[R-SIG-Finance] rugarch teste
Rafael Bressan
rfbressan at gmail.com
Wed Nov 22 17:07:50 CET 2017
Did the obvious and it worked. Remove and reinstall the package (rugarch
only).
Although, no clue why it was not converging before .
2017-11-21 17:34 GMT-02:00 Rafael Bressan <rfbressan at gmail.com>:
> I'm having a problem of convergence with rugarch, trying to fit an
> eGARCH(2,1).
> I've tried other models, not having out.sample option on, different time
> frames, and other time series too. Everything fails to converge ON UBUNTU
> 17.04.
>
> I stress ubuntu 17.04 because the same code, with the same time series,
> works perfectly in the same machine with windows 10 and another one running
> Ubuntu 16.04LTS 32-bit.
>
> R version is 3.4.2 (.1 for windows)
> rugarch version 1.3-8
> Everything running on RStudio Version 1.1.383
>
> I'd like it running in my laptop with 17.04, since it's my "to go"
> equipment, and I really prefer to use R in linux rather than in windows.
>
> Could someone, please, help me to discover and fix this problem?
>
> Below is the simple R code and the 3 sessionInfo(). My csv is taken from
> Yahoo! Finance and can be any index, it's not working with BVSP, GSPC,
> IPSA, etc.
>
> library(rugarch)
> library(PerformanceAnalytics)
> library(xts)
>
> tb <- read.csv("./Documentos/UDESC/mefca/artigo-IPSA.csv",
> stringsAsFactors = FALSE)
> prices <- as.xts(read.zoo(tb, format = "%Y-%m-%d", FUN = as.Date))
> losses <- -100*na.omit(Return.calculate(prices$Adj.Close, method = "log"))
>
> ruspec <- ugarchspec(mean.model = list(armaOrder = c(1,0)),
> variance.model = list(model = "eGARCH", garchOrder =
> c(2,1)),
> distribution.model = "sstd")
>
> fit <- ugarchfit(ruspec, losses, solver = "hybrid")
>
> Warning message:
> In .egarchfit(spec = spec, data = data, out.sample = out.sample, :
> ugarchfit-->warning: solver failer to converge.
>
> R version 3.4.2 (2017-09-28)
> Platform: x86_64-pc-linux-gnu (64-bit)
> Running under: Ubuntu 17.04
>
> Matrix products: default
> BLAS: /usr/lib/libblas/libblas.so.3.7.0
> LAPACK: /usr/lib/lapack/liblapack.so.3.7.0
>
> locale:
> [1] LC_CTYPE=pt_BR.UTF-8 LC_NUMERIC=C
> LC_TIME=pt_BR.UTF-8 LC_COLLATE=pt_BR.UTF-8
> [5] LC_MONETARY=pt_BR.UTF-8 LC_MESSAGES=pt_BR.UTF-8
> LC_PAPER=pt_BR.UTF-8 LC_NAME=C
> [9] LC_ADDRESS=C LC_TELEPHONE=C
> LC_MEASUREMENT=pt_BR.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] parallel stats graphics grDevices utils datasets methods
> base
>
> other attached packages:
> [1] PerformanceAnalytics_1.4.3541 xts_0.10-0
> zoo_1.8-0
> [4] rugarch_1.3-8
>
> loaded via a namespace (and not attached):
> [1] Rcpp_0.12.13 magrittr_1.5
> knitr_1.17
> [4] misc3d_0.8-4 xtable_1.8-2
> lattice_0.20-35
> [7] R6_2.2.2 FNN_1.1
> Rsolnp_1.16
> [10] GeneralizedHyperbolic_0.8-1 SkewHyperbolic_0.3-2
> tools_3.4.2
> [13] spd_2.0-1 grid_3.4.2
> KernSmooth_2.23-15
> [16] htmltools_0.3.6 yaml_2.1.14
> digest_0.6.12
> [19] rgl_0.98.1 numDeriv_2016.8-1
> Matrix_1.2-11
> [22] shiny_1.0.5 nloptr_1.0.4
> DistributionUtils_0.5-1
> [25] ks_1.10.7 htmlwidgets_0.9
> codetools_0.2-15
> [28] mime_0.5 compiler_3.4.2
> multicool_0.1-10
> [31] expm_0.999-2 jsonlite_1.5
> truncnorm_1.0-7
> [34] mvtnorm_1.0-6 httpuv_1.3.5
>
