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The following paper may be of interest to some. The author is generous about sharing a recently revised version. <A HREF="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=259648">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=259648</A> [[alternative HTML version deleted]]

...function(x) { fisher.test( matrix(unlist(x), ncol=2), conf.int=F)$p.value }) ans2 <- matrix(unlist(res2),ncol=4) return(ans2) } s2 <- sol2() ### solution 3 using mclapply # proper answer using input transform, output transform, parallelization, no progress update library(multicore) sol3 <- function() { tmp.list <- as.data.frame(rbind(as.numeric(Ax), as.numeric(Ay), as.numeric(Bx), as.numeric(By))) # determine fisher.test p-values as list res3 <- mclapply(tmp.list, function(x) { fisher.test( matrix(unlist(x), ncol=2), conf.int=F)$p.value }, mc.cores=4) a...

...o address this problem and get new alphas and betas... /(FOR INFORMATION: excess return without ammendements for ARCH effects is given as: ?t=Ri,t-alpha(from regression)-beta(from regression)*Rm,t)/ There is a paper which does this in a simple manner (see page 12 and 13 of http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1100573 http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1100573 ). It is described as follows: Ri=alpha(arch)+beta(arch)*Rm,i+et et=thetat*sqrt(h) h=lamda(0)+lamda(1)*e(t-1)^2 ##e are the residuals of the ols regression Thus my question is now: How can I regress this?...

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...tutorial on backtesting with the package is available on SSRN [2]. Comments/corrections/remarks/suggestions are very welcome; please send them to the maintainer (me) directly. Kind regards Enrico [1] https://enricoschumann.net/R/packages/PMwR/manual/PMwR.html [2] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3374195 -- Enrico Schumann Lucerne, Switzerland https://enricoschumann.net _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages

...tutorial on backtesting with the package is available on SSRN [2]. Comments/corrections/remarks/suggestions are very welcome; please send them to the maintainer (me) directly. Kind regards Enrico [1] https://enricoschumann.net/R/packages/PMwR/manual/PMwR.html [2] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3374195 -- Enrico Schumann Lucerne, Switzerland https://enricoschumann.net _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages

...s regression of the company desn) / And now I am stuck. For further analysis I want to estimate new alphas and betas which do incorporate this ARCH effect (thus including all the a's in some way). There is a paper which does this in a simple manner (see page 12 and 13 of http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1100573). It is described as follows: /Ri=alpha(arch)+beta(arch)*Rm,i+et ## equation one et=ut*sqrt(h) h=lamda(0)+lamda(1)*e(t-1)^2+lamda(2)*e(t-2)^2 ##e are the residuals of the ols regression / I don't know how I should include these a's in my linear regressio...

Dear R help. Hello. I want to fit the model of "FIGARCH" on TimeSeries data. So I need to use the code of "garchOxFit". I don't know how to estimate FIGARCH model. Please let me know which package I need and what is procedure of estimating FIGARCH by R. I think I need this code! &gt; garchOxFit(formula.mean = arma(0, 0), formula.var = garch(1,1), series =

Dear R Helpers, Is there any literaure available (including R code) on Fast Fourier Transform being used in CreditRisk+? I need to learn how to apply the Fast Fourier Transform. I agree I am too vaue in my question and sincerely apologize for the same, but I am not able to understand as to where do I start for this particular assignment. I tried to search google for CRAN and Fast Fourier

...equential or even detrimental patented techniques which could have _easily_ been avoided, as essential elements. ?? and this is the outcome when all of the parties are playing by the rules. For an in-depth analysis of the mess that patents are making of standardization, see: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1134000 It doesn't have to be this way. Most media coding patents are exceptionally narrow, as it's much cheaper and easier to obtain a very narrow patent. The fact that a patent can be trivially avoided? often by something as simple as changing the order of a proce...

Hi, The standards for audio and video to be used by the Wikimedia projects (like Wikipedia) are Ogg Vorbis and Ogg Theora. The use of Ogg Vorbis files is growing fast. For now the use of video is still very limited. The problem is that an audio and an video file looks the same because of the same file extension. This is very annoying because you do not know what for file it is when you look at