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) .

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How to calculate the conditional variance of a time series?

I am reading a paper where the term conditional variance is mentioned, but I am not really sure what is meant by this and how this can be calculated: Fig. 2 shows the conditional variances of the ...
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Is it too important that my residuals be normal? I am Using an ARMA/GARCH model

I am trying to fit an ARMA/GARCH model to a time series. I found that the best candidate is an ARMA(1,0) + GARCH(1,1) with gaussian white noise It has coefficients with p-values near cero and the ...
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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 ...
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578 views

garchOxFit in R

Could someone please help me with trying to get the Ox interface to work in R. I followed the steps outlined in this paper (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1752095), but I get the ...
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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 ...
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Multivariate GARCH in Python

Is there a package to run simplified multivariate GARCH models in Python? I found the Arch package but that seems to work on only univariate models. I'd like to test out some of the more simple ...
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274 views

2-step estimation of DCC GARCH model in Python

Embedded in this thread are multiple questions. I'm currently im the process of implementing a DCC GARCH forecast model on quantopian (a python-powered trading platform). The two step consists of ...
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64 views

Expected value of log-GARCH process

Is there a way to analitycally compute expectation of log-GARCH process? The GARCH(1,1) process: $dU_t = \theta(\omega - U_t) dt + \xi U_t d W_t$ The log-GARCH(1,1) process: $e^{U_t}$ The ...
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Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
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Could we estimate a portfolio's volatility using a GARCH on the portfolio returns?

Estimating the volatility of a portfolio is typically done by first estimating the covariance matrix. This, however, can be difficult to do accurately and predictivly. This paper gives a nice summary ...
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Autocorrelation in the GARCH model residuals

I am estimating GARCH model for volatility calculation and as a data input I have used log first difference data (ln(a)-ln(b)). Usually I would check for autocorrelation in residuals(to check the ...
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How to trade volatility?

I am analyzing the volatility of financial stock returns and let's say I have a pretty good model to forecast tomorrows volatility of the stock returns. So let's say for simplicity reasons I have a ...
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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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How to user GARCH(p,q) to identify most volatile sector?

I would like to ask help concerning the utilization of GARCH(p,q) models to identify volatility. Suppose that I have daily closing prices of 6 financial sectors spanning several years, and I am ...
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1answer
155 views

Forecasting using GARCH in R

I am using the predict and ugarchforecast functions in R. When I fit my models and try to forecast, I get either only increasing or decreasing values for sigma, does anyone know why? Thank you ...
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GARCH filtering and extreme value theory

We are evaluating a model for risk management based on extreme value theory using peaks over threshold and markov chain monte carlo methods. In doing this, we are firstly fitting a GARCH (we have ...
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GARCH estimation does not work, error in my returns?

Hey everyone and I hope that there are some smarter people out here that can help me out with my problem...: I have trouble with my implementation of a GARCH(1,1) model and I do not know how to move ...
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GARCH model, expectation of volatility?

Consider a time series $\{r_t\}$ following a standard GARCH(1,1) model, i.e., $$ r_t = \sigma_t \epsilon_t,$$ where $\epsilon_t \sim N(0,1)$ and are i.i.d, and $$\sigma_t^2 = \omega + \alpha_1 ...
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Garch models and assumption of stationarity ?

I found big inconsistency in the GARCH models and their underlying assumption of stationarity. GARCH models require that data must be stationary, where stationary means both mean and variance are ...
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158 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 ...
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94 views

Measure the effect of a natural disaster on a stock market index

I am very new to using stata and very new to using Garch models. I am currently doing my final dissertation for my MSc in Finance studies and regarding my topic I understood that i had to use garch to ...
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115 views

Constant decreasing volatility, GARCH forecasting

I am trying to forecast the volatility using GARCH modelling in R. I fit an ARMA(1,1)-GARCH(1,1) model, but my sigma predictions are constantly decreasing. Anybody know why? ...
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Accuracy of GARCH& ARCH forecast

I'm learing ARCH&GARCH model. I have four questions that I don't know the answers 1st: ARCH & GARCH are often used to evaluate equities. Does it mean that ARCH and GARCH are fitter for high ...
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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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Uses of Volatility models

I'm reading about volatility analysis here http://vlab.stern.nyu.edu/doc?topic=mdls. There are many variations of GARCH. My question is: rather than trial-and-error approach, is there any systematic ...
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How to decide if the ARCH coefficient is necessary in the GJR-GARCH model?

