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re: Technical trading

Posted on 6/17/17 at 6:50 am to
Posted by ATLdawg25
Atlanta, GA
Member since Oct 2014
4370 posts
Posted on 6/17/17 at 6:50 am to
If anyone is familiar with Quantopian, this should be relatively simple to model out and backtest.
Posted by Doc Fenton
New York, NY
Member since Feb 2007
52698 posts
Posted on 6/17/17 at 3:53 pm to
Yeah, I'm interested in stuff like Quantopian, and these crowd-sourced algo groups like Quantiacs. I wish I had more time to spend investigating that kind of thing, but unfortunately I do not. However, my general impression is that market dynamics shifts so often that it's difficult to truly verify most of these strategies through backtesting.

Bloomberg had a great article about a month ago on the dangers of p-hacking for investors: " A New Paper Just Took a Huge Shot at Some of the World's Hottest Investments."

quote:

Looking at 447 supposedly repeating price patterns identified in the last few decades, academics from Ohio State and the University of Cincinnati contend that more than half are basically figments of their discoverers’ imagination. The study, “Replicating Anomalies” by Kewei Hou, Chen Xue and Lu Zhang, attributed the findings to a statistical sleight of hand known as p-hacking.


quote:

The authors’ inquiry involved taking market anomalies previously observed by other researchers -- say, that certain cheap stocks tend to move in a predictable direction -- then trying to replicate them in their own data. Often, they found nothing but noise. Of 447 anomalies examined, 286 generated statistically insignificant predictions for stocks in the category, and the record was much worse for certain kinds of trading signals.

Broadly, the authors said that the signals failed because their discovers had considered too broad a universe of stocks when they set out to confirm their findings. Tiny companies make up the majority of stocks, they noted, but represent very little market capitalization -- and yet that’s where a lot of the anomalies work best. They posited various flaws of analysis that led earlier academics to give too much emphasis to these stocks in their research.
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