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Algo trading is nothing but a series of commands defined by experts to execute a buy/sell order with predefined conditions.
As we know, the prices of financial instruments like stocks, forex, and commodities fluctuate in fractions of a second.
So, it’s difficult for humans to be present every time and monitor the prices. Therefore, this work is delegated to a machine with a set of predefined conditions.
In the world of finance, information is power. But with the ever-growing sea of financial data, turning that power into actionable insights can be an important task.
This is where algorithmic trading (algo-trading) steps in, transforming information overload into trading opportunities in a disciplined manner.By leveraging technology and advanced algorithms, algo-trading is revolutionising the way trading decisions are made.The strategies deployed for creating algorithms are built using different mathematical concepts and vast data interpretation.
In the live markets, if the defined conditions are met, then algo will run and execute the order automatically. However, if the conditions are not met, then no trades will be executed.
Another advantage of algo is the disciplined execution of trade without involving human emotions. Generally, Algorithms process diverse data points, including stock prices, historical trends, technical indicators, price actions, etc.
This type of data is very useful for defining the logical conditions for decision-making. By analysing and interpreting the data, algorithms can uncover patterns and relationships that human analysts might miss.
This allows investors to identify potential opportunities and make informed decisions while the market is on the move.
Typical type of Algo Strategies
● Trend following: The Condition in such strategies is to follow the chart patterns or technical indicators to identify the trends and take positions accordingly.
● Arbitrage Opportunities: The logical condition is to identify the gap in prices in the same asset at two different places, say two different exchanges.
● Rebalancing: It is more to rebalance the position or portfolio to match the desired composition of the portfolio.
Downsides – What One Should Take Care For
Technical glitches can affect algorithmic trading, leading to issues like order execution delays and software bugs.
At times of market volatility, algorithms might struggle to adapt to the high volatility during any market events, which may backfire on unwanted trades.
Also, the success of Algo-trading heavily depends on the accuracy of the input data. If the fetched data is wrong, then executed trades may lead to financial loss.
One of the biggest hurdles is regulatory concerns; institutional investors may face legal and regulatory challenges if algorithmic trading results in incorrect or problematic trades.
Algorithmic trading has many advantages that help revolutionise trading in stock markets. It is gaining popularity in the investment field due to its ability to make decisions without human intervention, and it is likely to improve further in the days to come.
(The author is CEO of Bigul)
(Disclaimer: Recommendations, suggestions, views, and opinions given by experts are their own. These do not represent the views of the Economic Times)
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