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a bestiary of algorithmic trading strategies

Posted in finance, systematic tradingby Scott Locklin on August 17, 2009

One of the things which confronted me when I got interested in quantitative finance is the varieties of differentkinds of quant. Now I realize this is pretty simple. Quants come in three basic varieties.

1. Structurers:people who price complex financial instruments.2. Risk managerspeople who manage portfolio risk

3. Quant traderspeople who use statistics to make money by buying and selling

It took me quite a while to figure this out. I dont know why people havent bothered to state this taxonomyof quant jobs. I suspect its because most quants are structurers. Of course, there is often bleed overbetween these varieties -but its a useful taxonomy for looking for work. Ive done a little of all three at thispoint (very little, honestly), and have always liked quant trading problems more than the other two varieties.Its the most ambitious, and the most likely to net you a career outside of a large organization (go me: Armyof one!). Its also the most mysterious, since successful quant traders dont like to talk about what they do.Structurers and risk managers haveto talk about what they do, almost by definition. Quant traders gain little

from talking about their special sauce. The ones who have spilled the beans are guys like Ed Thorp-who onlytalk about old strategies, or guys like Larry Harris, who wrote thebest book there is on trading, though hewrote it without any interesting equations in it. Of course, there are going to be quant jobs which dont fitexactly into these categories; there is a lot of overlap between traders and risk managers, for example: Imonly presenting them as a useful framework to hang some thoughts on.

Since Im not presently employed as a quant trader, I dont mind talking about it a little bit. I hope to outlinebelow a rough but mostly complete taxonomy of how this stuff works. Later on, I might outline some specificsof how these basic ideas are applied in practice.


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To make money as a trader, assuming your motivation is to make a profit, you need to buy low and sell high.Thats really all there is to it. Losing sight of this is the source of much trading ruin. People often lose sight ofthis. They build spectacular technical analysis models based on whatever wavelet/fractical special saucethey can dream up, and forget that they are supposed to be buying low and selling high. To do this, you needsome kind of insight or information that other people in the market lack, or you need a structural edge whichother market participants dont have. The latter brings me to the first kind of trading strategy in my bestiary:

1. Liquidity peddlers.Market makers earn the spread. What does this mean? They will display pricesfor buying and selling an instrument, the difference of which is the spread. In an ideal situation, thismeans theyll buy from people who want to sell, then sell the same thing to someone else who wants tobuy, earning the price difference. Theyre taking a risk on that there will be no seller or buyer on theother leg of the trade, and that the price will move against their resulting position. If youre notcompeting with other people who do this, you can make tidy, low volatility profits. If you have acaptive audience, youre not competing with others who do this, and so this is a pretty good trade.This is what most people think of as liquidity provision or making markets. How this gets done maybe as simple as what I just outlined, or it can get very complex indeed.

This is why liquidity is good

2. Arbitrageursearn a different kind of spread. These guys rely on a structural advantage of some kind.It may take the form of having very fast software. It may be because they are large market participantsin geographically distant market locations. It may be because they happen to own a large boat with oil

in it, and they drive the boat to the place theyre most likely to get a nicer spot price. Sometimes theyarb things which are identical: FOREX futures for example. Sometimes they arb things which aresupposed to be identical, like index futures versus index ETFs. And again, sometimes it getscomplicated.

3. Statistical arbitrageursare a sort of squishy area, similar to arbs, but distinct from them. They findpieces of securities which are theoretically equivalent. For example, they may notice a drift betweenprices of oil companies which should revert to a mean value. This mean reversion should happen if thedrift doesnt have anything to do with actual corporate differences, like one companys wells catchingon fire. What youre doing here is buying and selling the idea of an oil company,or in other words, a

sort of oil company market spread risk. Youre assuming these two companies are statistically thesame, and so theyll revert to some kind of mean when one of the prices move. Similarly, in the mergerbetween two companies, there is a risk spread in the relative values of the stock prices of thecompanies, lest the merger doesnt go through. If your statistics or inside information is good enough,you can buy this spread at a profit. In some sense, statistical arbitrageurs are a hybrid of liquidity


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peddlers and arbitrageurs. They earn their money in both ways.

