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A summary of what quantitative trading firms do
- RyanShook 9y agoWas aware of arbitrage and market making as a quant strategy but had never heard of market taking as an outsider. Thanks for sharing, helps give a little better picture of how the market works.
- mlevental 9y agothe linked article (500k in one year...) is really good too.
- wind85 9y agothis is awesome.
- melling 9y agoHere are some useful quantitative trading links: https://github.com/melling/MathAndScienceNotes/blob/master/quant_trading.md https://github.com/melling/MathAndScienceNotes/blob/master/q... Some include previous HN posts.
- afeezaziz 9y agoThanks for this.
- kapauldo 9y agoNot concise.
- whoisninja 9y agoThis alludes that all quantitative trading is high frequency trading. I would think all high frequency trading is quantitative trading but converse is not always true.
- whoisninja 9y agoBecause then one of the most successful quant funds like twosigma and rentec are not doing quant trading since hft is only small portion of their business. You cannot manage 50B in an hft strategy single handedly. The author lives in a different dimension, but my dimension could be wrong!
- georgeek 9y agoHFT is best defined as predicting movements under a tick; everything above a tick is out of HFT territory. Latency requirements could still be pretty serious though, as many models at many firms can act simultaneously for longer frequencies as well.
- mathattack 9y agoExactly. Quant funds like AQR do very little high frequency trading.
- axlprose 9y agoIndeed. One of my favorite finance talks is "A Breif and Biased Survey of Quantitative Investing" by AQR's Cliff Asness, which talks about what quant funds actually are. Link for those curious: https://youtu.be/FqaP3VTKccE https://youtu.be/FqaP3VTKccE
- 0b01 9y agoLow latency is to trading is what database is to e-commerce site. The word you are looking for is quantamental.
- DrBazza 9y agoAlso low latency trading is not always high frequency trading. Low latency trading can just be about getting queue priority.
- zbentley 9y agoThis is substantially higher information density than anything I've read in the last week. Learning about triangular arbitrage programmatic trading alone looks like it's going to occupy most of the next few days for me.
- seanp2k2 9y agoBtw, people are doing lots of arbitrage with crypto currencies as well if you weren’t already aware. It could be a fun way to play with it without spending much if you’re interested.
- santiagobasulto 9y agoI've been thinking about this for some time now. Do you have any resource to share or know anybody doing it?
- jstanley 9y agoPeople doing it successfully are unlikely to share their secrets, unfortunately.
- pc86 9y agoUntil/unless the crypto market in general crashes, or the gains have all been arbitraged out, at which point we'll see a flood of Medium posts about how someone bought their house by arbing DOGE.
- S3raph 9y agothe problem with cryptocurrency arbitrage is that the profit depends on how fast/reliable the various exchanges process your transactions and how much the transaction fees are and not how sophisticated your algorithm is. nice read: https://steemit.com/arbitrage/@kesor/the-math-behind-cross-exchange-arbitrage-trading https://steemit.com/arbitrage/@kesor/the-math-behind-cross-e...
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- godelmachine 9y agoNever knew FPGA programming was so easy in quantitative trading. Would anyone kindly shed more light on use of FPGAs in HFT & Quantitative Trading? Any web links or PDFs?
- seanp2k2 9y agoNot sure how helpful this is but http://algo-logic.com/node/1 http://algo-logic.com/node/1 Is a vendor of NICs that have FPGAs built in to do programmable algo trading VERY quickly. A friend used to work there.
- kgwgk 9y agoAnother vendor: http://www.novasparks.com http://www.novasparks.com
- dfox 9y agoFPGA programming is easy when your problem space uses event-driven state machines even on sequential CPUs as is the case for many things besides HFT, but it is not always so obvious.
- S3raph 9y agohe published also a now kinda old, but still great trading introduction/summary: https://www.quantopian.com/posts/max-dama-on-automated-trading-pdf https://www.quantopian.com/posts/max-dama-on-automated-tradi... The pdf link seems broken, but through Google you should easily find the pdf (maxdama.pdf)
- KngFant 9y agohere it is: https://web.archive.org/web/20160515034451/http://www.decal.org/download/2582 https://web.archive.org/web/20160515034451/http://www.decal....
