As you may know, the Foreign Exchange (Forex) market is used for trading between currency pairs. But you might not be aware that it’s the most liquid market in the world.

A few years ago, driven by my curiosity, I took my first steps into the world of Forex trading algorithms by creating a demo account and playing out simulations (with fake money) on the Meta Trader 4 trading platform.

After a week of ‘trading’, I’d almost doubled my money. Spurred on by my own success, I dug deeper and eventually signed up for a number of forums. Soon, I was spending hours reading about algorithmic trading systems (rule sets that determine whether you should buy or sell), custom indicators, market moods, and more.

My First Client

Around this time, coincidentally, I heard that someone was trying to find a software developer to automate a simple trading system. This was back in my college days when I was learning about concurrent programming in Java (threads, semaphores, and all that junk). I thought that this automated system this couldn’t be much more complicated than my advanced data science course work, so I inquired about the job and came on-board.

The client wanted the system built with MQL4, a functional programming language used by the Meta Trader 4 platform for performing stock-related actions.

MQL5 has since been released. As you might expect, it addresses some of MQL4's issues and comes with more built-in functions, which makes life easier.

The role of the trading platform (Meta Trader 4, in this case) is to provide a connection to a Forex broker. The broker then provides a platform with real-time information about the market and executes your buy/sell orders. For readers unfamiliar with Forex trading, here’s the information that is provided by the data feed:

This diagram demonstrates the data involved in algorithmic Forex trading.

Through Meta Trader 4, you can access all this data with internal functions, accessible in various timeframes: every minute (M1), every five minutes (M5), M15, M30, every hour (H1), H4, D1, W1, MN.

The movement of the Current Price is called a tick. In other words, a tick is a change in the Bid or Ask price for a currency pair. During active markets, there may be numerous ticks per second. During slow markets, there can be minutes without a tick. The tick is the heartbeat of a Forex robot.

When you place an order through such a platform, you buy or sell a certain volume of a certain currency. You also set stop-loss and take-profit limits. The stop-loss limit is the maximum amount of pips (price variations) that you can afford to lose before giving up on a trade. The take-profit limit is the amount of pips that you’ll accumulate in your favor before cashing out.

If you want to learn more about the basics of trading (e.g., pips, order types, spread, slippage, market orders, and more), see here.

The client’s algorithmic trading specifications were simple: they wanted a robot based on two indicators. For background, indicators are very helpful when trying to define a market state and make trading decisions, as they’re based on past data (e.g., highest price value in the last n days). Many come built-in to Meta Trader 4. However, the indicators that my client was interested in came from a custom trading system.

They wanted to trade every time two of these custom indicators intersected, and only at a certain angle.

This trading algorithm example demonstrates my client’s requirements.

Hands On

As I got my hands dirty, I learned that MQL4 programs have the following structure:

  • [Preprocessor Directives]
  • [External Parameters]
  • [Global Variables]
  • [Init Function]
  • [Deinit Function]
  • [Start Function]
  • [Custom Functions]

The start function is the heart of every MQL4 program since it is executed every time the market moves (ergo, this function will execute once per tick). This is the case regardless of the timeframe you’re using. For example, you could be operating on the H1 (one hour) timeframe, yet the start function would execute many thousands of times per timeframe.

To work around this, I forced the function to execute once per period unit:

int start()
{  if(currentTimeStamp == Time[0]) return (0);
   currentTimeStamp  = Time[0];


Getting the values of the indicators:

// Loading the custom indicator
extern string indName = "SonicR Solid Dragon-Trend (White)";
double dragon_min;
double dragon_max;
double dragon;
double trend;
int start()
  // Updating the variables that hold indicator values

string actInfoIndicadores()
    dragon_max=iCustom(NULL, 0, indName, 0, 1);
    dragon_min=iCustom(NULL, 0, indName, 1, 1);
    dragon=iCustom(NULL, 0, indName, 4, 1);
    trend=iCustom(NULL, 0, indName, 5, 1);

The decision logic, including intersection of the indicators and their angles:

int start()
         if (dragon_min > trend && (ordAbierta== "OP_SELL" || primeraOP == true) && anguloCorrecto("BUY") == true && DiffPrecioActual("BUY")== true ) {
            primeraOP =  false;
            abrirOrden("OP_BUY", false);
         if (dragon_max < trend && (ordAbierta== "OP_BUY" || primeraOP == true) && anguloCorrecto("SELL") == true && DiffPrecioActual("SELL")== true ) {
            primeraOP = false;
            abrirOrden("OP_SELL", false);
           datetime ctm=OrderCloseTime();
           if (ctm>0) { 
          Print("OrderSelect failed error code is",GetLastError());

       if (ordAbierta == "OP_BUY"  && dragon_min <= trend  ) cerrarOrden(false);
       else if (ordAbierta == "OP_SELL" && dragon_max >= trend ) cerrarOrden(false);

Sending the orders:

void abrirOrden(string tipoOrden, bool log)
   double volumen = AccountBalance() * point; 
   double pip     = point * pipAPer;   
   double ticket  = 0;
   while( ticket <= 0)
   {  if (tipoOrden == "OP_BUY")   ticket=OrderSend(simbolo, OP_BUY,  volumen, Ask, 3, 0/*Bid - (point * 100)*/, Ask + (point * 50), "Orden Buy" , 16384, 0, Green);
      if (tipoOrden == "OP_SELL")  ticket=OrderSend(simbolo, OP_SELL, volumen, Bid, 3, 0/*Ask + (point * 100)*/, Bid - (point * 50), "Orden Sell", 16385, 0, Red);
      if (ticket<=0)               Print("Error abriendo orden de ", tipoOrden , " : ", ErrorDescription( GetLastError() ) ); 
   }  ordAbierta = tipoOrden;
   if (log==true) mostrarOrden();

If you’re interested, you can find the complete, runnable code on GitHub.


Once I built my algorithmic trading system, I wanted to know: 1) if it was behaving appropriately, and 2) if it was any good.

Back-testing is the process of testing a particular (automated or not) system under the events of the past. In other words, you test your system using the past as a proxy for the present.

MT4 comes with an acceptable tool for back-testing a Forex trading system (nowadays, there are more professional tools that offer greater functionality). To start, you setup your timeframes and run your program under a simulation; the tool will simulate each tick knowing that for each unit it should open at certain price, close at a certain price and, reach specified highs and lows.

After comparing the actions of the program against historic prices, you’ll have a good sense for whether or not it’s executing correctly.

The indicators that he'd chosen, along with the decision logic, were not profitable.

From back-testing, I’d checked out the robot’s return ratio for some random time intervals; needless to say, I knew that my client wasn’t going to get rich with it—the indicators that he’d chosen, along with the decision logic, were not profitable. As a sample, here are the results of running the program over the M15 window for 164 operations:

These are the results of running the trading algorithm software program I’d developed.

Note that our balance (the blue line) finishes below its starting point.

One caveat: saying that a system is "profitable" or "unprofitable" isn't always genuine. Often, systems are (un)profitable for periods of time based on the market's "mood":

A few trends in our algorithmic trading example.

Parameter Optimization, and its Lies

Although back-testing had made me wary of this robot’s usefulness, I was intrigued when I started playing around with its external parameters and noticed big differences in the overall Return Ratio. This particular science is known as Parameter Optimization.

I did some rough testing to try and infer the significance of the external parameters on the Return Ratio and came up with something like this:

One aspect of a Forex algorithm is Return Ratio.

Or, cleaned up:

The algorithmic trading Return Ratio could look like this when cleaned up.

You may think (as I did) that you should use the Parameter A. But the decision isn’t as straightforward as it may appear. Specifically, note the unpredictability of Parameter A: for small error values, its return changes dramatically. In other words, Parameter A is very likely to over-predict future results since any uncertainty, any shift at all will result in worse performance.

But indeed, the future is uncertain! And so the return of Parameter A is also uncertain. The best choice, in fact, is to rely on unpredictability. Often, a parameter with a lower maximum return but superior predictability (less fluctuation) will be preferable to a parameter with high return but poor predictability.

The only thing you can be sure is that you don’t know the future of the market, and thinking you know how the market is going to perform based on past data is a mistake. In turn, you must acknowledge this unpredictability.

Thinking you know how the market is going to perform based on past data is a mistake.

