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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1answer
40 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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22 views

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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1answer
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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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1answer
31 views

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 ...
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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 ...
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1answer
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Pricing options using the IG component GARCH model of BCHJ(2018)

Babaoglu, Christoffersen, Heston and Jacobs (2018) introduced a component GARCH model with inverse Gaussian innovations and an exponentially quadratic pricing kernel back in 2018. The article shouldn'...
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GARCH(1,1)-M MLE optimization with fmincon in R

I've searched thru dozens of papers and did not find in any of them satisfying and enough theoretical answers to my concerns. So I've combined everything what I found below. Please indicate if my ...
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Evaluating Markov switching garch models with R

Hello I have been working on a Markov switching GARCH model my intention is to use it to trade options volatility . I have created a Markov switching garch model using the MSGARCH package in R and in ...
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Fitting a non-stationary GARCH model

I'm very new to financial time series. I have a dataset containing the daily simple returns of the Dow Jones Industrial Average and I want to model a (univariate) GARCH model for the daily logreturns. ...
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Extract the short-run and long-run volatility of any time series with component sGarch (rugarch)

I try to estimate a component sGarch model with the rugarch package in R. My goal is to extract the short-run and long-run volatility components of any time series. I am not interested in the ...
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How to project 1 Year ATM Implied volatility for SPX 500 1Year from now? Final goal is to calculate 1 Year Call prices on SPX 500 1 year from now?

I have the historical data for 1Year ATM Implied Volatility on SPX 500. I want to simulate the 1 year call option prices 1 year from now. What methods and approaches do I need to use? (Heston,GARCH, ...
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Expected Shortfall for ARMA-GARCH Model

I need to find an analytical solution for the 99% confidence expected shortfall (CVaR) for a long position of 100 dollars at time $t$ for an asset with returns modeled by an ARMA(1,1)-GARCH(1,1) model ...
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1answer
78 views

Forecasting Volatility using GARCH in Python - Arch Package

Disclaimer: Posted this on stackoverflow, but maybe here should be the right place to ask something about GARCH I'm testing ARCH package to forecast the Variance (Standard Deviation) of two series ...
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1answer
78 views

Is this regression suitable for fixed income products (negative interest rates)?

I am currently looking at a regression which tries to model EWMA volatility in the presence of negative interest rates. The regression is as follows and uses absolute return instead of relative in ...
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1answer
116 views

evaluating garch models

I used ugarchroll to backtest my garch model on S&P returns this is my code ...
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How to fit AR(1)-GARCH(1,1) model in R? [closed]

I am currently working on the AR(1)+GARCH(1,1) model using R. I am looking out for example which explains step by step explanation for fitting this model in R.
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1answer
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Error message when backtesting GARCH in R

I am trying to backtest my ARCH model using ugarchroll from rugarch package in R, but I am getting this warning message ...
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2answers
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Pros and cons of mean equation equal to zero in a GARCH model

I fitted a standard GARCH model. The mean equation has no AR or MA terms. All the coefficients in the variance equation are significant at 5%. However the mean equation has a constant term equal to ...
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42 views

How can I estimate a dynamic GARCH model using a Kalman filter methodology in R or MATLAB?

Does anyone know of any R or MATLAB packages for estimating GARCH models using Kalman filtering or any other state-space methodology? I would like to estimate a GARCH so that not only the variance, ...
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1answer
125 views

Manually calculating and backtesting VaR and CVaR from DCC-GARCH R

I estimated a GARCH fit to the log returns of three series (CAC 40, a french real estate index and french T10 bond yield series) using rugarch. I then manually ...
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1answer
161 views

Duan (1995) GARCH Option Pricing Model with MATLAB

This is the MATLAB code that replicates the option pricing model proposed by Duan in his paper "The GARCH Option Pricing Model". However, the parameters estimated in the file do not match with the ...
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Weighting schemes - Volatility

One extension to this weighting scheme is to assume a long-run variance level in addition to weighted squared return observations. The most frequently used model is an autoregressive conditional ...
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Combining SARIMA and GARCH model for prediction in python

I need to understand the concept of combining (S)ARIMA and (G)ARCH model for the predicting time-series data. I understand that after fitting the arima model ...
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1answer
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model high frequency bitcoin volatility

I am trying to model volatility of 1-minute returns of BTC, but it seems to me that the data do not behave traditionally. I tried fitting GARCH, eGARCH with ARMA (1,1) or (2,0), but I am not confident ...
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1answer
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SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
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how to model NGARCH using 5min frequency data?

NGARCH model using 5-min High-frequency data in R I wanted to analyze some 5 minute frequency data of stock market. My teacher asked me to use NGARCH to model, but I didn't know how to program.Here ...
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1answer
67 views

Confidence Intervals for ARMA+GARCH forecasts

I have fitted an ARMA(1,1)+GARCH(1,1) model to my logreturns series. When it comes to my standarized error's distribution however, I have opted for a Skewed Generalized Error Distribution, because of ...
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1answer
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Covariance matrix from GJR-GARCH?

