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Ideas Made to Matter
Does statistical trading make markets less or more efficient?
Big data represents a big opportunity for Wall Street. It’s never been easier for investors to capture exorbitant amounts of data to analyze financial statements or interpret asset prices using algorithms. Even credit card receipts and social media posts can provide insight to those who know how to make sense of them.
“Thirty years ago, computers were super slow, and everything was written on paper, so it was hard to put all of the data available and make sense of it,” saidan assistant professor of finance at MIT Sloan who recently co-authored “Long Run Growth of Financial Data Technology” in American Economic Review.
“With the rise of the internet and computers getting better, investors and financial firms can process a lot more data,” providing a valuable opportunity to “explore the different forces that we believe are at work in this data economy.”
Traders often use big data when they engage in statistical high-frequency trading, which relies on computers to execute transactions based on demand dynamics and trading patterns.
However, some in the industry have raised concerns about this type of trading and its effect on the markets. Can statistical trading create instability?
To explore the possibility that the emergence of big data and technological growth might be “guiding the financial sector in the wrong direction,” Farboodi and co-author Laura Veldkamp, a professor of finance at Columbia Business School, developed a model to see how data processing can affect information choices, trading strategies, and market outcomes.
The model incorporated both statistical trading and fundamental trading — the classical way of trading, whereby traders analyze a company’s financial statements to forecast profitability. The authors’ research showed that technological growth (defined as the improvement in the ability of a firm or traders to process data using algorithms) caused a shift to statistical trading. But in the long run, the model indicated, both fundamental and statistical trades will keep growing, and price efficiency will keep improving.
'Data is a double-edged sword'
While proponents of statistical trading have often argued that this type of trading provides liquidity and keeps markets running smoothly, especially during times of volatility, others argue that technology harms the markets by creating a shift away from fundamental trading, which has historically played a huge role in the financial sector by helping investors finance or fund firms with the best prospects.
The authors, however, found that neither is quite correct.
“Data is a double-edged sword,” Farboodi said. “More data makes prices more informative, and in that sense financial markets more efficient.” But on the flip side, having more information on prices can make financial markets less liquid. “Simply put, investors who hold an asset today would need to trade it in the future in an environment with even more data.” And having more data in the future means that future prices are even more sensitive to future shocks.
The authors’ findings are in line with evidence from hedge fund data available in the Lipper TASS database, which contains assets under management from 1994 to 2015 and showed that the preference for statistical trading and fundamental trading began to even out as time went on.
“In the very long run, we expect that both types of trades — fundamental and statistical — will keep growing,” Farboodi said.
In the future, the authors are planning to conduct additional research on data production in the real economy and hope to do a follow-up empirical analysis of their theoretical model.
“While growth and the incorporation of data in economics and finance has changed many aspects of the economy,” a lot more work is required to better understand the role of data and how it should be regulated, Farboodi said.