All About Automated Trading: What It Is and What It Isn’t

48 Comments | Sales & Trading - Groups

13 Flares 13 Flares ×

Automated Trading[This is a guest post from a reader who currently works in an arbitrage development team. He wanted to clear up a few points about what "automated trading" is and isn't.]

Ah, taking a mid-day nap and waking up with extra money in your trading account… who wouldn’t want to make money while sleeping?

That promise of set-it-and-forget-it money draws lots of traders into the field and attracts computer science and engineering students who suddenly “discover their interest in finance.”

Only one problem: “automated trading” is far from automated cash flow, and you always need human intervention.

To find out why and to learn all about algorithmic trading, arbitrage and other forms of automated trading, read on.

Lexicon Confusion?

Part of the problem stems from all the terms used to describe “computer-assisted trading”:

  • “Algos”
  • “Trading machines”
  • “High-frequency trading”
  • “Black-box trading”

People use these interchangeably but are referring to different concepts – so let’s clear that up.

Algorithmic Trading vs. Trade Origination

Here’s the key question you need to ask:

  • Is a human making the trading decisions and simply having a computer help with the execution, or is the machine handling the execution and making the trading decisions?

The first category – where the computer only assists with the execution – is called algorithmic trading.

The second category – where the computer actually makes decisions – can be called trade origination, although that is not a canonical name (there isn’t any that I’m aware of).

Algorithmic Trading

So now we’ve cleared up the first misconception about algorithmic trading.

The second misconception: that algorithmic trading is about making the most money possible.

It’s actually about losing as little money as possible and reducing your costs.

To illustrate this, let’s walk through an example of how an algorithmic trading system might work:

Let’s say that you’re a pension fund manager and you’ve decided to sell 1 million of Company X’s shares that you currently own.

Notice how you – the human – make the initial decision here based on your analysis.

You want to get the best price available on the exchange that Company X’s stock is traded on, and you know that the highest bid price – the highest price at which someone else is willing to buy the stock – is $20.

So ideally, when you sell those 1 million shares you will get $20 million.

But not quite.

The problem is volume – most likely, that bid order for $20 was for far less than 1 million shares; it might have been your next-door neighbor trading 20 shares in his E*Trade account.

If that’s the case, then you’ll end up selling only 20 shares for $20 – and the remaining 999,980 shares will go for whatever the next best price after $20 is.

If the highest anyone else is willing to pay is $10, then you might only get around $10 million from your 1 million shares rather than $20 million – even though the bid price was $20 according to your trading software.

Limited Liquidity

This problem is called “limited liquidity” in trading circles – you receive less than the “paper value” of your position because there aren’t enough bid orders at the price you thought you were getting.

As a human, you could simply monitor the market all day long and be on the lookout for those $20 bid orders.

That’s extremely time-consuming and labor-intensive, but that was exactly what agency execution traders did in the “old days.”

And that’s why algorithmic trading was invented – to manage the trading process over an extended period of time and get as close to the “paper value” as possible.

A trading algorithm for this scenario might divide the order up into many smaller pieces – 1,000-share blocks rather than 1 million all at once – and execute them over the course of a day or longer.

This is one of the key reasons why algorithmic trading has become so popular: there’s a high upfront investment, but a single machine can replace tens of pure agency execution traders – so you start seeing huge cost savings once you’ve been up and running for awhile.

Trade Origination

Algorithmic trading saves traders a lot of time and money, but there’s a small problem: you still have to make your own decisions.

To make the process truly automated (in theory), various systems to originate trades were created.

There’s a huge variety in the strategies these systems use – just think about all the hedge funds and prop trading firms out there and all the different trading strategies they use.

To give a concrete example of how these systems work, though, we’ll focus on just one for now: non-statistical arbitrage.

Non-Statistical Arbitrage

Arbitrage refers to buying and selling multiple securities at the same time in the hope of making a profit.

The simplest type is non-statistical, or deterministic, arbitrage, where you find and exploit price discrepancies between 2 or more securities whose prices should be related. Ideally (ignoring technical issues), this kind of arbitrage is risk-free.

(Statistical arbitrage, by contrast, deals with expected values of securities over the long-term. There’s no guarantee that the future will behave like the past and so this is not risk-free in any form.)

Here’s how you might apply non-statistical arbitrage, and then how a computer could make it more effective:

The S&P 500 index has a futures contract associated with it – that just promises to deliver the stocks at a certain point in the future and is traded on an exchange.

