performance analytics- package

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performance analytics- package

sheenmaria
In performance analytics  - performance summary  session , i cant run the code of -
charts.PerformanceSummary(datafrom_table, rf = 0, main = NULL, method = "ModifiedVaR", width = 0,event.labels = NULL, ylog = FALSE, wealth.index = FALSE, gap = 12)

it just return blank chart.

 datafrom_table - having a csv file.
and the rest of the things are get from the site  https://www.rmetrics.org/files/Meielisalp2007/Presentations/Peterson.pdf
but i dont get the result -

could u please help me.
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Re: performance analytics- package

Michael Weylandt
On Thu, Oct 11, 2012 at 11:04 AM, sheenmaria <[hidden email]> wrote:

> In performance analytics  - performance summary  session , i cant run the
> code of -
> charts.PerformanceSummary(datafrom_table, rf = 0, main = NULL, method =
> "ModifiedVaR", width = 0,event.labels = NULL, ylog = FALSE, wealth.index =
> FALSE, gap = 12)
>
> it just return blank chart.
>
>  datafrom_table - having a csv file.
> and the rest of the things are get from the site
> https://www.rmetrics.org/files/Meielisalp2007/Presentations/Peterson.pdf
> but i dont get the result -
>
> could u please help me.
>

charts.PerformanceSummary() is well tested, so you'll need to supply
datafrom_table (or an approximation thereof) using the dput() function
to make this problem reproducible. Note that dput(datafrom_table) will
cause R to print a lot of what might seem to you "gibberish" but it's
important you copy and paste it directly into your reply to allow us
to replicate your problem.

If your dataset is large, use dput(head(datafrom_table, 30)) instead.

Finally, I note you're posting from Nabble. Please include context in
your reply -- I don't believe Nabble does this automatically, so
you'll need to manually include it. Most of the regular respondents on
this list don't use Nabble -- it is a _mailing list_ after all -- so
we don't get the forum view you do, only emails of the individual
posts. Combine that with the high volume of posts, and it's quite
difficult to trace a discussion if we all don't make sure to include
context.

Cheers,
Michael

>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/performance-analytics-package-tp4645834.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: performance analytics- package

sheenmaria

Thanks for your reply .
 
And i have a doubt 
      why cant get the result of chart.performanceSummary() with more than 40 row values in their with the input data??
 







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Re: performance analytics- package

Michael Weylandt
Hi sheenmaria,

Please reread my first post and try to do well.... any of what I asked of you.

Cheers,
Michael

On Fri, Oct 12, 2012 at 6:13 AM, sheenmaria <[hidden email]> wrote:

> Thanks for your reply .
>
> And i have a doubt
>       why cant get the result of chart.performanceSummary() with more than
> 40 row values in their with the input data??
>
>
>
>
>
>  View this message in context: http://r.789695.n4.nabble.com/performance-
> analytics-package-tp4645834.html
>
>
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/performance-analytics-package-tp4645834p4645965.html
> Sent from the R help mailing list archive at Nabble.com.
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: performance analytics- package

sheenmaria
This post has NOT been accepted by the mailing list yet.

hi Michael,
am sorry for the incomplete reply .


csv file data havinmg like this , 

>getSymbols("IBM")
>weekly_data = to.weekly(week_name)
>dataframe=data.frame(weekly_data)
>outputfile_name="F:\\R-programs\\Outputfile.csv"
>write.table(dataframe, file =outputfile_name,sep = ",",col.names =TRUE,row.names = T)

> datafrom_table <- read.csv(file=outputfile_name,head=TRUE,sep=",")
> d12=dput(datafrom_table)