This does not necessarily mean we should use Parameter B, because even the lower returns of Parameter A performs better than Parameter B; this is just to show you that Optimizing Parameters can result in tests that overstate likely future results, and such thinking is not obvious.

Overall Forex Algorithmic Trading Considerations

Since that first algorithmic Forex trading experience, I’ve built several automated trading systems for clients, and I can tell you that there’s always room to explore. For example, I recently built a system based on finding so-called “Big Fish” movements; that is, huge pips variations in tiny, tiny units of time. This is a subject that fascinates me.

Building your own simulation system is an excellent option to learn more about the Forex market, and the possibilities are endless. For example, you could try to decipher the probability distribution of the price variations as a function of volatility in one market (EUR/USD for example), and maybe make a Montecarlo simulation model using the distribution per volatility state, using whatever degree of accuracy you want. I’ll leave this as an exercise for the eager reader.

The Forex world can be overwhelming at times, but I hope that this write-up has given you some points on how to get going.

Further Reading

Nowadays, there is a vast pool of tools to build, test, and improve Trading System Automations: Trading Blox for testing, NinjaTrader for trading, OCaml for programming, to name a few.

I’ve read extensively about the mysterious world that is the Forex market. Here are a few write-ups that I recommend for programmers and enthusiastic readers:

About the author

Rogelio Nicolas Mengual, Argentina
member since November 19, 2012
Rogelio is a versatile, positive, and self-motivated full-stack engineer with more than 10 years of work experience in many programming languages, frameworks, and platforms. He enjoys taking on new challenges, and constantly strives to learn new skills. [click to continue...]
Hiring? Meet the Top 10 Freelance Data Scientists for Hire in February 2017


