There must have been many instances in your life where you expected something before beginning a new concept but it turned out to be a bit or completely different. While all your expectations from algorithmic trading may not be unrealistic, there may be some that you are not aware of.
Let us now see the list of such unrealistic expectations along with the realities below:
Expectation: I will be rich instantly.
Reality: Returns depend on the strategy creation based on technical and quantitative analysis of the historical data and backtesting of the strategy. There cannot be a guarantee of a particular amount or percentage of returns but the probability can be known.
Recommended reads:
- How to Use Technical Indicators for Trading?
- How to Become a Quantitative Analyst?
- How to Backtest a Trading Strategy?
Expectation: I will not have to intervene at all for algorithmic trading once the system is programmed.
Reality: Human intervention is a must for setting the conditions according to the trader’s preference. There needs to be a balance between human intervention and automation.
Also, a strategy running well at one point in time may not continue to give the same returns over a period. For instance, a trading strategy with annualised returns of around 6% or so may go down to 2% returns due to any of the following reasons:
- Bearish market because of a black swan event such as covid-19
- A glitch in the programmed system
- Industry specific decline in returns
It is highly imperative that a trader does the periodic monitoring of the strategy and finds out the main reason behind the decline in the returns in order to adjust/modify the algorithmic strategy accordingly.
Recommended read: What is Algorithmic Trading?
Expectation: Algorithmic trading means only automated trading.
Reality: Algorithmic implies coding the trading strategies and converting them into algorithms whereas automated implies automating the execution of trades every time the coded conditions are met. Algorithmic trading can be executed manually or in an automated manner.
Recommended watch: How To Automate A Trading Strategy
Expectation: Risk management will not be that important during algorithmic trading.
Reality: It is highly important for a trader to manage risk even with algo trading. Risk management shields the trader from the rare but possible glitches in the system and some biases.
Recommended read: Portfolio & Risk Management
Expectation: Since the algorithms maintain a discipline, I will not have to.
Reality: It is not true. Discipline as a trader is needed in algorithmic trading as well so that you can keep a check on any need to change the trading strategy in accordance with the situation in the financial market or any technical reason.
For instance, it is possible that some other stocks, bonds or commodities give better value for money than the one you have invested your capital in. This way you can change your trading strategy and invest your capital in some other financial market. Also, discipline will help you to not overtrade and maintain balance. Start with these key Algorithmic Trading books to build your knowledge.
To strengthen your discipline as a trader, explore algo trading courses that cover strategic adjustments, risk management, and insights into optimizing your trades based on evolving market conditions.
Expectation: Algorithmic trading requires intensive computing power.
Reality: It’s not necessarily true. It largely depends on your algorithm. High-frequency trading is a part of algorithmic trading that requires intensive computing power.
Algorithmic trading is an imprint of quantitative trading which implies that the algorithms help execute trades after systematic implementation of trading strategies with quantitative techniques.
Expectation: Algorithmic trading requires knowledge of complex mathematical modelling.
Reality: The expectation of needing the mathematical knowledge is partially correct. With the help of algorithms, it becomes possible to automate your trading strategy. Your trading logic can be as simple as a moving average crossover strategy.
However, you can always use the complex mathematical approach to use complex models such as machine learning models. In general, and to sum it up, you will simply need the knowledge of some basic mathematics that can serve the purpose as well.
Recommended read: Essential Mathematical Concepts for Algorithmic Trading
Conclusion
Algorithmic trading helps a trader with the logical execution of trades. Nevertheless, there are certain unrealistic expectations in the minds of novice traders. With this article, we covered some of those expectations and their realities so as to help you begin your algorithmic trading journey better.
Learn more about practicing algorithmic trading using quantitative approach with our course on Quantitative Trading Strategies and Models.
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