Questions tagged [garch]
A model for time series in which the conditional variance is time-varying and autocorrelated.
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Mean-level forecast from rugarch does not match manual calculation
I am looking into the rugarch package and am trying to understand how the one-step-ahead forecast is calculated.
Specifically, I am fitting an AR(2)-GARCH(1,1) ...
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Why is non-normality of time series not a problem for ARIMA and GARCH?
My time series is very leptokurtic and non-normal, which is of course highly common for time series data. However, I don't exactly understand why that is not a problem for ARIMA modeling and GARCH ...
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What model for volatility spillover effect in R? [closed]
I am doing research to study the volatility spill[over] effect. I have time-series data of Indonesian stock price (Jakarta composite index or JKSE), an exchange rate (IDR/USD), and oil price (BRENT). ...
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Is ARIMA-GARCH nested within ARIMA?
I wanted to compare ARIMA(1,1,1)-GARCH(1,1) and ARIMA(1,1,1) model forecasts with a Diebold-Mariano test, but I know that it cannot be used for nested models. Is ARIMA-GARCH technically nested within ...
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Interpretation of Li-Mak test [duplicate]
I have performed a Li-Mak test Weighted.LM.test on the squared residuals from a fitted GARCH(1,1) model. However, I find the understanding of the null hypothesis ...
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Can I compare model output from GARCH and EGARCH when the EGARCH is log conditional variance?
I have used the rugarch package in R to construct a sGARCH and an eGARCH model, but have ...
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python arch lib incorrect conditional volatility values, while tgarch and gjr garch vols are correct
Somehow when I estimated a GARCH model using arch.arch_model, its resulting conditional volatility took values that are not correct (around 12, cf picture). I did the exact same process for GJR GARCH ...
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Forecasting with ugarchforecast
I'm a bit confused on how to use the ugarchforecast function for forecasting. I estimated a GARCH(1,1) model based on the training dataset (...
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AIC/BIC of ARIMA and ARIMA-GARCH
I was modelling a time series with an ARIMA(1,1,1) model which had an AIC of -4782.96. However, after checking squared residuals and performing ARCH tests (Engle's and McLeod-Li) I detected the ...
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Formal test for TARCH (threshold ARCH) errors?
The statsmodels package includes a generic Lagrange Multiplier test for residual autocorrelation. The documentation mentions
Returns Engle’s ARCH test if resid is ...
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Does the Absence of a Unit Root Imply Wide Sense Stationarity?
I'm taking a course on time series currently and have been slightly confused about the interplay between unit roots and stationarity in a question I've been attempting to answer. The question set up ...
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Forecasting using Copula GARCH methods
I need to replicate what Huang and al (2009)* did without using built-in functions in R. What I'm struggling with is how to forecast returns for my two data samples. I've found the GARCH specs and ...
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How to estimate Pearson type-IV-GARCH using MLE in R?
I am just wondering whether there is an R program that can be applied to run GARCH specifications with Pearson types IV distributions. If you are familiar with any or can guide, it is greatly ...
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Estimating parameters GARCH model
Suppose I have the following model
\begin{equation}
R_{i t}-r_{t}=\alpha_{i}+\beta_{i}\left(R_{m t}-r_{t}\right)+s_{i} S M B_{t}+h_{i} H M L_{t}+\varepsilon_{i t}
\label{eqn:egarch}
\end{...
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GARCH(2,1) interpretation
I have a GARCH(2,1) model that mitigates heteroscedasticity, i.e. no ARCH effects.
I use GARCH(2,1) because GARCH(1,1) didn't mitigate heteroscedasticity.
Below I will give the values of the ARCH &...
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Parameters for specific coefficient in DCC-GARCH model in R
I am writing a paper about assets volatility spillovers, I have fitted a DCC(1,1)-GARCH(1,1) model and got omega alpha1 beta1 shape in R studio, and dcca dccb all significant. But I have no idea how ...
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Lag selection and model instability for ARIMA-GARCH in rolling windows for forecasting
I'm to produce rolling forecasts with an ARIMA-GARCH model using a moving window size of 1000. Given that structural changes in the series might take place at some point in the forecast horizon, is ...