structure(list(week_name.Open = c(97.18, 99.08, 99.4, 96.91, 
98.57, 100, 98.6, 98.66, 96, 92.4, 93.86, 94, 94.71, 95.45, 96.4, 
96.3, 97.23, 102.06, 102.42, 105.4, 106.95, 105.57, 106.55, 103.11, 
104.93, 105.1, 105.5, 108.55, 109.66, 115.32, 114.72, 113.02, 
112.83, 108.9, 112.9, 116.34, 116.35, 115, 116.02, 119.31, 117.85, 
118.02, 113.78, 114.5, 113.49, 102.73, 102.59, 102.7, 105.41, 
109.34, 105.08, 110.9, 108.99, 100.05, 102.03, 98.55, 105.5, 
107.06, 105.16, 106.94, 109.52, 113.4, 115.8, 116.6, 119.1, 115.2, 
115.72, 117.1, 123.87, 122.04, 121.5, 125.12, 126.05, 124.01, 
127.47, 124.88, 127.1, 123.08, 117.5, 120.55, 121, 127.5, 126.54, 
128.2, 126.01, 123.63, 122.58, 122.87, 117.78, 113.73, 116.21, 
115.83, 101.5, 96.42, 92.22, 81.4, 94.76, 83.25, 79.13, 81.37, 
77.8, 83.82, 83.11, 82.35, 81.83, 87.11, 85.5, 84.76, 91.77, 
91.07, 95.58, 91.73, 84.63, 90.16, 85.11, 91.11, 97.69, 94.96, 
100.17, 99.08, 98.41, 99.36, 106, 102.98, 104.33, 101.32, 107.51, 
108.15, 108.47, 104.75, 105.69, 101.34, 103.42, 115.87, 116.63, 
119.17, 118.03, 116.81, 119.25, 117.67, 117.94, 118.78, 122.09, 
119.36, 120.39, 126.22, 123.36, 120.18, 119.53, 125.3, 127.43, 
127.9, 127.29, 126.97, 129.46, 129.3, 132.28, 131.68, 129.03, 
131.63, 125.92, 124.79, 122.65, 124.91, 126.48, 128.7, 126.27, 
128, 127.94, 128.9, 128.68, 128.26, 129.2, 129.9, 128.89, 125.21, 
131.26, 121.47, 124.69, 124.26, 128.93, 130.37, 127.35, 123.58, 
128.97, 122.97, 128.78, 130.03, 131.18, 128.83, 125.21, 123.31, 
126.99, 128.43, 131.45, 134.67, 136.18, 138.4, 137.3, 139.29, 
143.85, 146.7, 142.93, 144.24, 142.24, 146.02, 144.26, 144.99, 
145.31, 147.56, 148.2, 149.82, 159.21, 162.11, 164.82, 162.89, 
163.57, 163.15, 159.7, 157.35, 158.56, 161.34, 163.81, 163.36, 
165.71, 167.99, 172, 169.25, 167.85, 168.5, 168.44, 165.11, 163.87, 
165.2, 168.33, 173.52, 174.93, 178.74, 182.94, 179.95, 167.46, 
172.19, 160.65, 172.06, 163.06, 163.64, 173.57, 176.82, 171.54, 
184.59, 178, 181.66, 181.55, 187.48, 187.49, 182.22, 182.02, 
190.65, 193.46, 185.5, 184.97, 186.73, 183.23, 180.36, 188.63, 
193.09, 192.45, 191.76, 193.73, 197.75, 199.14, 201.72, 204.74, 
208.46, 209.31, 204.94, 204.57, 199.06, 207.18, 202.44, 199.44, 
198.04, 195.22, 187.92, 192.14, 198.83, 193.54, 195.46, 190.3, 
185.73, 190.92, 196.5, 199.43, 198.88, 200.99, 195.56, 196.61, 
200.55, 206.88, 205.6, 210.96), week_name.High = c(99.5, 100.33, 
100.9, 98.66, 100.44, 100.4, 99.52, 99.5, 96.01, 94.85, 94.47, 
95.81, 95.5, 96.94, 96.8, 97.66, 103, 103.17, 106.25, 108.05, 
107.25, 107.67, 106.55, 105.65, 107.02, 106.92, 109.66, 110.04, 
116.48, 118.82, 114.72, 114.6, 113.15, 113.85, 117.35, 118.89, 
117.78, 118.1, 119.5, 119.6, 121.46, 119.94, 115.01, 116.25, 
113.95, 106.42, 105.15, 109.19, 110.26, 110.4, 112, 112.19, 108.99, 
105.59, 106.72, 107.79, 109.4, 108.05, 108.93, 110.32, 116.63, 
