Algorithmic trading (or simply algo trading) is a method of trading where we use computer programs to follow a defined set of instructions or rules to calculate the price, quantity, timing and other characteristics of the orders. In other words, trading signals (buy/sell decisions) are generated based on a set of instructions.
Algorithmic trading has become increasingly popular over the years due to its ability to:
- Remove emotions from decisions
- Make trades faster
- Execute a greater number of trades simultaneously
Hence, there are lot benefits of algorithmic trading. Algorithmic trading can also be used for high frequency trading, where many trades are made in a short amount of time. Other advantages include improved risk management and increased liquidity.
As the title suggests, in this blog we will discuss why you should do algorithmic trading.
Let us dive deeper into the discussion and explore the reasons why you should be doing algorithmic trading with this blog that covers:
- Algorithmic trading vs manual trading
- Skill set needed for algo trading are achievable
- Rapid growth of algorithmic trading
- Algo trading has a bright future
Algorithmic trading vs manual trading
Whether algo trading (algorithmic trading) is better than manual trading depends on various factors and individual preferences. Undoubtedly, there are several benefits of algorithmic trading. Here are some points to consider why algorithmic trading is better than manual trading:
|
Manual trading |
Algorithmic trading |
|
Manual execution of trades at the current price is done |
Trades are executed by predefined rules and parameters coded in programming language |
|
The trades are executed at the human speed which is not very fast |
Trades are timed correctly in order to avoid significant price change and losses |
|
Manually scanning different markets simultaneously for finding out the financial instruments with the best potential returns is not possible |
Scanning different markets simultaneously is possible and so is trading multiple instruments at the same time |
|
Backtesting the trading strategy manually is not as efficient as doing so with the help of an automated system using algorithms |
Backtesting can be done with ease |
|
Human emotions can lead to erroneous decision making with regard to the trading strategy |
No risk of emotions taking over the decision making power since the system is inputted with predefined rules and strategy based on logic |
Key points to note from the table
- Speed and efficiency: Algo trading allows for faster execution of trades since they are automatically placed based on predefined rules. This can be particularly beneficial in fast-moving markets where timely execution is crucial.
- Elimination of human emotions: Algo trading removes emotional bias from decision-making, as trades are executed based on predefined algorithms. Emotional decisions can often lead to poor trading outcomes.
- Backtesting and optimization: Algo trading systems can be backtested using historical data to assess their performance. This enables traders to refine their strategies and identify potential flaws before deploying them in real-time trading.
- Automation and multitasking: Algorithms can continuously monitor the market and execute trades, freeing up the trader's time for other activities or analysing additional opportunities.
- Reduced manual errors: Algo trading minimises the risk of manual errors, such as entering incorrect trade sizes or executing trades at the wrong prices.
Abovementioned can also be called the benefits of algorithmic trading.
Getting Started with Algorithmic Trading!
This course builds a foundation in Algorithmic Trading
Therefore, we can say that algorithmic trading is better than manual trading and hence, algorithmic trading should be preferred.
Skill set needed for algorithmic trading are achievable
Do you know that the skills required for algorithmic trading are not as difficult as you may have perceived them to be if you have the dedication, grit and perseverance to acquire the same.
So, one of the main reasons to become an algo trader can be that the skills needed to do algorithmic trading are achievable.
These skills are as follows:
- Programming is required to be able to code the strategy
- Strong analytical skills help the trader analyse the historical data and create a strategy based on a thorough analysis
- Risk management is an integral part of trading since it helps to avoid losses
- Technological proficiency is appreciated since an algorithmic trader needs to work with computers, AI, etc.
- Mathematical concepts such as probability and statistics are required for the pricing of derivatives, assessment of risk, or predicting market movements.
Further, if you have the following traits you can acquire the skills mentioned above with ease:
- Emotional discipline implies keeping a check on reacting on the basis of fear, greed, excitement, etc.
- Systematic approach implies that the problem should be approached with an organised mindset.
- Continuous learning mindset is a must because then only you will be able to take up the challenge and pick up on each skill.
- Attention to detail is required since it will help you not miss out on any important aspect while learning.
- Patience & resilience helps keep your cool while you figure out some complicated concepts.
- Critical thinking and problem solving abilities in an individual help to navigate through the important concepts such as mathematics, analytics etc.
Rapid growth of algorithmic trading
Algorithmic trading has been experiencing significant growth in recent years ⁽¹⁾. The increasing adoption of technology and the availability of market data have contributed to the expansion of algorithmic trading strategies.
Some factors that have influenced its growth include:
Market Efficiency
Algorithmic trading is favoured by institutional investors and hedge funds due to its potential to improve execution speed, reduce transaction costs, and exploit market inefficiencies.
