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.

Filter by
Sorted by
Tagged with
0
votes
1answer
35 views

Ratios or combinations of risk measures

In finance, alternative risk measures such as value-at-risk (VaR) and GARCH are introduced as replacements to standard deviation volatility. Is there any application or value where several risk ...
0
votes
1answer
40 views

How to obtain one-step ahead forecast in Python based on GARCH?

I am trying to produce one-step ahead forecast using GARCH in Python using a fixed windows method. I ultimately want to put the code below in a for loop, but this code snippet does not perform as I ...
2
votes
2answers
55 views

What is the difference between parametric and non-parametric models?

I'm reading about volatility modelling and I came across the concept of parametric and non-parametric models. For example, GARCH is a parametric model and Realized Volatility is a non-parametric model....
0
votes
1answer
24 views

GARCH(1,1) forecast plot in R with training data

I've fit a GARCH(1,1) model in R and would like to create a plot similar to the one in this question: Is this the correct way to forecast stock price volatility using GARCH Could someone direct me to ...
1
vote
1answer
43 views

Do you need to simulate the entire stock path for option pricing with GARCH?

I'm trying to price European options with a GARCH volatility model. What I have is a program that calibrates the GARCH volatility process for a stock which I intend to use to value a derivative on the ...
0
votes
0answers
29 views

Backtesting conditional VaR

I'm writing a thesis about conditional VaR of Standard & Poor's 500 index. I have fitted my log-returns with GARCH(1,1)-proces and then made some conditional VaR-forecast (500 observations) with ...
2
votes
2answers
85 views

How to predict realised variance?

I am trying to predict the realised daily close to close variance of an equity index. I checked the literature on volatility forecasting and tried a bunch of things on a dataset for the S&P 500....
0
votes
1answer
31 views

n day ahead forecast for assymmetric DCC model

I am working on forecasting covariances with the use of MGARCH models. I was wondering if anyone knows how to implement a n-day ahead forecast of the aDCC (assymmetric DCC) model in R. The rmgarch ...
2
votes
0answers
56 views

Implied volatility surface modelling in filtered historical simulation

What is the best way to model implied volatility surface in filtered historical simulation (other than keeping it constant)? Is it appropriate to apply GARCH-like model to every point on the surface? ...
0
votes
1answer
74 views

White noise in ARCH model

I am looking at the ARCH model where we have $\hat{\varepsilon}_t^2=\alpha_0 + \alpha_1\hat{\varepsilon}_{t-1}^2 + \alpha_2\hat{\varepsilon}_{t-2}^2 + \cdots + \alpha_q\hat{\varepsilon}_{t-q}^2 +v_t$ ...
2
votes
0answers
34 views

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 ...
2
votes
1answer
49 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}...
0
votes
1answer
16 views

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 ...
0
votes
0answers
16 views

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.
0
votes
0answers
29 views

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: ...
2
votes
1answer
100 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 ...
2
votes
2answers
112 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} ...
0
votes
1answer
52 views

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 ...
0
votes
0answers
25 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 ...
0
votes
1answer
42 views

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 ...
0
votes
1answer
50 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 ...
4
votes
1answer
178 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 ...
2
votes
1answer
52 views

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'...
2
votes
1answer
111 views

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 ...
0
votes
0answers
38 views

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 ...
0
votes
0answers
52 views

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. ...
0
votes
2answers
80 views

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 ...
1
vote
1answer
73 views

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, ...
3
votes
0answers
46 views

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 ...
1
vote
1answer
284 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 ...
0
votes
1answer
85 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 ...
3
votes
1answer
127 views

evaluating garch models

I used ugarchroll to backtest my garch model on S&P returns this is my code ...
1
vote
2answers
182 views

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.
6
votes
1answer
105 views

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 ...
2
votes
2answers
137 views

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 ...
0
votes
0answers
44 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, ...
1
vote
1answer
208 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 ...
1
vote
1answer
209 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 ...
0
votes
1answer
56 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 ...
1
vote
0answers
153 views

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 ...
3
votes
1answer
147 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 ...
1
vote
1answer
181 views

SARIMA+GARCH model

The model ARIMA+GARCH writing as this form with the rugarch package in R: ...
2
votes
0answers
46 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 ...
0
votes
1answer
88 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 ...
0
votes
1answer
63 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 ...
1
vote
0answers
164 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 ...
1
vote
1answer
558 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-...
2
votes
0answers
91 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 ...
1
vote
0answers
71 views

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 ...
0
votes
1answer
127 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 ...

1
2 3 4 5
7