116.41, 118, 119.79, 119.1, 118.37, 119.22, 125, 124.9, 124.43, 
125.99, 128.83, 126.4, 129.99, 129.04, 127.14, 127.1, 125.83, 
122.64, 124.5, 130, 130.93, 129.5, 129.97, 128.25, 125.35, 125.45, 
124, 119.95, 124, 121.99, 116.96, 102.62, 99, 92.46, 94.67, 94.76, 
85.4, 82.09, 82.4, 85.88, 85.43, 87.27, 82.81, 87.67, 90.41, 
86.59, 92.67, 94.94, 97.1, 96.82, 92.49, 93.28, 91.24, 93, 98.71, 
99.86, 102.66, 102.45, 102.04, 103.86, 106.75, 106.82, 104.71, 
106.12, 108.67, 108.8, 110.64, 109.14, 106.79, 106.27, 103.65, 
116.88, 118.15, 119.96, 119.91, 119.96, 120.88, 120.23, 118.93, 
119.25, 122.88, 122.74, 120.18, 127.1, 128.61, 124.11, 123.25, 
126, 128.24, 128.94, 128.32, 128.9, 129.98, 129.86, 132.31, 132.97, 
131.85, 132.89, 134.25, 127.75, 126.07, 124.2, 128.06, 128.83, 
129.09, 128.37, 128.93, 130.73, 129.8, 129.3, 132.28, 131.04, 
132, 128.93, 133.1, 131.99, 126.39, 128.22, 129.97, 131.94, 131.47, 
128.4, 128.83, 131.6, 128.8, 131.2, 132.34, 132.49, 130.2, 126.02, 
127.6, 130, 132.09, 135, 136.28, 139.94, 143.03, 141.4, 144.26, 
146.93, 147.53, 145.43, 146.44, 145.87, 146.3, 146.01, 146.4, 
148.2, 148.86, 150, 159.79, 164.35, 164.99, 166.25, 164.84, 164.26, 
164.31, 167.72, 159.64, 162.74, 164.73, 164.75, 166.34, 168.77, 
173.54, 173.48, 172.77, 171.41, 168.67, 169.89, 165.96, 165.61, 
168.24, 174.65, 177.77, 176.46, 185.63, 184.05, 182.29, 174, 
172.99, 172.72, 173.72, 169.58, 173.87, 177.67, 180.91, 186.63, 
190.53, 183.39, 188.07, 187.78, 189.84, 189.97, 182.98, 193.61, 
194.9, 194.3, 187.33, 186.48, 188.71, 183.72, 190.52, 192.79, 
194.81, 194.46, 193.86, 199.23, 201.19, 201.57, 207.52, 207.92, 
209.69, 210.69, 205.97, 207.64, 208.17, 208.93, 203.25, 201.47, 
198.26, 198.08, 196.7, 199.64, 199.99, 197.2, 196.85, 191.14, 
196.85, 197.84, 199.94, 200.88, 202, 201, 196.11, 201.82, 207.99, 
207.94, 211.75, 211.79), week_name.Low = c(96.26, 97.93, 94.55, 
96.2, 97.96, 97.81, 97.8, 96.46, 88.77, 92.26, 92.1, 93.55, 93.57, 
95.33, 94.53, 93.91, 97.23, 101.35, 102.21, 104.53, 103.57, 105.21, 
101.56, 102.1, 104.44, 104.1, 105.24, 108.1, 109.45, 113.52, 
110.02, 109.7, 103.7, 108.08, 111.63, 115.32, 114.3, 114.83, 
115.79, 115, 116.42, 110.96, 111.68, 112.83, 99.27, 101.34, 101.38, 
101.5, 104.72, 104, 104.13, 107.26, 99.03, 97.04, 100.05, 98.5, 
103.7, 100.6, 104.7, 104.53, 109.05, 111.8, 112.69, 113.81, 113.34, 
113.86, 115.28, 115.54, 121.64, 120.5, 120.78, 125.03, 123.02, 
124, 124.06, 122.86, 122.36, 118.15, 116.6, 120.4, 119.9, 126.13, 
126.25, 125.75, 123.68, 121.55, 121.5, 113.17, 115, 110.61, 109.95, 
96.6, 83.51, 84.35, 78.82, 79.52, 82.74, 75.4, 69.5, 76.79, 75.31, 
78.06, 80.32, 79.68, 81.52, 84.25, 82.11, 81.76, 89.69, 90.16, 
92.2, 84.19, 82.85, 83.02, 83.64, 89.41, 91.8, 94.85, 98.52, 
96.44, 98.2, 99.25, 99.83, 100.57, 101.74, 101.02, 105.11, 107.05, 
104.23, 103.51, 100.47, 99.5, 102.52, 115.06, 116.05, 116.7, 