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GARCH model and variance equation
I have wheat prices in log 1st difference. I tested it for ARCH(p) effects, and ARCH effects does exists. So i built an GARCH(p,q) model.
My issue is that I don't know which GARCH model I should use.
...
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Estimating volatility of 15 stock market indices: univariate vs. multivariate models
I am working with R and with financial series of 15 stock market indices with a weekly frequency.
I want to obtain the estimated volatility since it is the input I need to perform a volatility ...
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Error when forecasting volatility with GARCH model in R [closed]
I am trying to forecast volatility on four different time series which is returns of SP500, Nasdaq 100, Dow Jones and Russel 2000. the four time series consists of 3259 observation and is divided into ...
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Is it possible to create ARCH-GARCH model using MA(q) or ARMA(0,0,q) as conditional mean equation?
I tried to create ARCH-GARCH as conditional variance equation but the result of conditional mean analysis (I use ARIMA) shows MA(q) or ARMA(0,0,q) fits conditional mean modelling.
Data has ARCH ...
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Estimating abnormal returns with a GARCH(1,1) model in R Studio
I'm using the standard market model in an event study analysis to estimate abnormal returns for a particular event. In the baseline model, I use simple OLS and regress the returns of stock i (Ri) on ...
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Why Choose IGARCH over Standard GARCH?
I understand that IGARCH is a nested version of the standard GARCH model where alpha+beta=1, which implies a unit root. Although, I am struggling to see why having a GARCH process with a unit root is ...
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egarch using rugarch package in R
Hello.
I have been trying to wrap my head around GARCH (via rugarch package) for the past week and been trying to mimic the numbers as shown at vlab nyc's website.
I have not confirmed where they get ...
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How to determine whether to model GARCH effects over ARCH effects?
Based on my understanding, we could determine whether or not to include ARCH effects, by checking the residuals of the mean corrected model (EX: ARMA model). I know the difference between GARCH ...
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How do I forecast with external regressors in the rugarch package in R? The regressor appears to always be ignored in the forecasting [closed]
Here's the code to fit a GARCH(1,1) model with a external regressor x.
...
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DCC vs CCC GARCH models
What is the difference b/w the GARCH models.
I understand that these measure volatility spillover effects but i dont understand these properly.
Could it be possible to measure volatility/traffic of ...
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Problem in selecting arima parsimonious model for garch modelling
If I have some independent variables i.e. exchange rate, interest rate etc with 1 dependent variable. Then in that case for selecting parsimonious ARIMA model I should be considered for stationary of ...
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How were the probabilities calculated [closed]
I'm trying to calculate the probabilities in the paper 1 but I'm getting different results. In the paper, the forecasted smoothed probabilities are calculated as follows:
$$\mathbb{P}(S_{t+1} = i|\...
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Help in Understanding the Estimation Procedure Followed in a Paper
I would like to build a Markov regime-switching based early warning system. From the several papers I've skimmed through, [1][2][3][4] they go on about estimating a Markov regime-switching model as a ...
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GARCH model sensitivity to distribution assumptions
I am trying to fit an ARMA(4,4)- GARCH(1,1) model to return data, where the distribution of returns is highly leptokurtic. I plan to see whether autocorrelations exist in the data even after ...
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Long-Run Variance LRV for TGARCH and GJR-GARCH
As LRV calculation from GARCH parameters is on annual basis:
$$ LRV = \frac{\omega}{1 - \alpha - \beta} \cdot 252 $$
I wonder if it's not a composition of unconditional variance divided by the model ...
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Bivariate GARCH model to obtain dynamic optimal hedge ratio - R
The optimal hedge ratio is the ratio of the covariance between the futures and spot price, to the variance of the future price. I estimated it already as the slope coefficient of an OLS regression of ...
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Why is GARCH offering no predictive value?
I am playing around with GARCH models for the first time (I have a stats background but basically no experience with GARCH), trying to forecast volatility in a financial time series.
I trained a GARCH(...
