in the end it
| has to come together into a running organization that makes
| little mistakes and can run consistently (while also
| observing a lot regulations).
|
| For me the "spooky magic" is more the ability to pull this
| off in size.
|
| Edit: I do have friends on the buy side that use pretty fancy
| models, but those places are not in the HFT/market making
| game. But using those models does not take away from needing
| to be able to translate the edge consistently and
| efficiently.
| [deleted]
| noduerme wrote:
| I mean, every model's output is in the eye of the beholder
| (or modeler). Take any unpredictable wave-like chart and ask
| someone which direction it's going in next - and guarantee
| you'll throw $100M on their choice. Hey! You just
| successfully collapsed a wave! It's funny how after all these
| millennia, most people still don't understand that someone
| claiming to divine the future from bloody egg yolks or
| whatever is just _manipulating the future by getting people
| to believe in their magical divination_.
| jacquesm wrote:
| > Renaissance Technologies is rumoured to use methods from
| topological quantum field theory.
|
| Rumor is they use magic.
| HenryKissinger wrote:
| Maybe they use Maybelline.
| paulpauper wrote:
| > topological quantum field theory.
|
| doubt it.
| Kranar wrote:
| I have never worked at Renaissance Technologies, but I do run
| an HFT firm and am quite familiar with my own techniques as
| well as techniques of other competing firms, and none of us use
| anything that could be described as remotely sophisticated.
|
| One thing I tell new quants that I hire is that your job is
| kind of like a magic trick. To an outside observer the trick
| looks almost supernatural, but once you understand the trick
| you realize it's so unbelievably simple and straight forward
| you wonder how it is you were ever fooled by it.
|
| That said, even if someone tells you how a magic trick is
| performed and then hands you everything you need to perform it,
| you are almost certainly going to mess it up. It takes a lot of
| practice, skill and discipline to pull off even a simple magic
| trick even after you fully understand it. All of the difficulty
| of a magic trick is in the execution, not in the idea.
|
| It's the same with quantitative finance, the techniques do not
| involve anything remotely complex like quantum mechanics and in
| fact I am almost certain to reject strategies that are overly
| complex... but even if I revealed how our simplest of trading
| algorithms work, it's still incredibly difficult to actually
| execute them. Taking an idea and translating it into a high
| performance algorithm that is bug free, dealing with
| networking, collecting and dealing with petabytes of data,
| having a tight iteration loop, risk management, and most of
| all, having the creativity to identify something simple among a
| sea of complexity, those are what make my firm and other firms
| successful.
|
| It's unbelievably difficult work and most quants do end up
| failing, but it's not difficult in the way that many people
| think it is. If anything, most quants I've worked with fail by
| overcomplicating things and not being able to work from the
| ground up, off of first principles.
| xiaolingxiao wrote:
| This is exactly what I hear from people who have ran their
| own funds. In particular, the person who ran a HFT in the
| late 90s through the early 2010s said he rarely used anything
| more complex than linear regression with at most two
| variables. The speed of doing computations also matter here,
| his fund was eventually squeezed out by bigger guys w/ more
| racks. I did hear from a person who ran a quant fund with
| longer holding times that they used models such as Kalman
| Filter, which require far more computation to estimate values
| than regression.
| [deleted]
| jedimind wrote:
| I would love to hear about some recommended reading and other
| sources which could help hobby traders like me to develop
| their own algorithms.
| Kranar wrote:
| Good sources are very hard to find because most of it is
| absolute trash intended to appeal to a certain audience who
| think there's money to be made off of reverse Fibonacci
| patterns or other silly sounding technical indicators that
| once again, sound technical and fancy but are completely
| useless.
|
| If you want to know what it's really like to be a quant,
| review stuff from the ARPM; everyone I hire goes through
| their 6 day bootcamp but they have other materials as well:
|
| https://www.arpm.co/
|
| And as for books, Algorithmic and High Frequency Trading
| covers the foundations:
|
| https://www.amazon.com/Algorithmic-High-Frequency-
| Trading-%C...
