Demystify the next decade of global financial markets from the AI and ML lens of a computer scientist-turned-fund manager

What is AI & ML, and its applicability in Wealth Management by a Data Scientist turned Fund Manager

The difference between Artificial Intelligence(AI), Machine Learning(ML), and Deep Learning(DL) is that Machine Learning is a subset of AI like a young human learns. And, Deep Learning is a Narrower subset of ML – It uses one of the different methods i.e. Neural networks.

The current stage of development cycle in AI is Artificial Narrow Intelligence. It means AI is outperforming Human Intelligence in a few narrow fields. Later stages are AGI and ASI i.e. Artificial General Intelligence and Artificial Super Intelligence. And, this is the future of AI but it will take many years to reach there and it will mean, AI beats Human Intelligence in almost all fields of life!

AI started in 1960 and today, some of the technologies of AI are at different phases.

Today business growth is based on technology, not based on geography. This is evident from the fact that in the year 2020, out of the 10 largest companies worldwide by market capitalization, 8 are AI-based.

Way Forward for Wealth Management is AI & ML. In the Last 10 – 20 years, the ways have remained the same in the industry & big disruption is pending.

How AI-based machine views Market & Investing over the next decade

Artificial Intelligence (AI) is adaptive as it learns from multiple data points across various factors like – growth, valuation, quality, momentum etc. This learning helps the system understand an economy/asset class/market/security, there are many things that the computers do better than men.

Under AI & ML backed system, the machine learns from 100s of data points and factors to help the system create a view and suggest actions. This has an edge over how the human brain functions as the machine learn continuously and through multiple sources.

The machine has a more objective memory and remembers the market’s reactions across the time frame whereas the human mind attaches more importance to recent events and forgets the reaction of markets to previous events.

The artificial intelligence-based system due to various learnings from data points and events in markets understands the usual reaction of markets more objectively. For example, the AI-based system was of the view even before Covid-19 that Pharma would do well as multiple levers of growth were supporting it. AI and ML have been improving over the years, however, there’s a long way to go before AI can be a substitute for humans.

In short, the machine has various fundamental data points, as well as momentum data points; it combines both and through this information, the machine constantly learns and suggests actions, these suggestions tend to be more accurate than the human mind can suggest because the human mind has limitations.

Finally, taking cash calls while investing is what the human mind gets tempted for, and historical data does point out that taking cash calls does help, and remaining always fully invested is not the best approach. But, taking cash calls is extremely tricky and even machine is not equipped to determine that with accuracy, so investors could lose out doing that. Fully invested is also tricky as even that ways investors could lose in short to medium term. The ideal scenario is to do a scientific asset allocation based on the time horizon of the investment as well as attitude to risk, and then for the equity portion, look for a basket of stocks along with the credibility of the fund manager, rather than trying to time the market. A fine basket of quality businesses chosen and invested at any time should yield returns superior to timing the market, but if held over the long term.

Risk Disclaimer : - 

Investments are subject to market risks. Please read all Scheme Information Documents (SID) /Key Information Memorandum (KIM), addendum issued from time to time and other related documents carefully before investing. These are views as shared by a data scientist turned fund manager, and should not be construed as any kind of Advice or Recommendation. Past performance is not indicative of future returns.