I did some analysis for CAC 40, the French market benchmark, for the period 2005-2014, and I tried to fit the data with a GJR(1,1) model in MATLAB. Then some warning showed Lower bound ...
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EGARCH formulation

I am a bit confused about the formulation of the EGARCH(1,1) model. First, we have the error term: $\epsilon_t=\sigma_t*\zeta_t$, where $\zeta_t$ is white noise. Now the EGARCH(1,1) should be: $$ ...
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Residuals in the Ljung box test

does anybody know what type of residuals is used in the Ljung box test in R? raw or standardized? Because basically when I fit a GARCH model using garchFit, the summary() function gives me all the ...
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254 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, ...
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251 views

The use of GARCH

I have a conceptual question that I haven't managed to grasp yet and is most likely a econometrics 101 question by here it goes: If we estimate a GARCH model for a time series, how do we then use ...
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1answer
154 views

Explain the unconditional covariance in Dynamic Conditional correlation( DCC ) GARCH model

Confused about the unconditional covariance matrix in a DCC GARCH model. Could anyone help me understand it? My understanding is that we get the unconditional covariance before based on the data sets. ...
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Correctly applying GARCH in Python

Problem: Correct usage of GARCH(1,1) Aim of research: Forecasting volatility/variance. Tools used: Python Instrument: SPX (specifically adjusted close prices) Reference material: On Estimation of ...
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242 views

Constant Conditional Correlation GARCH (1,1)

I am a beginner in R and my econometrics background is not very sound either. I want to build a constant conditional correlation GARCH (1,1) model in R and I found the function, the description of ...
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327 views

How to fit a SARIMA + GARCH in R?

I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model. I'm using rugarch: model=ugarchspec( variance.model = ...
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Is there a way to adjust R PerformanceAnalytics function VaR with EWMA or GARCH method?

Is there a way to upgrade R PerformanceAnalytics function VaR with more risk sensitive approaches like EWMA or GARCH? Or is there another R package which can handle the issue?
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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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Is there any way to easily estimate and forecast seasonal ARIMA-GARCH model in any software?

I use R to estimate a seasonal ARIMA(8,0,0)(5,0,1)[7] model for the seasonal differences of logs of daily electricity prices: ...
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1answer
155 views

Can I do a GARCH model to forecast a time series?

I read this paper https://research.aston.ac.uk/portal/files/240393/AURA_2_unmarked_Energy_demand_and_price_forecasting_using_wavelet_transform_and_adaptive_forecasting_models.pdf the two authors ...
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using garch to forecast volatility but getting low persistence model

I am using a GARCH(1, 1) model to try model volatility for a certain stock. I have a GARCH function in matlab that returns the three parameters, omega, alpha & beta. I then use this parameters ...
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Difference between GARCH and Heston Volatility model

I know that the difference between the GARCH and the Heston model is volatility vs variance in the stochastic part of the volatility sde. However,from my solutions, there is only ever a 2 - 10 cent ...
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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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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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How to find the best fitting GARCH model for a portfolio composed of 3 ETFs in R?

I am doing a project for my class Financial Time Series in which I am trying to forecast my portfolio log returns using a GARCH fit. I am having a bit of trouble determining the best way to fit this ...
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1answer
169 views

Log returns and GARCH models

I try to model currency rates volatility using GARCH models through the RUGARCH package in R. Starting from the observed currency rate series, I compute the log-return through: ...
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253 views

Intuition behind interest rate models

I am modelling the 3M yield of US Treasuries using an ARMA/ GARCH approach. Most interest rate models (e.g. Vasicek) describe the process as follows: $r_{t}-r_{t-1} = some ARMA+ \epsilon_t $ ...
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HAR-RV, realized GARCH and HEAVY model for realized volatility

I don't have much experience with volatility modeling using intraday data but I'm in the process of collecting 5mins data. Currently I have ~6 months of data. Is it enough to use these models with ...
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what volatility do we calculate using GARCH model

what volatility do we calculate using GARCH model, Historical vol or Implied vol or Future Vol or Actual vol.
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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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135 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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R ARMA-GARCH rugarch package doesn't always converge

I'm trying to compute the standard ARMA(1,1)-GARCH(1,1) as shown in this answer for an entire index,just to store in a database to quickly lookup values for back ...