All Questions
36 questions
0
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0
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43
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eGARCH(1,1) model evaluation (R). How to assess model integrity?
I am using GARCH modelling for my bachelor thesis in Economics. I am entirely new to the concept, and have only been looking into these kind of models for about a week now. I am trying to do a ...
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1
vote
1
answer
97
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In copula modeling for time series data, why do we need to fit ARIMA/GARCH and then work on standardized residulas.?
I have read that for standard copula modeling, you can get empirical cdf of data and use it for copulas. But for time series data, we must first fit ARIMA/GARCH, get standardized residuals, and only ...
- 3,281
2
votes
1
answer
219
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Are ARMA-GARCH-type models suitable for monthly data?
I understand that ARMA-GARCH models and their variations are usually applied to daily time series. While I know that such models can be also estimated on monthly data, I have seen few applications in ...
- 3,281
2
votes
2
answers
6k
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How to fit a SARIMA + GARCH in R?
I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model.
I'm using rugarch:
...
- 3,281
3
votes
2
answers
425
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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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0
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0
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343
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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 ...
- 472
-3
votes
1
answer
110
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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 ...
- 3,281
1
vote
1
answer
312
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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 ...
- 167
2
votes
0
answers
55
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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 ...
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0
votes
1
answer
635
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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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0
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0
answers
182
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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. ...
- 101
3
votes
0
answers
118
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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 ...
1
vote
0
answers
646
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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 ...
- 111
0
votes
1
answer
5k
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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 ...
CommunityBot
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2
votes
0
answers
81
views
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+\...
- 2,946
10
votes
1
answer
4k
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ARMA+GARCH prediction with package rugarch (R)
I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework).
I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast (...
CommunityBot
- 1
5
votes
0
answers
1k
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Fitting Student t-distributions to log-returns
It seems that some tail-risk centric groups are bent on using Paretian and t-distributions to account for tail risk when fitting log-returns. It has been observed, however, that with and without ...
- 131
1
vote
2
answers
414
views
Error distribution assumption in a simple ARIMA model
why in an ARIMA-GARCH structure I have to assume an error distribution to run the estimation while in a simple ARIMA model it is not required?
Thank you
- 2,248
1
vote
1
answer
70
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Can GARCH volatility simulations generally be applied to return-modelling models?
This may be a naive question, but I still hope some discussion can elucidate a (so far) totally nebulous point for me.
I've recently learned that GARCH models can give one simulations of ...
- 942
25
votes
1
answer
10k
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Algorithm to fit AR(1)/GARCH(1,1) model of log-returns
I am fitting numerically an AR(1)/GARCH(1,1) process to index and stock log-returns, $r_t=\log(P_t/P_{t-1})$, where $P_t$ is the price at time $t$, and thus far am not clear on where the observed log ...
CommunityBot
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-1
votes
1
answer
116
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ARIMA vs ARIMA + GARCH [closed]
If an ARIMA model converges quickly, would using GARCH improve the forecast performance? By improve I mean provide longer time periods for forecasts. Basically trying to forecast returns.
- 8,621
1
vote
0
answers
227
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ARMA-GARCH Forecasting [closed]
I want to forecast a differenced time series of an Index using the combined ARMA-GARCH model (because I want to forecast the mean and not the variance). My model is a ARMA(2,2)-GARCH(1,1) model. So ...
- 21
1
vote
1
answer
639
views
Joint estimation of GARCH models with ARMA terms in the conditional mean: a necessity?
Supposing I am using the following models to forecast conditional volatility of index returns, whereby In-sample data is 1996-2007 and out of sample data is 2007-2012, using GARCH type models.
I have ...
CommunityBot
- 1
2
votes
0
answers
517
views
VARMA GARCH modelling in R
I want to simulate a VARMA-GARCH process in R. Unfortunately, I found no package to help me with that.
I tried modelling the MGARCH part on itw own and combine it with the VARMA simulation using MTS ...
- 21
3
votes
1
answer
742
views
Modeling tail data using Generalized Pareto distribution
I just estimated a ARMA(1,1)+GARCH(1,1)+Threshold order(1) equation for time series of stock prices.
Now I'm going to estimate the residuals' marginal ...
CommunityBot
- 1
3
votes
0
answers
1k
views
Forecast of ARMA-GARCH model in R
I managed to forecast a GARCH model yesterday and run a Monte Carlo simulation on R. Nevertheless, I can't do the same with an ARMA-GARCH. I tested 4 different method but without achieving an ARMA-...
CommunityBot
- 1
1
vote
0
answers
64
views
Distribution of AR and MA polynoms roots in ARMA/ARMA-GARCH models
I have another noob question. So, for example, I have ARMA(2,2) model:
$$ x_{t} = \phi_{1}x_{t-1} + \phi_{2}x_{t-2} + e_{t} + \theta_{1} e_{t-1} + \theta_{2} e_{t-2}$$.
So, I have 2 polynoms: $$1 - \...
CommunityBot
- 1
2
votes
1
answer
308
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distribution of AR, MA coefficients estimation in ARMA-GARCH models
could anyone give me an information about distributions of AR and MA coefficients via estimation?
So, for example, I have ARMA(1,1)-GARCH(1,1) model with the same AR(1) and MA(1) parameters ...
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1
vote
1
answer
1k
views
One-step ahead forecast of a AR(1) process (GARCH context)
I am using a Matlab toolbox for obtaining one-step ahead forecasts of the conditional mean from the ARMA(1,0)-GARCH(1,1) process and I have encountered a piece of code that contains, in my opinion, a ...
- 2,582
7
votes
2
answers
2k
views
Is it too important that my residuals be normal? I am Using an ARMA/GARCH model
I am trying to fit an ARMA/GARCH model to a time series. I found that the best candidate is an ARMA(1,0) + GARCH(1,1) with gaussian white noise
It has coefficients with p-values near cero and the ...
- 4,357
7
votes
1
answer
430
views
Filtering out AR(1) effects before using stochastic volatility model
I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
6
votes
4
answers
3k
views
Is there any way to easily estimate and forecast seasonal ARIMA-GARCH model in any software?
I use R to estimate a seasonal ARIMA(8,0,0)(5,0,1)[7] model for the seasonal differences of logs of daily electricity prices:
...
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6
votes
0
answers
141
views
What kind of errors arise when I fit ARMA(1,1) to data generated from ARMA(1,1)-GARCH(1,1) process?
As far as I know estimates of parameters of ARMA(1,1) are asymptotically optimal when fitted to data from ARMA(1,1)-GARCH(1,1) process, and only their variance increase, so when we assume large ...
- 1,018
5
votes
2
answers
753
views
Intuition behind interest rate models
I am modelling the 3M yield of US Treasuries using an ARMA/ GARCH approach. Most interest rate models (e.g. Vasicek) describe the process as follows:
$r_{t}-r_{t-1} = some ARMA+ \epsilon_t $
...
CommunityBot
- 1
4
votes
1
answer
7k
views
R ARMA-GARCH rugarch package doesn't always converge
I'm trying to compute the standard ARMA(1,1)-GARCH(1,1) as shown in this answer for an entire index,just to store in a database to quickly lookup values for back ...
CommunityBot
- 1
12
votes
1
answer
1k
views
rugarch: Joint estimation leads to different results
I want to fit an ARMA-GARCH model to my data using rugarch package in R.
First of all, I look at the acf and pacf:
...
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