The tag has no wiki summary.

learn more… | top users | synonyms

8
votes
2answers
3k views

Why do we use GARCH(1,1) to predict volatility?

What makes GARCH(1,1) so prevalent in modeling especially in academia? What does this model has that is significantly better than the others?
2
votes
0answers
413 views

Markov-Switching E-GARCH with R

I am looking for a R library for modeling a Markov-Switching E-GARCH process. In other questions at StackExchange related to GARCH models, the package rugarch is often mentionned. Do you recommend it ...
2
votes
1answer
543 views

R ARMA-GARCH rugarch package doesn't always converge

I'm trying to compute the standard ARMA(1,1)-GARCH(1,1) as shown in this answer for an entire index,just to store in a database to quickly lookup values for back ...
2
votes
2answers
596 views

Should I use GARCH volatility or standard deviation in cross-sectional regression?

I want to do a cross-sectional study where the historical, medium-long run volatility of some return series (call it $R_t$) is included as a regressor. Which of the following two estimates of ...
4
votes
1answer
2k views

How do I evaluate the suitability of a GARCH model?

Suppose I downloaded the closing price of a company, say Google or whatever, I want to use GARCH model to model and forecast the volatility of the return. To simplify, I only have two questions. ...
7
votes
1answer
1k views

Conditional or unconditional volatility?

I am reading a paper (reference below) that states "The conditional volatility for each underlying security (or for a market index) can be estimated using the standard deviation of the stock’s ...
4
votes
1answer
373 views

Volatility models using Rugarch

I have estimated sGARCH, EGARCH and TGARCH, which some for particular models are significant. For others, the alpha remain insignificant using various innovations such as the skewed variants of the ...
4
votes
0answers
141 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
3
votes
2answers
419 views

Backtesting VaR model violation independence

I am interested in hearing about the practitioner state of the art for testing the time independence of a VaR model (i.e. that VaR violations are independent in time). There are a number of tests in ...
2
votes
1answer
3k views

How do I model GARCH(1,1) volatility for historical indexes in Matlab?

I'm currently working with historical index data from Yahoo Finance and would like to plot the GARCH(1,1) volatility of these indexes. I'm working with the Datafeed and Finance Tollboxes in Matlab ...
9
votes
1answer
252 views

Is a linear combination of GARCH processes also a GARCH process?

If two time series follow a GARCH process, and a third is a linear combination of them, is the third also GARCH process?
3
votes
2answers
2k views

GJR-GARCH Model In R

Any idea how to estimate GJR-GARCH models in R? Is there any particular library like fGarch that supports such models?
5
votes
4answers
1k views

Stock Price Behavior and GARCH

In my (limited) understanding, the behavior of a stock price can be modeled using Geometric Brownian Motion (GBM). According to the Hull book I'm currently reading, the discrete-time version of this ...
3
votes
1answer
239 views

Does the correlation amongst stocks rise when stock values decline?

Is there any research on whether the correlations among stocks rise when stock indices decline? Which model could account and test for that effect ? Maybe GARCH-BEKK, or some models using copulas?
6
votes
2answers
4k views

How GARCH/ARCH models are useful to check the volatility?

Below a R code wrote by the moderator @richardh (whom I want to thank again) about ARCH/GARCH models. ...
2
votes
2answers
2k views

Garch modelling on Stata

I would like to ask "how to do GARCH modelling on stata". Basically I want to estimate stock market volatility using daily data. I have one variable as return series, $r_t=\ln(\frac{P_t}{P_{t-1}})$. ...