Finance as a sector has attracted a lot of innovation and technological advancement in recent times. As such it is all but natural that the world of trading has begun to understand the importance and potential impact of incorporating powerful tools like Artificial Intelligence and Machine Learning. Algorithmic Trading has gradually started becoming an integral part of investment strategies and the trend is not just limited to the developed nations of the world but is also gaining traction in economies like India.
AI driven platforms have established themselves to be capable of giving safe and reliable returns. The use of AI in trading is not only limited to trade strategies but also has tremendous scope in trade settlements, compliance and regulations, operations as well as data management. Numerous use cases of AI in trading are already in place. For example investment banks have begun to build Machine Learning (ML) algorithms to trade volatilities. Some of them use Natural Language Processing (NLP) to recognise patterns in market signals after scraping through news and articles. They then use these patterns for various purposes such as recognising volatility, predicting prices and movement among others.
AI has begun to find its place in everyday trading as well. Technical analysis can easily be replicated automated by the use of AI to learn and develop successful algorithms. Moreover, AI is also being deployed to reduce volatility in investments. Prediction of market movement and prices has become easier and more accurate with the help of AI thereby enabling investors to be smarter in trade execution. Even in India financial services providers are launching products which allow investors to create their own algorithms, backtest them and eventually deploy them for trades.
ML is increasingly being used to complement AI. It involves using historical prices as data samples. The algorithm can then use this to predict expected outcomes using predictor variables. The true power of ML relies in its ability to identify and adapt to changes in the market and macroeconomic conditions. It is rightly envisaged that the future lies in these technologies which have the ability to make trading smarter, more efficient and less volatile.