Algorithmic trading is the process of using a computer program that follows a defined set of instructions for placing a trade order. The aim of the algorithmic trading program is to dynamically identify profitable opportunities and place the trades in order to generate profits at a speed and frequency that is impossible to match by a human trader. Given the advantages of higher accuracy and lightning-fast execution speed, trading activities based on computer algorithms have gained tremendous popularity.
Algo Trading is a form of Automated trading that uses computer programs to analyse market data based on pre-defined parameters.
Who Uses Algorithmic Trading Software?
Algorithmic trading is dominated by large trading firms, such as hedge funds, investment banks, and proprietary trading firms. Given the abundant resource availability due to their large size, such firms usually build their own proprietary trading software, including large trading systems with dedicated data centers and support staff.
At an individual level, experienced proprietary traders and quants use algorithmic trading. Proprietary traders, who are less tech-savvy, may purchase ready-made trading software for their algorithmic trading needs. The software is either offered by their brokers or purchased from third-party providers. Quants generally have a solid knowledge of both trading and computer programming, and they develop trading software on their own.
Algo trading is widely used in financial markets by commercial banks, investment funds, hedge funds, non-bank market makers and retail traders. According to research 40% of institutional FX traders made use of algo trading in 2020 and expect that their usage will increase further in the future.
It is especially important to financial institutions who engage in market making. You may also have heard about high-frequency trading (HFT), which gained significant traction in the past few years. HFT is a type of algo trading that makes use of high-frequency data and electronic trading tools to execute significant volumes at very high speeds.
What is the difference between automated trading and algorithmic trading?
Automated trading is about automating the entire trading process, meaning that the automated trading system takes over the whole process from screening for opportunities in various financial instruments to taking the decision of buying/selling.
Where as algorithmic trading focuses on the execution process of a trade.
1.Remove human error
Trade without letting emotions get in the way of realizing profits, or cutting losses
2.Capitalize on rare or special events
Act on infrequent events, such as the Dow closing 500 points below its 20-day moving average
3.Supplement your existing strategy
Finely tune your risk management by using algos to implement stops and limits on your behalf
Set your algorithms up and let them trade around your schedule
Refine your algorithms against historical data to establish the best combination of buy or sell parameters
6.Increased opportunity with instant execution
Maximize your exposure to the underlying market with automated buy and sell orders
What are the risks of using algorithmic trading in forex?
While algorithmic trading certainly has its benefits, there are also risks involved. Algos operate at high speed, which means that a bug could lead to notable trading losses within a short time.
Furthermore, you are relying on the algorithm to function efficiently and may find yourself in a situation where you are temporarily out of control.
Algorithms operate based on rules. Removing emotions from trading can be a good thing, but it is a fact that intuition or “gut feeling” does play a role in trading – especially if you spend a significant amount of time monitoring the markets. Algos will not have this advantage.
There are also concerns that algorithms and HFT trading contribute to the rising occurrence of flash crashes. We talk about a flash crash when the price of an asset declines rapidly within a short period of time and quickly recovers. One of the most famous flash crashes happened in 2010 when the Dow Jones index declined more than 1000 points within 10 minutes. The price of many stocks declined rapidly, and the price action alone was sufficient to trigger a large amount of orders which essentially caused an avalanche.
Can anyone create an algorithm?
Well, yes and no.
Modern trading platforms have made it much easier to create your own very simple algorithms or, at the least, custom indicators. If you’re confident in your own ability, this is something that might be worth pursuing but, by and large, creating complex algorithms is a specialised skill most applicable to those with a background in mathematics, statistics, computer science or similar quantitative background.
Genuinely effective algorithms can take a long time to develop and require extensive and ongoing testing. If you’re not suitably qualified to create your own custom algorithms you can purchase them predesigned, or even work with a programmer to create some targeted specifically for your goals and strategy. Whatever the case, you should always use a demo environment to test comprehensively and make sure your algorithms work as intended. Sign up for a demo trading account to begin testing your algorithms.
You should also keep in mind that an algorithm that worked once, twice or even three times isn’t guaranteed to work the next time. As outlined above, the markets are ever-changing which will affect your rules as time goes on. For example, if your algorithm is based on historical data from the past three years, in another years time the entire data set will likely have changed significantly, requiring adjustments to your algorithm.
It’s easy to see the convenience to be had from automating your trades, but they can also help on a psychological level, removing cognitive bias. When you trade in a more manual fashion, it’s difficult to remove your own predispositions from your decisions –those times where you just have a “good feeling” about a trade.
Algorithms remove emotion from the equation. They don’t work on opinions or feelings, only facts and data. They are, therefore, always objective. However, they’re only as powerful or capable as the rules they’re written in.
As with any form of trading, you need to first determine your objectives and strategy then figure out which tools are the best to help you achieve them. No algorithm is entirely foolproof–not even the most complex ones – but for many traders, their usefulness is well proven.
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