4. Fundamentals traders:these guys are trying to be the electrical version of Warren Buffet. They buywhat they consider bargain stocks, and hold until they can realize some kind of profit, either fromharvesting dividends, or from the price appreciation of the stock. This gets a lot of press as being verysubjective, but it can be entirely quantitative. Indeed, I suspect Buffet, like most traders, at least uses aquant screen to make his picks. Many, many hedge funds are buying and selling stocks based on

accounting data, market trends, and other such information which may or may not have been bakedinto the price at any given moment. Liquidity providers and statistical arbitrageurs prey on fundamentalstraders (among other people). Since fundamentals traders want to control large blocks to harvest largereturns, they have to pay for their liquidity. This is the style most people think of as buying and sellingstocks -it looks a lot like investing. The ironic thing about it is, this is also the area where most moneyis lost in algorithmic trading. When you hear about quant funds crashing all at once like in 2007,this iswhat theyre talking about. It will be a bunch of funds going after the same opportunities in ops cashflow versus accruals, price/book ratio or sector momentum stocks then something in the marketgoes not according to the model. Since these guys all use the same dumb quarterly rebalanced models,

and the market value of the firms invested in is very large, lots of money gets lost. Arbs, liquiditypeddlers? The amounts of money involved are much smaller. Arbs and liquidity peddlers can be one ortwo or five man operations with only a little money in the bank. Thats why guys like me get upsetwhen media fiends go after high frequency. You know who theyre going after? The smallbusinessman; aka me, thats who. Little guys like me who didnt go to Yalevard and dont have anybazillionaires on the rolodex can still make a living as arbs or liquidity peddlers. Oh, the media makes itsound like theyre going after bloated behemoths like Goldman. I wouldnt be surprised if suchcompanies were actually behind this fake populist uproar. Goldman are certainly a lot more likely toprofit from changing legislation or exchange rules than I am; that is why they seem to be all for newregulation.I guess fundamentals traders can also be small firms, though theyre going to be much moreeasily wiped out than a large firm due to the volatility inherent in such strategies. But it is worth realizingthat virtually alllarge algorithmic firms are fundamentals traders. This is true because fundamentalstrading is the only kind with the large capacity required to cut lots of paychecks on a 2/20 deal withinvestors. I have to admit some bias here: some fundamentals algo trading annoys the hell out of me. A


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lot of what they do isnt much more sophisticated than picking stocks by price/earnings ratios. IMO,there should be Yahoo finance style services for individual investors to pick stocks in the same waythese guys do. I have considered building one and making money selling ads the way Yahoo does.Selling ads on a finance webpage is a much lower volatility business than seeking alpha in yet anotherlow Sharpe fundamentals trading business. Probably ads more value as well.

This is why its good to be a fundamentals trader: lots of company

Less pertinent to profit making algorithmic trading strategies, but worth mentioning anyway:

5. Hedgers:are not necessarily interested in making a profit by executing a trade. Theyre moreinterested in trading as a form of insurance. The insurance generally locks in a profit, or minimizeslosses someplace else in a business, but the hedging trade itself is not meant to be profitable. Much ofthe options, short interest and index futures market consists of people who are buying a form of marketinsurance. I partly mention this category out of historical interest: people sometimes blame the crash of1987on a hedging algorithm in common use in those days. Still, profitable trading strategies oftencontain hedges, and hedging is a large part of trading volume, so it is worth mentioning explicitly.Hedgers can also be a great source of profits. While this may sound very tooth and claw -you can

also look at it as providing hedging services to people who want to be hedged.6. Noise traders:many trading algorithms dont make any sense from the profit making or hedging point

of view. The most obvious category here are idiots with computers who dont know what theyredoing. Less obvious than this are index ETFs; all they want to do is track an index. This is harder thanit sounds; in fact, it isNP hard.Another not-so-obvious category are central banks trying tomanipulate their currency prices. While this is a rather grab-bag category, I have to put these guyssomewhere. While I dont know any central bankers, looking at Forex ticks, what theyre doingappears to be at least partially algorithmic. Noise traders are also a great source of profits. They arealso a very large fraction of trading volume.

