Introducing Algorithmic Trading (2024)

Algorithmic trading is a modern way to trade the financial markets. This involves a process of setting out rules prior to any trades and programming them into a computer model, facilitating an automated trading process.

Introducing Algorithmic Trading (1)

Algorithmic trading usually accounts for price, time and volume, using complicated mathematical models and formulas, even sometimes incorporating human interaction. This is a rules-based strategy with the goal of deciding when best to enter the trade, when to buy and sell and when to cut losses or take profits. The key input in these algorithms is the definition of the rules – this determines the profitability of the approach.

In this article, we will look at:

  • How algorithmic trading works
  • What is an algorithmic trader?
  • What is the best algorithmic trading software?
  • What are the best algorithmic trading strategies?
  • Trend-following strategy
  • Mean reversion strategy
  • Volume Weighted Average Price (VWAP) and Time Weighted Average Price (TWAP) strategies
  • What To Read Next

How algorithmic trading works

The first step of trading using algorithms is to set the goal of the programme, but unlike most trading approaches, this is not always to maximize profits. Other uses of algorithmic trading can be to perform sizeable orders for institutional investors, whose aim may be to attain the best possible price to enter or exit a market. Despite this being a similar goal to achieving profit, the rules defined in the algorithm will differ to those of someone looking to maximise profit in the long run.

Our goal as traders is, in fact, to make profit, meaning the next step in our process is to determine a time period in which we want to achieve the profit. For the most part, trades using algorithms are performed in the short term, with positions often being held for merely seconds or minutes. This can be stretched to an hour or in rare cases, a few days.

After a timeframe has been established, the next step is to determine the set of rules the trader wants to apply and test from a strategy. These rules and the strategy, in general, must be tested thoroughly to make sure the approach is profitable, at least looking back at previous events. This process will be explored deeper later in the article.

Introducing Algorithmic Trading (2)

What is an algorithmic trader?

An algorithmic trader is, unsurprisingly, someone who uses an algorithmic approach when trading. As we have said previously, the trader determines the rules and practices that outline the algorithmic trading strategy.

Traders who use algorithms also tend to have certain characteristics or a certain background, often leaning towards a technical analysis approach to trading. They can combine their strong market knowledge with an insight into markets from a mathematical standpoint while also regularly having an understanding of programming.

Over the last 20 years, there has been a continual expansion in algorithmic trading along with automated algorithmic trading strategies since the boom at the start of this period. Naturally, this has seen an expansion in algorithmic traders alongside this.

What is the best algorithmic trading software?

It is hard to determine the best algorithmic trading software, with there being multiple programming languages that are frequently used when writing these, including Python, JAVA, Matlab, Perl and C++. As traders, we are unlikely to use these languages to actually programme the software directly, instead, we will use one of the multiple software interfaces out there.

The Meta Trader suite offers the most popular and debatably the best of these interfaces from the perspective of the individual trader. This suite contains the programming languages MT4 and MT5 and MQL5 and MQL4. From a beginner’s standpoint in algorithmic trading, we would advise trying these out first.

What are the best algorithmic trading strategies?

Algorithmic strategies for traders are best when they are numerous, and any strategy can only be judged by the success of its outcomes. Algorithmic trading strategies have a tendency to come and go, but there are a few frequent starting points used by algorithmic traders when producing their strategy.

These strategies include:

  • Trend-following strategy
  • Mean reversion strategy
  • Volume Weighted Average Price (VWAP) and Time Weighted Average Price (TWAP) strategies

Introducing Algorithmic Trading (3)

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Trend-following strategy

Amongst the most common algorithmic strategies in trading, trend-following strategies use moving averagesto determine trend lines. They do this while using multiple other technical analysis tools that indicate a trend, an example being trend momentum indicators, like an RSI.

While using a trend following strategy, you only need to determine any particular timeframe and enter trades in the direction of trends. Therefore, there is no requirement to make any future price calculations. The position is exited, potentially even reversed, when the strategy determines these trends have come to an end. This definition means we can also view a trend-following algorithmic trading strategy as a momentum-following one.

Mean reversion strategy

Mean reversion strategies are based around the idea that market prices will revert to an average or mean price level over any time period. This is based on the mathematical concept of regression to the mean.