116.21, 116.12, 116.92, 115.15, 116.16, 118.16, 118.94, 117.26, 
120.22, 121.25, 119.55, 119.15, 119.53, 125.17, 126.46, 124.26, 
126, 126.11, 127, 129.19, 130.68, 128.67, 129, 125.37, 121.9, 
121.74, 121.61, 124.11, 125.57, 125.47, 125.2, 126.57, 127.64, 
127.55, 127.12, 127.84, 127.77, 128.71, 116, 125.15, 121.4, 121.47, 
124.13, 122.82, 128.34, 127.12, 120.61, 122.17, 127.85, 122.93, 
127.04, 128.76, 126.96, 126.44, 122.42, 122.28, 125.39, 128.43, 
130.78, 133.67, 136.12, 138.27, 136.7, 138.53, 142.63, 143.27, 
141.18, 141.5, 141.28, 143.52, 144.15, 144.33, 145.06, 146.64, 
146.75, 149.38, 158.67, 162, 162.85, 162.52, 159.03, 158.85, 
159.21, 151.71, 157.52, 161.15, 163.11, 162.3, 162.19, 167.4, 
167.5, 167.82, 166.53, 165.9, 164.13, 162.73, 161.52, 163.8, 
168.01, 173.52, 173.58, 178.65, 178.5, 166, 161.85, 157.13, 159.53, 
166, 158.76, 161.54, 165.76, 173.04, 168.88, 184.11, 176.17, 
179.03, 180.74, 181.16, 180, 177.06, 180.84, 190.32, 181.91, 
179.04, 183.34, 180.27, 177.35, 179.32, 188.22, 191, 191.28, 
190.83, 192.46, 196.45, 196.81, 201.61, 203.7, 206.02, 203.37, 
202.17, 196.79, 198.87, 202.9, 198.56, 194.63, 193.2, 187, 187.56, 
192.14, 191.68, 188.9, 188.05, 181.85, 183.2, 188.56, 193.02, 
197.24, 197.72, 194.2, 193.18, 193.25, 200.51, 204.9, 203.9, 
208.5), week_name.Close = c(98.9, 99.34, 97.11, 98.54, 100.38, 
98.58, 98.99, 96.91, 91.81, 94.11, 93.99, 95, 95.21, 96.62, 96.18, 
95.21, 102.21, 103.16, 105.57, 107.04, 105.18, 106.23, 103.22, 
105.33, 105.1, 105.01, 108.97, 109.66, 116.38, 114.52, 113.89, 
112.71, 109.22, 113.44, 116.69, 115.8, 114.52, 116.25, 119.03, 
117.77, 118.03, 113.37, 114.8, 113.4, 101.45, 102.22, 101.97, 
105.83, 109.39, 104.53, 111.65, 108.1, 100.05, 102.93, 103.4, 
104.98, 107.93, 105.14, 106.16, 110.08, 114.23, 114.01, 115.55, 
119.06, 115.14, 116.31, 117.28, 124.35, 121.69, 122.03, 125.24, 
126.49, 124.2, 127.36, 125.86, 126.71, 123.46, 118.53, 121.5, 
121.54, 128.66, 126.25, 127.56, 126.6, 124.59, 122.86, 121.73, 
117.29, 115.19, 116.21, 114.46, 100.62, 92.21, 92.51, 79.66, 
92.68, 83.87, 77.48, 79.89, 76.9, 84.86, 82.77, 81.99, 81.25, 
86.82, 85.71, 84.92, 91.6, 90.93, 96.82, 93.84, 84.37, 89.05, 
83.48, 91.22, 98.71, 94.52, 101.56, 99.95, 100.43, 99.95, 106.19, 
102.9, 104.58, 101.89, 108.37, 107.49, 107.62, 104.52, 105.83, 
101.65, 103.62, 116.44, 117.63, 119.92, 118.7, 116.86, 119.32, 
118.05, 117.46, 118.88, 121.57, 119.33, 119.75, 127.04, 123.06, 
120.11, 120.56, 126, 128.21, 128.2, 126.35, 127.04, 129.93, 128.65, 
132.31, 132.45, 129.48, 131.78, 126.12, 124.67, 121.88, 124, 
126.85, 128.57, 126.41, 127.83, 127.98, 128.59, 129.35, 128.36, 
132.23, 130.73, 129.6, 126.27, 130.44, 124.45, 125.26, 124.13, 
128.5, 130.65, 128.98, 121.86, 128.67, 129.79, 128.41, 130.76, 
132, 127.77, 126.47, 123.4, 127.58, 129.61, 131.79, 134.65, 135.25, 
139.66, 142.83, 139.84, 143.32, 146.46, 143.64, 145.39, 142.89, 
