Locating peaks in zoo objects in one go

require(xts)
vix <- as.xts(VIX)
vix[vix > 70]

index(vix[vix > 70])

Dear R users,

The following code will download the VIX volatility index to a variable
called "VIX" (what else)...

library(tseries)
VIX <- get.hist.quote("^VIX", start = "1990-01-01", quote = "Close")

Is there a way I could determine (in one go or iteratively), where the
peaks (local maxima) lie in the sequence
(say by using an arbitrary rule i.e., locate prices which are greater
than x% the sample's average or a certain value) ???

I would like to be able to capture the prices as well as their
time-stamps....

Thanks in advance &
Best regards,

Costas Vorlow



P Think before you print.

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Dear R users,

The following code will download the VIX volatility index to a variable
called "VIX" (what else)...

library(tseries)
VIX <- get.hist.quote("^VIX", start = "1990-01-01", quote = "Close")

Is there a way I could determine (in one go or iteratively), where the
peaks (local maxima) lie in the sequence
(say by using an arbitrary rule i.e., locate prices which are greater
than x% the sample's average or a certain value) ???

I would like to be able to capture the prices as well as their
time-stamps....

Thanks in advance &
Best regards,

Costas Vorlow



P Think before you print.

Disclaimer:
This e-mail is confidential. If you are not the intended recipient, you should not copy it, re-transmit it, use it or disclose its contents, but should return it to the sender immediately and delete the copy from your system.
EFG Eurobank Ergasias S.A. is not responsible for, nor endorses, any opinion, recommendation, conclusion, solicitation, offer or agreement or any information contained in this communication.
EFG Eurobank Ergasias S.A. cannot accept any responsibility for the accuracy or completeness of this message as it has been transmitted over a public network. If you suspect that the message may have been intercepted or amended, please call the sender.


? ? ? ?[[alternative HTML version deleted]]

Dear R users,

The following code will download the VIX volatility index to a variable
called "VIX" (what else)...

library(tseries)
VIX <- get.hist.quote("^VIX", start = "1990-01-01", quote = "Close")

Is there a way I could determine (in one go or iteratively), where the
peaks (local maxima) lie in the sequence
(say by using an arbitrary rule i.e., locate prices which are greater
than x% the sample's average or a certain value) ???

I would like to be able to capture the prices as well as their
time-stamps....

Thanks in advance &
Best regards,

Costas Vorlow



P Think before you print.

Disclaimer:
This e-mail is confidential. If you are not the intended recipient, you should not copy it, re-transmit it, use it or disclose its contents, but should return it to the sender immediately and delete the copy from your system.
EFG Eurobank Ergasias S.A. is not responsible for, nor endorses, any opinion, recommendation, conclusion, solicitation, offer or agreement or any information contained in this communication.
EFG Eurobank Ergasias S.A. cannot accept any responsibility for the accuracy or completeness of this message as it has been transmitted over a public network. If you suspect that the message may have been intercepted or amended, please call the sender.


? ? ? ?[[alternative HTML version deleted]]

Dear R users,

The following code will download the VIX volatility index to a 
variable called "VIX" (what else)...

library(tseries)
VIX <- get.hist.quote("^VIX", start = "1990-01-01", quote = "Close")

Is there a way I could determine (in one go or iteratively), where the 
peaks (local maxima) lie in the sequence (say by using an arbitrary 
rule i.e., locate prices which are greater than x% the sample's 
average or a certain value) ???

I would like to be able to capture the prices as well as their 
time-stamps....

Thanks in advance &
Best regards,

Costas Vorlow



P Think before you print.

Disclaimer:
This e-mail is confidential. If you are not the intended recipient, you should not copy it, re-transmit it, use it or disclose its contents, but should return it to the sender immediately and delete the copy from your system.
EFG Eurobank Ergasias S.A. is not responsible for, nor endorses, any opinion, recommendation, conclusion, solicitation, offer or agreement or any information contained in this communication.
EFG Eurobank Ergasias S.A. cannot accept any responsibility for the accuracy or completeness of this message as it has been transmitted over a public network. If you suspect that the message may have been intercepted or amended, please call the sender.


? ? ? ?[[alternative HTML version deleted]]

Dear Gabor,

Thanks for your prompt answer. One question though:

It seems to be missing the VIX peaks at the beginning and the very end of the history of the sequence.

What am I missing? I am trying to understand it from the help pages but...

Costas Vorlow


-----Original Message-----
From: Gabor Grothendieck [mailto:ggrothendieck at gmail.com]
Sent: Thursday, March 05, 2009 6:39 PM
To: Vorlow Constantinos; costas at vorlow.org
Cc: r-sig-finance at stat.math.ethz.ch
Subject: Re: [R-SIG-Finance] Locating peaks in zoo objects in one go

This locates peaks over plus or minus (k+1)/2 days (k odd):

# VIX from post
library(zoo)
k <- 201
idx <- rollapply(VIX, k, function(x) which.max(x) == (k+1)/2)
plot(VIX)
abline(v = time(idx)[idx])


On Thu, Mar 5, 2009 at 10:00 AM, Vorlow Constantinos <CVorlow at eurobank.gr> wrote:

Dear R users,

The following code will download the VIX volatility index to a
variable called "VIX" (what else)...

library(tseries)
VIX <- get.hist.quote("^VIX", start = "1990-01-01", quote = "Close")

Is there a way I could determine (in one go or iteratively), where the
peaks (local maxima) lie in the sequence (say by using an arbitrary
rule i.e., locate prices which are greater than x% the sample's
average or a certain value) ???

I would like to be able to capture the prices as well as their
time-stamps....

Thanks in advance &
Best regards,

Costas Vorlow



P Think before you print.

Disclaimer:
This e-mail is confidential. If you are not the intended recipient, you should not copy it, re-transmit it, use it or disclose its contents, but should return it to the sender immediately and delete the copy from your system.
EFG Eurobank Ergasias S.A. is not responsible for, nor endorses, any opinion, recommendation, conclusion, solicitation, offer or agreement or any information contained in this communication.
EFG Eurobank Ergasias S.A. cannot accept any responsibility for the accuracy or completeness of this message as it has been transmitted over a public network. If you suspect that the message may have been intercepted or amended, please call the sender.


? ? ? ?[[alternative HTML version deleted]]

Is there a way I could determine (in one go or iteratively), where the
peaks (local maxima) lie in the sequence 
(say by using an arbitrary rule i.e., locate prices which are greater
than x% the sample's average or a certain value) ???