“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:
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