144.99, 144.28, 144.51, 145.34, 147.48, 147.64, 150, 159.63, 
162, 164.82, 163.22, 164.84, 161.88, 159.93, 161.39, 157.68, 
161.37, 164.25, 163.95, 165.94, 167.67, 172.15, 169.1, 168.86, 
168.26, 167.5, 164.75, 163.17, 165.02, 167.62, 174.54, 174.99, 
175.28, 183.7, 180.75, 166.22, 172.99, 158.98, 172.62, 166.98, 
162.42, 173.13, 174.51, 173.29, 186.62, 186.59, 182.25, 184.63, 
187.32, 187.35, 181.48, 182.21, 190.84, 192.18, 182.89, 184.75, 
183.88, 181.59, 179.16, 189.98, 192.5, 192.82, 192.62, 193.42, 
197.53, 200.66, 201, 205.72, 207.77, 209.47, 204.94, 202.72, 
198.62, 207.08, 203.75, 199.44, 197.76, 194.3, 188.54, 192.51, 
198.29, 192.86, 195.83, 189.67, 184.79, 190.83, 196.68, 198.76, 
199.01, 200.5, 195.69, 194.85, 200.95, 207.15, 205.29, 210.47, 
210.59), week_name.Volume = c(37282600L, 34490200L, 72103000L, 
35304600L, 35062300L, 31814600L, 21716900L, 26604600L, 56820200L, 
38721500L, 35459800L, 29067900L, 33197100L, 18164700L, 29511500L, 
52169000L, 61078300L, 33877500L, 35091600L, 36793800L, 22759500L, 
27778100L, 66518900L, 32973100L, 37168200L, 27784000L, 25912300L, 
37629500L, 54802800L, 71895500L, 58311600L, 40516500L, 59093200L, 
35039700L, 27696100L, 35034600L, 31115400L, 38788700L, 34072400L, 
31575400L, 36526700L, 55268400L, 30288900L, 32096800L, 69116600L, 
46051300L, 25659000L, 47148000L, 28195400L, 39414600L, 38693000L, 
19929800L, 40717400L, 57960500L, 60116900L, 65627200L, 37134500L, 
40754300L, 27834600L, 39450600L, 52544400L, 42918100L, 48127600L, 
39096800L, 42806000L, 38850300L, 40554100L, 66402400L, 30926100L, 
36860400L, 41280900L, 38566900L, 25084400L, 40678500L, 33274500L, 
31999800L, 34940000L, 44494400L, 33408900L, 46532400L, 59004900L, 
44267500L, 28597400L, 35909400L, 31203800L, 34314800L, 24666200L, 
52464400L, 46239300L, 65242800L, 35473300L, 64743800L, 92429100L, 
67694100L, 59658900L, 57124300L, 49014100L, 58824600L, 78119400L, 
34933600L, 52366600L, 47455700L, 48363200L, 17953500L, 28316000L, 
40849400L, 40107300L, 71150300L, 50904900L, 51898900L, 40967100L, 
55929100L, 79527800L, 72403700L, 60473500L, 63944400L, 59507500L, 
62768300L, 31864500L, 46439300L, 55556000L, 46096800L, 42630800L, 
41405700L, 27170000L, 35055100L, 34231100L, 41116800L, 41658500L, 
28258100L, 26599100L, 37179800L, 59981900L, 36906700L, 29124700L, 
25766900L, 26769400L, 28636000L, 25199700L, 19870500L, 26587300L, 
40616200L, 29966100L, 34804800L, 39882700L, 55762400L, 35316400L, 
39296300L, 31506100L, 31122900L, 22663700L, 18406100L, 28149400L, 
30299600L, 34023700L, 19728600L, 18429900L, 28214900L, 30143100L, 
54549400L, 44290800L, 33539400L, 24370300L, 28241800L, 24394500L, 
30775100L, 32034400L, 33833600L, 30444800L, 17430600L, 24267600L, 
42690100L, 40276900L, 35084700L, 46575300L, 52467100L, 50683900L, 
33725800L, 38106600L, 36247600L, 35063700L, 35207000L, 33590800L, 
