If you’re here, it’s probably because you typed something like ‘what is a trading bot?’ into your search engine — or you randomly clicked on 'Start Here' — hoping for a simple, clear, and finally understandable answer. Good news: you’re in the right place!

 

Trading bots sound like a dream: algorithms that work while you sleep, racking up winning trades without even blinking. But let’s be honest, behind the promises lies a fascinating (and sometimes intimidating) world. No worries, though! No complicated jargon or confusing explanations here.

This blog is written by a human —with the occasional tweak from GPT, let’s keep it real!— for other humans. My goal? To explain, in simple terms, what a trading bot actually is and how it works. Whether you’re a beginner or a seasoned pro, you’ll walk away with a solid understanding—and hopefully, a fresh perspective on these famous bots.

 

So, ready to peek under the hood of trading bots? Let’s dive in!

 

So, What is a Trading Bot?

Simply put, a trading bot is a computer program designed to automate actions on financial markets. Instead of frantically clicking "buy" or "sell," you delegate that task to an algorithm that follows your rules. Basically, it’s like hiring a hyper-disciplined assistant who never sleeps, never panics, and always sticks to your instructions to the letter (which, let’s be honest, is pretty rare for humans). For beginners, imagine telling it: "When the price goes above X, buy. When it drops below Y, sell."

 

 

In short, a trading bot is like your co-pilot in the markets: it executes your orders but doesn’t replace you. For it to be effective, you need to give it a clear and realistic mission. And that’s your job!

Okay, but seriously, what IS it?

Indeed, if becoming rich was as simple as placing orders automatically, we would all be living off passive income by now! But a trading bot is much more than just a mechanical executor. It encompasses a multitude of essential functions that allow it to navigate efficiently through complex markets. Here are some key areas where it operates:

• Automatic order management: Stop-loss, take-profit, limit orders, or conditional orders… A well-programmed bot executes these orders automatically based on specific criteria. For example, a trader can configure a bot to exit a position once an asset reaches a certain price level, avoiding the need to stare at the screen all day.

• Volume and risk management: Imagine a diversified portfolio where the bot adjusts the size of each position based on the acceptable risk level. For instance, in forex trading, a bot can limit exposure to a single asset to 2% of the total capital. This is a key method to prevent a single bad decision from severely impacting the portfolio.

• Strategy design and backtesting: One of the strengths of trading bots is their ability to test strategies on historical data. For example, if you have an idea based on moving average crossovers, the bot can simulate it over several years of market data to assess its profitability in different market conditions, such as the 2008 financial crisis or the 2020 bull run.

• Market data management and protection: A bot must be able to collect, organize, and analyze data in real-time. High-frequency trading (HFT) algorithms, used by institutions like Citadel or Renaissance Technologies, exploit massive data streams to make decisions in a fraction of a second—literally.

• Broker communication: Bots interact with trading platforms through APIs (think of this as communication channels). For instance, a bot used on Binance for cryptocurrency trading needs to communicate effectively to place orders based on rapid market movements. An unstable connection or an API issue can result in significant losses.

• Customizable indicators: While indicators like RSI or moving averages are widely used, some traders build custom tools for their bots. A hedge fund might, for example, create an indicator combining technical signals with macroeconomic data to gain a competitive edge.

• Multi-asset adaptation: Whether it's stocks, commodities, cryptos, or bonds, a good bot can manage multiple types of assets simultaneously. For example, some funds use bots to arbitrage between gold futures contracts and the spot price.

• User interface, notifications, and alerts: Many modern bots come with user-friendly interfaces to track real-time performance. Some send notifications through apps like Telegram or WhatsApp to alert you of critical movements. Imagine receiving an alert on your phone notifying you of a sudden drop in the S&P 500, giving you time to adjust your positions manually if needed.

• Real-time adaptation: The most advanced bots, especially those incorporating artificial intelligence, can adjust their behavior based on market conditions. For example, an algorithmic trading bot might reduce its activity during macroeconomic events like the release of employment reports, to avoid excessive volatility.

In short, the concept of a trading bot is vast but can be simplified as follows:

A program that collects real-time data, processes it, applies a strategy, and sends orders to the broker. Its ultimate goal is, of course, to generate profits!

How to Start Creating a Bot?

To create a trading bot, you need to… program! And here, several languages are available to you:

• Python
• C++
• C#
• MATLAB
• PineScript
• Excel VBA
• Swift
• Java
• PHP

All of them can be used, but some are better suited than others. What matters is choosing a language that makes it easy to analyze time series data and integrate with brokers' APIs. So, to make your life easier, I recommend Python, C++/C#, and Java.

As for me, I chose Python. Why? It’s easier to learn, has tons of libraries for calculations, and a pretty simple API integration process. And of course, there’s no shortage of online resources to learn from, especially applied to finance. In fact, you’re currently on one of those resources!

And for the C fans, don't worry! I know you're out there, chuckling to yourselves, thinking that C is faster, so of course, it must be better. But don't panic, I'm sure your expertise with pointers will allow you to adapt everything I'm saying without any issues. 😉

 

Where to Start with the Project?

Building a trading robot isn’t just about writing a few lines of code and hoping it works. It’s a structured project that typically follows several key stages:

1. Concept: Everything starts with an idea. The goal here is to create or adapt a market hypothesis. You need to define what your robot is going to aim for: will it follow trends, detect anomalies, or take advantage of volatility? This phase is crucial because it sets the direction for your project.

2. Backtesting: Once you have your idea, it’s time to test it. But not just anywhere! The goal here is to simulate the strategy on historical data, under conditions as close to reality as possible. The objective: see if your idea holds up against past events. Be careful, though—it's important to test on data you haven't seen before to avoid getting carried away by overly optimistic results.

