Questions tagged [garch]

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used for time series in which the conditional variance is time-varying and autocorrelated. The conditional variance is a linear combination of lagged conditional variances and lagged squared errors. The conditional variance equation in GARCH models is deterministic, in contrast to Stochastic Volatility (SV) models.

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Why are my GARCH forecasts biased?

I've run an ARMA(1, 1)-GARCH(1, 1) model with normal density on log returns for twelve stocks. I computed the one-step-ahead out of sample forecast for daily volatility on a rolling windows for 500 ...
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117 views

What kind of errors arise when I fit ARMA(1,1) to data generated from ARMA(1,1)-GARCH(1,1) process?

As far as I know estimates of parameters of ARMA(1,1) are asymptotically optimal when fitted to data from ARMA(1,1)-GARCH(1,1) process, and only their variance increase, so when we assume large ...
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117 views

Measure how different forecasted volatility is from realized volatility

Hi Quantitative Finance Stack Exchange, I'm looking for an opinion on a simple question. Suppose I use a Garch(1,1) model to make a volatility forecast. At time $t$, I have realized volatility $\...
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940 views

Fitting Student t-distributions to log-returns

It seems that some tail-risk centric groups are bent on using Paretian and t-distributions to account for tail risk when fitting log-returns. It has been observed, however, that with and without ...
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2k views

Fitting GARCH(1,1) in Python for moderately large data sets

I am using the arch package in python to fit a GARCH(1,1) to fit daily S&P 500 returns from 1990 to 2017 (about 6800 data points). The code I am using is as follows: ...
4
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2k views

FIGARCH estimation in R

I am trying to estimate a FIGARCH(1,1) model in R for Value-at-Risk purposes. As I understand it, the rugarch package does not support FIGARCH or FIEGARCH. To that end, I used the garchOxFit function (...
4
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216 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
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1answer
271 views

VAR-aDCC full ARCH and GARCH parameter matrices in R

I am working with the rmgarch package in R and I estimated a VAR-aDCC model. Is there any way to extract the extended version of estimates (allowing for volatility ...
3
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781 views

'GARCH - extreme value theory - copula' approach to estimate risk measures in R

I'm reading about this approach of using GARCH-EVT-copula methodology to separate univariate and joint estimation and then estimate for example VaR and ES. I wanted to try something similar, but my ...
3
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209 views

When to use SV or a GARCH model

So i have been searching for this answer for a question if there is a rule or something that would say when to use GARCH type model or use an stochastic volatility model to predict the volatility of ...
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545 views

The difference in sign bias test in detecting the exist of asymmetric effects and the adequacy of symmetric GARCH model.

The question is that I want to know whether there is difference in the applying of sign bias test in detecting the exist of asymmetric effects and the adequacy of symmetric GARCH model. In the ...
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669 views

GARCH modelling and forecasting

I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling the log return of oil spot prices using various GARCH models: GARCH, ...
3
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2answers
230 views

When the two time series with different length, how could we analysis them with a bivariate GARCH model?

At this moment, i need to do the analysis of rouble/us dollars exchange rate and the stock market index in Russia, I prefer to do that in a multivariate GARCH model. However, I have a question about ...
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187 views

rugarch and rolling estimation

I use Rugarch for a long time in order to calibrate GARCH models on FX rates time series and perform simulations. I am trying to understand the ugarchroll method. However even if I can find plenty of ...
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228 views

What does negative gamma mean in APGARCH model?

I got a gamma of -0.1321677. ...
3
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1answer
271 views

Volatility estimation: sampling frequency and scaling

I have a year long stock data sampled at 5 min frequency and would like to estimate monthly volatility using it. I am thinking using GARCH or TGARCH for volatility estimation. However, I am not sure ...
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48 views

ARMA-GARCH estimation with EGB2 distribution

I want to estimate a ARMA-GARCH model by using the EGB2 distribution instead of the normal distribution. The model I want to estimate is: $$y_t = \mu + \phi_1 y_{t-6} + \phi_2 y_{t-8} + \theta_1 \...
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28 views

Constraints by estimating GARCH, EGARCH, GJR-GARCH models

I know that by estimating an GARCH model, given by: $$\sigma_t^2 = \omega + \alpha \epsilon_{t-1}^2 + \beta \sigma_{t-1}^2,$$ $\omega, \alpha, \beta >0$ and $\alpha + \beta <1$. But what are ...
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48 views

GARCH(1,1) one-step ahead volatility forecast biased, higher than Parkinson's HL volatility

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 ...
2
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1answer
108 views

Can you use GARCH-MIDAS for intraday data?