The underlying stocks of the S&P 500 trade on exchange as well, so you can take their prices, figure out how much it would cost to hold the stocks until the future expires, and based on that decide whether the future is a bargain or rip-off at the current price.

So let’s say you think the future is too expensive – it’s $1,000 but the underlying stocks are worth only $990 and it will cost you $5 to hold them until the future’s expiration.

You can then sell the future and buy the underlying stocks – you deliver the stocks when the future expires and then make a profit based on the difference between what you thought the future was worth and the higher price you sold it for.

Does That Actually Work?

This is a very simple example, and it would never work in real-life because everyone else is looking for the same price discrepancies.

And even if you’re Rain Man, it would still take at least a few seconds to spot this type of price discrepancy…

…which is where machines come in. They can spot arbitrage opportunities like this in milliseconds rather than seconds or minutes, and make trading decisions far more quickly than any human.

If you were creating an algorithm like this, you might program in the specific securities or trends to look for in the market and then give exact instructions on what to buy and what to sell when certain conditions are met.

These days algorithms have become far more advanced and go well beyond just looking at prices – some actually try to scan news stories to determine “sentiment” for or against a company and make trading decisions based on that.

Still Confused?

So going back to the terms at the top of this article, what does each one actually mean?

  • “Algos” – Short for “algorithms” – Could be either algorithmic trading or trade origination.
  • “Trading machines” – Generally trade origination.
  • “High-frequency trading” – A type of trade origination system where securities are held for milliseconds (or less) rather than hours or days.
  • “Black-box trading” – Might refer to either algorithmic trading or trade origination.

Many of these terms could refer to either variety of “computer-assisted trading,” so you need to dig in and ask what’s really going on when you see them.

Time to Retire to the Beach?

So you have a trade origination system set up and you’re making a lot of money with no intervention or decision-making on your part… time to retire?

Not so fast.

All types of automated trading systems must be supervised, checked, and updated constantly.

Even if the software itself is correct and has no bugs, market conditions themselves can be a “bug.”

We saw this back in 2008 during the start of the financial crisis when hedge funds started blowing up – supposedly “once-in-a-lifetime” events started happening every day and breaking all the old algorithms.

So no matter how great your algorithm is, it will only be effective until the next crisis, the next “unusual market condition,” or until everyone else starts copying you.

The top banks have spent a small fortune developing trading algorithms, and the tens of millions of dollars (or more) you need for such technology puts it well out-of-reach of anyone small.

And then there’s the small matter that no software is ever bug-free – especially when the algorithm is new, you need a human to monitor it all the time.

So even if your new automated trading program is making bank, you might want to hold off on buying that beach bungalow.

For Further Learning

This was just intended as a brief overview of automated trading – if you want to find out more, get a copy of Algorithmic Trading and DMA: An Introduction to Direct Access Trading Strategies by Barry Johnson.

Good luck with your trading, and let us know if you ever do make it to the beach for early retirement.

About the Author

is the Founder of Mergers & Inquisitions and Breaking Into Wall Street. In his spare time, he enjoys learning obscure Excel functions, editing resumes, obsessing over TV shows, and traveling so much that he's forced to add additional pages to his passport on a regular basis.

Break Into Investment Banking

Free Access to Exclusive Content for Members Only!

Loading the player...

Sign up for The Banker Blueprint today and enjoy:

ebook
  • Free Report: 57-page guide with the action plan you need to break into investment banking - how to tell your story, network, craft a winning resume, and dominate your interviews,
  • Exclusive emailed bonus material,
  • Free Banker Blueprint newsletter with more in-depth advice,
  • Unlimited access to all articles, videos, and advice - and free updates whenever new content is added to the site,

 

We respect your email privacy

Read below or add a comment...

48 Comments to “All About Automated Trading: What It Is and What It Isn’t”

Comments

  1. Noam says

    “These days algorithms have become far more advanced and go well beyond just looking at prices – some actually try to scan news stories to determine “sentiment” for or against a company and make trading decisions based on that.”

    Are you referring to The Stock Sonar by any chance?

  2. ben says

    “The S&P 500 index has a future associated with it”

    should be “futures” or “futures contact” unless you are saying S&P will exist at a later point in time

  3. Nick says

    Hey Brian,

    Thanks for all of the great articles, this one included. It’s great to get this inside track and while I have been able to leverage that into an offer yet I’ve certianly learned alot on here.

