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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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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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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53 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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44 views

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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80 views

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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46 views

SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
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27 views

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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40 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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40 views

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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86 views

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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91 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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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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65 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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109 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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96 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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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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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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107 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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171 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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59 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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110 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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470 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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What kind of ARMA-GARCH model is that?

My question is what kind of ARMA-GARCH model is the following equation and how to specify it in rugarch R module: $$r_{t+1}- r_t = \alpha_0 + \alpha_1r_t+\...
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Rolling forecast using GARCH model

EDIT This is not a duplicate of my original question linked, since I have since overcome that problem and have posted an answer. Since solving the previous problem, I have run into the problem ...
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62 views

GARCH Parameters Standard Errors

How do you compute the standard errors of a GARCH model estimated with MLE ? This paper references a method by Bollerslev-Wooldridge: [...] and computed standard errors using the robust method of ...
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181 views

Can you use GARCH-MIDAS for intraday data?

I'm working on a project to forecast volatility and I'm using intraday data (1 min). I want to include exogenous variables to the model that have daily frequency. I was wondering if GARCH-MIDAS can be ...
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Log likelihood function, GARCH(1,1) with asymmetric term

I am modelling a GARCH(1,1) and a GARCH(1,1) with an asymmetric term. $$h(t)=\omega+\alpha\varepsilon(t-1)^2+\beta\sigma(t-1)^2$$ and $$h(t)=\omega+\alpha u(t-1)^2+\beta\sigma(t-1)^2 + \gamma (u(...
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63 views

Estimating an GARCH(1,1) model? Long hand method

I am really trying to invest some time to estimate a GARCH(1,1) method, I know there is many statistical packages that will do this for me (Eviews, MATLAB, R), but I am trying to do this by hand, so ...
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302 views

Is this the correct way to forecast stock price volatility using GARCH

I am attempting to make a forecast of a stock's volatility some time into the future (say 90 days). It seems that GARCH is a traditionally used model for this. I have implemented this below using ...
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VaR of ARCH model

Consider the following: $r_t = \theta r_{t-1}+u_t$ $u_t=\sigma_t\epsilon_t$ $\sigma^2_t=\omega+\alpha u^2_{t-1}$ $-1<\theta<1,\omega>0,\alpha \in(0,1)$ What is the 99% 2-day VaR of a ...
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Poor results forecasting stock price volatility using Python's GARCH model

As far as I understand, forecasting stock price volatility should be more achievable than forecasting absolute prices or returns. It seems as though GARCH models are the traditional and most widely ...
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267 views

RiskMetrics VAR calculations and conditional distribution of sum of log returns

According to Tsay's book in Chapter 7, for the Risk Metrics model: A nice property of such a special random-walk IGARCH model is that the conditional distribution of a multiperiod return is ...
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When modelling ARCH/GARCH effects, do we use excess returns?

When modelling ARCH/GARCH effects, do we use excess returns? Is it common in the literature to use excess returns when modelling volatility as opposed to raw return data?
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306 views

Fractionally Integrated GARCH

I am currently working on a project to compare different GARCH(1,1) models on a financial data set. I use the rugarch package in R, and everthing seemed fine at first. However, now that I have started ...
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GARCH(1,1) and Value at Risk: Rolling window or non-overlapping samples

Currently studying on financial risk management. I want to test different methods of VaR estimation. I want to model volatility using a GARCH(1,1) model. My question is what should the size of the ...
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Time series analysis for stock prices

I am using GARCH model to simulate price of an index for 7 years. For input I am using difference of Log of prices (log of return). GARCH(1,1) has the lowest AIC, and I found parameters for the ...
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Predicting stock returns with GARCH in Python

I have seen this post: Correctly applying GARCH in Python which shows how to correctly apply GARCH models in Python using the arch library. Now I am wondering how I ...
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134 views

Volatility clustering and Behavioral Finance, possible explanation

Currently studying about time series modelling of financial data and faced the known GARCH$(p,q)$ model for modelling volatility. We observe that big changes are followed by large changes and vice ...
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211 views

Kurtosis in GARCH

In a GARCH(1,1) model $$ x_t = \sigma_tz_t$$ $$\sigma_{t+1}^2=a_0 + a_1x_t^2 + b_1\sigma_t^2$$ the kurtosis (when it exists) can be shown to be equal to $$ \kappa_x = \kappa_z \frac{1-(a_1+b_1)^2}...
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Unconditional correlation in CCC GARCH

What is the unconditional correlation (covariance) in CCC GARCH model $$\mathbf{x}_{t+1} = \mathbf{H}_{t+1}^{1/2} \mathbf{z}_{t+1}$$ $$\mathbf{H}_{t+1} = \mathbf{D}_{t+1}^{1/2} \mathbf{R} \mathbf{D}_{...
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140 views

GARCH fit: “failure to achieve convergence”… a problem?

Sometimes when one is trying to fit a GARCH model may happen that in the estimation summary (whatever software is) there is written "failure to achieve convergence after n iteration" or similar things....