At just five years old, Dhruv Krishnan watched his grandfather trade stock with great interest.
The retired orthopedic surgeon would scour financial news and observe the market in idle hours. He told Krishnan about his hobby, its highs and lows. Sometimes, he asked the boy to dig for data or ponder questions.
Krishnan answered dutifully.
“All I did then was read and play with action figures, but I would always hang out with my grandfather,” said Krishnan, now 18. “And that was what he did in his spare time.”
That initial interest blossomed into a passion for finance. Krishnan’s mother is a retired cancer researcher; his dad, an attorney. But their son gravitates toward numbers, to code — and also to cash.
In middle and early high school, he questioned why stocks rarely benefit everyday people or organizations such as “charities, hospitals and nonprofits,” he said.
Big companies rake in all the profit, Krishnan thought. What about everyone else?
“On Wall Street, the goal is to make money. You work for 20 or 30 years. You make all this cash. That’s the end,” he said. “There has to be a bigger and more meaningful purpose to trading.”
So Krishnan devoted late nights in 9th and 10th grade to creating a stock market algorithm, or a series of instructions that tell a computer how to complete a specific task. He wrote it in the hopes of maximizing return on investment for people the market leaves behind.
Think graduates with student loan debt they’re toiling to pay off or Indian hospitals struggling with resources during the COVID-19 pandemic.
Many people lack the time or financial knowledge to navigate stocks, he said. The algorithm simplifies the process for them. It introduces the prospect of investing a sum based on an individual’s goals and risk tolerance, and then actually seeing that money grow.
And it eliminates the need to turn to an investment company that charges fees. Instead, the person putting down the funds is the one firmly in control.
An educational nonprofit, for example, could invest a few thousand dollars in donations into the stock market. When the algorithm helps that initial amount grow to an agreed-upon target, they sell. Those profits can then be funneled into a budget for scholarships or school supplies.
“Having a system that can produce money for you, essentially, gives you the power to help the community,” Krishnan said.
His creation predicts movement in different stock market sectors, like telecommunication, energy and real estate. When he tested the algorithm in a simulation of the 2012 market, he made a 138 percent return on the investment for the year.
By 2012, the stock market had recovered most losses from the Great Recession, Krishnan said, making it a suitable test period.
“Most people are happy to see something in the double digits,” said Suzanne Costanza, executive director of the Florida Council on Economic Education. “He got in the triple digits.”
Stock market returns have averaged 9.2 percent annually over the past 140 years, according to global investment bank Goldman Sachs.
In late May, the Tampa Bay Business Hall of Fame honored Krishnan, a Tampa resident, for his achievements with its first Future Hall of Famer Award. The organization recognizes influential business leaders as part of an annual ceremony dating back 34 years.
Krishnan and his algorithm also took second place at the Hillsborough County Regional STEM Fair two years ago. His high school grade-point average was 3.9, with just a smattering of A minuses.
“He’s poised, put together, and confident, with good intentions for his work and the world,” said Costanza, who helped select Krishnan from a dozen Future Hall of Famer applicants.
Krishnan took the reins of his technical education early and independently. Software design classes at the Carrollwood Day School sparked his love for programming.
But the real progress happened at home, according to his mother, Sadhana Ginde.
After homework, Krishnan read up on math and economics, including textbooks on calculus-based financial modeling by mathematician Steven Shreve. Youtube videos and online courses helped him learn programming languages with relative ease. He voluntarily passed up seeing friends to write and review code.
“Incredibly, incredibly focused,” Ginde said.
Hour by hour, his algorithm came to life.
It runs with Python and Quantopian programming languages using random forest techniques, a learning method that determines the likelihood of one choice over another. The thinking behind the project is inspired by a well-known framework for diversifying money in the stock market, titled the Fama-French model.
“I, of course, adapted it with my own factors,” Krishnan said.
To Ginde, Krishan’s algorithm is outside her area of expertise (“I don’t understand anything about the project,” she said).
She knows him for loving sushi and Thai, for watching soccer and tennis. He aches to travel, and grew up plunging himself into the worlds of classic novelists — Jules Verne, Charles Dickens and Shakespeare. Most of all, Krishnan “liked the idea of technology playing a part in his life,” Ginde said.
And it seems it always will.
He leaves for Carnegie Mellon University in August to take advantage of its leading computer science program. There, Krishnan will await the approval of two patent applications on his algorithm and its potential applications.
If all goes as planned, Krishnan’s algorithm will pair with a phone app and a smart device, à la Amazon Alexa or the Echo Dot, that provide advice and assistance.
The device’s name? Kirby — after the initials of five famous computer scientists.
“You could ask [Kirby] questions,” Krishnan said. “Like what are my goals for the future? What style of risk do I want to use? How much should I invest?”
The phone application would function as an automated investing service or offer projections of investors’ existing stock portfolio. It may even churn out an analytical report.
“When investing stock on your own, there’s a lot of risk involved. This is supposed to provide them with a strong foundation and less worry,” Krishnan said. “You’ll know your money is in good hands without any sort of mismanagement.”