The three myths of algorithmic trading
With the advent of new technologies, it is crucial to understand the concepts associated with them because failure to do so could result in catastrophic errors and losses. One rapidly expanding field is algorithmic trading, which is surrounded by numerous myths that have developed due to misinformation and a lack of understanding. These are a few of the myths that we ran across that we believe everyone needs to understand.
Quantitative trading, high-frequency trading (HFT), and automated trading are all forms of algorithmic trading
Algorithmic trading is frequently conflated with terms and concepts like automated trading, HFT, and quantitative trading. Despite being closely linked, these are distinct from one another. By clarifying what each phrase means, let’s better comprehend these disparities.
Algorithmic trading: Algorithmic Trading is the process of translating a trading strategy into an algorithm or computer code and determining whether the method gives us good returns by performing backtesting on historical data.
Quantitative trading: Trading Strategies Utilizing Quantitative Analysis and Sophisticated Mathematical and Statistical Calculations – Quantitative trading is the process of developing trading strategies using advanced math and statistics. Depending on the approach (and the strategist!), this can then be carried out manually or automatically.
Automated trading: It refers to the process of automating the execution of orders, such as buying or selling, as well as the management of a portfolio and risks.
Trading at a high frequency (HFT) – High-frequency trading entails carrying out orders in a very brief amount of time, typically under a second, with the goal of making extremely small profits on a large number of trades. HFT is a subset of algorithmic trading that requires automation due to the speed at which orders must be sent. Surprisingly, the majority of HFT techniques, with the exception of standard arbitrage, are highly quantitative. This sphere is mostly professional and individual investors are not involved, instead it is run by institutional investors, big trading companies, etc. One of the examples is BHFT – a trading solutions provider and HFT-class trading platform owner.
Because high-frequency traders employ colocation, retail traders are losing money
One of the most widespread misconceptions about colocation is that high-frequency traders compete with retail traders. In reality, they instead compete with one another.
Colocation entails positioning the HFT traders’ servers close to the exchange. Since HFT desks make up the majority of the markets and aim to make only a few pennies on each deal, any unexpected occurrence or piece of news might result in large losses. Being in a colocation facility guarantees that they may quickly change their orders to reflect fair pricing. As a result, they are able to provide far better quotes, which enables the average retail trader to save significantly on transaction costs. Since the bid-ask spread is decreased and they may execute their orders at a lower price overall, it essentially has the potential to be advantageous to retail traders.
Individual traders cannot use trading algorithms
Individual traders can engage in algorithmic trading in the majority of the world’s major geographical regions, unlike HFT, which is not permissible. Since significant infrastructure and technological investments are not required for algorithmic trading, it is a field that is open to all research. It calls for the implementation of an algorithm or piece of code that represents a trading notion or strategy. Backtesting, a procedure that involves testing the strategies using past data, is quite beneficial to guarantee the trading technique is as effective as possible. Many people may be reluctant to try out algorithmic trading on their own in live markets.
Now that you are familiar with these ideas and have some understanding of these widespread misconceptions, you can start learning more about the field of algorithmic trading and dispelling more misconceptions of this nature.