26983200L, 34873200L, 42114800L, 30349700L, 26447800L, 25598600L, 
24864600L, 28421300L, 21493500L, 21957500L, 31840900L, 27366900L, 
28739400L, 25971400L, 37617800L, 36301100L, 33387900L, 25886500L, 
24184000L, 24110800L, 16566000L, 26904000L, 22440100L, 27448800L, 
11905100L, 16973400L, 22515800L, 16245100L, 43051900L, 32415000L, 
23102000L, 25299000L, 14460200L, 26206300L, 22076300L, 30084300L, 
43281500L, 23560600L, 18318600L, 18516600L, 24189700L, 27181100L, 
28671300L, 27664200L, 24566100L, 26479700L, 17574600L, 26962300L, 
22120500L, 28242500L, 23468600L, 18954000L, 25544400L, 27951500L, 
33608200L, 27150100L, 51191400L, 48519200L, 47115400L, 31833500L, 
20994900L, 30576100L, 32972600L, 33780600L, 39165300L, 34860000L, 
29226400L, 43896300L, 27538400L, 21739700L, 23410900L, 24628600L, 
15736500L, 27018800L, 22239600L, 31429900L, 22126900L, 12119700L, 
24554100L, 21432000L, 37772600L, 21429500L, 21984400L, 16963100L, 
14691000L, 21713700L, 22510200L, 18005300L, 26489600L, 16787200L, 
15977000L, 15631400L, 18022300L, 30358900L, 19202500L, 15299800L, 
16875200L, 23183500L, 14138300L, 26339400L, 16651400L, 20490000L, 
23027000L, 18252500L, 13081600L, 22155100L, 32267700L, 17678100L, 
14494800L, 12456600L, 12291400L, 14303100L, 10614800L, 19380300L, 
18406400L, 25103400L, 19908200L, 12329200L), week_name.Adjusted = c(89.57, 
89.96, 87.94, 89.24, 90.91, 89.54, 89.92, 88.03, 83.4, 85.48, 
85.38, 86.29, 86.48, 87.76, 87.36, 86.48, 92.84, 93.71, 96.27, 
97.61, 95.91, 96.87, 94.12, 96.05, 95.84, 95.76, 99.37, 100, 
106.12, 104.43, 103.85, 103.14, 99.95, 103.81, 106.78, 105.97, 
104.8, 106.38, 108.93, 107.77, 108.01, 103.75, 105.05, 103.77, 
93.17, 93.87, 93.64, 97.19, 100.46, 96, 102.53, 99.27, 91.88, 
94.53, 94.96, 96.41, 99.12, 96.92, 97.87, 101.48, 105.3, 105.1, 
106.52, 109.76, 106.14, 107.22, 108.12, 114.63, 112.18, 112.5, 
115.93, 117.08, 114.96, 117.89, 116.5, 117.29, 114.28, 109.72, 
112.46, 112.5, 119.09, 116.86, 118.07, 117.64, 115.77, 114.17, 
113.12, 108.99, 107.04, 107.99, 106.36, 93.5, 85.68, 85.96, 74.02, 
86.12, 78.37, 72.4, 74.65, 71.86, 79.3, 77.34, 76.61, 75.92, 
81.13, 80.09, 79.35, 85.59, 84.97, 90.96, 88.16, 79.27, 83.66, 
78.43, 85.7, 92.74, 88.8, 95.42, 93.9, 94.36, 93.9, 99.77, 97.18, 
98.77, 96.23, 102.35, 101.52, 101.64, 98.71, 99.95, 96, 97.86, 
109.97, 111.09, 113.26, 112.63, 110.88, 113.21, 112.01, 111.45, 
112.8, 115.35, 113.22, 113.62, 120.54, 116.76, 113.96, 114.39, 
120.09, 122.2, 122.19, 120.42, 121.08, 123.83, 122.61, 126.1, 
126.24, 123.41, 125.6, 120.2, 118.82, 116.68, 118.71, 121.44, 
123.09, 121.02, 122.38, 122.52, 123.11, 123.83, 122.89, 126.59, 
125.15, 124.07, 121.5, 125.52, 119.75, 120.53, 119.44, 123.65, 
125.72, 124.11, 117.26, 123.81, 124.89, 123.56, 125.82, 127.65, 
123.56, 122.3, 119.33, 123.37, 125.34, 127.44, 130.21, 130.79, 
135.05, 138.12, 135.23, 138.59, 142.26, 139.52, 141.22, 138.79, 