|
| Those are pretty good sources to get an overview of what
| actual quants at successful firms know.
|
| Quantitative trading is technical, I don't want to give the
| impression that it's not technical... but it's not "fancy"
| technical. It's more along the lines of rigorous and iron
| clad instead of flashy and sophisticated. Every strategy is
| built up step by meticulous step in precise detail and
| every step needs to be rigorously justified and
| experimentally verified.
|
| Generally the thought process starts from the assumption
| that there is no money to be made on the stock market,
| either due to perfect efficiency or things like fees eating
| up any potential profits... when we talk about models, the
| models we construct describe how the stock market would
| behave if it were perfectly efficient, ie. free of any
| arbitrage opportunity.
|
| Then given our model of a perfectly efficient stock market,
| we simulate what we should expect to observe in such a
| perfectly efficient market... we then investigate
| empirically whether these observations happen in reality.
| Is the market genuinely efficient all day every day across
| every security.
|
| For some phenomenon it really is, but sometimes the market
| deviates from the model, so our model is either incorrect
| or an arbitrage opportunity has presented itself. If an
| arbitrage opportunity presents itself, we investigate how
| feasible it is to capture it, things like engineering
| effort, risk factors, profitability etc...
|
| If all of that works out, then we get to work constructing
| a state machine for an algorithm to capture that
| opportunity. We implement the state machine, write tests
| for it, run it through our backtester, then run it through
| our live simulator, and after everything checks out we
| deploy it live.
|
| Every algorithm is treated like a person, it's given its
| own human-like name, has its own account, its own set of
| permissions, capital allocated to it, risk profile, and
| algorithms are evaluated on a daily basis to reallocate
| capital to them and modify their risk profile.
| jedimind wrote:
| Thank you so much for taking the time and sharing your
| knowledge, much appreciated!
| mrjangles wrote:
| Assuming one has an appropriate PhD in math/physics, what
| other kind of general knowledge questions would you be
| asking people in an interview? For example, I've read
| that one should learn modern portfolio theory before
| going for an interview. Is this sort of thing true, or
| would that be a waste of time?
| nradov wrote:
| Fascinating. Could you describe how you deconflict your
| various named algorithms and prevent them from competing
| with each other?
| sampo wrote:
| The description says they already have a market
| simulator, which must be a significant piece of software
| to initially construct. Once you have that, you could
| just run simulations and observe empirically, if your
| algorithms end up competing against each others.
|
| Not that I know, how they actually do it.
| alpineidyll3 wrote:
| Well put.
| oarabbus_ wrote:
| >Renaissance Technologies is rumoured to use methods from
| topological quantum field theory.
|
| I am struggling to convey the magnitude of how skeptical I am
| of this claim.
| matheweis wrote:
| Nick Patterson, formerly a senior statistician at Rentech, was
| on a podcast saying that their most important tool was a simple
| regression.
|
| I suppose he could've been lying, but the believable accounts
| suggest that the majority of their magic is simply having smart
| people use simple tools very, very well.
| abzug wrote:
| Do you have a link to this podcast? Or just the name.
| matheweis wrote:
| Talking Machines: AI Safety and The Legacy of Bletchley
| Park http://www.thetalkingmachines.com/episodes/ai-safety-
| and-leg...
|
| Transcript with time stamps by @clausok:
| https://news.ycombinator.com/item?id=19065226
| dahak27 wrote:
| I think this is right - my experience as JS and similar
| places is that really understanding your data-generating
| process and the nitty-gritty assumptions of your data/simple
| model makes a huge difference
|
| E.g knowing what's causing missing values in your data and
| what implications various fixes on that might have on bias in
| your linear regressor is probably way way more valuable than
| fitting some shiny non-linear toy
| wolverine876 wrote:
| > their founder worked in that field [topological quantum field
| theory] before moving to business:
| https://en.wikipedia.org/wiki/Chern%E2%80%93Simons_theory
|
| > Famously, he was sacked by the NSA for giving an interview
| opposing US involvement in the Vietnam war.
