If an auto regressive moving average model (ARMA model) is assumed for the error variance, the model is a generalized auto regressive conditional heteroskedasticity (GARCH) .

learn more… | top users | synonyms

2
votes
1answer
102 views

garchOxFit in R-oxo file does not match

Could someone please help me with trying to get the Ox interface to work in R. I get the following errors as output: This version may be used for academic research and teaching only Link error: '...
0
votes
0answers
26 views

How to estimate an Engle's asymmetric DCC model in R?

I have a $N x d$ matrix of standardized residuals, and I want to estimate the parameters $\alpha$, $\beta$ and $\gamma$ of the asymmetric version (Cappiello, Engle, Sheppard, 2006) of the usual ...
1
vote
0answers
30 views

Robust standard errors in GARCH modelling (rugarch)

I am currently conducting some GARCH modelling and I am wondering about the robust standard errors, which I can obtain from ugarchfit() in ...
3
votes
1answer
362 views

ARMA+GARCH prediction with package rugarch (R)

I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework). I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast (...
2
votes
1answer
86 views

Question regarding volatility forecasting using High Frequency Data

Hi guys this is my first question on the Quantitative Finance section of the Stack Exchange network. I am currently reviewing the paper by Professor Alan E. Speight and David G. McMillan 'Daily FX ...
3
votes
0answers
49 views

Regression coefficient and basic trading strategy

This question might be very basic but still I couldn't really find a satisfying answer anywhere. I want to analyse the effect of a repeated event (data release) on the price of a specific asset (I ...
0
votes
0answers
15 views

HN-GARCH Option Pricing Function produces negative values (fOptions HNGOption)

I have implemented the fOptions package's hngarchFit() function to fit a Heston-Nandi GARCH model to a set of option prices, followed by the HNGOption() function to price them. Unfortunately, the ...
3
votes
2answers
189 views

GARCH models vs VIX

I am examining how investor sentiment affects the probability of stock market crises. I am using methodology similar to this paper https://ideas.repec.org/p/dij/wpfarg/1110304.html. VIX (equivalents) ...
3
votes
1answer
59 views

Streaming update of the GARCH(1,1) model

Given the estimate of GARCH(1, 1) model parameters I observe the new price. How to update the estimate with this new information. Let's assume I know the coefficients that maximize the likelihood ...
1
vote
1answer
231 views

BEKK - GARCH model in Stata

Is it possible to run BEKK-GARCH in Stata? mgarch is of a different model type and google provide me with no good hints.
1
vote
1answer
34 views

Define the order of GARCH(m.s)

I know that if the order of Arch(m) is over 3, we should use GARCH and GARCH(1,1) was proved to be the best. But was GARCH(1,1) proved to be available for any country's stock market? My result show ...
3
votes
2answers
103 views

GARCH variance vs standard deviation for volatility

in my series of questions related to GARCH and volatility I finally think I've got a decent grasp on it. You guys have been great help clearing up my questions for me. My next question is just a ...
4
votes
1answer
127 views

GARCH volatility modeling, squared returns, and convergence

After reading some more of Volatility Trading, I decided to try to make a simple volatility model using daily log returns of an ETF I follow. It turns out "simple" is sort of relative. Unfortunately, ...
3
votes
1answer
174 views

rugarch: GARCH external regressors

I'm currently playing around with the great rugarch package in R. However, I tried to test the external regressor functionality. I implemented a GARCH(1,1) process and compared it with a GARCH(0,1) ...
2
votes
1answer
130 views

VEC GARCH (1,1) for 4 time series

I have to estimate a VEC GARCH(1,1) model in R. I already tried rmgarch, fGarch, ccgarch, mgarch, tsDyn. Has somebody estimated a model like that? ...
1
vote
0answers
42 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 ...
1
vote
1answer
47 views

logarithm and absolut value in returns of stocks [closed]

Well, i'm interested in model a GARCH for a serie. The original serie is $y_t$ (price index of a Stock Market), which has a unit root. So i create the returns: $x_t = ln(y_t) - ln(y_{t-1})$. Now, i'm ...
2
votes
0answers
52 views

What is the unconditional variance for a GARCH model?