I'm working on a project to forecast volatility and I'm using intraday data (1 min). I want to include exogenous variables to the model that have daily frequency. I was wondering if GARCH-MIDAS can be ...
2
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40 views

VaR of ARCH model

Consider the following: $r_t = \theta r_{t-1}+u_t$ $u_t=\sigma_t\epsilon_t$ $\sigma^2_t=\omega+\alpha u^2_{t-1}$ $-1<\theta<1,\omega>0,\alpha \in(0,1)$ What is the 99% 2-day VaR of a ...
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264 views

RiskMetrics VAR calculations and conditional distribution of sum of log returns

According to Tsay's book in Chapter 7, for the Risk Metrics model: A nice property of such a special random-walk IGARCH model is that the conditional distribution of a multiperiod return is ...
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62 views

Determine GARCH(1,1) from a mean reverting time series recursion

Let $(v_t)$ be a discrete time series of variance obeying a mean-reverting variance process $v_t$, which is actually the discrete version of the Heston model in finance. \begin{align} x_t &= \sqrt{...
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63 views

Deduce GARCH(1,1) to the stochastic variance model

Here is the proof that the limit of GARCH(1,1) $$\sigma_n^2 = \gamma V_L + \alpha u_{n-1}^2 + \beta\sigma_{n-1}^2$$ is equivalent to stochastic process of variance $$d V = \alpha(V_L - V) dt + \xi VdW....
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164 views

Unconditional variance of an E-GARCH model

I am attempting to calculate the unconditional variance of an E-GARCH model: $$\log(h_{t+1}) = \beta_{0} + \beta_{1}\log(h_{t}) + \beta_{2}\left[|\varepsilon_{t} - \lambda| + \gamma(\varepsilon_{t} - \...
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409 views

GARCH Option Pricing Model (Duan 1995)

I am trying to replicate Duan's results from his 1995 Paper, "The GARCH Option Pricing Model". I have written this code in Python myself, and using his parameters I consistently seem to obtain results ...
2
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228 views

Heston & Nandi GARCH model, parameters estimation from option data

I wonder if anybody has code for the HN-GARCH model where the parameters is NOT estimated with maximum likelihood and instead estimated by looking at the option data where an loss function is chosen ...
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241 views

VARMA GARCH modelling in R

I want to simulate a VARMA-GARCH process in R. Unfortunately, I found no package to help me with that. I tried modelling the MGARCH part on itw own and combine it with the VARMA simulation using MTS ...
2
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37 views

Rotations and Shifts in the f-GARCH News Impact Curve

I re-post my question from the Cross Validated section as requested by another user. I am using the beautiful "rugarch" package and presently have an issue concerning the interpretation of two ...
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97 views

Negative constant in GARCHX model

I am fitting the following ARX(1,1)-GARCHX(1,1,1): \begin{align*} y_t&=c+a_1y_{t-1}+\gamma_1x_t+\varepsilon_t\\ h_t&=\delta+\omega_1h_{t-1}+\theta_1\varepsilon_{t-1}^2+\pi_1x_{1,t} \end{align*...
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44 views

LSE GARCH Modells

currently I am working with GARCH Modells. And it came to my attention that for the parameter estimation Maximum Likelihood approaches are commonly used. However I was wondering why Least Squared ...
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273 views

Problems in computing VaR with GARCH-GPD-copula approach

I use a time-varying Gaussian copula (with GARCH-filtered standardized residuals modeled semiparametrically with Gaussian kernel interior and GPD tails, i.e. generalized pareto distributed) to ...
2
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63 views

False warning messages in R, is it possible?