|
| Another cult of personality in business. Bill Gates, Jeff
| Bezos, Henry Ford, JP Morgan, etc. managed to do a lot without
| cults of personality.
|
| The more BS I see, the more I question what they are hiding,
| and the more I question their judgment in distracting their
| organizations from practical business, and distorting reality.
| bidirectional wrote:
| The famously outperforming fund at Renaissance (Medallion)
| does not take outside money, and Renaissance itself is a
| privately held company, so there's not much need to cultivate
| such a cult.
|
| Honestly, I don't really get your perspective. Simons
| legitimately was one of the best mathematicians in the world
| and was sacked from the NSA. This isn't some Musk-esque 'I
| sleep on the factory floor and sign off on everything despite
| lacking the bona-fides' nonsense, he was 40 before entering
| the investment industry and before that won top research
| prizes, published quality research and ran a math department.
| wolverine876 wrote:
| Yes, but who cares? Why is that important?
|
| > ran a math department
|
| OT, based on what university faculty have told me, so maybe
| not true everywhere: chairing a department is a thankless
| political nightmare. It's foisted on people who can't say
| no; it isn't an honor.
| bsedlm wrote:
| I like to think about Natural numbers as a basis for money
| (accounting) giving way to Integer numbers as a basis for money
| (banking). Going on along this trend, one gets to Real numbers
| (Finance? trading stock?) and so until modernity with Complex
| numbers as the basis for money (global financial? trading options
| and other derivatives?)
| trylfthsk wrote:
| Relativistic trade: Quaternions
| massinstall wrote:
| Having worked in the industry for almost 25 years (in options
| trading), I must comment that the general quality of the article,
| and the author's apparent level of understanding of the industry
| and options are highly questionable.
| mebassett wrote:
| for those not in the know - can you point out some specific
| parts of the article that are erroneous or misleading ?
| massinstall wrote:
| Sure thing. :)
|
| _This interference creates a very different probability
| distribution for the asset's final price to that generated by
| the classical model. The bell curve is replaced by a series
| of peaks and troughs._
|
| -- No, it's not replaced by "a series of peaks and troughs".
| This is nonsense. It sounds flashy, as it reminds of the
| peaks and troughs seen in the double-slit experiment, but it
| does not accurately describe what could be done to improve
| modeling with probability distributions. Looking at it from
| an information-theoretic point of view, peaks and troughs in
| a probability density distribution would just mean lower
| entropy, i.e. it would be implicitly assumed to contain
| (quite a lot) more specific information than another,
| smoother PDF. So where does this information suddenly come
| from?? If this is not what the author meant, then it is at
| least an unfavorable choice of wording to write that "the
| bell curve is replaced by a series of peaks and troughs". To
| have mercy on the author, one could maybe assume they meant
| to speak about a characteristic function (https://en.wikipedi
| a.org/wiki/Characteristic_function_(proba...) but that does
| not seem to be the case.
|
| Furthermore, any probability distribution may be used to
| model financial instruments, depending on how well it appears
| to be suited for the purpose of modeling reality. However, if
| the author already speaks about it so specifically, it is
| almost misleading not to mention that normal distributions
| (the bell curve) are in practice not used in the way
| described, at least not by people who know what they are
| doing. Consider why Nassim Nicholas Taleb (author of "Fooled
| by Randomness" and "Black Swan") said that no one in the
| industry uses Black-Scholes, or ever has. What he was
| referring to - correctly - is that (in the options space)
| nobody uses the normal distribution assumption to be correct
| for the modeling of asset prices per se. It is rather used as
| a stepping stone with some convenient mathematical properties
| to describe things analytically.
