Dear All,
Please, i have been thinking if we can selecting a best VaR output based on the
backtest report in rugarch from a series of garch models of models.
Any ideas please would be welcomed.
Thanks
paps
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Hi R users:
There are some possible candidates of self-fulfilling prophecies in financial
study.
Could some people share some thoughts about the relevant theories, econometric
tests, and R packages for implementation?
Thanks for your attention and sharing.
Wei-han
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I suppose you mean something along the lines of:
the more widespread the use of a certain financial model is, the better it
works ?
I would be interested in some concrete examples of that too and therefore
support your request :) [although this is not really a topic specific to R]
Soren
-
h
This book has some good examples:
An Engine, Not a Camera: How Financial Models Shape Markets
by Donald Mackenzie
-- David
-Original Message-
From: r-sig-finance-boun...@r-project.org
[mailto:r-sig-finance-boun...@r-project.org] On Behalf Of Wei-han Liu
Sent: Wednesday, May 09, 2012 7:02
Is this an R question?
Are you taking about anomalies that disappear after we discover them? If we
discover an anomaly and it disappears, then we have to wonder if we priced
it right before or after. See the size effect.
http://schwert.ssb.rochester.edu/hbfech15.pdf
Richard Herron
On Wed, May
Disappearance of size effect will not be an example of self fulfilling
prophesy (it disappeared rather than become stronger).
In the stock market, possible examples are:
1. Index inclusion effect in returns
2. The tendency of traders to put in trades early in the day or later in
the day but not i
Hello, I would like to run several regressions by stock ticker using panel
data. Here is some code that describes what I would like to do. Does
anyone have any suggestions? Thank you!! Geoff
TICKER <- c(rep('IBM',5), rep('GOOG',5), rep('VZ',5));
YEAR <- c(seq(2000,2004), seq(2000,2004), seq(20
Thank you Alexios for always prompt and patient reply!
Yes, you are right. It does not make sense to look at the simulated cov for
1-ahead. I was trying to do a portfolio allocation exercise.
1) If the mean-variance approach is adopted, basically what I need is the
1-day-ahead return of each ass
1. GHST was added recently to rugarch and I have not updated the rmgarch
package to accomodate this (I guess it is due for an update soon).
2. If you only want mean-covariance, you can recover the conditional
mean forecast directly by using the 'varxforecast' function (if using
VAR) else from th
Hi all,
I have a quick question on the macross demo in quantstrat.
>From previous discussions in the mailing list it would seem that the
>applyRules() had been patched to account for the rules execution order
>(http://r.789695.n4.nabble.com/quantstrat-td3208477.html).
This being said, when I ru
Hi!
I apologize for my english.
I'm working with the YieldCurve package in the estimation of the
Nelson-Siegel parameters. In this model, the arguments are: rate, maturity
and MidTau.
I don´t have problem with the rate and maturity, but i can´t understand the
MidTau, because the argument is: MidT
And there are several articles that cited this book, some with more
examples and tests
http://scholar.google.com/scholar?hl=en&sciodt=0%2C5&q=self-fulfilling+prophecies&btnG=Search&cites=5508630854283908327&scipsc=1&as_sdt=0%2C5&as_ylo=&as_vis=0
Robert
-Mensagem Original-
From: David
I have come up with the following expression to strip a time series tsm of
class timeSeries from holidays contained in timeDate class object
index.holidays. index.holidays covers a wider date range than time series tsm.
tsm[-na.omit(match(as.character(index.holidays),as.character(time(tsm,]
I don't want to argue semantics, but for your examples there is a
real, underlying change.
Inclusion in an index improves liquidity and information production
for the real reasons you discuss (e.g., increased trading by index
funds or an increase in capitalization that added the firm to the
index)
Sometimes, there is and sometimes there is not, which is why I was trying
to make a distinction between real informational reason versus simple index
benchmarking. Netflix was a very well known stock before S&P discovered it.
Some other stocks are not so (Xilinx?). One would expect the index effect
Thank you!
I just found there is a name "stdresid" under slot "mfit", i.e.
fit1@mfit$stdresid. I guess it refers to standardised residuals (it looks
like in the plot), is it true?
--
View this message in context:
http://r.789695.n4.nabble.com/copula-with-rmgarch-tp4616138p4621613.html
Sent fro
Turns out that the following accomplishes the same:
tsm[-which(as.Date(time(tsm)) %in% as.Date(index.holidays)),]
However, I still wonder if there is not a more elegant way to achieve this
while remaining within the timeDate/timeSeries classes.
From: r-s
True.
Details of the calculation are in the copula-postestimation.R.
-Alexios
On 09/05/2012 21:07, Alex Fei wrote:
Thank you!
I just found there is a name "stdresid" under slot "mfit", i.e.
fit1@mfit$stdresid. I guess it refers to standardised residuals (it looks
like in the plot), is it true?
You don't need the call to which() and its results may confuse you if
there are no matches, in which case your code below will return
whatever tsm[integer(0)] returns.
Try this instead:
tsm[!(as.Date(time(tsm)) %in% as.Date(index.holidays)),]
Best,
--
Joshua Ulrich | FOSS Trading: www.fosstradi
There is a timeSeries equal to this, but you an also merge in xts against a
known time series of valid dates (often easier to find) and only return the
columns of interest.
In xts you'd use:
merge(x,known, join="inner",retside=c(TRUE,FALSE))
That will be very fast.
Jeff
Jeffrey Ryan|
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