- dogruck 9y agoThank you. I’m having trouble downloading the pdf from that link. Tips?
- liftingdutchman 9y agogoogle : inurl:maxdama.pdf
- tomp 9y agoActually I think that document is a far better overview, it actually outlines some statistical techniques (that are still very useful AFAIK) and doesn't focus exclusively on HFT.
- ComodoHacker 9y agoIs quantitative traders' role in the economy similar to that of cryptocurrency miners: they form consensus on the state of the market?
- rocqua 9y agoThat would be the case for Market Taking and Arbitrage. They help with determining an accurate price (Market Taking) and with keeping prices equal on all exchanges (Arbitrage). For Market Making the goal is not to form consensus on the state of the market. Instead, Market Making is about creating a liquid market. That is, making sure that when someone wants to buy or sell, there is a willing counterparty at a non-stupid price. Alternatively, you could describe them as 'keeping the spread low'. That is, keeping the difference between the lowest buy order and highest sell order low.
- godelmachine 9y agoThe author says that he is giving a high level overview of the work done in quantitative trading firms, and then mentions that - "things like co-location, direct connection to the exchange without going through an API, using a high-performance language like C++ for production (never Python, R, Matlab, etc), Linux configuration (processor affinity, NUMA, etc), clock synchronization, etc are taken for granted." I'm surprised to see that engineers are required to know hard core VLSI stuff like processors and physical affinity to cores, Non Uniform Memory Access, clock synchronization et al. Thought only Integrated Circuit Digital Design/ Chip design engineers are required to know that. Would anyone kindly shed more light on this subject? Has anyone used VLSI / Digital Design topics as part of his Quant trading / HFT work?
- aldanor 9y agoOne of the main reasons here is minimizing the number of (FPGA) cycles it takes you from reading the first byte of the incoming UDP packet to writing the first (or last; depending on exchange gateways configuration) byte of the order that contains your reaction to the market data. If you're also doing computations "inline" (as opposed to what the author described in the article), it's even more complicated since you now have to build the books and calculate various things before committing to a decision. This may affect the general design of the strategy / execution strategy, so quants/engineers involved are often assumed to have the knowledge of how things work, down to the cycle level.
- grkvlt 9y agoThis is not really about VLSI style hardware knowledge. The 'processor affinity and NUMA' config is all about minimising the cost of memory access, and maintaining cache consistency. They want to make sure that processes aren't continually being moved to different cores or accessing memory that is further (slower) away, to minimise latency. The 'clock synchronisation' talked about is probably not at the CPU clock level, but rather the wall-clock time, using GPS receivers or atomic clocks and NTP servers to ensure all involved servers are synchronised.
- godelmachine 9y ago
- human803658052 9y agoMany companies make a profit by doing something that benefits society in at least some way, society pays them for their service. E.g. selling electronics: the company makes a profit, but society benefits by being able to buy and use those electronics. What about quantitative trading firms. They make a profit themselves. But how do they benefit society?
- bgitarts 9y agoThey would argue that they get paid to capture market inefficiencies and make the market efficient so goods, services and companies are properly priced.
- S3raph 9y agoand they improve liquidity (reduce bid/ask spread)
- tomp 9y agoYou could say the same thing about most advertising companies (i.e. including Google, Facebook and most startups).
- Synaesthesia 9y agoPeople have a misconception of advertising as a noble or worthy, and necessary thing. In business school it’s taught that it’s purpose is to inform rational consumers about what to buy. Actually if you look at advertisements, you learn it’s purpose is to misinform irrational consumers into buying. Advertisements have learned to use emotional messages, sex, repetition and other irrational means to sell.
- gaius 9y agoQuite. If a person needs a thing they will realise that themselves and go out and buy one. Advertising is 100% about things you don't need and have no real reason to purchase. https://genius.com/Bill-hicks-on-advertisers-and-marketing-annotated https://genius.com/Bill-hicks-on-advertisers-and-marketing-a...