    My question today though is I’m currently working on the retail side (wealth mangement) of one of the Canadian “big 5″ banks and I’m really looking to move over into IB. I’ve been here just about three years now as I was fairly late out the gate (my life plans changed around a lot just as I finished school and so I missed recruiting) and I’m quite frankly getting a little desperate to move on. At this point I’m considering emailing all of our MD’s and executive directors in my city just to introduce myself, explain what feel I bring to the table, and inquire as to if they’d be open for maybe chatting on the phone for a few minutes about their story and how I can best position myself. I’m going to be emailing them from my personal email and frankly I’m not sure I can just ask to meet up with them and so how would you reccomend I go about this? Do you think it’s be inappropriate to email them and is it possible to sneak into the current FT recuiting class? I’ve read over your guides and I’m just not exceptionally confident on how to go about this productively while not coming across desperate.

    Thanks very much for your time Brian.

    • says

      You can email / cold-call bankers and ask to chat or present your story and then ask about recruiting at the end. The thing is that it’s very difficult to get in if you have 3 years of full-time work experience, so you probably want to focus on smaller banks and if that doesn’t work, think about business school.

  4. Mike says

    “So no matter how great your algorithm is, it will only be effective until the next crisis, the next “unusual market condition,” or until everyone else starts copying you.”

    Are there people who create algorithms which are designed to create these unusual market conditions and then exploit the other algorithms? Is trading all one big mathematical chess game now?

    Is there any room for an “average joe” trader now, or will he just be absolutely crushed? Should I even bother attempting a career in trading without a quantitative background?

    • says

      You can’t really control enough shares to “create” unusual market conditions – it’s more how when different algorithms interact with each other, sometimes there are unpredictable results.

      You can still do trading without a math background, but it’s only getting more and more math-oriented going forward.

      Also keep in mind that you can still be successful if you trade smaller amounts of money… when you get to the huge amounts that big institutions and banks are trading it’s always competitive, but it’s easier if you’re working with smaller quantities.

    • Author says

      There are 2 issues re the chess game:

      1) Short-term-wise (i.e. everything happening in a matter of seconds/minutes/max hours), some market participants actually can create highly unusual conditions, although this does not happen very often, for one thing due to regulation. However, check out the report linked to by the “unusual market conditions” hyperlink — that report describes just how a few people created very unusual conditions which then resulted in 1000 points or so fall in Dow for a few seconds. Most of such hacks are really technical devices.

      2) The “unusual conditions” comment actually referred to statistical arbitrage methods which very much tend to be long run and perceived as low risk, but they assume 1 massive things: that market will tend to behave is it has in the past. And that does break, with one less recent casualty being LTCM.

    • says

      Yeah, certain prop trading firms and hedge funds specialize in automated trading so you’d have to find one that’s relevant and looking for interns. You could also get in full-time if you have the right background and are moving in from another industry (e.g. engineer / tech). Banks of course also do automated trading but it’s much harder to get in there and recruiting is more structured.

  5. Jonyk says

    Can you do trading if you don’t want to program at all ? Do people in engineering and hard math courses better fit trading jobs ?

    • says

      Yes, there are still a lot of traders who don’t do any programming – but at the same time, you still need to be good at math and making quick decisions. Trading attracts math/engineering grads more than banking because of that. You can still get in from a liberal arts / other background but you need to be good quantitatively.

      • Jonyk says

        So basically if I’m an econ/fin major and want to do trading I should take less investment courses and more math, stats, accounting ?

      • sg says

        You mention here that “Yes, there are still a lot of traders who don’t do any programming”

        I dont understand why a trader would be required to do any programming. Could you please explain.

        Also, is programming done by traders at all kind of firms – Investment Banks, Hedge Funds, Prop Trading etc ?

        Thanks !

        • M&I - Nicole says

          Yes most traders aren’t required to do programming, which is why we said “there are still a lot of traders who don’t do any programming”

  6. Peter says

    Hey Brian,

    I need some help. I’ve been to an informal session at BB and we have been talking to each other with first name.

    I know want to follow up with some of them. Is it okay to address the person with their first name at the beginning? Or is it more applicable to switch to their last name, although we were talking to each other with first names?