My categoriesare somewhat arbitrary, just as my aforementioned categories of quant are somewhatarbitrary. Again, these categories are to hang thoughts on. Im pretty sure you can chop any quantitativetrading system into one or more of these categories as a useful way of thinking about things. For example:lets say Im trading on the spread between an actual basket of stocks comprising an index, and an ETF or


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index future. Id categorize that as statistical arbitrage. Sure, people have a special name for it: indexarbitrage, but its really a kind of stab art, the same way as trading pairs is: youre just trading a lot morepairs. But wait: it could get more complicated. Lets say you want to build an index better than the actual anduse the index to hedge risk: is that still stab art? Or is it more like fundamentals trading? Really, it is a bit ofboth. To build an index beating portfolio (usually a subindex), you need to do some fundamentals modeling. Isthe Tu Jeng Hound of the Hedgesplant or an animal? Maybe he is a little of both.

Which of these are high frequency?All of them. That is not an exaggeration, though I am mostly saying itto make clear that Im not breaking things down by time scale. People like Warren Buffet may have a longinvestment horizon, but they also need to pay as little as possible for liquidity. Shopping the block is a non-trivial problem. Speed is important in all kinds of trades. Latency isnt always that important, however. Forexample, while speed is probably important in your hypothetical index arb problem, Im pretty sure latency isa secondary consideration. Latency of course is important in pure arbitrage and most kinds of liquidityprovision.

What is a predatory algorithm?Generally speaking, this is an algorithm that makes your lifeinconvenient on any of these trades. Seriously: thats what the phrase means. Anyone who tells you otherwiseis selling something.


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1. a bestiary of algorithmic trading strategies Locklin on science Netcrema - creme de lasocial news via digg + delicious + stumpleupon + redditsaid, on August 18, 2009 at 3:45 am

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2. chrissaid, on August 18, 2009 at 4:42 am

can you explain how tracking an index ETF is an NP hard problem?

Reply

Scott Locklinsaid, on August 18, 2009 at 5:14 am

Probably, though not very well off the top of my head. I shouldnt really have mentioned it, sincethere are obvious solutions like, buy by weighted sector rather than looking in the universe ofequity stocks for an equity which will help a basket track an index.

It sounds simple: just buy the whole index, but lets say you are faced with some real worldconstraints. My basket consists of one share each of the components of the CAC-40, which iscapitalization weighted. I have $1000. What stocks do I buy to make my dumb basket trackCAC-40 better? It gets crazier with dividends, taxes and stuff, but the basic idea is, without


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having any more information about the components, you have to try a lot of differentpermutations and combinations to find the best way to track the index. And if youre smart,youll resample it a zillion times to make sure youre right. Worst of all is when you dont reallyknow what the index is made of.

I was confronted with such a problem, and read about its NP-hardness in some paper with aGenetic Algo solution (couldnt find the specific paper easily, sorry). I kind of freaked out, until I

realized that just buying by sector was a pretty good answer, and what the boss wantedanyway.

Reply

hysaid, on August 18, 2009 at 5:50 pm

Yeah, you shouldnt have said anything about NP-hard, made yourself sound lessintelligent than you probably are.

Reply

Scott Locklinsaid, on August 18, 2009 at 9:27 pm

I was an auto mechanic before I went to college: Im used to people thinking Im adumb grease monkey, and dont mind it one bit. Being smart is overrated.

Reply

gappysaid, on August 18, 2009 at 8:07 pm

The answer is simpler than that. The portfolio tracking problem asks to match a givenexpected return and minimize the expected square difference between a known security(including a synthetic one, like an index) and a target portfolio with a max cardinality. Thecovariance matrix and the return vector are assumed to be known. NP-hardness comesfrom the fact that the cardinality (i.e., the max number of different stocks in the targetportfolio) is bounded. There is a corresponding number of 0/1 variables for each stock,and this makes it look like a quadratic knapsack.

Dan Bienstock (of Columbia U) worked on this about ten years ago. A first reference is

here(check under cardinality). The approach is currently implemented by at least acouple large investment banks.

Reply


Thanks! Im glad my memory was not faulty here.

Reply

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8. Robertosaid, on August 18, 2009 at 9:53 pm

What about directional trading using money management/risk control. You know. The guys who makemoney pretty much year-in year-out?

Reply


Well, you could say any of the categories Ive cooked up are directional trading in some senseof the word, and hopefully they all use risk control. Im more interested in breaking it down bywhere their money comes from than what techniques they use to actually do it. If you dontknow where the money comes from, you dont know nuthin!