I am implementing a AR(1)-GJR-GARCH(1,1) model to some asset returns, and I would need to have a covariance matrix but I struggle to see how I can compute one from the model I used? I know I can have ...
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To calculate the Hedge Efficiency and Optimal Hedge Ratio with BEKK in R

I estimated an MGARCH-BEKK model (using the R package BEKK, i.e. Baba, Engle, Kraft and Kroner; see Engle and Kroner (1995)) on time series of spot and futures ...
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1answer
318 views

ARMA+GARCH day-trading strategy

I have a question regarding this particular post on quantstart: https://www.quantstart.com/articles/ARIMA-GARCH-Trading-Strategy-on-the-SP500-Stock-Market-Index-Using-R In it, he designs a day-...
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76 views

Portofolio optimization using ARMA-GARCH-EVT-Copula

I am currently trying to do some portfolio optimization by reproducing the methodology found in Sahamkhadam, Stephan & Östermark (2018) ("Portfolio optimization based on GARCH-EVT-Copula ...
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What's the interpretation behind this GARCH modeling?

I have an ARIMA model for monthly returns of the brazilian stock market index. Then I test the residuals of the model for ARCH effects. The ACF/PACF of squared residuals show that there are no ...
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How to forecast monthly volatility with daily gjrGarch estimates

I'm currently writing a paper and need to regress the 22 days realized volatility of the following month on its GARCH estimate and the 126days realized volatility up to t=1 The paper im referring to ...
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why we seldom see application of copula-garch model in macroeconomic

I find a lot of reference about copula-garch in finance market,but it seems that articles about copula-garch model in macroeconomic are rare.Is there any instrinc problem when it comes to ...
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1answer
116 views

Interpretation conditional volatility plot

I have plotten the log differences of exchange rates and in the same plot, I show the conditional volatility $\sigma_t^2$. The conditional volatility follows approximately the same path, but is much ...
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ARMA-GARCH estimation with EGB2 distribution

I want to estimate a ARMA-GARCH model by using the EGB2 distribution instead of the normal distribution. The model I want to estimate is: $$y_t = \mu + \phi_1 y_{t-6} + \phi_2 y_{t-8} + \theta_1 \...
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1answer
141 views

In-sample volatility measurement

I would like to know what is the most reasonable way to measure volatility in a sample of past observations. Aside from standard deviation, are more complex models like GARCH used for (historical) ...
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GARCH, EGARCH, GJR with different distributions

I have estimated different models based on different distributions. Since they are not nested models of each other, I can't use LR tests. But how can I compare the models? Can I do something with the ...
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Constraints by estimating GARCH, EGARCH, GJR-GARCH models

I know that by estimating an GARCH model, given by: $$\sigma_t^2 = \omega + \alpha \epsilon_{t-1}^2 + \beta \sigma_{t-1}^2,$$ $\omega, \alpha, \beta >0$ and $\alpha + \beta <1$. But what are ...
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1answer
149 views

How to account for intraday seasonality in GARCH model?

I am using a GARCH(1,1) model to estimate volatility. I am using hourly data to do this (I have hourly data for 100 trading days). Besides removing the first hour (which represents the overnight ...
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GARCH(1,1) one-step ahead volatility forecast biased, higher than Parkinson's HL volatility

I am trying to create one-step ahead forecasts for the S&P500 using a GARCH(1,1) model. I am using the rugarch package in R. As you can see, the forecasted points are consistently higher than the ...
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1answer
42 views

Backtesting EGARCH-NIG CVaR in R

I fitted an EGARCH model with a NIG distribution to a series of returns. Using the following link I tried got how I should calculate the CVaR of the model http://r.789695.n4.nabble.com/CVaR-with-NIG-...
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225 views

What is the best GARCH model for forecasting daily stock return and why?

If I want to forecast daily stock return let say Apple what would be the best GARCH model and why? (ARCH, GARCH-M, IGARCH, EGARCH, TARCH etc)
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RUGARCH (output) and Residual Resampling using GARCH(1,1)

I try to replicate the methodology proposed by Freedman and Peters (1984a, 1984b) which was applied in the famous paper by Brock, Lakonishok and LeBaron (1992) to generate many artificial log return ...
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0answers
112 views

Fitting a forecasting S&P500 roll volatilities

I have a time series of S&P500 prices, for which I have calculated log-returns and roll-volatility. My goal is to forecast daily realized volatility and test a straddle strategy based on it (I ...
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1answer
339 views

Multivariate Markov Regime switching GARCH

I have a regression with 4 independent variables and a dependent variable. I want to implement a Regime switching GARCH model but have been unable to find a package in R,Python or Matlab. MSGARCH ...
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1answer
131 views

GJR-GARCH model using garchFit function

I'm trying to use the garchFit function described here in order to define a GJR-GARCH model to estimate volatility and then forecast VaR. I tried using ...
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1answer
146 views

Standard GARCH(1,1) model with external regressors

I have a queastion how does a standard GARCH(1,1) model with external regressors in mean and variance euqations look like ? I know that standard GARCH(1,1) model without external regressors has the ...
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1answer
1k views

MLE error in R: initial value in 'vmmin' is not finite

I am trying to fit an ARIMA(1,1)-GARCH(1,1) model. I changed the starting values a lot but still its returning the same error. Below is my code which contains two functions ...

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