I'm modeling GARCH-filtered standardized residuals via semiparametric distribution with Gaussian kernel and GPD (generalized pareto distribution) tails with thresholds at 5% and 95%. For some series I'...
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547 views

Modelling log-returns and calculating the portfolio return

I know this might be a trivial question, however, I would be grateful for some clarification. I am working on weekly log-return data, doing volatility-foracasting using GARCH models and then using ...
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908 views

How to fit a VAR + GARCH in R

I should create a VAR model with Garch error in R but i don't know how to do it and which package to use. The Vector Autoregressive model (or VECM) should also have covariates in it. Then I should ...
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0answers
869 views

Forecast of ARMA-GARCH model in R

I managed to forecast a GARCH model yesterday and run a Monte Carlo simulation on R. Nevertheless, I can't do the same with an ARMA-GARCH. I tested 4 different method but without achieving an ARMA-...
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542 views

How can I do a dynamic GARCH model using extended Kalman filter in R?

Today I was reading an article quoted here, in this article is proposed an adaptive (dynamic) Garch model. How can I do it in R? The use of extended Kalman filter or particle filter is indifferent. I ...
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338 views

Why random walk Metropolis Hasting algorithm works bad on GARCH(1,1) parameters estimation

I am trying to estimate the parameters of the GARCH(1,1) model with MCMC method, firstly, I read the paper: http://mpra.ub.uni-muenchen.de/12985/1/MPRA_paper_12985.pdf Metropolis Hasting method is ...
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262 views

Dummy variable and negative estimation in GARCH (1.1)

I am trying to use GARCH model for my research. However, when I am running them, I see negative value for alpha and beta. How I can restrict them so that they do not provide me any negative value. Is ...
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111 views

volume augmented garch(1,1) model in matlab

Actually I want to add volume traded of a stock in my Garch(1,1) model to forecast the volatility.In Matlab I can specify the model as garch(1,1) and then use estimate and forecast commands.But I am ...
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40 views

Portofolio optimization using ARMA-GARCH-EVT-Copula

I am currently trying to do some portfolio optimization by reproducing the methodology found in Sahamkhadam, Stephan & Östermark (2018) ("Portfolio optimization based on GARCH-EVT-Copula ...
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0answers
67 views

What's the interpretation behind this GARCH modeling?

I have an ARIMA model for monthly returns of the brazilian stock market index. Then I test the residuals of the model for ARCH effects. The ACF/PACF of squared residuals show that there are no ...
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1answer
106 views

In-sample volatility measurement

I would like to know what is the most reasonable way to measure volatility in a sample of past observations. Aside from standard deviation, are more complex models like GARCH used for (historical) ...
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27 views

RUGARCH (output) and Residual Resampling using GARCH(1,1)

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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0answers
96 views

Fitting a forecasting S&P500 roll volatilities

I have a time series of S&P500 prices, for which I have calculated log-returns and roll-volatility. My goal is to forecast daily realized volatility and test a straddle strategy based on it (I ...
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0answers
72 views

Standard GARCH(1,1) model with external regressors

I have a queastion how does a standard GARCH(1,1) model with external regressors in mean and variance euqations look like ? I know that standard GARCH(1,1) model without external regressors has the ...
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0answers
63 views

What kind of ARMA-GARCH model is that?

My question is what kind of ARMA-GARCH model is the following equation and how to specify it in rugarch R module: $$r_{t+1}- r_t = \alpha_0 + \alpha_1r_t+\...
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0answers
36 views

Log likelihood function, GARCH(1,1) with asymmetric term

I am modelling a GARCH(1,1) and a GARCH(1,1) with an asymmetric term. $$h(t)=\omega+\alpha\varepsilon(t-1)^2+\beta\sigma(t-1)^2$$ and $$h(t)=\omega+\alpha u(t-1)^2+\beta\sigma(t-1)^2 + \gamma (u(...
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0answers
60 views

Estimating an GARCH(1,1) model? Long hand method

I am really trying to invest some time to estimate a GARCH(1,1) method, I know there is many statistical packages that will do this for me (Eviews, MATLAB, R), but I am trying to do this by hand, so ...
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136 views

Poor results forecasting stock price volatility using Python's GARCH model

As far as I understand, forecasting stock price volatility should be more achievable than forecasting absolute prices or returns. It seems as though GARCH models are the traditional and most widely ...