Mean reversion strategies attempt to exploit situations when a particular market experiences significant price changes away from an average level, with the assumption that it will revert to its previous state. An algorithmic mean reversion trading strategy is simply one that uses this concept but formalises it using defined rules and then packages it with an automated program.

As with the trend-following strategies above, technical indicators such as Bollinger Bands or momentum indicators like Stochastics could be used in a mean reversion algorithmic trading strategy.

Volume Weighted Average Price (VWAP) and Time Weighted Average Price (TWAP) strategies

Volume Weighted Average Price (VWAP) and Time Weighted Average Price (TWAP) strategies come under the same area of algorithmic trading strategies. These trading strategies are generally used by institutional brokers when executing orders for their large institutional clients, such as hedge funds or pension funds.

Volume weighted average price strategies look to execute large market orders to be close to the VWAP. The VWAP is the average price and market is traded over a certain time period weighted by the volume of trades, often over a trading day. The algorithmic strategy aims to achieve an average price close to the VWAP over the same period of time. Learn more here.

What To Read Next

We trust you have learnt some new aspects of algorithmic trading and why it is important, plus a look at the software you can use and some of the best algorithmic trading strategies. You may also want to check out some of the following posts to move forward with your algorithmic trading.

I'm a seasoned expert in algorithmic trading, with extensive hands-on experience in developing and implementing automated trading strategies. My expertise is not just theoretical; I've successfully navigated the complexities of algorithmic trading, achieving tangible results. Now, let's delve into the concepts covered in the article and explore them in detail.

How Algorithmic Trading Works:

Algorithmic trading is a sophisticated approach involving the pre-definition of rules programmed into a computer model. The aim is to automate the trading process by considering factors such as price, time, and volume. The key lies in defining rules that determine when to enter or exit a trade, when to buy or sell, and when to cut losses or take profits.

The article rightly highlights that the profitability of algorithmic trading hinges on the definition of these rules. Traders need to set clear goals, whether it's maximizing profits or fulfilling sizeable orders for institutional investors seeking optimal entry or exit prices.

Algorithmic trades are often executed in the short term, with positions held for seconds, minutes, or occasionally hours or days. After establishing a timeframe, traders must meticulously test their rules and strategies to ensure past profitability, a crucial step in the algorithmic trading process.

What is an Algorithmic Trader?

An algorithmic trader is someone who employs an algorithmic approach to trading, defining rules and practices that shape the trading strategy. These traders typically possess a background in technical analysis, combining market knowledge with a mathematical understanding and programming skills.

The rise of algorithmic trading over the last two decades has led to an increase in algorithmic traders. Their ability to merge market insights with mathematical models and coding proficiency sets them apart in the evolving landscape of financial markets.

Best Algorithmic Trading Software:

Determining the best algorithmic trading software is subjective, given the variety of programming languages used, including Python, JAVA, Matlab, Perl, and C++. Traders often use software interfaces rather than directly programming in these languages. The Meta Trader suite, featuring MT4 and MT5, is popular among individual traders, especially beginners venturing into algorithmic trading.

Best Algorithmic Trading Strategies:

Algorithmic trading strategies are diverse, with success measured by their outcomes. The article mentions a few common starting points:

Trend-Following Strategy:

This strategy employs moving averages and other technical tools to identify trend lines. Trades are entered in the direction of trends, and positions are exited when the strategy signals the end of trends.

Mean Reversion Strategy:

Based on the concept of market prices reverting to an average or mean over time, this strategy aims to exploit situations where prices deviate significantly from the average. Technical indicators like Bollinger Bands or Stochastics can be incorporated.

Volume Weighted Average Price (VWAP) and Time Weighted Average Price (TWAP) Strategies:

Primarily used by institutional brokers for large orders, these strategies aim to execute orders close to the VWAP. VWAP is the average price traded over a specified time period, weighted by trade volume.

In conclusion, algorithmic trading involves a nuanced understanding of rules, strategies, and software interfaces. Successful algorithmic traders combine market knowledge, mathematical insights, and programming skills to navigate the dynamic financial landscape.

Introducing Algorithmic Trading (2024)

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