|
| _Broadly speaking, the classical random walk is a better
| description of how asset prices move. But the quantum walk
| better explains how investors think about their movements
| when buying call options [...]_
|
| -- Nonsense. There is not even a hint of an explanation why
| either of the two would be so. It is merely an empty sentence
| that reads well. Quantum walk explains investor rationale and
| psychology? And only when buying call options?! This is quite
| funny actually.
|
| _A call option is generally much cheaper than its underlying
| asset, but gives a big pay-off if the asset's price jumps._
|
| -- Not always so. It depends on many things. Calls actually
| consistently disappoint some buyers by moving much less on
| the way up than what they expected / had hoped for. Having
| looked at a call's delta as per Black-Scholes, they end up
| wondering why the call did not move as much as the delta
| would have predicted. It has to do with spot-vol correlation
| (and other things), but I won't go down this rabbit hole
| now... (I would say you can PM me if you are truly interested
| and want to know more, but it does not seem to be possible on
| HN.)
|
| _The scenarios foremost in the buyer's mind are not a gentle
| drift in the price but a large move up (from which they want
| to benefit) or a big drop (to which they want to limit their
| exposure)._
|
| -- If you are a buyer of a call option you would certainly
| not hope for a big drop in the underlying (!) and neither
| would you limit your exposure to such event by buying a call.
| This is, unless you hedged it either delta-flat or fully,
| which essentially transforms the call into a synthetic put.
| Nothing of that sort is mentioned here.
|
| _The prices of such options closely match those predicted by
| an algorithm based on the classical random walk (in part
| because that is the model most traders accept)._
|
| -- No, they do not match a price "predicted" by an algorithm
| (assuming the author is referring to market prices of the
| options here). It is the other way around. The assumptions
| ultimately used to make the algorithm fit the market are what
| is "predicted" by the market. The "algorithm" referred to
| here is likely the Black-Scholes formula and it does not
| predict any market prices. It gives you an idea where the
| expected value of the option would be if all of its
| unrealistic assumptions were true (which they aren't). So you
| have a function with many parameters, one of the most
| important ones in this context being implied future
| volatility (average future variance to be super-correct). But
| you still have to make a choice of what such inputs you want
| to use for them (the formula will spit out almost anything
| for the right choice of inputs). In practice, a subset of
| these parameters differs for each option from strike to
| strike, so there is no "close" match found to market prices
| at all.
|
| _But a quantum walk, by assigning such options a higher
| value than the classical model, explains buyers' preference
| for them._
|
| -- No. Rubbish. How is this comparison even made. Assigning a
| higher value, based on what benchmark or standard of
| comparison? The same input parameters to the pricing model?
| Hardly, as a quantum model would likely have quite different
| parameters than a "classical" one. This is just textual
| fluff.
|
| _Such ideas may still sound abstract. But they will soon be
| physically embodied on trading floors, whether the theory is
| adopted or not. Quantum computers, which replace the usual
| zeros and ones with superpositions of the two, are nearing
| commercial viability and promise faster calculations. Any
| bank wishing to retain its edge will need to embrace them.
| Their hardware, meanwhile, makes running quantum-walk models
| easier than classical ones. One way or another, finance will
| catch up._
|
| -- Hype paragraph.
| tylerrobinson wrote:
| I think given that the article was a five minute read intended
| to introduce the financially literate reader to the new concept
| of quantum finance that the level of detail was quite
| reasonable.
| kvathupo wrote:
| To add on to the comment of /u/massinstall outlining the
| objectively incorrect info, finance has already been
| investing in quantum computing (from which quantum walks
| originate and are useful). JP Morgan has had a bunch of
| people who've put out quality work in quantum computing for
| options pricing. Goldman probably took heed since Nikitas
| Stamatopoulos is working there now? Also rumorish, but there
| are people at ren tec who did work in quantum information
| science. As to whether they use it? -\\_(tsu)_/-
|
| Regardless, finance isn't playing catch up.
