Hello; I've been following the "dough" trading platform for a bit and they
are big on short options strategies such as strangles, straddles, verticals, etc. One nice thing their platform does is compute the probability of reaching 50% of target (max) profit, and they recommend taking profits at that point in time. I was wondering if there is a way to do this in R... I know there is (monte carlo, for example) but if there is a package or tool that has done some of the heavy lifting already, it would save me re-inventing the wheel. The motivation, of course, is that I'd like to pass many tickers into a script that helps me find the best trading opportunities. Their thinking is described here: https://www.dough.com/blog/probability-of-50-profit-on-dough Can anyone point me in the right direction to get started? --------------------------------------- David L. Van Brunt, Ph.D. mailto:[hidden email] [[alternative HTML version deleted]] _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
1) Why not ask the Dough Boys to do your heavy lifting? They developed this
strategy using 10 years of historical data. Ask them to run it over these 10 years for the Mar/Jun/Sep/Dec major SPY expirations for options with about 45 days until expiration. 2) Ask the Dough Boys why they only used a theoretical Monte Carlo simulation for 2005 to generate their results. I'm retired, but I think it is 2016. 3) What about the L in P/L? I see nothing about the losses that might have occurred. How about the losses for the Sep 2001 strangles and straddles? And likewise for the Sep 2008 strangles and straddles. I don't know of any successful option traders that only sell options short. But 91% probability of making a profit in all these straddles and strangles at 50% of profit and 81% if held until expiration. I'm incredulous. All the successful option traders I know trade spreads in which at least one leg is long and has a reasonable delta or gamma relative to the short option(s). They put time into models and analysis that identify option spreads that have one leg that is cheap or correctly priced and the short leg that is expensive. What are three things that are short-lived? 1) Dogs that chase cars. 2) Basketball teams that can't free-throw. 3) Traders that sell naked options. Best, Frank Chicago, IL -----Original Message----- From: R-SIG-Finance [mailto:[hidden email]] On Behalf Of David L. Van Brunt, Ph.D. Sent: Thursday, December 22, 2016 9:57 PM To: [hidden email] Subject: [R-SIG-Finance] probability of 50% profit on short options trade Hello; I've been following the "dough" trading platform for a bit and they are big on short options strategies such as strangles, straddles, verticals, etc. One nice thing their platform does is compute the probability of reaching 50% of target (max) profit, and they recommend taking profits at that point in time. I was wondering if there is a way to do this in R... I know there is (monte carlo, for example) but if there is a package or tool that has done some of the heavy lifting already, it would save me re-inventing the wheel. The motivation, of course, is that I'd like to pass many tickers into a script that helps me find the best trading opportunities. Their thinking is described here: https://www.dough.com/blog/probability-of-50-profit-on-dough Can anyone point me in the right direction to get started? --------------------------------------- David L. Van Brunt, Ph.D. mailto:[hidden email] [[alternative HTML version deleted]] _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
Frank and Chris-
Yes, the Dough folks are advocating a strategy that I'd like to study a bit more since the things you both mentioned all jump right out. I think Chris took my "get started" comment to mean get started in trading this (or trading at all), rather than get started on the evaluation of their claims-- I was not clear. My "finding the best trading opportunities" is so I can study their strategy from there. I've been investing and trading profitably for 20 years (longs, shorts, equities, indices, options, actual real estate...), but I enjoy reading and studying what others are up to in my spare time (as FT job responsibilities allow). So when I see extraordinary claims I like to try replicating and studying them for myself - it's fun, and I learn a lot in the process. So many gurus cherry pick from history (Frank caught that right off), since the most popular thing to sell for a profit is "advice". :-) To dissect Dough's broader claims, I'd have to reproduce what they've done with their "probability of 50% profit" but they're not really giving