- SirLJ 9y agoVery interesting article, but heavily focused on high frequency trading... I am really involved in low frequency trading with as I call them stock trading robots and have been doing this for many years with double digits return on average and all is done with python and few VPS around the world for redundancy e.g. very low brier of entry...
- chirau 9y agoHi, can you elaborate on low frequency trading? Is that day trading or it's holding positions for much longer? Any resources?
- SirLJ 9y agoNope, it is not day trading... I think you cannot win against the HFT shops, unless you spend millions on co-location and the whole arms race... No resources, everything is based on my own experience...
- MarkMc2412 9y agoWould love to hear more about this, you should do an article/post!
- SirLJ 9y agoFrankly I won't... I am not selling or promoting anything, I don't need clients or investors, I am not promoting myself and I am not looking for a new job, quite the opposite, I am actually looking for an early retirement, (but I just can't leave the team I am leading behind, so I am postponing very year...)
- Dowwie 9y agoA vital enabler of these firms is leverage through margin financing. There wouldn't be quant trading firms without leverage, extended by a prime broker. Larger firms deploy fairly interesting, complex arrangements across multiple prime brokers. You don't want a pb to know your entire trading strategy. The PB, on the other hand, wants self-funding accounts, featuring hard-to-borrows and other types of valuable securities as collateral that can be rehypothecated and used by its securities lending businesses. Finding a viable leverage policy across multiple prime brokers is a nice, juicy challenge for the problem solvers.
- aldanor 9y ago> There wouldn't be quant trading firms without leverage, extended by a prime broker. Please allow me to disagree :) Most larger pure-algo HFT prop shops are self-clearing, they are exchange members (possibly with more favorable fees due to market making) and don't use pbs, instead relying on their own co-located execution infrastructure and funding.
- ycombobreaker 9y agoIt really depends on the trade, and what margin offsets you can use. Simplest case is everything in a single exchange, with full margin offsets. If it is split in a way that several exchanges or regulators require capital to be posted, then you need to sort out financing somehow.
- turingcompeteme 9y agoThis is true for, as you said, large hft shops. But there are thousands of quant trading firms that are not on this scale and will not be an exchange member. You can see all the NYSE exhchange members here [0], and it's a very small portion of all quant funds. Managing margin and leverage between prime brokers is an important job for the backoffice at the fund I work for. These numbers are watched very closely, and we have strong, multiyear relationships with the people who work at these PBs. [0] https://www.nyse.com/markets/nyse-arca/membership#directory https://www.nyse.com/markets/nyse-arca/membership#directory
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- lifeisstillgood 9y agoOne of the things that interests me is just how much, if anything, the development of these systems can be applied elsewhere outside of finance. Now I get some attempts to financialise other industries (usually having large social costs) but just wondered if we are seeing this creep out elsewhere (online advert auctions perhaps?)
- gravypod 9y agoHow do you get started with pulling in this data? I've always wondered how you could break into this market at all. The only impossible part is finding tick-by-tick market data
- jorbrad 9y agoIt's very difficult to touch the market independently. The amount of infrastructure that is needed for algorithmic trading is more than any single person could reasonably handle. Not to mention the markets are incredibly efficient already.
- gravypod 9y agoThe overhead of developing a prediction algorithm is fairly low from what I understand. Implementing it into the existing trading market is impossible, I agree, but developing something that can predict stock changes does not sound out of reach. It's likely a fun project and quant trading seems like an interesting job. If you include on your resume your machine learning quant algorithm, your white paper, how you've extend one market's train data to say altcoins/penny stocks, I'm pretty sure you'll peak an interviewers ear. Hell you may even make a few bucks.
- jzwinck 9y agoFinding tick by tick data is easy. Every major lit exchange sells it for a few hundred to a few thousand dollars per year, either directly or indirectly (through a data vendor). Just search for "market data price list" and the name of your preferred exchange.
- stuxnet79 9y agoThe author of this article has also summarized most of the basics in a mini-book called "Max Dama On Automated Trading" which can be found online. Highly recommended.