140.83, 140.14, 140.37, 141.17, 143.25, 143.41, 145.7, 155.05, 
157.35, 160.09, 159.17, 160.75, 157.86, 155.96, 157.38, 153.76, 
157.36, 160.17, 159.88, 161.82, 163.51, 167.87, 165.64, 165.4, 
164.82, 164.07, 161.38, 159.83, 161.64, 164.19, 170.97, 171.41, 
171.69, 179.94, 177.05, 163.53, 170.19, 156.4, 169.82, 164.27, 
159.79, 170.32, 171.68, 170.48, 183.6, 183.57, 179.3, 181.64, 
184.28, 185.05, 179.26, 179.98, 188.5, 189.83, 180.65, 182.49, 
181.63, 179.37, 176.96, 187.65, 190.14, 190.46, 191, 191.79, 
195.87, 198.97, 199.31, 203.99, 206.02, 207.71, 203.22, 201.02, 
196.95, 205.34, 202.04, 198.59, 196.92, 193.47, 187.74, 191.69, 
197.45, 192.04, 195, 188.86, 184, 190.02, 195.84, 197.91, 199.01, 
200.5, 195.69, 194.85, 200.95, 207.15, 205.29, 210.47, 210.59
)), .Names = c("week_name.Open", "week_name.High", "week_name.Low", 
"week_name.Close", "week_name.Volume", "week_name.Adjusted"), class = "data.frame", row.names = c("2007-01-08", 
"2007-01-12", "2007-01-22", "2007-01-29", "2007-02-05", "2007-02-12", 
"2007-02-16", "2007-02-26", "2007-03-05", "2007-03-12", "2007-03-19", 
"2007-03-26", "2007-04-02", "2007-04-09", "2007-04-16", "2007-04-23", 
"2007-04-30", "2007-05-07", "2007-05-14", "2007-05-21", "2007-05-25", 
"2007-06-04", "2007-06-11", "2007-06-18", "2007-06-25", "2007-07-02", 
"2007-07-09", "2007-07-16", "2007-07-23", "2007-07-30", "2007-08-06", 
"2007-08-13", "2007-08-20", "2007-08-27", "2007-08-31", "2007-09-10", 
"2007-09-17", "2007-09-24", "2007-10-01", "2007-10-08", "2007-10-15", 
"2007-10-22", "2007-10-29", "2007-11-05", "2007-11-12", "2007-11-19", 
"2007-11-26", "2007-12-03", "2007-12-10", "2007-12-17", "2007-12-24", 
"2007-12-31", "2008-01-07", "2008-01-14", "2008-01-18", "2008-01-28", 
"2008-02-04", "2008-02-11", "2008-02-15", "2008-02-25", "2008-03-03", 
"2008-03-10", "2008-03-17", "2008-03-24", "2008-03-31", "2008-04-07", 
"2008-04-14", "2008-04-21", "2008-04-28", "2008-05-05", "2008-05-12", 
"2008-05-19", "2008-05-23", "2008-06-02", "2008-06-09", "2008-06-16", 
"2008-06-23", "2008-06-30", "2008-07-07", "2008-07-14", "2008-07-21", 
"2008-07-28", "2008-08-04", "2008-08-11", "2008-08-18", "2008-08-25", 
"2008-08-29", "2008-09-08", "2008-09-15", "2008-09-22", "2008-09-29", 
"2008-10-06", "2008-10-13", "2008-10-20", "2008-10-27", "2008-11-03", 
"2008-11-10", "2008-11-17", "2008-11-24", "2008-12-01", "2008-12-08", 
"2008-12-15", "2008-12-22", "2008-12-29", "2009-01-05", "2009-01-12", 
"2009-01-16", "2009-01-26", "2009-02-02", "2009-02-09", "2009-02-13", 
"2009-02-23", "2009-03-02", "2009-03-09", "2009-03-16", "2009-03-23", 
"2009-03-30", "2009-04-06", "2009-04-13", "2009-04-20", "2009-04-27", 
"2009-05-04", "2009-05-11", "2009-05-18", "2009-05-22", "2009-06-01", 
"2009-06-08", "2009-06-15", "2009-06-22", "2009-06-29", "2009-07-06", 
"2009-07-13", "2009-07-20", "2009-07-27", "2009-08-03", "2009-08-10", 
