---
title: Human Traders Retain Edge Over Quants and Algos
description: eFinancialCareers reports that low-vol markets favor man over machine.
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 08.30.2017

 By Terry Flanagan

 Electronic Trading

# Human Traders Retain Edge Over Quants and Algos

 08.30.2017 By Terry Flanagan

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Human traders are seemingly an endangered species in today's largely electronic, algorithm-driven market, but humans still have an edge over machines in low-volatility markets, according to an eFinancialCareers report.

eFinancialCareers noted that old-school trading pits have been cleared out as electronic trading platforms powered by various types of artificial intelligence, including machine learning and artificial neural networks are in ascendance.

But many quants and algorithmic trading strategies struggle mightily in the absence of market volatility, which means in the current prolonged period of market calm, human traders have an opportunity to prove their worth.

“Some of these algorithms will focus on market-making, trying to capture the difference between the bid and the offer, which are typically categorized as high-frequency trading,” Daniel Gramza, founder and president of Gramza Capital Management and DMG Advisors, told eFinancialCareers. “Sideways or calm markets can be a challenge for the machine-learning trend-following algorithm – primarily because it needs a number of steps to recognize that it may be in a sideways market and how it will trade that environment.”

Human traders can quickly recognize the potential for a sideways move and more easily adjust their trading strategy.

“The trader can assess what is the typical magnitude of a sideways move, how long it typically last, is there a particular time of day, week or month when sideways moves occur and how does it typically break out of the sideways move,” Gramza told eFC. “Although these parameters are simple to assess for the trader, it can be challenging for the machine-learning algorithms.”

“My experience with trading firms around the world is that the human trader still has an edge over the machine-learning algorithms in the calm sideways market environment.”

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