10 Doubts About Algorithmic Trading You Should Clarify

6 min read

By Chainika Thakar

Algorithmic trading is a contemporary and systematic concept with some doubts and misbeliefs still surrounding people right from its meaning to adopting it. The doubts must be clarified before you begin learning about or trading in this domain.

Let us find the answers to those 10 common doubts about algorithmic trading, which are:

  1. What is an algorithm and how do the algorithms work?
  2. Is algorithmic trading safe?
  3. Can algorithmic trading beat the market?
  4. Are algorithmic traders about to replace manual traders?
  5. Is algorithmic trading too tough?
  6. Is algorithmic trading too easy?
  7. Is algorithmic trading the same as automated trading?
  8. If algorithmic trading fails, does it mean it should never be trusted?
  9. Will algorithmic trading eliminate all the emotions?
  10. Can I learn algorithmic trading in very little time?

What is an algorithm and how do the algorithms work?

An algorithm is a sequence of unambiguous instructions to obtain a required output for any legitimate input within a finite amount of time.

Algorithms have a defined beginning where the input data is processed using a definite logic and executed systematically using a sequence of steps that will always give the same result. One can combine several short algorithms and perform tasks of varying complexities while solving problem statements.

Financial companies use algorithms in areas such as loan pricing, asset liability management, stock trading, portfolio management etc. For example, algorithmic trading deploys algorithms to make trading decisions like timing, price, and quantity in the orders.


Is algorithmic trading safe?

Algorithmic trading is a much safer approach as compared to manual trading since it is free of emotions and is filled with logic. Usually, while placing manual trades, the emotions such as fear, greed, etc. may lead to wrong decisions and hamper your true potential to identify the opportunities in the financial markets.

All you need for algorithmic trading is a complete understanding of the system, financial markets, the trading strategies as well as the coding skills. Algorithmic trading may seem unsafe because of some glitches in the past such as the 2010 flash crash in which the computerised trading systems reacted to the anomaly in the financial markets, but, with the changing time advancements are getting picked up and it is becoming better. With lesser glitches to deal with and better efficiency, algorithmic trading is the future.


Can algorithmic trading beat the market?

Algorithmic trading is a systematic concept that helps you code your trading strategy for automated execution of the trades whenever the coded conditions in the strategy are met. More than beating the market, it is highly important to capture the moves in the market that are efficient. Delivering higher risk-adjusted returns from the financial markets is the main aim of any trader.

Let's say the market will deliver a 10% annualized return in the next 10 years. But with two -50% drawdowns and 20% average yearly volatility. Market's Sharpe ratio is 0.5 (10%/20%) in this case, and its Calmar ratio is 0.2 (10%/50%).

Algorithmic traders code their strategy in a way that their overall portfolio has a high return to risk ratios, and then they allocate capital based on their risk tolerance. Riskier algorithmic trading strategies will surely outperform the market on an absolute basis but will also carry a higher risk.


Are algorithmic traders about to replace manual traders?

Although algorithmic trading requires very little human assistance, the answer to this question is a simple NO! This is because algorithmic trading cannot completely eliminate manual functions in trading such as building the trading strategies with prudent thoughts to ensure better stability in the financial markets. At present, and even in the future, the systems will definitely be needing human intervention for algorithmic trading.

With the help of machine learning, the algorithmic trading system can self-teach to predict future trends in the financial markets by studying historical data. Still, artificial intelligence can not mimic the human mind completely and requires human intervention to get to the right solution.

Algorithms are used since they are quick, more efficient and do not change their decisions on the basis of emotions. For instance, the algorithms are capable of checking multiple financial markets across the globe simultaneously, which helps save a lot of time and effort.

Whereas, it is not possible for human beings to simultaneously go through all the financial markets to find the best trading opportunities. Also, if the market does not favour your trading strategy rules, the machine learning system’s self-learning algorithms would adjust trading to different patterns and alter the rules to match market conditions.