enough information to replicate it that I've been able to find. Hence the post. It sounds like thus far the short answer from this R forum is simply "we don't know how to reproduce that." On Fri, Dec 23, 2016 at 11:34 AM, Frank <[hidden email]> wrote: > 1) Why not ask the Dough Boys to do your heavy lifting? They developed this > strategy using 10 years of historical data. Ask them to run it over these > 10 > years for the Mar/Jun/Sep/Dec major SPY expirations for options with about > 45 days until expiration. > > 2) Ask the Dough Boys why they only used a theoretical Monte Carlo > simulation for 2005 to generate their results. I'm retired, but I think it > is 2016. > > 3) What about the L in P/L? I see nothing about the losses that might have > occurred. How about the losses for the Sep 2001 strangles and straddles? > And > likewise for the Sep 2008 strangles and straddles. > > I don't know of any successful option traders that only sell options short. > But 91% probability of making a profit in all these straddles and strangles > at 50% of profit and 81% if held until expiration. I'm incredulous. > > All the successful option traders I know trade spreads in which at least > one > leg is long and has a reasonable delta or gamma relative to the short > option(s). They put time into models and analysis that identify option > spreads that have one leg that is cheap or correctly priced and the short > leg that is expensive. > > What are three things that are short-lived? > > 1) Dogs that chase cars. > 2) Basketball teams that can't free-throw. > 3) Traders that sell naked options. > > Best, > > Frank > Chicago, IL > > -----Original Message----- > From: R-SIG-Finance [mailto:[hidden email]] On Behalf > Of David L. Van Brunt, Ph.D. > Sent: Thursday, December 22, 2016 9:57 PM > To: [hidden email] > Subject: [R-SIG-Finance] probability of 50% profit on short options trade > > Hello; I've been following the "dough" trading platform for a bit and they > are big on short options strategies such as strangles, straddles, > verticals, etc. One nice thing their platform does is compute the > probability of reaching 50% of target (max) profit, and they recommend > taking profits at that point in time. > > I was wondering if there is a way to do this in R... I know there is (monte > carlo, for example) but if there is a package or tool that has done some of > the heavy lifting already, it would save me re-inventing the wheel. The > motivation, of course, is that I'd like to pass many tickers into a script > that helps me find the best trading opportunities. Their thinking is > described here: https://www.dough.com/blog/pro > bability-of-50-profit-on-dough > > Can anyone point me in the right direction to get started? > > --------------------------------------- > David L. Van Brunt, Ph.D. > mailto:[hidden email] > > [[alternative HTML version deleted]] > > _______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-finance > -- Subscriber-posting only. If you want to post, subscribe first. > -- Also note that this is not the r-help list where general R questions > should go. > > [[alternative HTML version deleted]] _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
David,
I downloaded the SPY options for November 2016. There are 102160 rows of data. Looking only at the 1/20/2017 expiration options, there are 398 out-of-the-money calls with both volume and open interest and 802 out-of-the-money puts. Figuring out which strangles and straddles would meet their 1 sigma strategy definition would be a daunting task. This is not really a problem with R but a problem of what is the definition of a 1 sigma strategy or straddle. There is also the possibility of data mining the best strategies. Once the strategies that meet the 1 sigma definitions are identified, it is a piece of cake to identify how many strategies make it to 50% profit and how many are profitable at expiration. I'd do the calculations in C and also keep track of the maximum loss. In just writing this email, I've figure out another problem. I could identity strangles that are about 1 sigma away from the current SPY price, but, what do they mean by a 1 sigma straddle? Best, Frank Chicago, IL ________________________________________ From: David L. Van Brunt, Ph.D. [mailto:[hidden email]] Sent: Sunday, December 25, 2016 1:46 PM To: Frank; Chris Waggoner Cc: [hidden email] Subject: Re: [R-SIG-Finance] probability of 50% profit on short options trade Frank and Chris- Yes, the Dough folks are advocating a strategy that I'd like to study a bit more since the things you both mentioned all jump right