I have always wanted to learn about this. Thanks! I studied a bit of market theory in college and learned about channel trading. I always thought that would be a good fit for algo trading since the strategy is recursive. Do you have any pointers on how to implement channel type of strategies (as opposed to Moving Average strategies)? I'm sure you know this, but some (old) research shows that Exponential MA strategies make more and even out perform buy and hold strategies without taking into account tax advantages.
Hi Rismay, thanks for commenting, about this: "Do you have any pointers on how to implement channel type of strategies (as opposed to Moving Average strategies)?" There are many channel indicators out there (ie: Donchian, IREGR, and many more); also you can code your own channel indicator, once you have that you can make the ExpertAdvisor to make decisions based on whatever indicator/s you are using. The values of the indicators are referenced as a reverse zero point array [oo..0] (ie: the most recent data would be in the position 0 of the indicator buffer). Andrew R. Young's book is a good starting point to understand how indicators work.
Awesome article thanks. Curious if you've engaged in the community? Seems like a great way to get your feet wet
Jubin Roy
Thanks for this awesome article
Simanas Venckauskas
Congrats Great post Rogelio! Just wanted to share my experience as well :) Almost every trading book states, that most traders fails because of psychological factor, when they make exceptions from their own strategies, so as an engineer my only tought was that this is a perfect place for a software solution to avoid human inntervention to the trading system once you decide to start using it. I have spend one entire year of my career just by programming, testing and optimizing with past data every single strategy I was able to find online and on variuos different trading books. And you know what - none of them had constant profitability. And after reading a lot of blog posts etc... I came to the conclusion: We are living in a world where everyone can write his own trading robot and big trading corporations, banks etc... they are constantly analyzing all the markets by using not just strategies developed by some trading gurus but also machine learning algorithms deployed on super computers, who tries to find at least some patterns on every market. And here is the result: Once some pattern comes true at least for some period of time it emediatly turns in to no pattern, because everybody on this game are looking for these patterns. Once you see some pattern you place an order to buy or sell, your order pushes the market to the opposite direction you want it to go at least for a bit. But do not be naieve, if you see the pattern most probably a lot of other traders with hudge investmens sees this pattern as well so this time they are doing the same and you all lose your money all together. Think of it before you decide to become a trader with software engineering background.
Hi Simanas, Thanks for the thoughtful comment. In a previous sketch of this article I described who the really smart players in this game are, and I mentioned the guys from Jane Street among others that play the role of middle-man and arbitrageurs in the market. We (The Editor, Charlie Marsh and Me) decided not to include that among another reflections that considered just that you are mentioning in this comment. All that being said, I like to believe that you can find an edge of the market if you use the correct tools and make the correct simulations using the proper variables. Thanks!
Thanks for commenting! I haven't engaged in that community; it looks awesome to start programming and reuse the code offered there!
Good article Rogelio, In further reading, why would you suggest Ocami for programming instead of MQL4 or MQL5 or "R" or whatever?
Stephan Unrau
I enjoyed this article as it is exactly the kinds of important big milestones I ran into. The project which started for a custom formula for several separate clients became a commercial product driven by user submissions. Now users can copy or sell their trades and copy trades from indicators in Meta Trader. It's called the Binary Options Auto Trader (BOAT for short) and only does Binary Options (2 results win or lose only).
Juan Manuel Ramallo
Can you try it whit horses..... Forex robot are like set up a ROBOT in front of roulette. ..
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the pattern is in the mind of the trader a trader should identify the pattern rather than rely on the machine to identify the trend because the machine will fail as it will be late in identifying the trend (patterns) after all the machines were built by human brain. so the patter is in the brain . watching the screen how the rates behave. there are various patterns in different market bull markets ,bear mkts, range bound mkts.
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Great article; pitched at a great level and I LOVE your diagrams! (any clue on how you produced them?) Simple question you might be able to answer: Do you know anyone that provides a streaming API for share prices of shares listed on LSE and US markets? Any advice appreciated thanks.
I have never seen an automated system that works. The best forex trading system would be semi automated with some manual controls.
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Interesting article - so Nico, have any of the trading systems you built for clients proved to be consistently profitable? I've toyed with developing one for a while but question whether or not FX price movement is predictable enough to make a consistent profit. Always makes me wonder why 'experts' write trading books - presumably if their systems & approaches actually worked they wouldn't have bothered to write the books!
Totally agree with your belief in the beauty of brain. And would like to suggest here that the use of machine is just to avoid the human limitations. The human body combination (brain, body, hands) cant possibly be as fast as the machine to trade in the market with a latency of under 100 milliseconds. The decision making of the wonderful brain is not independent of time. That's why we put most of the efforts of brain in developing and back testing strategies that normally we would use our brain for. No doubt there will be situations where manual approach might prove to be better than a machine decision. But its as likely as emotions making an impact on the decision making. With machines, the problem of emotions, and feelings do not hinder in making a rational decision. If your brain can think it, you can make a machine do it. No offence.
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how do you state the code to define the right angle of the curve?
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awesome write up, even if its a couple years old..
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Thanks for the interesting article..!! Understanding market behavior and strategy is the essential skill that every trader needs to possess to trade smartly. Backtesting is a great approach, which empowers traders to test out their strategies without risking a penny. Besides, backtesting a lot of things are present here which could help you in evaluating whether your strategy is correct or not.
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Really great post and I know you have lots of experience in this field...
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Why so much people so interested in those "algorithms" on MAs making them so undeservedly popular? There are numerous studies showing trading on moving average rules are trading on noise, meaning there is no real information (signal) in those. You can optimize it as much as you can, but when market regime changes, your "algorithm" fails. We see too much of them in FX world.
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Great read, I recently automated my strategies and I'm slapping myself for not doing it earlier. I found a prop trading firm in Melbourne Australia that shows you how to build algo's from ground up without the need to code, they have their own proprietary software and provided me with all the tools to automate and best of all they give me unlimited support with my builds. (Trade View Investments) is the place, I'm dealing with Dieter however all the traders there are very helpful. It's also helped me save money as I can backtest and forward test my strategies to see if there profitable before trading it live.
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Very confused about this post, bought a forex algorithm for relatively it turned out it was not profitable. However, my approach was tweak it and test it and see. Tried different currencies and numerous back testing adjustments and without any software programming background I got it to produce consistent results in one weird currency for the last two years. Now live off it and quit my job and working as a mentor! I think rule is humans will always win because of tenacity and determination.
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About the author
Rogelio Nicolas Mengual
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Rogelio is a versatile, positive, and self-motivated full-stack engineer with more than 10 years of work experience in many programming languages, frameworks, and platforms. He enjoys taking on new challenges, and constantly strives to learn new skills.