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.
408 questions
1
vote
0
answers
73
views
Can you approximate stochastic volatility processes using GARCH processes?
Let me specific. Suppose that you have the following process:
\begin{align}
z_t &= \sigma_t \epsilon_t \\
\sigma_t &= \sigma \exp \left( \frac{v_t}{2} \right)
\end{align}
where $v_t$...
- 2,536
2
votes
1
answer
364
views
Modelling Geometric Browian Motion price model with stochastic volatility
I'd like to generate scenarios (simulate several paths of the process) for several stocks using multinomial Geometric Brownian Motion under Stochastic volatility assumption. I'm going to use it in my ...
1
vote
0
answers
149
views
Modelling volatility for higher frequency data
I'm doing some academic work on volatility forecasting. I've got 1-minute bar data. It is not clear to me what model is best suited for forecasting volatility when higher frequency data is available.
...
- 472
2
votes
0
answers
59
views
Non-Linear Time-Dependent Volatility
My data consist of monthly electricity futures contracts. Unlike other commodities, electricity is delivered throughout a month (rather than on a specific date), which means that, as the active month ...
- 555
2
votes
0
answers
97
views
Garch models - are they useful for hedging? If so how?
I understand that Garch models are useful to predict volatility. But are they useful for hedging in practice? If I want to hedge volatility, why shouldn't I just use a Variance Swap?
In other words, ...
- 8,621
0
votes
1
answer
85
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 ...
- 3,090
0
votes
2
answers
2k
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 ...
- 103
2
votes
2
answers
930
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....
- 472
1
vote
1
answer
2k
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 ...
- 11
1
vote
1
answer
312
views
What are some good models for stock price predictions?
For the fitting and forecasting of time-series data on stock price, the most frequent model I have heard of is ARIMA. ARIMA is actually conducting a regression of stock prices and residuals of stock ...
- 111
1
vote
1
answer
325
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 ...
- 912
2
votes
2
answers
270
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....
- 263
1
vote
2
answers
335
views
$n$-day ahead forecast for asymmetric DCC-GARCH 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 (asymmetric DCC) model in R. The ...
- 11
3
votes
0
answers
185
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? ...
- 41
0
votes
1
answer
969
views
White noise in ARCH model
I am looking at the ARCH model where we have $\hat{\varepsilon}_t^2=\alpha_0 + \alpha_1\hat{\varepsilon}_{t-1}^2 + \alpha_2\hat{\varepsilon}_{t-2}^2 + \cdots + \alpha_q\hat{\varepsilon}_{t-q}^2 +v_t$
...
- 73
2
votes
0
answers
55
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 ...
- 21
2
votes
1
answer
159
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}...
- 2,536
0
votes
1
answer
259
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 ...
- 186
6
votes
2
answers
859
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 ...
- 73
2
votes
2
answers
837
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} ...
- 2,536
2
votes
1
answer
508
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 ...
- 912
0
votes
1
answer
576
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
1
answer
635
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 ...
5
votes
1
answer
1k
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 ...
- 912
2
votes
1
answer
596
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'...
- 2,536
5
votes
1
answer
611
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 ...
- 314
0
votes
0
answers
182
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. ...
- 101
1
vote
1
answer
267
views
What is a good way to think about and estimate VIX half life?
Would it make sense to run an AR(1) regression to estimate a beta and then estimate the half life as -ln(2)/beta?
- 1,029
0
votes
2
answers
599
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
1
answer
363
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
0
answers
118
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
1
answer
4k
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 ...
- 121
0
votes
1
answer
117
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 ...
- 331
4
votes
1
answer
351
views
evaluating garch models
I used ugarchroll to backtest my garch model on S&P returns
this is my code
...
- 339
1
vote
2
answers
2k
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.
- 11
6
votes
1
answer
367
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
...
- 339
2
votes
2
answers
1k
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 ...
- 21
1
vote
1
answer
838
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 ...
- 43
1
vote
1
answer
722
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 ...
- 13
0
votes
1
answer
77
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
0
answers
646
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 ...
- 111
3
votes
1
answer
339
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 ...
- 732
1
vote
2
answers
965
views
3
votes
0
answers
99
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 ...
- 31
3
votes
2
answers
425
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 ...
- 175
0
votes
1
answer
122
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
0
answers
535
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
1
answer
2k
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-...
- 175
2
votes
0
answers
188
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 ...
- 21
2
votes
0
answers
90
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 ...
- 21