Reply

Robertosaid, on August 18, 2009 at 11:19 pm

The money comes from clients (or traders themselves) who wish to make directional betsAND size their positions based upon risk (many measures) and their Equity.This adds an important category to your list.

Reply


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It is a technique used in all listed categories. Saying the money comes from theclients who make bets is not what I am talking about. If there is a trend, and youcash out of it, where does your money come from? If your trend lasts amillisecond, it probably comes from some dude paying the spread. If the trend

comes from unrolling a mean-reverting trade, your money comes from marketparticipants who were slow to digest the information which made the first equitydiverge from the second. if your trend comes from some long term mispricing, itcomes from you knowing more about a companys prospects than everyone elsedoes, and the people who were more ignorant of this than you are the ones payingyou.

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12. zeqasaid, on August 27, 2009 at 11:00 pm

nice info hope i can learn it

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13. andisaid, on August 28, 2009 at 1:57 pm

thanks your info

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14. Sri Lestarisaid, on August 31, 2009 at 7:45 am

Finance is a very vital issue for a country. Especially in America who became the mainstream of worldtrade. Financial situation in countries affected by many things, one of the countrys security. Thank youfor this useful news.


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Reply


Aaron Brownis apparently coming up with something like this as well. He generally knows whathes talking about more than I do, so its likely to be better. I have no idea where its going tobe published: hopefully somewhere where lots of people read it.

Reply

15. structuredsettlementsaid, on September 1, 2009 at 1:19 pm

you have some really good posts here. Im going to spend the next few days reading them. i love yourwriting style and Im really happy to visited your blog. keep those posts coming

Reply

Scott Locklinsaid, on September 1, 2009 at 7:53 pm

Thanks!

Reply

16. Forex signals today .comsaid, on September 3, 2009 at 7:11 pm

Very good text !R.E.S.P.E.C.T.

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17. Evasaid, on September 4, 2009 at 4:26 am

One thing dont forget manage your margin. Nobody know the way of price so trader should studyMM-money management.

Reply

Scott Locklinsaid, on September 4, 2009 at 4:41 am

No doubt about that; Ill be discussing MM at some point in the future. MM is arguably moreimportant than forecasting.

Reply

18. Ericsaid, on September 16, 2009 at 5:33 pm

Common sense is the most important thing. Quantitative methods dont serve any purpose withoutinherent common sense. Buy Low and Sell High is part of common sense. There are other elements

like exposure and risk concentration etc.

Reply

19. handysaid, on November 11, 2009 at 2:19 pm


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Nice article. Thanks for share.

Reply

20. Dennissaid, on January 2, 2010 at 10:54 pm

Great article! I will look into it a bit deeper

Forex books

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21. Onixsaid, on January 28, 2010 at 2:06 pm

Magnificent article

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23. Minhsaid, on December 7, 2010 at 12:58 am

Nice article. Like your objective of bringing to light charlatanry pseudo-science. Btw, Im applying to anumber of PhD Finance prog. next year. The ones I think I have hope of getting into are mid-tier ones

such as USC, UCLA, Baruch, UC San Diego Is a PhD at those schools sufficient to turn me into aquant ? Where do PhD kids (Im in my 20s) get jobs out of school ?

Reply

Scott Locklinsaid, on December 7, 2010 at 2:06 am

The last Ph.D. in finance I met in the business worked at Bear Stearns, modeling mortgagebacked securities. His Ph.D. was of 70s vintage though; I have no idea where modern ones getjobs, or if you can be a quant. Most quants I know are more or less like me: former hard

science types.

If you really want to work as a quant, Id advise you or anyone else who is asking to just get ajob and work your way up the totem pole. College is kind of useless.

Reply

24. FugSesgurcesaid, on June 2, 2011 at 11:10 am

What is the best search engine google.com or yahoo.com?

Reply25. Quorasaid, on December 28, 2011 at 3:38 am


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Notif me of follow-up comments via email. Post CommentPost Comment

Where can I find an introduction to HFT algorithms?

Most of the well performing ones are of course, hidden, that shouldnt however discourage you.Forgive me if Im being imprecise, but when most people say HFT, they mean Algorithmic Trading,rather than the general low-latency strategy of placing a l

Reply26. What the heck is Statistical Arbitrage? | mansiparikhsaid, on December 31, 2011 at 7:31 pm

[...] Source [...]

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