- godelmachine 9y agoDoes it cover anything about FPGAs in HFT?
- frankc 9y agoThis is a good write-up but it's also missing huge other sections of quant finance like statistical arbitrate and factor investing. I guess you could put this under the 'market taking' section except everything he describes is still in the mode of single stock thinking while these strategies are more about portfolios. You typically estimate some factor model of the market and use a portfolio optimizer to create your trade baskets. In these types of strategies you care about latency but on the order of milliseconds not microseconds. The challenge is in building multi-day predictive alpha models with low correlation to each other, getting good executions though brokers can do a reasonable job these days, and especially combining alphas into one book which requires sophisticated mathematical programming (conic programming etc)
- infinii 9y agoIs there an error in this? "In this case book pressure is simply (99.0010 + 98.755)/(10+5) = 98.9167." in the Market Structure signals section. I can't see how that equation relates to the trade data given just prior.
- arnioxux 9y agoI don't really get it either so here's an attempt to justify it with gambler's ruin: http://mathworld.wolfram.com/GamblersRuin.html http://mathworld.wolfram.com/GamblersRuin.html > Let two players each have a finite number of pennies (say, n_1 for player one and n_2 for player two). Now, flip one of the pennies (from either player), with each player having 50% probability of winning, and transfer a penny from the loser to the winner. Now repeat the process until one player has all the pennies. > The chances P_1 and P_2 that players one and two, respectively, will be rendered penniless are > P_1 = n_2 / (n_1 + n_2) > P_2 = n_1 / (n_1 + n_2) So if the current order book looks like: - Sell 5 for $99.00 (best offer) - Buy 10 for $98.75 (best bid) And you chomp up orders randomly, flipping a completed order to the opposite position: - the probability that the price is above $99.00 (all 5 sell got filled first) is 10 / (5 + 10) - the probability that the price is below $98.75 (all 10 buy got filled first) is 5 / (5 + 10) So expected value is (99.00 * 10 + 98.75 * 5) / (10 + 5) = 98.9167. I am not happy with this explanation. It seems like after you execute an buy for $98.75 you need to immediately put a sell for it at slightly above $98.75 (and vice versa) to fit the random walk model described above. And then I took the expected value using the price at two different points in time. Overall I am still confused myself.
- known 9y agoJust port your trading strategy to kernel space.
- anonu 9y agoHaving been in this space, I agree with most of the article. Good summary. The one thing I would say is that it's very hard to make money doing this. The profits accrue to the select few who have cornered the market in terms of technology and speed. Which is why firms who make money doing this usually have an edge beyond the technology. In one word: flow. They are able to interact with a stream of orders... Not theirs... That is low in alpha and they are able effectively to get "first look".
- mkalygin 9y agoDoes it mean that trying to make some cash doing automated trading in 1-2 people is nearly impossible?
- anonu 9y agoI'd say your probability of success is going to be low. Success is not solely defined by PnL. If you're making money then you will certainly have to deal with increased compliance and oversight from whoever is sponsoring your access to the markets - this comes with a cost. Furthermore you can never just "sit" on a strategy. Eventually your edge gets arbed out and you need to be creative enough to data-mine the heck out of the market to find some new edge. Some thoughts on figuring out your edge: 1. You're not the only smart person looking at something. There are armies of PhDs who have been there and done that. 2. Study regulation and regulatory changes. Keep abreast of new & upcoming changes. 3. Look for markets where barrier to entry is higher or not as studied. eg: Electricity markets are a _bit_ less understood or traded. 4. Always think in pairs or more... Longing or shorting something outright is almost never the answer. But trading the spread between two (3,4,many) related products is more difficult to calculate and backtest. 5. Always do the more difficult thing - but don't make it complicated. Simple math is usually what works.
- mkalygin 9y agoThanks for your explanation, I don't have illusions that it's going to be easy. I rather think the opposite. For now I'm trying to get a basic understanding of trading and finance. This is just a hobby along with my programming job. From your words I understand that I have got to be very creative in order to find an edge. Especially your advice on thinking in pairs or more is valuable.