Advancements in Technology
The development of faster and more powerful computers, along with improvements in connectivity and data storage, has facilitated the growth of algorithmic trading.
Regulatory Changes
Regulatory changes, such as the implementation of the Markets in Financial Instruments Directive (MiFID) in Europe and the adoption of electronic trading platforms, have encouraged the use of algorithmic trading.
Increased Data Availability
The availability of vast amounts of real-time market data and the development of sophisticated analytical tools have enabled traders to develop and deploy more complex algorithms.
High-Frequency Trading (HFT)
High-frequency trading, a subset of algorithmic trading that involves executing a large number of trades in fractions of a second, has gained popularity. HFT firms use algorithms to exploit short-term market movements and capture small price discrepancies.
Hence, learning algorithmic trading seems to be a good decision for seeing the growth it has achieved so far.
Algo trading has a bright future
The benefits of algorithmic trading are immense and more and more traders are becoming inclined towards it. There is no doubt that algorithmic trading has a bright future.
Therefore, this is yet another reason you must do algorithmic trading. Algorithmic trading is expected to grow ⁽²⁾ in the coming years. The future of algorithmic trading is expected to be shaped by ongoing technological advancements, regulatory developments, and market dynamics.
The global algorithmic trading market is valued at US$ 18.06 billion in 2023. Further, it is expected to exhibit a CAGR of 12.2% and reach US$ 28.59 billion in 2027. Hence, the future of algorithmic trading seems to be bright.
You can see the predicted growth of algorithmic trading below.
However, the future is subjected to various uncertainties and market forces.
One thing is for sure that new technologies, regulations, and market conditions can significantly influence the development of algorithmic trading. Furthermore, algorithmic trading is likely to see increased integration of artificial intelligence (AI) and machine learning (ML) techniques.
The use of alternative data sources, such as social media sentiment, satellite imagery, and web scraping is also expected to grow in algorithmic trading. By incorporating non-traditional data sets, traders can gain unique insights and develop innovative strategies.
In the future, the regulatory body may focus on issues like algorithmic transparency, risk management, and potential market manipulation risks associated with high frequency trading.
As algorithmic trading becomes more prevalent, robust risk management systems will be crucial. It will be important to monitor and control potential risks associated with algorithmic errors, system failures, and cybersecurity threats.
With the growth so far, it is expected that algorithmic trading strategies will continue to evolve as market conditions change. Traders will explore new approaches, such as sentiment analysis, deep learning, and reinforcement learning, to gain a competitive edge. This implies that adopting algorithmic trading practices will help in future.
Next steps
Now that you have gone through all the reasons why algorithmic trading must be preferred over manual trading, you can check this section to go to the next step.
This section discusses how learning algorithmic trading is not difficult if you hold the dedication, perseverance and willingness to learn.
The steps to learn algorithmic trading are:
- Having the knowledge of the core areas such as quantitative analysis, financial markets and programming etc.
- Beginning with the books and courses
- Learning through free sources such as blogs, podcasts, webinars, workshops, videos etc.
As mentioned above, learning algorithmic trading is not at all as difficult as you think. The key points to successful algorithmic trading are:
- Appropriate skills
- The right trading strategy
- The courses which help to build the practice from scratch as well as from the point you require.
But, the point of relevance here is to understand that dedication and perseverance to learn the relevant skills are equally important in order to become an algorithmic trader. Without the above-mentioned traits and commitment, algorithmic trading may seem difficult.
Bibliography
- https://roboticsandautomationnews.com/2022/10/08/why-algorithmic-trading-is-the-future-of-investing/55033/ ⁽³⁾
- https://www.openpr.com/news/3045682/automated-algo-trading-market-opportunity-analysis ⁽⁴⁾
- https://en.wikipedia.org/wiki/Algorithmic_trading ⁽⁵⁾
- https://shop.elsevier.com/books/algorithmic-trading-methods/kissell/978-0-12-815630-8 ⁽⁶⁾
- https://www.quantinsti.com/algo-trading-ebook
Conclusion
This blog was intended to enhance your knowledge and understanding with regard to why it is a good idea to invest in algorithmic trading. The top algorithmic traders experience a multitude of advantages through the practice of algorithmic trading, owing to a variety of reasons. You must go through all the necessary details to understand the core of algorithmic trading before taking a step, to begin with the same.
If you wish to learn more about algorithmic trading, do explore the course Algo Trading Course. This course will cover all your algorithmic trading-related topics in a comprehensive way over 6 months and help you grow in the field of algorithmic trading and quantitative trading.
Note: The original post has been revamped on 29th June 2023 for accuracy, and recentness.
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