# 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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### Forecasting VIX with GARCH(1,1)

Aim: Forecast VIX using GARCH(1,1) Reason: I want to be able to forecast VIX on several horizons, in order to be able to forecast the SP500 index through linear regression. Tools used: Python, ...
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### Optimal Hedging Ratio using Copula Models

Let $r_{s, t}$ and $r_{f, t}$ be the return rates of the spot and futures of a commodity at time $t$. The hedging ratio based on variance minimization is calculated by finding the minimum of the ...
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### Can one estimate rather than forecast volatility using the GARCH model?

Can one use the GARCH model to estimate the realized variance/volatility, such as done in this paper, rather than forecast the volatility, from (high frequency) price/tick data?
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### Long-run volatility forecast of a GARCH(1,1)

Can I assume that "the long run volatility forecast of a GARCH(1,1) is higher in periods of high volatility than in periods of low volatility?
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### GARCH option pricing

I have been trying to implement GARCH(1,1) model for pricing call options. Suppose I have calibrated Garch(1,1) model for modelling the conditional volatility using the historical data of an equity ...
1 vote
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### 2-day ahead prediction of value at risk with GARCH(1,1) in R

Let's say I have a 10 year dataset of Tesla (example) and I am taking the percentage change of lag 2: ... 1 vote
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### Variance of the price from returns variance

Let's say that we have the variance of the daily return at $t_0$: $$\sigma_{r_{t_0}}^2=\text{Var}[r_{t_0}]=\text{Var}[\frac{S_{t_0}-S_{t_0-1}}{S_{t_0-1}}]$$ for price process $S_t$. Is there a way to ...
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### How to deal with negative intercept terms on GJR-GARCH(1,1) model?

Recently, I have been studying the relationship between COVID-19 and stock returns using a GJR form of threshold ARCH model. However, I got some unusual estimation results I can't figure out whether ...
1 vote
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### What implies "conditional heteroskedasticity" in (G)ARCH? [closed]

I have trouble to understand what implies "conditional heteroskedasticity" term in (G)ARCH models. The residual $\epsilon$ is stationary, hence homoskedastic (unconditional variance is ...
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### Deciding (p,q) in garch and model test on empirical data

I'm currently working on a dataset containing data from the 29 January till the 29 July 2009. In the dataset I have prices of the S&P 500 index for all days. Furthermore, I have the implied ...
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### HNGARCH Option Pricing in R (How to loop)

I am having difficulties when using the HNGOption program in R. The program will only run for 1 specific option price, meaning that I would have to manually insert strike price etc. and this would ...
1 vote
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### Calculating E^2[σ^2] where σ is a GARCH(1,1) Proces

Given that α =0,113079 β = 0,873884 ω = 0,0000081 Need the calculate a call price using garch volatility I alsa calculated the kurtosis = 235 enter image description here: https://www.researchgate.net/...
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### EGARCH(1,1) mean

I'm trying to model an EGARCH(1,1). However, I dont understand why the mean from the general to (1,1) becomes $\sqrt{(\frac{2}{\pi})}$. The following I am refering to is:
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### Heston Nandi Garch Implementation Problem for Python

I have a coded my own Garch class in order to implement the Heston-Nandi Garch model. ...
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### Skewness and Kurtosis in GARCH vs Heston

GARCH(1,1) In discrete time, we can model returns as follows \begin{align} r_t &= \mu + \sigma_t\epsilon_t\\ \sigma_t^2 &= \omega + \alpha \epsilon_{t-1}^2 + \beta\sigma_{t-1}^2 \end{align} ...
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### How skewed are FX returns? Does this look like a plausible histogram of EURUSD?

I'm reading about volatility. I've charted the histogram of EURUSD and I am wondering if this looks plausible? What I've charted are the 1-hour percent change returns (not log returns). I've removed 0 ...
1 vote
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### Correct terminology - estimate or model?

I am doing some academic work and I'd like to summarise the picture around volatility models. As such, I'd like to refer to several ways of estimating volatility and I'd like to use proper terminology....
1 vote
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### negative gamma value for gjr-garch output

I was wondering if anyone could tell me if my model is completely incorrect as I haven't been able to find anything online for this. I am running a Gjr Garch model to measure volatility in gold ...
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### Do I use % return, log return or diff of prices to plot ACF?

I am reading a book on time series. To make a non-stationary series stationary, sometimes we need to difference the series. When it comes to finance, prices are non-stationary. Many authors fit ARMA ...
1 vote
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### Is there an alternative to the rugarch package for GARCH modelling?

I have been trying to use the rugarch package but I find it sometimes limiting. After certain amount of data points the package doesn't converge and it becomes kind of annoying. Is there any R/Python/...
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### Is there a HAR that deals with the leverage effect?

The EGARCH is a special GARCH model that treats the leverage effect of the volatility. The HARV does not make a distinction between negative and positive returns. Is there a special HARV that deals ...
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### Estimation of time series using GARCH on Eviews

Firstly I should mention that I am new to both Eviews and GARCH models. Anyway, I am conducting some research into the effect that different macroeconomic factors have had on stock index volatility ...
1 vote
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### Option pricing and GARCH resources

Can anyone suggest resources for option pricing using GARCH models? Although I have a fairly good knowledge of GARCH models, for some reason I cannot seem to be able to follow Duan's paper and how to ...
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### Heston model vs. GARCH

Heston model is a stochastic volatility extension of the Black-Scholes model. On the other hand, there is also closed-form expression for option pricing that uses GARCH stochastic volatility model. ...
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### Comparison of results given by volatility estimators: Garman-Klass Vs Garch(1,1)

I am pretty new with volatility estimators and I am trying to see if Garman-Klass estimator and Garch(1,1)estimator are closed. So I implemented a python code for the two estimators (an also for the ...
1 vote
My understanding of ARMA-GARCH models for a variable $X$ is as follows: I estimate a conditional mean of a variable $X$ by use of the ARMA part of the model. I estimate the conditional variance of ...