Again, all of this is possible only with humans programming the system since in case the program needs to be stopped due to any other preference of the trader, only a human can make it stop.


Is algorithmic trading too tough?

Algorithmic trading is tough indeed because of the requirements such as the knowledge of machine learning, programming, quantitative analysis etc. but it is not impossible to learn even if your educational background or professional background is an unrelated one.

With so many self-taught algorithmic traders out there serving as live examples, one must know that it requires perseverance, dedication and self-confidence to become one.

However, there is no doubt that the information and learning resources such as courses, books, videos etc. for algorithmic trading are available everywhere. But, it is also a fact that the courses are not available in a structured manner everywhere. Moreover, one needs to be sure about the authenticity of the course.

Hence, you must get enroled only in the recognised ones and algorithmic trading will not be as difficult as it seems.


Is algorithmic trading too easy?

Now we come to another doubt when we say that it is not impossible and that is “Does it mean algorithmic trading is that easy?” Well, No! Just like needing to acquire any new skill takes a lot of effort, time, perseverance and dedication, algorithmic trading is also the same.

It is neither too easy nor too difficult. Only after you have gained all the necessary skills and you practice them significantly, can you become a successful algorithmic trader.


Is algorithmic trading the same as automated trading?

Often used interchangeably, the words algorithmic trading and automated trading are not the same. Algo trading implies turning a trading idea into a strategy via a coded algorithm.

The algorithmic trading strategy thus created can be backtested with historical data to check whether it will give good returns in real markets. The algorithmic trading strategy can be executed either manually or in an automated way. Automated trading means completely automating the order generation, submission, and order execution process.

If algorithmic trading fails, does it mean it should never be trusted?

In case algorithmic trading fails, it should not mean that you can not trust it from then onwards.

Since algorithms are software, it does not mean they are perfect. In the past, few instances of algorithms failing in trading have been noticed such as Black Monday that happened in 1987.

After that, a Flash crash took place in 2010. Hence, considering the long gap between the occurrence of such infamous events, it is expected that market crashes may become a thing of the past with algorithmic trading becoming more advanced with time.

Algorithms are becoming much better to take action when a buy/sell goes wrong or market volatility occurs. We can thus expect the elimination of certain glitches that we mentioned.

Algorithmic trading has innumerable benefits that no human can contribute to the trading industry.


Will algorithmic trading eliminate all the emotions?

Algorithmic trading does eliminate emotions from trading such as fear, greed etc. because of which the manual traders lose out on many good opportunities of getting better returns from the investments in the financial markets.

It is still possible to mess up a trade if the trader lets the emotions take over and changes the algorithmic trading strategy on the basis of fear, greed etc. Overtrading is also one of the problems when it comes to an algorithmic trader just like it is the case with a discretionary trader.

A major difference between algo trading and discretionary trading here is that once you have run an algorithmic strategy, no emotions can change the decision making. Hence, emotions during the execution of the trade are taken care of with algorithmic trading but, for making those algorithms work the trader needs to be rational enough.


Can I learn algorithmic trading in very little time?

There are various categories of learning resources such as books, videos, courses, etc. available across the internet for learning the required skills meant for algorithmic trading. Skills namely programming, machine learning, quantitative analysis, backtesting, risk management etc. are necessary for algorithmic trading.

You can opt for a course and begin your algo trading journey or to make yourself better at the already acquired skills, you can watch videos and read books. The courses vary in the completion time period and also vary with regard to whether you are starting from scratch, are mid-way or beginning as a seasoned trader to enhance your knowledge.


Conclusion

Algorithmic trading is a simple concept of executing trades with the coded steps and requires perseverance, dedication, time and effort for one to become successful.

In case you have any doubts about algorithmic trading, we have mentioned the most common ones and if you feel the need to clarify some doubts that are not here, feel free to reach out to our community. I hope this article helped!

To learn one of the most essential algorithmic trading skills for beginning the endeavour, enroll in our course on Python for Trading!


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