3. Paper Account: Now, we move to the next stage: testing in real conditions, but without risking any money. The robot starts interacting with the market in real time, using a paper account (demo account). This is the opportunity to check its robustness against technical challenges, such as connection issues, latencies, or other unexpected events. But more importantly, it’s where you begin to assess the performance and relevance of the strategy.

4. Real Account: If everything goes well, it's time to take real action. You open a live account and let the bot run. The goal? To generate consistent profits (and not too many surprises). This is the phase where you’ll truly see if your robot can navigate the murky waters of the market.

5. Decommissioning: And finally, we reach the end of the story. If the robot stops generating profits or becomes irrelevant, it’s time to remove it from the market.

But be careful, if any step doesn't go as planned, it’s often wiser to start with a new idea rather than forcing the situation. For instance, repeatedly redoing the backtesting in the hope that the strategy will eventually work can lead to overfitting. There are two main reasons for this:

1. A model that performs too well at the outset: A model that gives excellent results on past data may seem perfect, but it's often too tailored to those specific data points and not to real-world situations. It will fail on new data.
2. Too many backtests: If you perform too many backtests on different periods or parameters, you risk landing on false positives.

In both cases, the bot may become excellent on known data, but completely ineffective when confronted with new situations. That's why it’s crucial to maintain a realistic view and avoid overfitting the strategy to your past data.

Relevance: The Key to Success

The crucial point of a trading robot is its relevance. Indeed, there are many other ways to invest your money. Personally, if I weren't so obsessed with high-frequency trading, I'd be perfectly happy with a long-term strategy, backed by good old Excel spreadsheets. Less risky, more stable, and you can sleep easy without worrying about losing hundreds, even thousands of euros in a few hours.

I definitely don’t want to discourage anyone from diving into the world of trading robots, but let’s be realistic: it's a massive investment in both skills and time. For a robot to have true relevance, it must be based on a solid understanding of the market, translated into a clear and coherent strategy. But even with such an advantage, you'll have to consider things like broker fees, the lifespan of your edge, and a multitude of other little joys that we’ll discuss in future posts.

If you're not completely sure you have that advantage, I recommend not jumping straight into a live account with your robot. Otherwise, you might find yourself sitting in your banker’s waiting room, crying over your balance. 😅

 

Skills You Need to Succeed

To give yourself the best shot at creating your trading robot, there are a few key areas where you’ll need to excel. Don’t worry, I’m not talking about becoming a math genius, but these skills will help you avoid the classic pitfalls.

• Finance and Econometrics: Understanding the markets and the risks involved is crucial. Econometrics will help you analyze data like a pro and spot interesting patterns… or avoid the ones that are worthless.
• Statistics: You’ll need to master the art of time series analysis and statistical tests. Yes, it sounds a bit dry, but it’s essential to make sure your strategy isn’t just a lucky guess.
• Technical Indicators and Fundamental Analysis: Indicators like moving averages or Bollinger Bands are your best friends. At the same time, a solid grasp of fundamentals will help you understand market movements better.
• Market Knowledge: A trader without market culture is like a fish out of water. If you're trading stocks, you’ll need to understand corporate finance and accounting; if you're into Forex, you should also know the ins and outs of monetary policy.
• Instrument-Specific Knowledge: Each instrument has its quirks, so you really need to know your playing field. Whether you’re trading options, stocks, or futures, each product comes with its own set of rules!
• Programming Skills: Finally, to code your strategy, programming is a must. No need to become a seasoned developer, but being able to understand and master your code will be essential.
  

Conclusion: Ready to Conquer the Market?

So there you have it, you’ve taken a nice journey through the world of trading bots, but if you jumped straight to this conclusion without reading the beginning, just know that you’ve missed some crucial explanations! Don’t worry, it’s not too late to catch up. If you’ve landed here without understanding the basics —I see you!—, head back and read the previous sections—otherwise, you’ll be starting off on the wrong foot and making the same mistakes as everyone else! 😅

To sum up what we’ve covered:

1. Simple Definition of a Trading Bot
   • A trading bot is a program that automates your trading decisions. Think of it as your virtual assistant—but it doesn’t drink coffee or take breaks.
2. The Areas a Trading Bot Can Cover
   • Order management, volume, risk, backtesting, strategy, communication with brokers... Basically, a bot is a multitasking beast!
3. How to Design a Trading Bot
   • To create a bot, you’ll need solid programming skills (Python, C++, Java...) and a good understanding of finance. You’ll need an edge, otherwise your money will melt away like snow in the sun.
4. Key Skills Before You Dive In
   • Finance, econometrics, statistics, technical indicators, and of course, a strong programming foundation. Don’t forget market culture—otherwise, you’ll end up trading like a tourist.

So, if you’re ready to dive into the fascinating world of automated trading, you’re in the right place! The goal here isn’t to bombard you with lists of technical indicators that lead nowhere, nor to sell you a strategy with RSI overfitting that promises 300% returns and eternal riches before collapsing in real-world conditions. No, here we’re building solid, realistic knowledge!

For the passionate and curious, I want to create a true community resource, a learning space where we can grow together, improve, and support each other. So feel free to comment if there’s a related topic that excites you. And for those of you into things like Time-Varying Bidirectional Causal Relationships Between Transaction Fees and Economic Activity... please, be patient, think of my mental health! 😅

 

Don’t hesitate to comment, share, and most importantly, code!
I wish you an excellent day and lots of success in your trading projects!
La Bise et à très vite! ✌️