Common Myths of Algorithmic Trading

With the emergence of new technologies, it becomes crucial to have an understanding of the concepts related to it, otherwise , it can lead to mistakes that result in losses. Algorithmic trading is one trend in the investment world that has experienced rapid growth and therefore surrounded by many myths arising due to misinformation and lack of clarity.

In this article, we are going to go over some of the most common myths associated with algorithmic trading.

MYTH: Algorithmic Trading is the Same As Quant Trading, High-Frequency Trading, and Automated Trading

Algorithmic Trading is often confused with similar concepts and terminologies like quantitative trading, high-frequency trading, and automated trading. While all of these concepts are similar, each has distinct differences. Let’s take a closer look at which each means.

• Algorithmic Trading. Algo trading is the process of converting a trading strategy into an algorithm or code, and checking whether or not said strategy provide good returns by performing backtesting on historical data.

• Quantitative Trading. Quant trading involves using advanced mathematical and statistical computations along with quantitative analysis to create trading strategies. This can then be executed manually or automatically, depending on an investor’s strategy.

• Automated Trading. Automated, or automatic, trading involves the process of order executions such as buying and selling stocks, and often automated portfolio and risk management as well.

• High-Frequency Trading. HFT involves executing multiple orders in an extremely short span of time and targeting small profits from each trade, but doing a vast number of them overall. HFT is a subset of algorithmic trading, and given the speed at which traders need to send the orders, it must be automated. Interestingly, most HFT strategies have a quantitative nature.

MYTH: You Can Set and Forget With Algo Trading.

While it is true that algorithmic trading does the work to accumulate profits, saving time from everyday trading routines, they still require some level of supervision. Investors should monitor all trades for any code error. Additionally, some of the trades may not be executed properly and therefore investors will have to solve the issue with the code. It is not an issue you would encounter every day, but all trades should be monitored to an extent.

MYTH: HFT Put Retail Traders at a Loss

This is one of the most common myths regarding the use of algorithmic trading and colocation and stands completely incorrect as the High-Frequency Traders do not compete with retail traders, rather they are competing amongst themselves.

Colocation involves placing the servers of the HFT traders in close proximity to the exchange. Being in colocation facility ensures that traders are able to update their orders to the fair price within a very short time. This enables them to offer much better quotes, resulting in significant savings in transaction costs for an average retail trader. Effectively, this can potentially benefit the retail traders as the bid-ask spread is lowered and they can execute orders at a smaller price in general.

MYTH: Algorithmic Trading is Too Technical

Many people have the misunderstanding that you have to be a programmer or technical whiz to be a successful algorithmic trader. While it may sound logical initially, the truth is that if you’ve got an idea for a trading system you don’t have to program it yourself. There are plenty of algorithmic trading programs available that make algorithmic trading a breeze., some even come with effective algorithmic trading strategies.

MYTH: Individual Traders Cannot Do Algorithmic Trading

Unlike HFT which can’t be done by an individual trader, algorithmic trading can be done by individual traders in most major geographies globally. It does not involve huge capital investments in infrastructure and technology, which is why it is an open domain for everyone to try. However, it does require that a trading strategy converted into an algorithm is implemented. Many traders may be hesitant to try algorithmic trading on their own in live markets for which backtesting, a process which involves testing the strategies on historical data, is of great benefit to ensure maximum efficiency of the trading strategy.

Now that you are familiar with these concepts and have gained more clarity about common myths associated with algorithmic trading, you can start trying it on your own. For the best experience, traders should try using an elite algorithmic trading software, such as Alpha Droid. AlphaDroid makes it easier to analyze, construct, and compare their investment portfolios. To learn more, contact us!