Outspoken quantitative trader Manoj Narang, founder of MANA Partners, gave an interview this week in which he warned traders that building trading strategies from the bottom-up can result in black box systems that appear to work, but are actually fools gold.

Narang talked about his “top-down” approach to building trading models, which borrows from a more fundamental approach to investing.

Here is an excerpt from an interview with Narang in CMC Markets:

Manoj Narang claims, “A lot of traders use data to build their beliefs. And because there’s so much data out there it virtually guarantees identifying strategies that look to have statistically significant results, but are in fact absolute trash.”

It’s a characteristically bold gambit from Manoj Narang, who first came to prominence during the 2007 financial crisis when his quantitative firm Tradeworx turned to high-frequency trading – and built a platform for others to do it, which resulted in the company becoming responsible for up to 5% of daily volume on the S&P 500.

[…]

Shortly afterwards, he launched MANA Partners, a $1bn fund aiming to do something different: using statistical arbitrage (the go-to method alongside high-frequency trading strategies for most quants) to emulate what traditional hedge fund managers and discretionary investors do. “The approach is very fundamental and very structural. It’s basically reading the news and looking at the same information human beings are looking at. Valuation is key,” says Narang.

The approach is a cure for the “curse of dimensionality,” he adds, explaining that traders are able to build an “infinite” number of strategies which wrongly appear to have statistical significance due to the sheer amount of data. Applying prior beliefs and “known facts” to this data, as a discretionary investor would, is a simple way of solving this.

“I work top-down, using models based on known facts. If, like most [traders], you go bottom-up, it results in building black box systems, when nobody can understand how decisions are arrived at, including the architects of the system themselves,” he says.

For Narang, the edge comes from the ability to achieve scale through computer power and automation. “Quantitative and algorithmic trading is just technology applied to investment management to achieve scale and efficiency. The ability to do that kind of analysis for thousands of securities in real time gives you a tremendous advantage. And that’s the power of quantitative trading: automating things that have previously taken a lot of human labour and time. It’s no different to the role of technology in any other industry.”