out. I think Chris took my "get started" comment to mean get started in trading this (or trading at all), rather than get started on the evaluation of their claims-- I was not clear. My "finding the best trading opportunities" is so I can study their strategy from there. I've been investing and trading profitably for 20 years (longs, shorts, equities, indices, options, actual real estate...), but I enjoy reading and studying what others are up to in my spare time (as FT job responsibilities allow). So when I see extraordinary claims I like to try replicating and studying them for myself - it's fun, and I learn a lot in the process. So many gurus cherry pick from history (Frank caught that right off), since the most popular thing to sell for a profit is "advice". :-) To dissect Dough's broader claims, I'd have to reproduce what they've done with their "probability of 50% profit" but they're not really giving enough information to replicate it that I've been able to find. Hence the post. It sounds like thus far the short answer from this R forum is simply "we don't know how to reproduce that." On Fri, Dec 23, 2016 at 11:34 AM, Frank <[hidden email]> wrote: 1) Why not ask the Dough Boys to do your heavy lifting? They developed this strategy using 10 years of historical data. Ask them to run it over these 10 years for the Mar/Jun/Sep/Dec major SPY expirations for options with about 45 days until expiration. 2) Ask the Dough Boys why they only used a theoretical Monte Carlo simulation for 2005 to generate their results. I'm retired, but I think it is 2016. 3) What about the L in P/L? I see nothing about the losses that might have occurred. How about the losses for the Sep 2001 strangles and straddles? And likewise for the Sep 2008 strangles and straddles. I don't know of any successful option traders that only sell options short. But 91% probability of making a profit in all these straddles and strangles at 50% of profit and 81% if held until expiration. I'm incredulous. All the successful option traders I know trade spreads in which at least one leg is long and has a reasonable delta or gamma relative to the short option(s). They put time into models and analysis that identify option spreads that have one leg that is cheap or correctly priced and the short leg that is expensive. What are three things that are short-lived? 1) Dogs that chase cars. 2) Basketball teams that can't free-throw. 3) Traders that sell naked options. Best, Frank Chicago, IL -----Original Message----- From: R-SIG-Finance [mailto:[hidden email]] On Behalf Of David L. Van Brunt, Ph.D. Sent: Thursday, December 22, 2016 9:57 PM To: [hidden email] Subject: [R-SIG-Finance] probability of 50% profit on short options trade Hello; I've been following the "dough" trading platform for a bit and they are big on short options strategies such as strangles, straddles, verticals, etc. One nice thing their platform does is compute the probability of reaching 50% of target (max) profit, and they recommend taking profits at that point in time. I was wondering if there is a way to do this in R... I know there is (monte carlo, for example) but if there is a package or tool that has done some of the heavy lifting already, it would save me re-inventing the wheel. The motivation, of course, is that I'd like to pass many tickers into a script that helps me find the best trading opportunities. Their thinking is described here: https://www.dough.com/blog/probability-of-50-profit-on-dough Can anyone point me in the right direction to get started? --------------------------------------- David L. Van Brunt, Ph.D. mailto:[hidden email] [[alternative HTML version deleted]] _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
>From watching their videocasts, they call a 1 sigma straddle the first
strikes outside the 68% window (so it's two-tailed) -- though it could be taken to mean, post premium credits, that the breakevens are outside that window. It's all done visually enough in TOS, but of course, Dough/TastyTrade's p50 (as they call it) is not anywhere in ToS. I saw them do a show where they described it as an equation to get past having to do monte carlo every time, but then the tech guys were there and described it exactly as a monte Carlo simulation (10,000 runs even, IIRC). They are also using the Probability ITM from Black-Scholes rather than taking the Delta as an approximation. The other barriers in studying this are simply data: getting current option data isn't too tough, but historical options I'm sure is messy and expensive (and huge). And then here's historical Implied Volatility (not