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Exploring the World of Algorithmic Trading

  • Rumzz Bajwa 
Algorithmic investment and trading concept. Double exposure of s
Algorithmic investment and trading involves developing deep data models.

Algorithmic trading can be fun and rewarding. To the unaware, it refers to trading based on pre-programmed instructions instead of human sentiment. The idea is to leverage computers’ superior speed and analytical abilities relative to humans.

Algorithmic trading has gained a lot of popularity with retail and institutional traders. It’s responsible for between 60-73% of all US equity trades. In Europe, it’s between 19-40%. In Asia, it’s around 20%.

The algorithmic trading market is still increasing, with an expected compound annual growth rate (CAGR) of 11.23% between 2021 to 2026 (Mordor Intelligence). Many people are opting to become algorithmic traders. Who doesn’t want to ride a growth wave?

We acknowledge it’s enticing, but you should know that algorithmic trading isn’t an easy task. There are essential steps to follow and factors to pay attention to to become a successful algo trader. This article will walk you through such steps and critical factors and introduce you to tools and strategies to make money as an algorithmic trader.


1. Find successful and profitable strategies

The first step to becoming a successful trader is having the proper knowledge and trading strategies. You can build your trading strategies from the ground up, but doing so requires sufficient knowledge of computer programming and financial instruments. If not, you can copy techniques built by others and adjust them to your taste if needed.

There are countless strategies you can adopt. Some common types include:

  • Mathematical model-based strategies;
  • Trend-following strategies;
  • Arbitrage opportunities;
  • Volume-weighted average price (VWAP);
  • Index fund rebalancing.

Here’s a simple example of an algorithmic strategy:

  1. Buy 100 shares of a stock when its 100-day moving average goes above the 200-day moving average.
  2. Sell shares of the stock when its 100-day moving average falls below the 200-day moving average.

Above is a simple implementation of the volume-weighted average price (VWAP) strategy. It can get more complicated than that, but this is a good starting point.

If you doubt you can build your strategies, there are online communities where you can find and imitate those made by other professional traders. MQL5.com Market is an example of a unique algorithmic trading marketplace with trading robots, indicators & trading apps. Here you can buy ready-made strategies created by pros and implement them yourself. In case there is no ready-made solution, you can order custom development from community members. 

2. Pick the right trading platform

If your trading strategy is good, but you’re not sure which trading platform to choose, find one that’s suited for automated trading and easy to understand. Many platforms have different features, so be sure to know what you need. For example, some platforms have trading volume limits that may hinder your work. Some have backtesting features, and some don’t.

After weighing your options, pick the right platform and get registered. But don’t rush into trading. You should first test your strategies thoroughly to minimize your risk of losses. More on that below

3. Test your strategies

Whatever trading strategy you build or imitate, it’s necessary to demonstrate it on historical market data to see how it’ll fair. Testing entails simulating hypothetical trades through an in-sample data period. You could spot mistakes and correct them during testing, but imagine you had already executed your strategy in real-time before spotting an error. The risk of losing capital will be significant.

The two main types of testing are back-testing and forward-testing.


Back-testing is the method of modeling how well a trading strategy would fare ex-post. It evaluates the profitability of a trading strategy by discovering how well it would work on historical market data. The underlying idea is that any theory successful in the past will probably replicate that success afterward, and, mutually, any previously failed approach will likely fail again.


Forward-testing simulates actual trading on live market data, but you execute no actual trades. It’s also called paper trading because all the trades are executed on paper only and not real life.

Many brokerages and trading platforms let you simulate trades on historical data or live data. To optimize the duration of such testing and in view of the lack of technical resources, industry professionals are resorting to the use of cloud services. An example of a fast cloud network is the MQL5 Cloud Network. With its capacity of 34 000 cores, testing can take not just a few days, but a few hours.

4. Diversification

A successful algorithmic trader should take steps to diversify their trading strategies. Diversification reduces the risk of losses if an approach goes wrong. You should implement multiple strategies instead of depending on one or two.

Factors to consider

There are specific factors vital to your success as an algorithmic trader. They include:

1. Discipline

You must be disciplined enough to be a successful trader. Trading discipline can come in many forms, such as;

  • Establishing clear rules on when to take profits or cut losses;
  • Pre-determining your level of risk tolerance;
  • Avoid trading on a hunch. Have a concise plan before starting;
  • Keep up-to-date records on all trades.

2. Market study

The markets for securities, commodities or other financial instruments are enormous and involve tens of millions of players globally. You should always study the markets to keep up with the rapid changes and adjust your strategies accordingly. No algorithmic trader can be successful without proper market research.

3. Learn from failures

Don’t beat yourself up over failures you experience in the markets. No trader is perfect, and all will make mistakes at some point. Instead, you should learn from your mistakes and ensure not to repeat them.

Tools required for algorithmic trading


A broker-dealer buys and sells securities on behalf of customers. In this case, we’re referring to the platform where you can buy and sell financial instruments.

You need a suitable place to execute trades based on your algorithms. Picking the right broker is vital to your success as an algo trader.

Analytical Software

Analyzing the markets involves comparing vast amounts of data. Hence, you need software to help you. You need the right visualization tools, trade books, financial data providers, and so on.

In-house/Cloud servers

You need sufficient computing resources to be a successful algo trader. Online hosting is required to store the vast amount of data you’ll be working with. You can either use in-house servers or rent some from cloud providers like AWS, Google Cloud, or MQL5 Cloud Network.

Remember that latency (time-delay) is crucial in algo trading, so ensure you use reliable and super-fast servers.


You need to write and run computer programs within your trading platform. Most algo trading platforms already let you do that, so your main work is building up the required programming skills. You should also give preference to trading software supporting platform-independent programming languages because you don’t know what language you’ll pick up at any point.

When choosing algo trading tools, pick the tools with detailed documentation that you can readily learn about. Avoid any tool that is a complete “black box” and claims to be a secret money-making machine.

Benefits of algorithmic trading

The benefits of algorithmic trading include:

  • You can execute trades at the best possible prices;
  • Back-testing lets you evaluate the viability of your strategy before deploying on the live market;
  • Reduced probability of human errors;
  • It takes less human resources to run;
  • Order placement is instant and accurate;
  • Lower transaction costs.

Final Words

Algorithmic trading is rewarding and profitable if properly implemented. It can help you make better decisions than relying on your human instincts. We’ve mentioned steps to take and factors to consider to implement algo trading properly. We’ve also shown you the kind of tools needed to be a successful algo trader.

Just because you’ve heard of many successful stories in algo trading does not mean that you can easily replicate it. It’s a field that requires you to build up significant expertise and experience to become successful. But, you have to start from somewhere to build up that expertise. Hence, we’ve given you tips on how to do that. We wish you a very successful trading journey.