Using AI To Interpret Market Sentiment
Comprehending market sentiment is a key, if not the main element of investing; the capacity to read it in real-time and view the long run can give a trader a heavy advantage in a competitive market. Many say sentiment is emotional, or a contrarian indicator, so it may seem counter-intuitive to utilize machine learning to get a clearer picture of it. This is exactly why AI is useful—it prevents the emotional and reactionary element humans can deploy when trying to interpret market sentiment, while still using the largest possible sample of data available. Unlike humans, AI is not humiliated by making mistakes; instead it adapts instantaneously to feedback on outcomes: it learns, applies and delivers improvements on results.
One of the biggest challenges for financial professionals is Information overload; a challenge that might have been impossible to overcome without the advantages of AI and machine/deep learning. Rather than analyzing the anecdotal evidence of just a couple advisers or trend-predictors or the statistics in several articles from a few sources, AI can be utilized to find and process all available data—in the finance sector, this could be 200,000 articles per day—in a constantly updating cycle, giving an instant and in-depth image of where market sentiment lies. In a market driven by information, having the ability to process and analyse such a large quantity of it to get a strong picture of sentiment and act on what you find is extremely valuable.
Augmented Language Intelligence (ALI) is the term to describe the process of integrating natural-language processing (NLP) and machine learning to cut down and sort the available data and evolve our abilities to analyse key factors in sentiment including global and local events, shifts in government policy, leadership changes, accidents etc. Using ALI to process financial news yields a previously impossible overview of the market and allows insight into specific news events, regions, time periods, and companies.
ALI increases people’s command over information. ALI doesn’t replace human involvement in decision-making, but allows informed decision-making that uses the widest possible range of data for financial professionals to use. It might even be possible that ALI will unearth new applications of “sentiment” or new ways of utilising trends.
Testing AI in the financial sector is a good idea. We don’t have to go from horses to cars - we can ease this technology in as we learn its benefits and how to protect against any downsides.