[R] ARCH modelling/MA process

Hi all ARCH modelling I have a problem now on how to proceed with further steps in my analysis. I did a linear OLS regression with my daily data of stock and index returns. There is now the problem of arch in my error terms. Thus I used the following r command: garch(resid_desn, order=c(0,2)) #

[R] Problem with ARCH

Hi I have a problem on how to proceed with further steps in my analysis. I did a linear OLS regression (ri,t=alpha*beta*rm,t+et) with my daily data of stock and index returns. There is now the problem of arch in my error terms. Thus I used the following r command: /garch(resid_desn, order=c(0,2)

[R] looking for an add-in for daily data analysis

Hi all I am looking for an add-in. I am currently working on something and I use daily data of closing stock prices. As not all companies are traded daily (e.g. on monday, then on thursday etc) at the stock exchange, there is satistically a problem. There are some papers which explain the approach

[R] Problem with Autocorrelation and GLS Regression

Hi, I have a problem with a regression I try to run. I did an estimation of the market model with daily data. You can see to output below: /> summary(regression_resn) Time series regression with "ts" data: Start = -150, End = -26 Call: dynlm(formula = ror_resn ~ ror_spi_resn) Residuals: M

Re: [R] Problem with Autocorrelation and GLS Regression

For the analysis I follow the approach of Keown & Pinkerton ( http://e-m-h.org/KePi81.pdf http://e-m-h.org/KePi81.pdf ). They do also use daily data to compute alphas and betas of the market model. These estimated coefficients are then used to estimate abnormal returns for a given period. market

[R] Arima model, breusch godfrey/breusch pagan test

Hi all I did an estimation of a simple regression model (ror_xxx~ror_spi_xxx) and assessed the quality of this estimation. After having detected that there are indications of autocorrelatio and an AR(1) process, I used an arima model: absi.arima=arima(ror_absi, order=c(1,0,0), xreg=ror_spi_absi)