| whytaka wrote:
| Do you have a link to any article related to your industry that
| you found insightful and erudite but still accessible to
| outsiders of finance? Not complete novices, but maybe an
| intermediate-level familiarity to the industry.
| massinstall wrote:
| There are so many. What in particular are you looking for?
| tubby12345 wrote:
| http://isomorphisms.sdf.org/maxdama.pdf
| saltedonion wrote:
| What is this exactly? Looks both interesting and intense
| perpetualpatzer wrote:
| The linked pdf contains notes explaining HFT circa ~2011.
| The About section explains it's sourced from the author's
| blog, and was also used as lecture notes for an undergrad
| course. I've not read the whole thing, but at a minimum,
| the brainteasers contain some good nerd-sniping content.
|
| For those wanting more recent additions, the author seems
| to have more updated thoughts here[1], as linked on the
| LinkedIn profile to which their former blog redirects.
|
| [1]
| https://blog.headlandstech.com/2017/08/03/quantitative-
| tradi...
| saltedonion wrote:
| Wow. Thanks a ton. This is why I love HN
| cercatrova wrote:
| Sounds like the Gell Mann amnesia effect.
|
| https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnes...
| vmception wrote:
| This doesn't seem accurate, many newer physics theories are used
| heavily in finance.
|
| I would say its mostly in communication.
|
| People set up laser beam networks on rooftops to get faster
| pricing data.
|
| The processors and hardware are all pushing for faster reading
| and trading, with continual research at the physical level.
|
| Some formulas still go into financial models or back into
| physics.
|
| Just like the article started off its examples with.
| throwaway210222 wrote:
| The uses of advanced laser networking kit is to to gain an
| advantage in front-running.
|
| Which is to say, to get your brokerage's orders in ahead of a
| large institutional order.
|
| IOW: Legally-sanitised insider trading.
| vmception wrote:
| I don't care.
|
| Maybe informative for others.
|
| My actual opinion on that is that you used to have to go to
| the square where people were exchanging. People farther
| distances away simply were not there and had to wait in the
| newspaper to know what happened with prices. I don't consider
| advances in communication to be controversial in that regard.
| I do think people should be aware of who sees their
| communications.
| amelius wrote:
| The problem is that you need an increasing amount of
| capital to trade. It raises the barrier to entry.
| bidirectional wrote:
| Not 'to trade' but to enter the small world of HFT. Many,
| many industries have capital barriers to entry, I don't
| really see the big deal. Just as I cannot start an HFT
| firm, I also cannot start a toy factory or restaurant
| without sufficient capital. If you actually look at how
| much money HFT firms earn relative to the finance sector
| as a whole, they're pretty small fish. They just pay a
| lot because they have relatively few staff.
| djbebs wrote:
| Thats not true at all
| amelius wrote:
| Why is that? You have to own some laser networking kit in
| a line-of-sight to play along. That costs money.
| throwaway210222 wrote:
| The dogy bit is _knowing_ that a large institutional order
| is coming.
| [deleted]
| GDC7 wrote:
| I feel like people should separate RenTech and Medallion.
|
| RenTech funds which are not Medallion have experienced losses
| similar to any other .
|
| The idea is great: looking at past events to understand how a
| particular event such as a sunny day in Manhattan or what did the
| Yankees do the night before (and millions of other things)
| influences the price of a stock.
|
| If you have enough data you can go back and test if a signal is
| really a signal or just random coincidence.
|
| But somehow it's not working as well as it sounds on paper, I
| think one of the reason might be that signals like that are very
| weak and they fade over time so you need leverage to make sure
| that you cash in while the signal there (because it's weak and
| subtle) and also you end up losing a bunch of money by chasing a
| signal which is on its way out.
| acidbaseextract wrote:
| https://archive.md/Ye8v3
| neonate wrote:
| http://web.archive.org/web/20211108075421/https://www.econom...
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