Professionals on Wall Street are highly paid to predict where stocks and stock markets are headed. The most prescient, think Warren Buffet, are billionaires.
Izzy Simpson, 18, who graduated last year from Animas High School and is a math major at the University of Denver, thinks the pros’ use of two methods of predicting stocks, fundamental analysis and technical analysis, are all wrong, or at least grossly incomplete.
She spent the summer during an internship at State Street, a Wall Street custodian bank, trying to prove that stocks move around based on principles of swarm intelligence, the same rules that guide ants and bees to food, controls the migration routes of birds and the behavior of fish in a school.
“It’s a biological view of the way stocks move,” Simpson said. “I developed a couple of models. None of them worked with extreme accuracy, but some showed promise.”
This summer, Simpson said, she hopes to land another internship to further refine her work and develop a model “accurate enough to turn a profit.”
Technical analysis of stocks looks at past market data, primarily price and the volume of trading, to predict where stocks are headed.
Fundamental analysis looks at stocks and where they are headed based on the assets, liabilities, earning, competitors, regulations and taxation of a busines.
In essence, Simpson maintains that neither method is accurate in accounting for the fluctuations in stock prices. Instead, it’s human swarming behavior based on the stock market that truly accounts for where stocks are headed.
The trading floor and the computer data handling billions of transactions a day from around the world are essentially human hives similar to the way ants communicate when a new food source is discovered, Simpson said.
She’s eager to continue her research, but she admits she still has a long way to go before she can produce anything usable in the daily frenzy of stock trading.
“I’m not a programmer. I’m not a trader. I’m not a data scientist,” she said.
Simpson’s idea to tie stock valuations to swarm intelligence, a theory developed in biology, came after listening to a National Public Radio report on swarm intelligence.
She had begun predicting stock market valuations using traditional fundamental and technical analyses in an Animas High School senior math class taught by Kyle Edmondson, and she thought combining all models into a “super model” would give her the key to stock prediction.
But she soon discovered there are so many different technical and fundamental models out there that combining them into one model was “basically impossible.”
She latched onto using the idea of swarm intelligence to see if it would be a better predictor of stocks’ future values.
Edmondson, who said Simpson was among the most skilled math students he’s taught over a 20-year career, was impressed she taught herself computer programming to complete her senior project.
“She’s a sharp kid,” he said. “It’s a combination of intellectual ability and interest and drive.”
Simpson’s senior project, he said, was among the best last year.
“An average student couldn’t have done it. And an intelligent student couldn’t either without stick-to-itness and drive,” he said.
Now, Simpson is looking to prove her theory that the stock market “is a swarm intelligence interface” like a beehive.
She learned the definition of a stock in August of 2017, and the first time she looked at computer programming script was in January, but now she’s combining all those skills along with attributes of swarm intelligence to refine her ability to find the next big thing on Wall Street.
“The idea is a stock price over time represents the true value of a stock, and trading based on under- or overvalue is something like the wiggle dance returning bees do in the hive,” she said.
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