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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Any way to identify optimal lag length for garch model using Python

Is there any python library that automatically calculate p and q for the GARCH model? (for example: auto_arima in pmdarima) since that for both statsmodels and arch library in python needs to manually ...
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93 views

How to use implied volatility under GARCH model to forecast price?

I have come across videos on youtube about GARCH model in stimulating and forecasting stock price, however, it is programmed in R language. Is there any tutorials teach the similar as the videos shown ...
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GARCH(1,1) parameter estimation optimization method

In estimating a GARCH(1,1) model, $$\sigma_{t+1}^2 = \omega+\alpha \epsilon_t^2+\beta\sigma_t^2$$ Usually the parameter tuple $(\omega,\alpha,\beta)$ is estimated by the quasi-maximal likelihood. ...
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65 views

GARCH parameter estimation by linear regression?

In estimating a GARCH(1,1) model, $$\sigma_{t+1}^2 = \omega+\alpha \epsilon_t^2+\beta\sigma_t^2$$ Usually the parameter tuple $(\omega,\alpha,\beta)$ is estimated by the quasi-maximal likelihood$. Can ...
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65 views

Realized Volatility + GARCH - can I use hourly realized volatility?

I hav minute bar FX data and I am trying to fit a realized variance GARCH model using rugarch. This normally works by providing daily returns and daily realized volatility to the model. Realized ...
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111 views

GARCH calibration with overlapping time intervals

In constructing a GARCH(1,1) model over a time length $\delta$, I am considering the following procedure. The purpose of this procedure is to give more training (calibrating) samples than non-...
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95 views

Fitting GARCH(1,1) to log returns instead of residuals - centering crucial?

For a project I need to fit a GARCH(1,1) model to the log returns of an index. When using the residuals of an ARMA or ARIMA model it is clear that the (conditional) mean is 0. When using the log ...
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76 views

How to include heteroscedasticity in copula modelling

I have a dataset of 9 variables and I want to fit a t-copula to them in order to construct a multivariate and after that resample from it. I am using Matlab. ...
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No standard deviations using the hngarchFit function in R [duplicate]

I am trying to estimate a HN-GARCH model in R. However, when using the hngarchFit() function in R, no standard deviations for the coefficients are printed. I have looked at the function behind the ...
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42 views

HNGARCHFIT in R (No standard deviations or P values printed)

When I estimate an HN-GARCH model using the hngarchfit() from the fOptions package in R, only the coefficient estimates are printed. There are no standard deviations or P-values printed. Does anyone ...
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26 views

Perfect in-sample size for out-sampling volatility prediction (EGARCH(1,1)

I have a few questions regarding in-sample size for volatility forecasting in EGARCH(1,1). I'm currently sitting with a dataset consisting of 1387 trading days of the S&P-500 index. I would like ...
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1answer
237 views

Realized Variance (realized volatility)

I'm confused about realized variance. I roughly know the theory around Ito Calculus and quadratic variation and integrated volatility so I understand what realized variance measures (even though as ...
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28 views

How to estimate lambda from NAGARCH submodel in R

I am trying to estimate the model="fGARCH", submodel="NAGARCH" from the rugarch package in R. However, when I am estimating the parameters, only omega, alpha, beta and gamma are ...
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74 views

GARCH Option Pricing in R

I am trying to code a GARCH option pricing model in R. I am still new to R so this does seem a bit complicated. I want to estimate an asymmetric GARCH model as well as an EGARCH model. This I have ...
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29 views

Empircal data analysis delta hedge error of Black-Scholes by Mark Davis

Regarding Mark Davis derivation of the delta-hedging error occuring in the black-scholes as a result of difference in realized volatility and implied volatily. The formula reads as follows: $$ Z_t = \...
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75 views

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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94 views

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 ...
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29 views

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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136 views

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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150 views

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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85 views

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 ...
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79 views

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....
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Understanding GARCH

I asked this on stats.stackexchange but I realized this might be a better place to ask this question. I am new to finance and volatility forecasting and am trying to understand how garch model works. ...
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1answer
179 views

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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54 views

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 ...
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75 views

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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32 views

does anybody know a package for the estimation in python of multivariate garch model? [duplicate]

is there any package in python for the estimation of multivariate garch models? (bekk, dcc) i tried with the package mgarch but it provides only a few commands and wanted to know if there are some ...
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36 views

Ideal Training Set for a GARCH (p,q) model ( what is the optimal number of periods? )

I have searched high and low in the web and I cannot find a good answer on what is the ideal training set for Garch (p,q). I am attempting to use GARCH to do stop loss for my algo base on the ...
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109 views

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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67 views

Forecasting returns and volatility using ARIMA-GARCH model in R

I am using rugarch package in R to forecast returns and volatility of a stock. I train an ARIMA (p ,d q) + GARCH(s, r) model on ...
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39 views

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 ...
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45 views

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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112 views

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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103 views

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 ...
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1answer
87 views

Looking for a good introduction to modelling ARCH-type models

I am starting to think about my dissertation topic for my undergraduate degree. I am interested in comparing volatility of stock indices during COVID-19 to the years leading up to the pandemic. I have ...
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45 views

Squared Residuals equal Variance of Dependent Variable (ARMA-GARCH)

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 ...
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66 views

Should stock return series be modeled with a parametric distribution, or an autoregressive function? [closed]

If I have prior knowledg that a stock return series follows a parametric distribution, such as a Student t-distribution with 4 degrees of freedom, without actively looking for prior knowledge of ...
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32 views

GARCH model with exogenous events

GARCH models capture positive serial correlation in volatility. Sometimes events occur "out of the blue", causing volatility that a GARCH model cannot be expected to predict. One example is ...
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36 views

EGARCH and GARCH effects with White Noise squared residuals

I'm asked to model a series which it's returns are white noise and after adjusting a regression like $r_t=c$ and looking it's squared residuals (white noise too) I'm asked to adjust a GARCH and EGARCH ...
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34 views

How to estimate Hodrick Standard Errors in R

Does anyone know how to implement Hodrick Standard errors in R? I could not find any package for it in R. Is anyone aware of the same or any open source code that implements it? I want to use Hodrick ...
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1answer
283 views

Can we model Implied volatility using GARCH?

Can I use Implied volatility as a dependent variable in a GARCH model? I believe my IV data shows ARCH effects and hence can I use it to model volatility of the volatility? I know literature has used ...
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31 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 ...
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79 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 ...
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22 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 ...
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43 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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56 views

GARCH(1,1) variance forecast in one-step or multi-step?

I would like to forecast the 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 ...
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42 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 ...
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36 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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1answer
188 views

GARCH model using high frequency price return

I would like to forecast variance at time length $k\delta$ based on a price (return) time series of time step length $\delta$. I will apply a GARCH(1,1) model to subsamples at time intervals length $k\...

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