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I'm not surprised Niederhoffer feels this way. Michael Covel hangs him out to dry quite a bit in his book titled "Trend Following", and from the account of Niederhoffer's story in this book he seems like the kind of smart person who couldn't appreciate what trend following is about. These people seem to believe that their smarts are the secret to their success in the market and the market itself is responsible for their failures. Self-attribution bias I believe it's called.I don't pretend to be experienced or extensively knowledgeable on this topic. I started writing code for a system about 2-3 months ago. But I had a hunch that this needed to be the case and I agree with his statement. For this reason before working on any system I created a random entry/exit system to which I added various componentents such as equal-weighting of positions and price filters. I then made 2500 random runs over 10 years of data (imperfect data by Howard and Blackstars definition and survivorship biased too, but it's a benchmark so I believe relative comparisons between different systems can still be made...if it can't I'm not sure I want to know ) and observed the changes in distribution of CAGR and Max DD. These become part of my benchmark to which a system with superior edge should have superior Monte Carlo distributions.ASX.G
I'm not surprised Niederhoffer feels this way. Michael Covel hangs him out to dry quite a bit in his book titled "Trend Following", and from the account of Niederhoffer's story in this book he seems like the kind of smart person who couldn't appreciate what trend following is about. These people seem to believe that their smarts are the secret to their success in the market and the market itself is responsible for their failures. Self-attribution bias I believe it's called.
I don't pretend to be experienced or extensively knowledgeable on this topic. I started writing code for a system about 2-3 months ago. But I had a hunch that this needed to be the case and I agree with his statement. For this reason before working on any system I created a random entry/exit system to which I added various componentents such as equal-weighting of positions and price filters. I then made 2500 random runs over 10 years of data (imperfect data by Howard and Blackstars definition and survivorship biased too, but it's a benchmark so I believe relative comparisons between different systems can still be made...if it can't I'm not sure I want to know ) and observed the changes in distribution of CAGR and Max DD. These become part of my benchmark to which a system with superior edge should have superior Monte Carlo distributions.
ASX.G
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