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Questions tagged [garch]

A model for time series in which the conditional variance is time-varying and autocorrelated.

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Patton's Symmetric Joe-Clayton copula

I am currently trying to apply Patton's Symmetric Joe-Clayton Copula, described in his "Modelling Asymmetric Exchange Rate Dependence". I am currently looking for the closed-form relation (if there is ...
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1answer
29 views

ARIMA GARCH model

According to what I have found so far, in order to implement ARIMA we need to have a stationary (constant mean and variance) transformed data set. In addition, I have also seen that the square of the ...
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1answer
29 views

Home-brewing GARCH implementation

Motivation I want to wrap up my own GARCH implementation to make sure I have understood the underlying model/assumption. to leverage forecast::auto.arima to ...
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ARIMA-GARCH MODEL STEPS [closed]

Could you tell me which steps (such as first stabilize variance using which method afterwards make mean stationary using which method) I need to take into account to obtain relevant ARIMA-GRACH model ...
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1answer
21 views

Standard BEKK parameters

I am looking at a BEKK Multivariate GARCH model. In a standard GARCH model, we generally expect, $$h_t=\omega+\alpha u_{t-1}^2 +\beta\sigma_{t-1}^2$$ The alpha ($\alpha$) coefficient to be ...
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1answer
17 views

Standardized residuals GARCH models

Lets say I have a GARCH(1,1) model, First, I model the conditional MEAN, $$Y_t=\delta+\beta Y_{t-1}+\varepsilon_t$$ NextI gather the residuals $\varepsilon_t$ and model the conditional variance, ...
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Minimal number of obs for BEKK(1,1) and DCC GARCH

For my thesis I am using a rolling regression to estimate the BEKK(1,1) and DCC GARCH parameters and their corresponding confidence intervals. There is literature on the minimal number of ...
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1answer
19 views

F test (joint significance) for two parameters

I want to test for the joint significance of two parameters (dcca1 and dccb1) estimated from a multivariate DCC GARCH model. does anyone know how to do it using R? any help is greatly appreciated.
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fitting high dim copula to residuals of a garch model very slow in R [closed]

I'm looking for some help on understanding on the fitting procedure of a normal (or any other for that matter) copula in R. My main goal is to either improve computational speed, or revise my strategy....
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35 views

Variance of (ARIMA/GARCH) [closed]

I want to find the analytical expression of the conditional variance of the ARIMA-GARCH model. Variance (Yt)=? where Yt has been modeled by ARIMA/GARCH combined model. It means that the mean and ...
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1answer
78 views

Estimating When A Time Series with Random Spikes Crosses a Threshold for the First Time

tl;dr Is there a way to estimate when a random spike in a time series would cross a threshold for the first time? The following is data of my performance in the game Super Hexagon, whose goal is to ...
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42 views

auto-correlation of squared residuals after fitting GARCH model

Hell, I'm completely new to R and am not experienced in statistics but I got some stock price data and tried to fit an ARIMA+GARCH model. I'm a little confused because as the title suggests, I looked ...
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How to compare and select the better GARCH model?

I am reading this article which is talking about a GARCH trading strategy. I follow the steps and tried different parameters like window size (stock historical data). From the back test, I can see ...
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2answers
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What's the point of (G)ARCH when you can square the residual and use ARMA?

I'm taught that $$ \begin{equation} \begin{aligned} X_t \sim \text{ARCH}(p) & \rightarrow X_t^2 \sim \text{AR}(p) \\ X_t \sim \text{GARCH}(p, q) & \rightarrow X_t^2 \sim \text{ARMA}(\max(p, q)...
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48 views

Volatility forecast with GARCH(1,1)

I am having trouble with this question: $Y_t = \sigma_t \epsilon_t$ $\sigma^2_t = 0.003+0.41Y^2_{t-1}+0.53 \sigma^2_{t-1}$ and I am given that $\sigma^2_T = 0.01$ and $Y_T = 0.2$. I am asked to ...
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6 views

gogarch package

I have read the description to gogarch package, but i don't understand the function of external.regression option in that package.. How it is working ? could you give an example? ...
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1answer
25 views

Probability Integral Transforms (Not getting U(0,1))

I am trying to transform my GARCH standardized residuals to PITs in order to use them in a copula. The following code has been so far applied: ...
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28 views

Portfolio Value at risk (VaR) with DCC Garch model in R

Hello respected members, I need your help to forecast portfolio VaR for 3 assets(returns) with the help of DCC Garch model in R. I have done the following steps as you can see from my codes also, 1) ...
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Need for existence of stochastic processes behind models of conditional variance

Background Michael John McAleer with coauthors has in multiple articles (2013, 2019a, 2019b and other) criticized the BEKK, DCC and VCC sorts of multivariate GARCH models on the grounds that there is ...
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1answer
44 views

ARMA/GARCH estimation with standard errors

I want to estimate the parameters and standard errors of the following ARMA/GARCH model: $$y_t = a + by_{t-6} + cy_{t-8} + d\epsilon_{t-1} + \epsilon_t $$ $$\sigma^2_t = \omega + \alpha \epsilon_{t-1}^...
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1answer
45 views

GARCH(1,1) volatility forecast looks biased, it is consistently higher than Parkinson's HL vol

I am trying to create one-step ahead forecasts for the S&P500 using a GARCH(1,1) model. I am using the rugarch package in R. As you can see, the forecasted points are consistently higher than the ...
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Can I use ARMA instead of GARCH?

I am a beginner to econometrics and STATA, so I would like to apologise if this is a bad question, but have accidentally dwelled down into volatility modeling. I have come to understand that the ...
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Question regarding GARCH modeling using RUGARCH package in R

I have 2 questions regarding ARMA-GARCH modelling using rugarch package In R Question 1 This may be an elementary statistics question . But i couldn't find out a way to do this. I have simulated ...
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1answer
28 views

AR(k)-GARCH(1,1) model. Why am I getting same Log-likelihoods and AICs?

I am trying to for loop an AR(k)-GARCH(1,1) model, however it seems that I am getting same log-likelihoods and AICs. I believe that my code is fine, since I manually checked the iterations. Is there ...
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2answers
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Fitting a GARCH model and forecast using validation set approach In R

I have seperated the data into training and testing data. Then I fitted this simple garch model for training data as follows,(using rugarch package) ...
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1answer
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How can I see if a variable such as a lag in a stata regression for a GARCH/ARCH model is statistically significant?

If I was to look at data such as what I have posted here, how would I interpret it to model arch or garch. Which lags would be statistically significant and how does the datatset show this. Sorry for ...
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24 views

Dynamic Conditional Correlation - insignificant correlation parameters

I am trying to get the variance covariance among 4 sectors using DCC in Stata. mgarch dcc (var1, var2, var3, var4=), arch(1/1) garch(1/1) The arch and garch ...
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35 views

R: H is singular

For my thesis I need to estimate BEKK GARCH models. For this I have tried several packages. I keep getting the same error: "H is singular". I have found that this can be caused by highly correlated ...
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29 views

R BEKK GARCH H is singular

So I havbe used several BEKK GARCH packages, but I keep getting the same error message: "H is singular". I have taken the Log returns, and also tried to use the scaled log returns (x100). Anyone knows ...
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Heteroscedasticity in VAR Residuals and Least Squares

If I have a VAR model, think of the simple case with two variables $y_1$ and $y_2$, Vilasuso (2001): says that if the conditional variances of $y_1$ and $y_2$ are correlated, significant size ...
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1answer
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Is my understanding on how to estimate the parameters in a GARCH model correct?

Assume (for the sake of simplicity) we have observed only $X_1,X_2$ and we want to estimate the parameters of a GARCH(1,1) that tells us the variance of $X_t$ (that is normally distributed) evolves ...
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Forecasting a DCCGARCH model estimated by the ccgarch package

How can one predict a dcc-garch model in R using parameters estimated from dcc.estimation from the package ccgarch? MWExample: ...
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1answer
31 views

Constraints, bounds, and initialization variables in the GARCH / ARMA-GARCH models

I am interested in the correct way to estimate a GARCH/ARMA-GARCH model. I will refer to the coefficients as: ...
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stationary vs. non-stationary GARCH process

I estimated a GARCH(1,1) model and the sum of the ARCH paramter alpha and GARCH paramter beta equals 1.7. This points to an undefined unconditional variance and it follows that the conditional ...
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EViews - How to estimate ACD model?

I was wondering if anyone knows how to estimate an ACD model in EViews. I have an input for the adjusted durations and have been trying to modify the ARCH framework to allow for ACD estimation.
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Instrumental variables and GARCH

Can you use the predicted value from the first stage (as estimated using 2SLS) to replace the endogenous variable in a GARCH model? Or, what would be a different way of using instrumental variables in ...
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1answer
33 views

Mean Equation Specification using rugarch in R

I fitted a GARCH(1,1) to my 4511 return observations using rugarch in R. Question: Which of these two mean equation specifications does ...
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47 views

Estimation-based bootstrap using GARCH(1,1) and Rugarch

I try to replicate the methodology proposed by Freedman and Peters (1984a, 1984b) which was applied in the famous paper by Brock, Lakonishok and LeBaron (1992) to generate many artificial log return ...
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45 views

Adjusted Pearson Goodness-of-Fit Test - Rugarch Package

I fitted a GARCH(1,1), GARCH-M and EGARCH of first order (using maximum likelihood) to my return dataset using both, Gaussian normal and Student-t distribution assumption for the error term. When ...
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1answer
33 views

ARIMA(p,d,q) + GARCH(p,d,q) model

I found an article where they fit an ARIMA(p,d,q) model to a time series and then fit a GARCH(p,d,q) to the residual of the ARIMA (the parameters (p,d,q) are passed as the volatility model lags to ...
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1answer
68 views

Residual Bootstrapp based on GARCH models with student-t distributed innovation

I want to generate 500 simulations of my original return time series. My original return series (n = 4000) exhibits significant serial autocorrelation at lag 1 & 2, is non-normally distributed (...
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76 views

Converting log transformed and differenced time series back into original in R

I have built a Garch model in R based on taking a log transformation and a one order difference on the original time series. I would like to know how develop a forecast based on the Garch model for ...
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2answers
28 views

Can a dummy variable be used to correct ARCH?

Is it possible to use a dummy variable to allow for a structural break, in order to correct Autoregressive Conditional Heteroscedasticity?
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1answer
43 views

Why am I getting an 'explosive' GARCH on this series?

I am fairly new to time series econometrics and I am working with a series I want to model the in-sample second moments. I am not super sure that this is stationary, but I rely on the ADF saying that ...
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1answer
33 views

How can i choose the optimal lag in GARCH-MIDAS?

I have to choose individual GARCH-MIDAS models for some variables. But the BIC value continues to decrease as I increase the lag (its even the case for k=70 and more which is unrealistic) so the BIC, ...
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GARCH, EGARC, GJR-GARCH EViews

I'm using Eviews to model and forecast volatilities for 6 different stock markets( it's for my dissertation). I found serial correlation in almost every log-return and even after running the GARCH ...
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1answer
22 views

How can I write an asymmetric-BEKK(1,1,1) model

To write a BEKK(1,1) model, I would write something like this, $$H_t=C^*C^{*'}+A_{11}\varepsilon_{t-1}\varepsilon_{t-1}'A_{11}'+ B_{11}H_{t-1}B_{11}' $$ How could I extend this to write the BEKK(1,...
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39 views

GARCH model with t-innovations

I am modelling a time series with GARCH model with t-distributed error using RUGARCH package. My model is specified as: ...
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1answer
20 views

Maximum Likelihood estimator for GARCH with jump (papers on this topic)

Does anyone know a reference to a paper that would show an actual calibration of GARCH(1,1) model with jumps to a historical time series?
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Can someone help me understand this plot?

I am struggling to understand the outcome of DCC GARCH correlations in this plot. I don't understand how the y-axis points are the same even though the correlations look like they are moving over time?...