# 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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22 views

### Applying GARCH to Panel Data

I have a panel consisting of some quantity - say earnings/cash flows/or something similar. I am interested in forecasting the volatility that is inherent to that respective measure. In a single time ...
33 views

### Can you apply GARCH to ARIMAX models?

Is it possible to apply the idea of GARCH to time series models that include exogenous variables? For example, say I estimate a cash flow forecast model. Does it make sense to model the residuals by ...
15 views

### Models that can improve FHS (with possible residuals manipulation)

The Filtered Historical Simulation (FHS) is a tough benchmark. By: choosing among the most complicated ARMA-GARCH variants with automatic model and lag selection, manipulating standardized residuals ...
34 views

### Preferred stock volatility model [closed]

If I want to forecast stock volatility, what would be the best GARCH model and why? (ARCH, GARCH-M, IGARCH, EGARCH, TARCH etc)
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### GARCH(1,1) variance forecast in one-step or multi-step?

Suppose I want to forecast daily variance of a stock using GARCH(1,1) model while I have high frequency data of 5 minute returns. What is the difference between applying GARCH(1,1) in one-step ...
28 views

### ARMA Order in GARCH

I want to do a GARCH forecast with a GARCH(1,1) Model but I am confused on which mean model I can or should choose. If I call the Auto.Arima function on the squared returns I get an ARMA(0,4) process ...
28 views

### EGARCH interpretation

I run EGARCH Model for my data, in Mean and Variance Equation.all P value are significant, but my ARCH Coefficient is negative. so my question .. is it ok if I use this model ? or maybe there’s a ...
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### The residuals of GARCH model reject Engle’s Test despite large parameters

I'm trying to build a model to predict the volatility for a financial asset with ARIMA-GARCH model. (I use log returns as data) I fit my ARIMA model with AIC and I did Engle’s Test to ensure there is ...
60 views

### Maximizing a GARCH likelihood: Good practice on constraining solutions and initial values

I am currently working on option pricing model and I'd like to include a method for maximizing the likelihood of returns under the P measure. I am using the Heston and Nandi (2000) model: \begin{align}...
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### Suggestions for choosing an optimization algorithm for fitting custom GARCH models by QMLE in R?

I am trying to fit a custom GARCH model by QMLE in R. I have written out the log likelihood function and am now working on optimizing it. However, choosing an optimization algorithm has proven to be ...
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### I would like to fit a CARR model using the 'rugarch' package in R - what should I include in the specification?

I know I have to specify a GARCH model for the square root of range without a constant term in the mean equation - just unsure how to apply this in the rugarch function.
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### Value at Risk with Monte Carlo using DCC-Garch in R

So I was trying to compute the 1- day Value at Risk of a hedge portfolio (consisting of 1 stock and one future) with a DCC-Garch model in R. So what I did is since I had historical data of 10 years: ...
134 views

### Why is volatility unobservable even ex post?

I am looking into how to measure volatility, and I am not sure if I have confused myself too much in my research. So now I really need your help. So please either confirm my understanding of ...
137 views

### Problem with the maximum likelihood for a GARCH-type of model

I'm currently working with the following GARCH process from Heston and Nandi (2000): \begin{align*} r_{t+1} - r_f &= \lambda h_{t+1} - \frac{h_{t+1}}{2} + \sqrt{h_{t+1}}z_{t+1} \\ h_{t+1} ...
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### How do you handle implied volatility performing a VaR Monte-Carlo simulation using a stochastic volatility process calibrated on the underlying

Say you have a portfolio consisting of options each having a market implied volatility. If you now use some stochastic volatility model like GARCH to calibrate the real world volatility of the ...
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### Correlation in GARCH model

I don't think I have ever come across the concept of stochastic correlation so I imagine it's not very widespread, but I had the idea to implement a Monte Carlo VaR model for a portfolio of stocks by ...
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### VARX DCC GARCH in R for volatility spillover

I have 5 series for which I want to analyze volatility spillover (to and from the series) via VARX DCC GARCH for both dynamic and comtemporaneous effect. Moreover, I would like to analyze seasonal ...
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### Can ARMA and GARCH models be estimated separately in ARMA/GARCH？

Can I use the residuals of the ARMA model to build a GARCH model(with Zero mean)? If so, does this mean that this GARCH model(with Zero mean) has no effect on ARMA's estimates. For example, if I want ...
199 views

### What stochastic volatility models are industry standard for option pricing and how do they work?

I've started reading up on stochastic volatility models and it seems very difficult to discern which ones are used in practice and which have been mostly left alone in theory. What are the popular ...