    Thank you

  7. S.Jacobs says

    I have a question. I’m a recent grad with a undergard degree in finance and I screwed up by not getting a internship. I tried but didn’t get anything. After college with the economy and my lack of real experience I was having a hard time finding a job in finance, and just recently landed a job at a small independant full service brokerage firm as a research analyst (but my job title isn’t completely certain at this point since its a smaller firm – my boss still hasn’t figured it out). What are my possible exit opportunities and how long should i stick to working at this company. I feel like i’m taking the job just to get experience since i have so little work exp.

    Thanks for your help.

  8. J says

    Hi,

    Is a 3 minute story ok for a phone interview (first round)? I am refering to the “Walk me through your resume” question.

    Thanks.

  9. Scott says

    Do you know good books where I can build basic/working knowledge of investment banking valuation so I can speak intelligently during interviews?

    Thanks

    • says

      Hard to tell from that description what they actually do… it’s probably a decent group but not as good as M&A / LevFin and so in terms of exit opportunities.

  10. DK says

    Hi Brian
    This article was very intriguing.
    Could you explain a bit further on how unusual market conditions broke down those auto trading system? Or some references. Thx

    • says

      I don’t know the specifics aside from what was linked to in the article – but if you have a trading strategy that always assumes a certain outcome will follow a trading pattern and then suddenly the market shifts dramatically, all your formulas will break… it’s like if addition and subtraction suddenly switched places in every formula.

    • Author of the article says

      Sorry for late reply.

      As Brian said, have a look at the link to the flash crash. This was 600 drop on Dow that took place in units of seconds. The reason this breaks down an awful lot of automated trading systems is that most of these “models” essentially take past price data (say a “chart” of S&P for the past year) and fit some theoretical model (say something that predicts price on xth day given price on x-1st, x-2nd and x-rd day) so that it accurately describes the data, and this will typically be reasonably tight fit.

      So when you apply it and tell it recent prices, it will tell you some price that will be wildly different from 600 down-break on the Dow simply because it has never seen anything even distantly similar to this.

      By the way, in single stocks and other more specific financial market instruments, this happens much more frequently. Check out especially OHLC (Open/High/Low/Close) for LSE stocks and after some research you should find more examples.

  11. Jeremy says

    Hi,

    This is a very interesting subject. I am a recent graduate who works in the Actuarial field. One of my exams pertained specifically to derivative/financial models and I completely fell in love with the idea of quantitative trading. Do you have any advice for how someone in my position could break into this type of career?

    Thanks.

    • says

      Start trading on your own in your free time, then cold-call small/local prop trading firms, talk about your background + trading experience and pound the pavement until you get in.

  12. Alexis says

    The second category – where the computer actually makes decisions – can be called trade origination, although that is not a canonical name (there isn’t any that I’m aware of).

    ^^ I think some people refer to that as systems trading (as opposed to discretionary)?

    Also the New Market Wizards would be a good book to refer to for some system traders…

  13. Dre60 says

    Since trading is becoming more automated (electronic trading) would developing technical (computer programming) skills help one to get into Sales & Trading?

  14. Lau says

    Hi,

    Do large banks recruit algo trader? Is an internship at a bulge bracket banks in technology division doing strategy implementation and risk calculation for fixed income trading particularly useful for such position?

    • M&I - Nicole says

      Yes banks recruit algo traders. I am not quite sure how useful this internship will be for such a position; readers may have better insights to this one.

  15. says

    Human intervention after results have been automated and provided, I would think is imperative even for central banks to use. The biggest problem is the control of risk management when dealing with stocks. I

  16. Daniel says

    Sorry to say but your article is incorrect.
    Goal of robotic trading are vast, such as avoiding missing trade opportunities, eliminating human factor error of emotions and technical or simply comfort of doing nothing.

    Also you saying that this industry is out of reach because banks spent millions on this without success is also wrong assumption. You can develop a profitable algorithm for less than 200 bucks if your algorithm idea is correct (don’t argue as I know from personal experience)

    This article has raised my question on whether the rest of articles on this site are viable and can be trusted.

    This comment goes out to people seeking financial freedom, robotic trading is possible for the simple guy, just got to work hard and smart to find something that works.

  17. says

    Automated trading systems appeal to investors who understand how the market works and want to have more control over their trading. There’s risk involved with automated trading just as there is risk involved in manual trading.

Leave a Reply