to be confused with historical volatility). It may just be too much of a PITA to even try to pick it apart. --------------------------------------- David L. Van Brunt, Ph.D. mailto:[hidden email] On Sun, Dec 25, 2016 at 2:44 PM, Frank <[hidden email]> wrote: > David, > > I downloaded the SPY options for November 2016. There are 102160 rows of > data. Looking only at the 1/20/2017 expiration options, there are 398 > out-of-the-money calls with both volume and open interest and 802 > out-of-the-money puts. Figuring out which strangles and straddles would > meet > their 1 sigma strategy definition would be a daunting task. This is not > really a problem with R but a problem of what is the definition of a 1 > sigma > strategy or straddle. There is also the possibility of data mining the best > strategies. > > Once the strategies that meet the 1 sigma definitions are identified, it is > a piece of cake to identify how many strategies make it to 50% profit and > how many are profitable at expiration. I'd do the calculations in C and > also > keep track of the maximum loss. > > In just writing this email, I've figure out another problem. I could > identity strangles that are about 1 sigma away from the current SPY price, > but, what do they mean by a 1 sigma straddle? > > Best, > > Frank > Chicago, IL > > > > ________________________________________ > From: David L. Van Brunt, Ph.D. [mailto:[hidden email]] > Sent: Sunday, December 25, 2016 1:46 PM > To: Frank; Chris Waggoner > Cc: [hidden email] > Subject: Re: [R-SIG-Finance] probability of 50% profit on short options > trade > > Frank and Chris- > > Yes, the Dough folks are advocating a strategy that I'd like to study a bit > more since the things you both mentioned all jump right out. I think Chris > took my "get started" comment to mean get started in trading this (or > trading at all), rather than get started on the evaluation of their > claims-- > I was not clear. My "finding the best trading opportunities" is so I can > study their strategy from there. I've been investing and trading profitably > for 20 years (longs, shorts, equities, indices, options, actual real > estate...), but I enjoy reading and studying what others are up to in my > spare time (as FT job responsibilities allow). So when I see extraordinary > claims I like to try replicating and studying them for myself - it's fun, > and I learn a lot in the process. So many gurus cherry pick from history > (Frank caught that right off), since the most popular thing to sell for a > profit is "advice". :-) > > To dissect Dough's broader claims, I'd have to reproduce what they've done > with their "probability of 50% profit" but they're not really giving enough > information to replicate it that I've been able to find. > > Hence the post. > > It sounds like thus far the short answer from this R forum is simply "we > don't know how to reproduce that." > > > On Fri, Dec 23, 2016 at 11:34 AM, Frank <[hidden email]> wrote: > 1) Why not ask the Dough Boys to do your heavy lifting? They developed this > strategy using 10 years of historical data. Ask them to run it over these > 10 > years for the Mar/Jun/Sep/Dec major SPY expirations for options with about > 45 days until expiration. > > 2) Ask the Dough Boys why they only used a theoretical Monte Carlo > simulation for 2005 to generate their results. I'm retired, but I think it > is 2016. > > 3) What about the L in P/L? I see nothing about the losses that might have > occurred. How about the losses for the Sep 2001 strangles and straddles? > And > likewise for the Sep 2008 strangles and straddles. > > I don't know of any successful option traders that only sell options short. > But 91% probability of making a profit in all these straddles and strangles > at 50% of profit and 81% if held until expiration. I'm incredulous. > > All the successful option traders I know trade spreads in which at least > one > leg is long and has a reasonable delta or gamma relative to the short > option(s). They put time into models and analysis that identify option > spreads that have one leg that is cheap or correctly priced and the short > leg that is expensive. > > What are three things that are short-lived? > > 1) Dogs that chase cars. > 2) Basketball teams that can't free-throw. > 3) Traders that sell naked options. > > Best, > > Frank > Chicago, IL > > -----Original Message----- > From: R-SIG-Finance [mailto:[hidden email]] On Behalf > Of David L. Van Brunt, Ph.D. > Sent: Thursday, December 22, 2016 9:57 PM > To: [hidden email] > Subject: [R-SIG-Finance] probability of 50% profit on short options trade > > Hello; I've been following the "dough" trading platform for a bit and they > are big on short options strategies such as strangles, straddles, > verticals, etc. One nice thing their platform does is compute the > probability of reaching 50% of target (max) profit, and they recommend > taking profits at that point in time. > > I was wondering if there is a way to do this in R... I know there is (monte > carlo, for example) but if there is a package or tool that has done some of > the heavy lifting already, it would save me re-inventing the wheel. The > motivation, of course, is that I'd like to pass many tickers into a script > that helps me find the best trading opportunities. Their thinking is > described here: https://www.dough.com/blog/probability-of-50-profit-on- > dough > > Can anyone point me in the right direction to get started? > > --------------------------------------- > David L. Van Brunt, Ph.D. > mailto:[hidden email] > [[alternative HTML version deleted]] > > _______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-finance > -- Subscriber-posting only. If you want to post, subscribe first. > -- Also note that this is not the r-help list where general R questions > should go. > > > [[alternative HTML version deleted]] _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
I'm already concerned if they call two separate strikes a straddle when it is a strangle. Also be careful of stale data, since the closing price of an option used to be (not any more, though) the last traded price which may or may not correspond to the last traded price of the underlying. Not a problem for futures options and indices probably but single-stock options used to be rife with this problem. Not sure if they are any more; it has been a long time since I was an options trader and I was primarily fixed-income derivs.
On Dec 25, 2016, at 4:53 PM, David L. Van Brunt, Ph.D. <[hidden email]> wrote: >> From watching their videocasts, they call a 1 sigma straddle the first > strikes outside the 68% window (so it's two-tailed) -- though it could be > taken to mean, post premium credits, that the breakevens are outside that > window. It's all done visually enough in TOS, but of course, > Dough/TastyTrade's p50 (as they call it) is not anywhere in ToS. I saw them > do a show where they described it as an equation to get past having to do > monte carlo every time, but then the tech guys were there and described it > exactly as a monte Carlo simulation (10,000 runs even, IIRC). > > They are also using the Probability ITM from Black-Scholes rather than > taking the Delta as an approximation. > > The other barriers in studying this are simply data: getting current option > data isn't too tough, but historical options I'm sure is messy and > expensive (and huge). And then here's historical Implied Volatility (not to > be confused with historical volatility). > > It may just be too much of a PITA to even try to pick it apart. > > > > --------------------------------------- > David L. Van Brunt, Ph.D. > mailto:[hidden email] > >> On Sun, Dec 25, 2016 at 2:44 PM, Frank <[hidden email]> wrote: >> >> David, >> >> I downloaded the SPY options for November 2016. There are 102160 rows of >> data. Looking only at the 1/20/2017 expiration options, there are 398 >> out-of-the-money calls with both volume and open interest and 802 >> out-of-the-money puts. Figuring out which strangles and straddles would >> meet >> their 1 sigma strategy definition would be a daunting task. This is not >> really a problem with R but a problem of what is the definition of a 1 >> sigma >> strategy or straddle. There is also the possibility of data mining the best >> strategies. >> >> Once the strategies that meet the 1 sigma definitions are identified, it is >> a piece of cake to identify how many strategies make it to 50% profit and >> how many are profitable at expiration. I'd do the calculations in C and >> also >> keep track of the maximum loss. >> >> In just writing this email, I've figure out another problem. I could >> identity strangles that are about 1 sigma away from the current SPY price, >> but, what do they mean by a 1 sigma straddle? >> >> Best, >> >> Frank >> Chicago, IL >> >> >> >> ________________________________________ >> From: David L. Van Brunt, Ph.D. [mailto:[hidden email]] >> Sent: Sunday, December 25, 2016 1:46 PM >> To: Frank; Chris Waggoner >> Cc: [hidden email] >> Subject: Re: [R-SIG-Finance] probability of 50% profit on short options >> trade >> >> Frank and Chris- >> >> Yes, the Dough folks are advocating a strategy that I'd like to study a bit >> more since the things