"2009-08-17", "2009-08-24", "2009-08-31", "2009-09-04", "2009-09-14", 
"2009-09-21", "2009-09-28", "2009-10-05", "2009-10-12", "2009-10-19", 
"2009-10-26", "2009-11-02", "2009-11-09", "2009-11-16", "2009-11-23", 
"2009-11-30", "2009-12-07", "2009-12-14", "2009-12-21", "2009-12-28", 
"2010-01-04", "2010-01-11", "2010-01-15", "2010-01-25", "2010-02-01", 
"2010-02-08", "2010-02-12", "2010-02-22", "2010-03-01", "2010-03-08", 
"2010-03-15", "2010-03-22", "2010-03-29", "2010-04-05", "2010-04-12", 
"2010-04-19", "2010-04-26", "2010-05-03", "2010-05-10", "2010-05-17", 
"2010-05-24", "2010-05-28", "2010-06-07", "2010-06-14", "2010-06-21", 
"2010-06-28", "2010-07-02", "2010-07-12", "2010-07-19", "2010-07-26", 
"2010-08-02", "2010-08-09", "2010-08-16", "2010-08-23", "2010-08-30", 
"2010-09-03", "2010-09-13", "2010-09-20", "2010-09-27", "2010-10-04", 
"2010-10-11", "2010-10-18", "2010-10-25", "2010-11-01", "2010-11-08", 
"2010-11-15", "2010-11-22", "2010-11-29", "2010-12-06", "2010-12-13", 
"2010-12-20", "2010-12-27", "2011-01-03", "2011-01-10", "2011-01-14", 
"2011-01-24", "2011-01-31", "2011-02-07", "2011-02-14", "2011-02-18", 
"2011-02-28", "2011-03-07", "2011-03-14", "2011-03-21", "2011-03-28", 
"2011-04-04", "2011-04-11", "2011-04-18", "2011-04-25", "2011-05-02", 
"2011-05-09", "2011-05-16", "2011-05-23", "2011-05-27", "2011-06-06", 
"2011-06-13", "2011-06-20", "2011-06-27", "2011-07-01", "2011-07-11", 
"2011-07-18", "2011-07-25", "2011-08-01", "2011-08-08", "2011-08-15", 
"2011-08-22", "2011-08-29", "2011-09-02", "2011-09-12", "2011-09-19", 
"2011-09-26", "2011-10-03", "2011-10-10", "2011-10-17", "2011-10-24", 
"2011-10-31", "2011-11-07", "2011-11-14", "2011-11-21", "2011-11-28", 
"2011-12-05", "2011-12-12", "2011-12-19", "2011-12-23", "2011-12-30", 
"2012-01-09", "2012-01-13", "2012-01-23", "2012-01-30", "2012-02-06", 
"2012-02-13", "2012-02-17", "2012-02-27", "2012-03-05", "2012-03-12", 
"2012-03-19", "2012-03-26", "2012-04-02", "2012-04-09", "2012-04-16", 
"2012-04-23", "2012-04-30", "2012-05-07", "2012-05-14", "2012-05-21", 
"2012-05-25", "2012-06-04", "2012-06-11", "2012-06-18", "2012-06-25", 
"2012-07-02", "2012-07-09", "2012-07-16", "2012-07-23", "2012-07-30", 
"2012-08-06", "2012-08-13", "2012-08-20", "2012-08-27", "2012-08-31", 
"2012-09-10", "2012-09-17", "2012-09-24", "2012-10-01", "2012-10-05"
))

-------------------------------------------------------------------------------------------------------------------------------------
datafrom_table having these values .

i used to do with 

d=dput(head(datafrom_table, 30))

charts.PerformanceSummary(d, rf = 0, main = NULL, method = "ModifiedVaR", width = 0,event.labels = NULL, ylog = FALSE, wealth.index = FALSE, gap = 12)

it gives the result . but the number of morethan 40 it print a blank chart sheet. 

i hop now u can reply to me ..