> R version 3.4.1 (2017-06-30)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> Running under: Windows >= 8 x64 (build 9200)
>
> Matrix products: default
>
> locale:
> [1] LC_COLLATE=Portuguese_Brazil.1252 LC_CTYPE=Portuguese_Brazil.1252
> [3] LC_MONETARY=Portuguese_Brazil.1252 LC_NUMERIC=C
> [5] LC_TIME=Portuguese_Brazil.1252
>
> attached base packages:
> [1] parallel stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] PerformanceAnalytics_1.4.3541 xts_0.10-0 zoo_1.8-0
> [4] rugarch_1.3-8
>
> loaded via a namespace (and not attached):
> [1] Rcpp_0.12.13 magrittr_1.5 knitr_1.17
> [4] misc3d_0.8-4 xtable_1.8-2 lattice_0.20-35
> [7] R6_2.2.2 FNN_1.1 Rsolnp_1.16
> [10] GeneralizedHyperbolic_0.8-1 SkewHyperbolic_0.3-2 tools_3.4.1
> [13] spd_2.0-1 grid_3.4.1 KernSmooth_2.23-15
> [16] htmltools_0.3.6 yaml_2.1.14 digest_0.6.12
> [19] rgl_0.98.1 numDeriv_2016.8-1 Matrix_1.2-10
> [22] shiny_1.0.5 nloptr_1.0.4 DistributionUtils_0.5-1
> [25] ks_1.10.7 htmlwidgets_0.8 codetools_0.2-15
> [28] mime_0.5 compiler_3.4.1 multicool_0.1-10
> [31] expm_0.999-2 jsonlite_1.5 truncnorm_1.0-7
> [34] mvtnorm_1.0-6 httpuv_1.3.5
>
>
> R version 3.4.2 (2017-09-28)
> Platform: i686-pc-linux-gnu (32-bit)
> Running under: Ubuntu 16.04.3 LTS
>
> Matrix products: default
> BLAS: /usr/lib/libblas/libblas.so.3.6.0
> LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
>
> locale:
> [1] LC_CTYPE=pt_BR.UTF-8 LC_NUMERIC=C
> LC_TIME=pt_BR.UTF-8
> [4] LC_COLLATE=pt_BR.UTF-8 LC_MONETARY=pt_BR.UTF-8
> LC_MESSAGES=pt_BR.UTF-8
> [7] LC_PAPER=pt_BR.UTF-8 LC_NAME=C
> LC_ADDRESS=C
> [10] LC_TELEPHONE=C LC_MEASUREMENT=pt_BR.UTF-8
> LC_IDENTIFICATION=C
>
> attached base packages:
> [1] parallel stats graphics grDevices utils datasets methods
> base
>
> other attached packages:
> [1] PerformanceAnalytics_1.4.3541 xts_0.10-0
> zoo_1.8-0
> [4] rugarch_1.3-8
>
> loaded via a namespace (and not attached):
> [1] ggplot2_2.2.1 lattice_0.20-35
> compiler_3.4.2
> [4] htmlwidgets_0.9 xtable_1.8-2
> Rcpp_0.12.13
> [7] shiny_1.0.3 plyr_1.8.4
> tools_3.4.2
> [10] DistributionUtils_0.5-1 SkewHyperbolic_0.3-2
> truncnorm_1.0-7
> [13] R6_2.2.2 knitr_1.17
> scales_0.5.0
> [16] spd_2.0-1 multicool_0.1-10
> rgl_0.98.1
> [19] digest_0.6.12 gtable_0.2.0
> mime_0.5
> [22] numDeriv_2016.8-1 KernSmooth_2.23-15
> Matrix_1.2-11
> [25] ks_1.10.7 htmltools_0.3.6
> misc3d_0.8-4
> [28] munsell_0.4.3 grid_3.4.2
> colorspace_1.3-2
> [31] FNN_1.1 httpuv_1.3.5
> rlang_0.1.2
> [34] Rsolnp_1.16 nloptr_1.0.4
> magrittr_1.5
> [37] GeneralizedHyperbolic_0.8-1 lazyeval_0.2.0
> yaml_2.1.14
> [40] mvtnorm_1.0-6 codetools_0.2-15
> jsonlite_1.5
> [43] tibble_1.3.4 expm_0.999-2
>
>
>
> 2017-11-21 16:27 GMT-02:00 Rafael Bressan <rfbressan at gmail.com>:
>
>> library(rugarch)
>> library(PerformanceAnalytics)
>> library(xts)
>>
>> tb <- read.csv("./Documentos/UDESC/mefca/artigo-IPSA.csv",
>> stringsAsFactors = FALSE)
>> prices <- as.xts(read.zoo(tb, format = "%Y-%m-%d", FUN = as.Date))
>> losses <- -100*na.omit(Return.calculate(prices$Adj.Close, method =
>> "log"))
>>
>> ruspec <- ugarchspec(mean.model = list(armaOrder = c(1,0)),
>> variance.model = list(model = "eGARCH", garchOrder =
>> c(2,1)),
>> distribution.model = "sstd")
>>
>> fit <- ugarchfit(ruspec, losses, solver = "hybrid")
>>
>>
>
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