I have read all your threads; that is how I emailed you and determined that you trade financial instruments for a living--please look at the second email I sent you.
Yes, the stop is arbitrary for a group or a system, but not for an individual based on their bankroll and risk profile.
I ran the numbers and everything is very straightforward. The only thing that you need to worry about, stats-wise, is that your sample is greater than 30 when compiling your data for a selection--this comes from the Central Limit Theorem. The Central Limit Theorem can also be used for a selection based on the last 30 plays: if the 50/50 plays are several standard deviations from the norm, a play in the opposite direction may be wise. Also, as is almost always the case, more data = better results.
I understand what you're saying. I would consider an individual's unit risk management strategy as a different issue than the question of progression. If you consider them as a whole, however, I would agree that it is no longer an arbitrary question. I find that most gamblers bet far too much per event, and I personally have tried to move towards 1% per event.
You're right about CLT, I tried to address this more simply using binomial distribution. If I'm using thousands of events but applying that to only, say 150 or so in a season, there can be a substantial deviation. The only way I know how to counter this is by increasing the number of total bets while maintaining a comparable confidence per event.
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Quote Originally Posted by Sumtingwong:
sdiinc,
I have read all your threads; that is how I emailed you and determined that you trade financial instruments for a living--please look at the second email I sent you.
Yes, the stop is arbitrary for a group or a system, but not for an individual based on their bankroll and risk profile.
I ran the numbers and everything is very straightforward. The only thing that you need to worry about, stats-wise, is that your sample is greater than 30 when compiling your data for a selection--this comes from the Central Limit Theorem. The Central Limit Theorem can also be used for a selection based on the last 30 plays: if the 50/50 plays are several standard deviations from the norm, a play in the opposite direction may be wise. Also, as is almost always the case, more data = better results.
I understand what you're saying. I would consider an individual's unit risk management strategy as a different issue than the question of progression. If you consider them as a whole, however, I would agree that it is no longer an arbitrary question. I find that most gamblers bet far too much per event, and I personally have tried to move towards 1% per event.
You're right about CLT, I tried to address this more simply using binomial distribution. If I'm using thousands of events but applying that to only, say 150 or so in a season, there can be a substantial deviation. The only way I know how to counter this is by increasing the number of total bets while maintaining a comparable confidence per event.
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