I want to use a Matlab script to calculate Heston Nandi GARCH prices. I found an appropriate script online and it asks for the "unconditional variance" as an input. How do I calculate the appropriate ...
3
votes
0answers
41 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'...
1
vote
0answers
36 views

Forecasting conditional returns in DCC-GARCH-copula approach in R

anyone who could help me interpreting and modifying this code? I have a dataset and want to reserve the last 100 returns for out-of-sample analysis. After specifying and fitting the garch-spd-copula, ...
0
votes
1answer
51 views

GARCH Model Constant in Regression

When regressing a variable on a constant of 1, the coefficient of this constant is the mean. However, when I specified that the residuals follow a GARCH(1,1) model, the coefficient of the constant ...
0
votes
1answer
118 views

Package for multivariate Garch Vech model for R?

I`m new to programming and searching a package for R which inherents the estimation for a Vech Garch(1,1). This is a multivariate Garch model which forms the residuals and the covariance matrix from a ...
6
votes
1answer
130 views

Why is the GARCH intercept supposed to be strictly positive?

Maybe it's a simple question but I don't really understand why it is theoretically required. Let's take the standard GARCH(1,1) $$\sigma^2_{t+1}=\omega+\alpha\epsilon^2_{t}+\beta\sigma^2_{t}$$ In most ...
3
votes
0answers
79 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
votes
3answers
153 views

GARCH parameters

I'm trying to estimate parameters of GARCH(p,q) model. I tried p=1, q=1 with t-distribution errors. Ljung-Box showed no correlation in residuals and squared residual. But the null hypothesis that ARCH-...
1
vote
1answer
114 views

Does the unconditional variance implied by a GARCH equal the sample variance?

In the MATLAB default settings for GARCH estimation they say "presample conditional variance is the sample average of the squared disturbances of the offset-adjusted response data y". Am I right in ...
0
votes
2answers
116 views

GARCH model is better for index than stock

We have used a standard GARCH(1,1) model with t distributed innovations for daily data of S&P index and JPM stock. Question: is there any financial or statistical reason why the GARCH model ...
1
vote
0answers
47 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 ...
1
vote
0answers
72 views

How to choose a GARCH model which delivers iid standardized residuals?

For my thesis I first need to examine nine financial time series and fit a conditional volatility model such that the obtained standardized residuals ($z_t = \epsilon_t / \sigma_t$) are approximately ...
0
votes
0answers
33 views

Evaluation of Bayesian GARCH

I am using the bayesGARCH package to estimate Bayesian GARCH models and I was wondering how to evaluate them in terms of precision of forecast or at least the quality of the model. I have encountered ...
15
votes
0answers
3k views

Algorithm to fit AR(1)/GARCH(1,1) model of log-returns

I am fitting numerically an AR(1)/GARCH(1,1) process to index and stock log-returns, $r_t=\log(P_t/P_{t-1})$, where $P_t$ is the price at time $t$, and thus far am not clear on where the observed log ...
1
vote
0answers
43 views

Distribution of AR and MA polynoms roots in ARMA/ARMA-GARCH models

I have another noob question. So, for example, I have ARMA(2,2) model: $$ x_{t} = \phi_{1}x_{t-1} + \phi_{2}x_{t-2} + e_{t} + \theta_{1} e_{t-1} + \theta_{2} e_{t-2}$$. So, I have 2 polynoms: $$1 - \...
2
votes
3answers
506 views

How to predict daily range of forex?

I am trying to predict the intraday moving range of stock/forex (essentially, high-low). Here are some ideas based on what I've been reading recently (do not have quant background, so basic level of ...
2
votes
1answer
80 views

distribution of AR, MA coefficients estimation in ARMA-GARCH models

could anyone give me an information about distributions of AR and MA coefficients via estimation? So, for example, I have ARMA(1,1)-GARCH(1,1) model with the same AR(1) and MA(1) parameters ...
4
votes
2answers
138 views

How to deal with negative ARCH terms?