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A Markov Regime-Switching GARCH with Time-Varying Transition Matrix Package in R
Does anyone know if there exists any Markov regime-switching GARCH with time-varying transition matrix package or tutorial in R? I know of the "MSGARCH" package by D. Ardia et al. but the ...
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How to Combine ARMA + GARCH For Estimates + CI in Python
I know I'm trekking down a well beaten path with this type of question, but I find myself trying to clarify how to combine several snippets on the internet and coming up empty handed. There is one ...
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SARIMA+GARCH predict 2 step on R
I was trying to implement SARIMA+GARCH(1,1) on R, but there is no option in fGarch to do that. Hence, I run GARCH on residuals from SARIMA, and it worked well. However, I don't know how to implement ...
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Why should a Li-Mak Test on Squared Standardized Residuals be preferred over a ARCH LM Test or Ljung-Box Test on Squared Residuals?
If I didn't misunderstand the literature, the predominant approach to test for autoregressive conditional heteroscedasticity in (G)ARCH models is to apply the ARCH LM test of Engle or the Ljung-Box ...
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Do Time Series Models fall under GLM?
I have the following question: Can Time Series Models (e.g. ARMA, GARCH) be considered as GLM's?
For example, below is the standard form of a GLM:
At first glance, Time Series Models have some ...
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Contradictory results when estimating GJR-GARCH(1,1) with rugarch package
I am using financial stock data (1588 observations, daily returns) to estimate
a GARCH(1,1) and a
GJR-GARCH(1,1) model.
A GARCH(1,1) takes the form:
$\sigma_t^2 = \omega+\alpha_1 a_{t-1}^2+\beta_1\...
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Linear Mixed Models with GARCH Errors
Currently, I'm trying to analyze the factors affecting rice prices in certain localities over five years. I have monthly data on rice prices of 60 localities for 2015 to 2020.
I would like to ...
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Forecasting volatility from serially uncorrelated (squared) returns
I am trying to estimate future volatility based on historical stock price data, using (G)ARCH models. I have computed the ACF and PACF of returns and squared returns, and none of them show signs of ...
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How to estimate a Vector Autoregression model using ARCH estimation (VAR-GARCH)?
I estimated a vector autoregression (VAR) model using 3 lags and 5 variables. However, when I estimated the equation using OLS, heteroskedasticity was present. In this sort of a situation, what is the ...
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Fourth moment of arch(1) process
I have an ARCH(1) process
\begin{align*}
Y_t &= \sigma_t \epsilon_t, \\
\sigma_t^2 &= \omega + \alpha Y_{t-1}^2,
\end{align*}
and I am trying to express the fourth moment $\mathbb{E}[Y_t^4]$ ...
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How to do a post estimation of BEKK-GARCH?
How to do a diagnostic check for BEKK-GARCH estimation?
Should we check GARCH effect in the residuals and decide from that because variance residuals and mean-variance of residuals are given in the ...
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How to calculate synchronized returns among two different stock market using DCC-GARCH?
I am working out with the thesis paper Cheang(2018) to calculate synchronised returns between two stocks from different markets.
I am trying to code this in R. I am using rmgarch package and using <...
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Maximum Likelihood in the Markov Switching GARCH(1,1) Model
In the standard GARCH(1, 1) model with normal innovations:
$${\displaystyle ~\epsilon _{t}=\sigma _{t}z_{t}},$$
$$\sigma^2_t=\omega+\alpha\epsilon^2_{t-1}+\beta\sigma^2_{t-1}.$$
The (negative) log-...
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Can you compare two time series using the same GARCH model
Hi so I’m looking at how a company investing in Bitcoin changes the volatility of that stock (Tesla, MicroStrategy etc) in short, it doesn’t. I’m pretty new to modelling etc so I’m just wondering can ...
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Realized GARCH estimation problem
I'm trying to produce one-day ahead volatility forecasts for Bitcoin with Realized GARCH(1,1) using the rugarch package in R. The realized variance(...
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Realized variance/volatility as input in Realized GARCH model
I want to produce one day ahead volatility forecasts with Realized GARCH(1,1) using the rugarch package in R. I've defined the realized variance (RV) as the sum of ...
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