you both mentioned all jump right out. I think Chris >> took my "get started" comment to mean get started in trading this (or >> trading at all), rather than get started on the evaluation of their >> claims-- >> I was not clear. My "finding the best trading opportunities" is so I can >> study their strategy from there. I've been investing and trading profitably >> for 20 years (longs, shorts, equities, indices, options, actual real >> estate...), but I enjoy reading and studying what others are up to in my >> spare time (as FT job responsibilities allow). So when I see extraordinary >> claims I like to try replicating and studying them for myself - it's fun, >> and I learn a lot in the process. So many gurus cherry pick from history >> (Frank caught that right off), since the most popular thing to sell for a >> profit is "advice". :-) >> >> To dissect Dough's broader claims, I'd have to reproduce what they've done >> with their "probability of 50% profit" but they're not really giving enough >> information to replicate it that I've been able to find. >> >> Hence the post. >> >> It sounds like thus far the short answer from this R forum is simply "we >> don't know how to reproduce that." >> >> >> On Fri, Dec 23, 2016 at 11:34 AM, Frank <[hidden email]> wrote: >> 1) Why not ask the Dough Boys to do your heavy lifting? They developed this >> strategy using 10 years of historical data. Ask them to run it over these >> 10 >> years for the Mar/Jun/Sep/Dec major SPY expirations for options with about >> 45 days until expiration. >> >> 2) Ask the Dough Boys why they only used a theoretical Monte Carlo >> simulation for 2005 to generate their results. I'm retired, but I think it >> is 2016. >> >> 3) What about the L in P/L? I see nothing about the losses that might have >> occurred. How about the losses for the Sep 2001 strangles and straddles? >> And >> likewise for the Sep 2008 strangles and straddles. >> >> I don't know of any successful option traders that only sell options short. >> But 91% probability of making a profit in all these straddles and strangles >> at 50% of profit and 81% if held until expiration. I'm incredulous. >> >> All the successful option traders I know trade spreads in which at least >> one >> leg is long and has a reasonable delta or gamma relative to the short >> option(s). They put time into models and analysis that identify option >> spreads that have one leg that is cheap or correctly priced and the short >> leg that is expensive. >> >> What are three things that are short-lived? >> >> 1) Dogs that chase cars. >> 2) Basketball teams that can't free-throw. >> 3) Traders that sell naked options. >> >> Best, >> >> Frank >> Chicago, IL >> >> -----Original Message----- >> From: R-SIG-Finance [mailto:[hidden email]] On Behalf >> Of David L. Van Brunt, Ph.D. >> Sent: Thursday, December 22, 2016 9:57 PM >> To: [hidden email] >> Subject: [R-SIG-Finance] probability of 50% profit on short options trade >> >> Hello; I've been following the "dough" trading platform for a bit and they >> are big on short options strategies such as strangles, straddles, >> verticals, etc. One nice thing their platform does is compute the >> probability of reaching 50% of target (max) profit, and they recommend >> taking profits at that point in time. >> >> I was wondering if there is a way to do this in R... I know there is (monte >> carlo, for example) but if there is a package or tool that has done some of >> the heavy lifting already, it would save me re-inventing the wheel. The >> motivation, of course, is that I'd like to pass many tickers into a script >> that helps me find the best trading opportunities. Their thinking is >> described here: https://www.dough.com/blog/probability-of-50-profit-on- >> dough >> >> Can anyone point me in the right direction to get started? >> >> --------------------------------------- >> David L. Van Brunt, Ph.D. >> mailto:[hidden email] >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> [hidden email] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-sig-finance >> -- Subscriber-posting only. If you want to post, subscribe first. >> -- Also note that this is not the r-help list where general R questions >> should go. >> >> >> > > [[alternative HTML version deleted]] > > _______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-finance > -- Subscriber-posting only. If you want to post, subscribe first. > -- Also note that this is not the r-help list where general R questions should go. _______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. |
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