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  #41  
Old 08-28-2005, 06:17 PM
Sniper Sniper is offline
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Posts: 704
Default Re: Finally - A Real World Perspective

Actually, 2x equity turnover for a day trader would be considered very low.

Consider that a Day Trader can have positions up to 4x equity at any given moment and turn that over several times a day.

However, he didn't classify himself as a day trader (which it sounds like he is), he stated he was a hedge fund. Turning over 2x equity every day would be a bit unusual for a hedge fund, unless he's day trading around core positions.
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  #42  
Old 08-30-2005, 02:23 AM
bobbyi bobbyi is offline
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Join Date: Nov 2003
Location: Seattle, WA
Posts: 14
Default Re: Major Problem with Bill Chin\'s Article on Variance

[ QUOTE ]
Ever wonder why casinos keep increasing the denomination of your chips if you win?

[/ QUOTE ]
They give you bigger chips to encourage you to big a larger amount so that their EV is higher. That's it. It's not about the "gambler's ruin theorem"; it's just about wanting you to bet a lot.
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  #43  
Old 09-01-2005, 11:49 PM
chris_a chris_a is offline
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Join Date: Dec 2004
Location: Eat fish twice a week!
Posts: 172
Default Re: Major Problem with Bill Chin\'s Article on Variance

[ QUOTE ]
Such as computing the probability that a 2 BB/100 player with SD = 15 BB/100 will experience a loss over a given set of 2000 hands.

[/ QUOTE ]

Just how far from Gaussian do you think a set of 2000 indepedent hands is? The answer might suprise you.
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  #44  
Old 09-13-2005, 01:39 AM
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Default Re: Major Problem with Bill Chin\'s Article on Variance

[ QUOTE ]
[ QUOTE ]
SD assumes the distribution of observations is symmetrical around the mean; i.e., that the normal distribution is the correct statistical model to use.

[/ QUOTE ]
Whether or not the assumption of normality is justified, calculating the standard deviation requires no knowledge of the shape of the distribution. It would be a valid statistic, whatever the distribution. Or am I crazy?

[/ QUOTE ]

Not crazy. Inferential statistics using the mean and standard deviation assume a normal distribution, but as descriptive statistics the standard deviation and mean require no distributional assumptions.
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