Lately I have been trying to fit a GJR-GARCH(1,1) model to fit against the S&P 500 returns over 1985-2015 but I have ran into some problems I can't quite figure out. The GJR-GARCH(1,1) model I am ...
3
votes
2answers
90 views

ARMA-GARCH model, bset model selection and confidence levels calculations

I'm a newbie in GARCH models. I tried to realize ARMA(p, q)-GARCH(u, v) model via fGarch. So, 2 main questions. 1) Can I use BIC/AIC for selection best model for all (p, q)-(u, v) models? So, is it ...
2
votes
1answer
106 views

GJR-GARCH with $\alpha = 0$ as parameter estimate

I am estimating a GJR-GARCH(1,1) model with variance targeting in R. As data I am using returns on some stock indices. While calculating the GARCH models I obtain $\alpha=0$ for some indices. From ...
4
votes
2answers
116 views

Degrees of freedom in calculating significance of GARCH coefficients

I am trying to determine the significance of coefficients of a GARCH model by calculate the p-values using the following Matlab formula: pvalues = 2*(1-tcdf(abs(t),n-v)), where $t$ is the t-stat,...
2
votes
1answer
51 views

How do I get Value-at-Risk for a GED distribution in R?

I need to calculate parametric Value-at-Risk using a GARCH model assuming a GED distribution. How can calculate it in R? thank you
1
vote
1answer
39 views

Disappear Standard Error in OxEdit/G@rch6 package

Hellow everyone, I'm new here. Please instruct me to do something. My problem is when I run FIGARCH(0,d,1), OxEdit still show me a matrix with variable names, coefficient, s.e, t-stat... like this ...
1
vote
1answer
55 views

Events effect on intraday volatility and large outliers

I have an event that takes place over a period of a few days, and I want to estimate the effect it has on market volatility using intraday data with one minute frequency. The problem is, that e.g. ...
0
votes
0answers
29 views

Approximating the conditional expectation in simulations

I am simulating stock returns, which are governed by the following equations $r_t = \mu + \delta r_{t-1} + \sigma_t z_t$ $\sigma^2_t = \omega + \alpha \varepsilon_{t-1}^2 + \beta \sigma^2_{t-1}$ $\...
2
votes
1answer
121 views

Simulating returns from ARMA(1,0)-GARCH(1,1) model

I want to obtain a simulation of one-step ahead forecasts of stock returns process governed by ARMA(1,0)-GARCH(1,1) process. The returns are of form: $x_t = \mu + \delta x_{t-1} + \sigma_t z_t$ From ...
4
votes
1answer
301 views

Does Matlab support exogenous variables in GARCH models?

Is it possible to introduce dummy variables or explanatory variables in the GARCH variance equation (garchset and garchfit) in ...
4
votes
1answer
61 views

Sum of two GARCH(1,1) Models

I have two GARCH(1,1) processes ($q=1,2$) $$ \sigma_{q,t} = \gamma_q + \alpha_q \, \sigma^2_{q,t-1} + \beta_q \, \epsilon^2_{q,t-1} $$ that have a constant correlation $\sigma_{12,t} = \rho \, \...
1
vote
1answer
96 views

how to calculate RMSE, MAE, given ugarchforecast results?

Given S&P500 returns for the past 20 years I fitted an ARMA(1,1)-GARCH(1,1) model using the rugarch package, so using ugarchspec() and the ugarchfit(), with different innovations distributions, i....
1
vote
0answers
45 views

Is this a GARCH Monte-Carlo simulation?

I tried this as a simulation for a GARCH(1,1) model. Is it correct? (I'm not speaking about the code itself, which works, but the underlying idea). Here is plot (of ...
3
votes
1answer
339 views

Error term/Innovation process in ARCH/GARCH processes?

I am wondering about the distribution of the error term/innovation process in a ARCH/GARCH process and its implementation, I am not sure about some points. The basic assumption is $r_t=\sigma_t*\...
4
votes
2answers
150 views

ruGarch - Interpret test results

I'm working on a R project, trying to calibrate a GARCH (so far, (1,1) ) model to the yields of the STOXX50 index over the last 2 years. I've tried the garch function of the tseries package, but it ...
0
votes
0answers
58 views

VECM model with GARCH (1,1) error in R

I should create a VECM model with 8 lags and with Garch (1,1) error in R but i don't know how to do it and which package to use. The VECM should also have covariates in it. Then I should perform a ...