Finance

High-Frequency and Algorithmic Trading Overview

No way can humans compute giant data volumes like a machine can. This concept served as an inspiration for the development of automated trading tools. 

Today, innovative technologies made the whole market trading process cheaper and less sophisticated, so even people who are far from being financial experts can become successful and prosperous at trading. 

So, here’s our look into the world of high-frequency and algorithmic trading: what each method brings to the table, their benefits, the most popular strategies, and the cost of automated tools that you can use when trading with the Exness broker via, for example, Exness MT4 or other trading platforms.  

Computers’ place in modern trading markets 

The US stock trade placed by computers currently sits at about 75% and is constantly increasing. The phenomenon of automated trading solutions made the market more liquid as traders can now make quick investments and fully execute their trades. 

Regardless of the trading type an investor chooses, the use of algorithms can’t be taken away. It is an established factor in today’s market reality. And since these services have a defined purpose, they need to be constantly updated and perfected. 

The application of trading tools has replaced the stress soaring over the old-fashioned trading pits at stock exchanges and the use of paper documents, as well as granted unlimited possibilities for the success of any trader, hence full automation should grow further on. 

High-frequency and Algorithmic trading: The Comparison  

High-Frequency trading 

High-Frequency trading solutions process small scale trade orders as they send those orders to a market or exchange at great speed, thereby benefiting from bid-ask spreads. The height of the transaction speed makes this trading method a market maker. 

In a nutshell, this approach’s major characteristics are high speed and order-to-order ratios, co-location, and a massive turnover rate. It is managed by using complex technological tools and algorithms in order to trade securities. 

Algorithmic trading 

Algorithm trading is a trading solution that involves pre-programmed coded sets of variables, such as time, volume, and price and execution algorithms known as trading instructions to submit smaller orders to a market or exchange, making up for large orders, automatically after a technical analysis. 

The main objective of this trading type is to save costs and minimize the execution risk of an order, apart from just profiting off of trades. The best thing is that a trader doesn’t need to watch stocks or send orders manually. 

Benefits of High-Frequency trading 

  • More possibilities  

Since algorithms scan multiple stock markets and exchanges automatically, traders are free to discover additional opportunities. For instance, arbitraging the same asset with lower price differences on several exchanges. 

  • Big wins on small price changes 

With this method, traders can earn large profits even from minor price fluctuations as financial institutions can obtain considerable bid-ask spread returns. 

  • High market liquidity 

Due to increased market competition, greater speed of execution, and larger volumes, high-frequency trading is proven to make markets more price-efficient. Thus, market risk declines since someone always buys what another one is selling and vice versa. 

Benefits of Algorithmic trading  

  • Better prices  

Trades are executed at the highest possible price by being timed to instantly avoid significant price fluctuations. 

  • Increased speed 

Since execution algorithms are pre-programmed to run automatically, the speed at which trades are carried out is noticeably boosted. 

  • Improved accuracy 

With trades performed by a computer instead of a human, the likelihood of a mistake made in the process is lower. Hence, when the algorithm is processed by a machine, no human factor is involved, which leads to increased precision.  

  • Low transaction costs 

Thanks to execution of an order being carried out without a trader’s involvement, their time is freed up. With that, transaction costs are minimized and traders may engage in other activities. 

Common strategies for High-Frequency trading 

  • Market-making  
  • Price movement ignition 
  • Liquidity provision 
  • Statistical arbitrage 

Common strategies for Algorithmic trading 

  • Trend-following 
  • Percentage of volume 
  • Implementation shortfall 
  • Arbitrage leveraging 
  • Volume-weighted average pricing 
  • Mean reversion 
  • Index fund rebalancing 
  • Mathematical model-based 
  • Time-weighted average pricing 

Overall Difference  

As we see, the core difference between these two trading approaches is that high-frequency trading is designed for buying and selling at a fast rate, while algorithmic trading is best for long-term trades. And since both of these methods absolutely beat human capacity, they became very common with traders and make for a far superior option for trading activities.  

Algorithmic trading Software and its Cost  

You now know the nuances of high-frequency and algorithmic trading methods, so it is where you might be getting curious about adopting either one of these techniques for your trading business. In order to do that you can choose between two ways of getting your hands on one of these solutions. You can either purchase a ready-to-use product or build your own. 

The good thing about ready-made trading software tools is that they provide quick access to begin applying them almost immediately. However, just before starting your hunt for one of those out-of-the-box systems, remember that such solutions can be quite hard to customize. 

Should you decide to go the custom trading software development route, you are expected to wonder about its associated costs. But keep in mind that bespoke solutions are developed specifically for you to cater to your unique financial goals. Of course, it takes time, effort, and a good deal of technical expertise to build such a tool. And if you seem to lack any of these components to develop the algorithmic software by yourself – consider looking for experienced providers.  

Bear with us here, custom development might appear pretty costly at first. Especially, when you see the price range skyrocket from $5,000 all the way to $1,000,000! Bespoke trading programs come with such a wide budget range mainly because a lot of factors affect the final software development cost. All of them should be considered when calculating how much you might need to invest. So, if you want to find out a more accurate price, you can try reaching out to particular vendors and ask them for a quote. In this way, you can plan your spending better. 


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Amaury Reynolds

A freelance writer covering many topics.

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Amaury Reynolds

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