Hello Readers, as promised, we are here with the fourth blog in the series “AI in Banking and Financial Services”. In our previous blogs, we focused on Anti-Money Laundering (AML) Pattern Detection, Chatbots, and AI in Fraud Detection, while in this blog we will focus on the impact of AI in Stock Trading.
Algorithm trading has transformed the stockbroking industry. Earlier, dealer rooms used to be buzzing with activities, where many dealers used to communicate with clients to buy and sell stocks. Today, dealer rooms wear a deserted look, thanks to algorithm-based stock trading.
The advent of algorithm-based trading involves computers that trigger orders based on technical indicators. Previously, though traders or brokers used to make money through strategies like arbitrage and relative strength in the movement of the funds.
That said broking houses have registered a manifold increase in their profits with the acquisition of split-second decision-making and speed of execution. The sales functions too have shifted more towards the web, thanks to next-gen technologies such as AI, ML, NLP and powered solutions like chatbots that are serving as the next frontier in customer care.
AI can also help humans with qualitative analysis by triggering alerts for specific stocks based on patterns and financial ratios while correlating the same with news reports feeds of those stocks and industry.
Experts believe that today most equity investors do not buy or sell stocks based on specific fundamentals and narratives that explain the price action abound. In fact, fundamental discretionary traders account for mere 10% of trading volume in stocks, while the passive and quantitative trading generates about 60%, which is more than two times the share a decade ago.
Marty Chavez, Goldman Sachs’s deputy chief financial officer (CFO) and former chief information officer (CIO) echoes similar thoughts. He explains that automated trading programs, today take on a bigger pie of human trading operations at the company’s US cash equities trading desk in New York. The growth is testified by the fact that only two equity traders are working at the desk, compared to 600 traders in 2000.
Impact of AI in Trading
The use of AI in trading has grown in recent years. According to a report in the Wired, at least 1,300 hedge funds are leveraging some form of the computer model for trading. We can apply AI in trading in three ways.
Supercomputers can process humongous volumes of data points within minutes. Thus, the systems can unearth historical and redundant patterns for smart trading that human investors are often unable to identify. This is because cannot process that much volume of data or review patterns at the same rate of technology.
Consider that AI can evaluate hundreds and thousands of stocks in moments. CNN highlights that some hedge funds leverage AI to interpret as many as 300 million data points alone, when it comes to high-frequency trading, on the NYSE in the opening hour of daily trading.
Sentiment-based Predictive Trading
AI along with Machine Learning (ML) can analyze news headlines, social media comments, expert columns and other content around stocks and forecast the movement of the stock and other traders through sentiment analysis.
With even milliseconds considered precious time, AI helps enhance the overall speed of stock trading. The technology automates trading and provides you with all the information on the go, without having to call your broker or get on an app.
With algorithms replacing human efforts in several financial areas, it was a matter of time before they started influencing stock trading. The recent developments in next-gen technologies such as AI and robotics are impacting the overall functioning of the stock trading organizations. If you have experienced something similar or have more insights on the topic, share them in the comments below.
Thanks for reading. That is it from our side.
Until next time!
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