Algorithmic Trading vs Discretionary Trading. Algorithmic trading (algo trading)is the process of using computer programs that follow a set of defined instructions that are faster and more efficient than a human trader to generate profits. Discretionary trading, on the other hand, is the trade execution based entirely on human judgment with technical or fundamental analysis to make trading decisions. Most people when they hear or read of algorithms, they associate them with high technical frequency trading (HFT) which is not the case. Retail traders need to stay away from HFTs because it is difficult to compete with groups or individuals that spend millions on their infrastructure and staff because these groups can trade faster and at a cheaper cost.
Algo trading is just systematic, mechanical or rule-based trading technique that sets instructions on automation to determine when to trade. You can calculate simple moving average crossovers manually to obtain trading signals or write complex trading programs for a hedge fund by just following these rules of trade.
There are two keys to algorithm trading:
Backtesting the Algo strategies
According to most investors, past performance is not indicative of future results, and this means that what worked yesterday may not necessarily serve to your advantage today. With algorithms, you can go back and check their historical performance and test them for clarity. It is better to work with some rules which have worked before than taking on those that have no known history of working or not. Since money is involved, it is essential to back test to see if you are overcoming the costs involved.
Well Defined rules in algorithmic trading
Algos are rigidly defined rules for trading, and so to make the most out of them, all an investor has to do is to follow these guidelines.
There are however a few things to consider before getting started
Simplicity: What is important to note, however, is that a strategy that is simple and works will make trading easier while still making profits.
Dedication: Treat it as business and not just a part-time thing, giving it your all while continually improving and developing on the strategies.
Don’t Focus on the Past: There are few strategies like the Turtle method that worked in the past but have become obsolete over time. Avoid relying so much on these past legendary methods because though they might work, most of them are falling off.
Avoid Sharks: Most HFTs are market makers and love to scout for opportunities that will earn them high returns. Competing with these sharks may not be a good idea because trying the same approach could lead to paying a lot in trading costs while the sharks are doing things faster, efficiently and cheaply.
Let’s get into how to get started with algo trading:
Step 1. Is it what you want?
There are a few questions you need to ask before venturing into this kind of trading. For instance, do you like testing strategies? Do you love programming? Are you comfortable with having computer enter and exit trades for you?
Step 2. Learn the platform and how to program
The programming language is simple and easy to understand so take it up and get started right away.
Step 3. Get a Trading Platform
A platform such as the retail platform can test and automate trades. The retail software is relatively affordable, easy to use and learn, easy to debug and share strategies with other traders.
Step 4. Learn proper development and strategy testing
You need to get out of your way and develop strategies that will make the most profits. There are many methods out there that will work, and there is no definite answer as to what parts must be included in the strategy creation process.
Trading algorithms have advantages that make them more beneficial and they include:
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Diversification
You can create many strategies and automate them to make huge profits. For example, you can have one strategy for gold, crude oil, soybeans and so much more such that if you have a long for one product and a short in another the difference balances them out and in the long run, you get the most out of it.
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Historical performance
You can have confidence in executing a strategy being fully aware that it worked before.
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Can be tested
One reason to trade algorithmic trading is that you do not need to hire or rely on a guru to check the rules. You can correctly test and verify them on your own.
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Lack of human emotion
Lack of emotion is a considerable advantage because computers are not susceptible to human emotions which cloud their judgment leading to poor decisions. The predefined criteria remove any emotional attachments.
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Reduced transaction costs
Continually monitoring the markets needs continuous supervision but Algo trading cost has significantly been reduced as trades can be executed without many follow-ups that are usually costly.
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Speed
Algos use computers to trade, and this is a huge advantage because of the automation making them a faster, efficient way than humans can perceive.
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Accuracy
Computer algorithms have been double checked to avoid pitfalls of accidentally placing wrong orders in illegal trades a common mistake that happens in manual entries associated with human trades.
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Discipline
There are predetermined rules that have been established and so even in volatile markets it is almost impossible to execute trade unethically as a result of emotional factors like fear or greed.
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Consistency
Automation of algorithms allows traders to achieve professional levels of flexibility by trading according to the plan.
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Time involved to trade is less as a result of the industrialization of this kind of system.
Disadvantages of Algos
- Most people override the strategy by getting in their way and not following the rules.
- Developing a strategy the wrong way, without thinking things over, might create a flawed plan.
- Past performance may not guarantee future success or results. The fact that a strategy worked in the past may not necessarily guarantee that it will work in the future.
Summary
Retail traders can try out Algo trading without fear but should be willing to learn a platform, learn to program and to develop best practices in developing strategies properly.