Financial investment firms and traders have been using IT tools extensively over the last couple of decades for planning and investing with the help of data and trends.
Financial investment firms and traders have been using IT tools extensively over the last couple of decades for planning and investing with the help of data and trends. They have been in the forefront of adopting technologies which have showed potential to enhance their time critical decision-making process leading to attractive returns. The new technologies related to Machine Learning, Deep Learning and Artificial Intelligence (AI) are ideally suited for these firms and have made substantial inroads into this segment, transforming the behaviour of trading.
Although studying patterns and trends based on statistical models has been prevalent for a while, such models have been restricted to quantitative structured data. Over the last several years, there has been a deluge of unstructured data that has been available to financial firms and traders, namely financial information on company sites, interviews of key stakeholders, blogs and social media content.
Machine Learning and Deep Learning are enabling the firms to convert such unstructured data into usable patterns through sentiment analysis thus adding a significant value to the decision making process related to the buy-sell process of stocks. However, since the financial objectives would be different for different individuals trading on the stocks, tools specially designed to study behaviour patterns of the traders provide further useful insights and thus investments have become more adaptive and centred around specific targets.
The high levels of volatality in stock markets have thrown up the challenge in making predictions on how stocks will behave. AI tools could lend support to minimise the risks by being able to project possible trajectories under various scenarios. Robo Advisors are the tools that fund managers and individual investors have begun to incorporate in their investment strategies to handle the volatality.JP Morgan’s LOXM is an AI based trading system which has the ability to handle the buy/sell transaction involving huge equity stakes without upsetting market prices and execute client orders at top speed and at the best prices possible.
As AI tools mature and they reach new levels of capabilities to learn and act in different situations in a way that they can even influence the markets, it may become feasible to cover most factors that could impact the prices of stocks and decision making in real time. The average time of holding the stocks has been reducing over the years but with AI tools getting matured and being able to address most of the factors, the time to hold on to the stocks would be for a fraction of time and therefore the action would be in real time. All of this seems a far fetched possibility as of now as the investment and efforts being spent on AI tools are likely to have the most impact on high frequency trading and not on transactions that occur on account of a completely different basis. The example of such a transaction is when Warren Buffet could change the course after 2008 crash by offering big deals to big banks in return for preferred shares. Further, as AI tools function on the basis of factors fed into them during training, unknown and unforeseen factors would derail them. That is why human skills coupled with actions based on emotions guided by AI tools would continue to create the excitement in the stock markets!
The writer is chairperson,
Global Talent Track, a corporate training solutions company