摘要： Manof 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.”
Manof 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.
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“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.
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“If you're going to train a machine to be good at something, or perhaps better than a human being at something, it better be in an area where you can train a human being to be good at it in the first place. But is it possible for somebody to be a good technical analyst? I don't think it is. So, if it's not possible for a human being to be a good technical analyst, how do you train computers to be technical analysts?
“Your ability to be successful as a quant depends almost exclusively on the quality of your technology, and how much you can spend on developing it. So you'd better be a fully-fledged tech firm if you're going to have any hopes of succeeding as a quant”
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Full Text： cmcmarkets
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