BQ Edge: Shankar Sharma’s Investing Model Marries Machine Learning And Human Intelligence

Why Shankar Sharma altered his investing approach...

<div class="paragraphs"><p>Computer code reflected in glasses. (Photographer: Chris Ratcliffe/Bloomberg)</p></div>
Computer code reflected in glasses. (Photographer: Chris Ratcliffe/Bloomberg)

“There are very few examples of people outperforming algorithms in making predictive judgments.” economist and psychologist Daniel Kahneman.

Market veteran Shankar Sharma acknowledges this limitation and has altered his investing approach accordingly.

When faced with a deluge of data, humans end up ignoring most conflicting facts and form under-analysed, oversimplified, lazy opinions, Sharma, co-founder of First Global financial advisory firm, Sharma said in a BQ Edge event.

Even experts in “supposedly more objective fields” such as radiology, insurance and DNA analysis can differ widely in their conclusions on the same data, let alone in a more uncertain one like investing, Sharma in a conversation with BloombergQuint’s Niraj Shah.

To remove that possibility, he relies on a model that combines machine learning with human intelligence.

His successful investments in the previous 25 years had a big element of luck, Sharma said. But the combination of machine learning and human intelligence, he said, is a skill that is helping him manage money well now.

Watch the full interview with Shankar Sharma here: