Questions tagged [garch]
A model for time series in which the conditional variance is time-varying and autocorrelated.
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Interpreting test results for ARCH effects in ARIMA model
I would like to ask you, how to correctly interpret different results for different number of lags in arch.test (R)? We reject the null hypothesis (homoscedasticity)...
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How to implement Girardi & Ergun's (2013) three-step multivariate GARCH estimation of CoVaR in R?
I'm trying to calculate multivariate GARCH estimation of conditional value-at-risk, by adopting a three-step model from Girardi & Ergun (2013) paper entitled "Systemic risk measurement: ...
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GARCH (sGARCH) with ARFIMA (ARIMA) model in Rugarch equation formula output
Could you please help to write down the exact equation?
It is clear for Garch part but not clear how to add ARFIMA (1,0,1) or here just ARMA(1,1) in model equation specification.
Should we also type ...
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GARCH fit to the residuals of AR/ARMA mean equation previously fitted
Suppose I have an ARMA (p,q) (let it be ARMA (2,2)) fitted to my original returns series and have the residuals of said ARMA model extracted.
Next, it is my understanding that I need to fit a GARCH ...
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gradient of the conditioned log-likelihood from GJR-GARCH model
given the following GJR-GARCH(1,1)
$y_t = \sqrt{h_t} \epsilon_t$ where = $h_t= \alpha_0+(\alpha_1+\bar{\alpha_1}\mathbb{I}(y_{t-1}<0))y_t^2+\beta_1h_t$
and $\alpha_0>0$ $\alpha_1,\beta_1>0$ , ...
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Estimating and fitting a GARCH model
By far I've become really familiar with the concept of GARCH but I'm still confused on how to go on with the implementation especially that I've seen multiple sources using different approaches:
...
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How to compare the performance of a volatility forecast like GARCH (1,1) with exogenous variables (MSE?)
I want to investigate, weather financial news have an influence on the volatility prediction of asset returns (daily data) when including them into the variance model/mean model.
I have fit a GARCH/...
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Unconditional variance of MA(1)-GARCH(1,1) process
Let $y_t = \Delta{p_t}$ denote a time series of asset log-returns, where $p_t$ are logarithmic prices; $y_t$ is generated by the conditionally heteroscedastic MA(1) process
$y_t = \epsilon_t + \theta \...
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Auto_arima and ARCH
I Have an auto_arima model that works in python but I want to optimize it using ARCH. I have run an ARCH model on my Arima residuals but I do not know what to do with my results. How do I incorporate ...
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Full time-series analysis steps
I had a few classes related to time-series econometrics, however most were theory heavy. I would like to practice this, so I will try to analyse few stock prices, however I am not fully sure about the ...
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Testing if volatility increases during ECB-Monetary Press Releases
I'm currently writing a thesis where I am trying to disect the ECB monetary press releases and their impact on the European stock market. I am using an event study methodology. Computing Daily Excess ...
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Can I use VECM, GARCH and HAR-RV for forecasting of carbon price? [closed]
Can I use VECM, GARCH and HAR-RV for forecasting of carbon price?
I'm not sure the assumptions of the models don't contradict each other.
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How can I calculate time-varying Value at Risk (VaR) and Conditional VaR for return series?
I am working on ABT index and I calculated the return series. Also, I intend to fit a GARCH(1,1) model to the return series and then calculate the VaR and CVaR as ...
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GARCH(1,1) variance equation
I need some help understanding how to write a variance equation.
I have the general variance equation written as
$$
\sigma_{t}^2=\alpha_0+\alpha_1u_{t-1}^2+\beta_1\sigma_{t-1}^2.
$$
I am wondering how ...
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Practical guide or book for time series analysis [duplicate]
I am writing a thesis now, and I ran into a problem - I understand the basic concepts of time series econometrics and what models and tests exist, what exactly they check, but I can not find good ...
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Cross-correlation for univariate GARCH models
I have a strange and maybe stupid question about cross-correlation.
Let's imagine having 2 times series, for example, asset A and ...
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How can I determine which algorithm estimates GARCH(1,1) best?
In R, we have many packages to estimate the GARCH model. They choose different algorithms to estimate like quasi-Newton, SQP. Unfortunately, the estimated parameters are totally different from each ...
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Inaccuracies due to initial values in GARCH(1, 1) simulation
I'm experimenting with non-normal innovations standard GARCH(1, 1) model
$$\epsilon_t = \sqrt h_t z_t$$
$$h_t = \omega + \alpha \epsilon_{t-1} + \beta h_{t-1}$$
Where $E[z_t] = 0$, $E[z_t^2] = 1$, but ...
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Error when using eGARCH but not sGARCH in rugarch
I have implemented the basic sGarch model using the code below:
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How can I interpret the below GJR-GARCH model in terms of "leverage effects"?
I'm very new here and am struggling to interpret the model. Please help me in layman's terms.
...
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GARCH model analysis using python
I have an AR(3)-GJR-GARCH(2,2,2) model. How can I test the presence of ‘leverage effects’ (i.e. asymmetric responses of the conditional variance to the positive and negative shocks) with 5% ...
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Interpretation of DCC-GARCH model
For my Master thesis I have to perform the DCC-GARCH model to examine the correlation between real estate house prices and the stock market. I tested the data for normality (both not normal) and ...
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VaR from Bayesian GARCH / Quantile Estimation
I have fitted a Bayesian GARCH(1,1) model with Student $t$ innovations to some time series data, $X_1,...,X_n$ and now want to estimate Value-at-Risk (VaR) (i.e., 5% quantiles) at each times $t=1,,...,...
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GARCH CCC/DCC : empirical correlation coefficient different than the one in input CCC matrix
I implement a GARCH-DCC model in Python, for number of asset = 2. My implementation is the following :
...
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Implementing DCC GARCH Model with External Regressors in R
I am trying to estimate a DCC GARCH model with an external regressor in the DCC equation. However, the external regressor option in the rmgarch package is for the ...
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Implementing GARCH(2,2) QMLE: where does the data (squared returns) come into play?
I am trying to implement a QMLE estimation of GARCH(2,2) model as a side project.
We can represent GARCH(2,2) as follows:
\begin{aligned}
r_{t} &= \mu_{t} + \epsilon_{t}, \\
\mu_{t} &= 0, \\
\...
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rugarch: Forecast result does not show any AR structure
I am currently working with the rugarch package to forecast the EU-ETS price. While I get reasonable results for the in-sample volatility, the forecast of the of the time series does not look correct ...
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Evaluating goodness-of-fit for GARCH models in R with QQ-plots (rugarch package)
I'm currently working with multivariate GARCH representations of time-series for financial data using the rmgarch R package. This package in turn uses the well-...
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Autocorrelation in residuals of mean model to be used in a GARCH model
My question is related to the autocorrelation present in the mean-model (which is an ARMA process), which will be used in a GARCH model. Is it ok to have autocorrelations in the residuals of the mean-...
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Log-likelihood function for GARCHs parameters
I am writing a bachelor thesis on the evaluation of value-at-risk using GARCH models. To estimate the parameters for the GARCH models, I explained that we can do it with maximum likelihood as shown in ...
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Accelerate the fitting of an ECM-GARCH model by computing MLE gradient numerically?
I'm trying to fit an ECM model with variance following a GARCH-DCC model (GARCH with dynamic cross correlation). It has 16 parameters for 2 assets (ECM : 4 gammas, 2 lambda, GARCH: 2 alphas, 2 beta, 2 ...
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Forecasting the conditional variance of AR(p)-GARCH(1,1) model
How can I derive forecasting formula for the conditional variance $h_{t+k}$, $k\geq1$ for AR(p)-GARCH(1,1)?
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Autocorrelation function of AR(1)-GARCH(1,1) [duplicate]
How can I derive the Autocorrelation function of AR(1)-GARCH(1,1) process which is the combination of AR(1) with GARCH(1,1) process?
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Initial guess of a GARCH-DCC model?
I’m trying to fit an ECM-GARCH-DCC model for 2 time series, the whole 3 in the same time using log-likelihood estimation. It has 14 parameters to estimate:
ECM has 2 gammas and 1 lambda per time ...
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External regressor rugarch
Consider a ARMA$(p,q)$ model of $y$ with $m$ external regressors $x_1, ..., x_m$. Do I understand the documentation of the R package rugarch correct, that the considered model is of the form
$$y(t):=\...
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$k$-th order autocorrelation of a squared ARCH(1) process
I want to derive that in ARCH(1) model, $\operatorname{Corr}(y_t^2,y_{t-k}^2)=\alpha^k$. Could you please take a look at to the photo attached and help me on how to proceed:
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Is a generalized linear model (GLM) an appropriate model where ARCH effects are found in the dependent variable?
The dependent and independent variables are all time series variables. The dependent variable is found to have ARCH effects. Is a GLM an appropriate model for modeling the relationship between the ...
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Likelihood function of GARCH with exogeneous variables in the variance model
I can see the R package rugarch allows the estimation of GARCH models with exogenous variables in the specification of the ...
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Test for multivariate stationarity
Given a bivariate time series $(X_{1t}, X_{2t})$ with $X_{it}\sim N(0,1)$, I want to know if there is a way of testing if the bivariate distribution does not change over time. This is, if $F_{12}(x_1,...
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rugarch: finding the optimal ARMA GARCH model
I am new to the rugarch package in R and I would like to know how to find the optimal ARMA-GARCH model using ...
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Estimating Volatility in financial time series
According to Ruey S. Tsay's Analysis of Financial Time Series, the way volatility is estimated is to fit ARMA model to log-return data and then square the residuals from ARMA model. The squared ...
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Question on the 2002 Engle paper regarding GARCH-DCC model
Paper here, please open using Incognito tab: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=236998 press "Download this paper" button
Let me sum up the core of that paper in simple ...
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I'm getting bigger values of AIC and BIC after applying the p and q (obtained from auto.arima() function) to the standard GARCH model
I tried to find p and q by using auto.arima function in RStudio. It gave ARIMA(1,1,0). However, after applying p=1 and q=0 to the GARCH model, ar1 became ...
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How to estimate a ARCH/GARCH model since we don't know last period conditional variance?
I'm wondering how it's possible to forecast a conditional variance using a GARCH model since we don't know last period conditional variance.
If I understand correctly, the conditional variance is the ...
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How to compute loss on GARCH multi-horizon predictions vs realized time series
Suppose I have a daily financial timeseries of zero-mean returns r(t), and I fit a GARCH model.
I'm using the arch_model package which forecasts volatility by ...
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How do I impose restrictions $ 0\leq \alpha \leq \beta <1$?
I want to restrict values s.t. I get $\theta = (\alpha, \beta) =g(\theta_1, \theta_2)$
with the following restrictions.
$
0\leq \alpha \leq \beta <1
$
I know the correct answer should be $\beta = (...
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Autocovariance of ARMA-GARCH vs. that of pure ARMA
Is the autocovariance of an ARMA-GARCH process the same as that of the ARMA part of that process?
If this is too difficult/cumbersome to show, analysis of a special case like MA(1)-GARCH(1,1) or AR(1)-...
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What is the autocovariance of a GARCH process with a constant mean?
What is the autocovariance of a GARCH process with a constant mean?
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Estimate autocovariance of an ARCH(1) process given its parameters
I have estimated an ARCH(1) model using a skew-$t$ distribution. The results summary is:
I am wondering how to get an estimate for the autocovariance given the parameters. Assuming mean zero, I am ...
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GARCH specification when series is autocorrelated
I want to model volatility of a stock index with 1460 observations. The specification of the GARCH model is planned to be EGARCH-X where X is the external regressor, with no mean specification. ...
