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12
votes
2answers
5k views

Why do we use GARCH(1,1) to predict volatility?

What makes GARCH(1,1) so prevalent in modeling especially in academia? What does this model has that is significantly better than the others?
11
votes
1answer
520 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: ...
11
votes
0answers
2k views

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 ...
8
votes
3answers
820 views

DSP: stationary non-periodic signal: what's the best causal technique?

This is a bit DSP-related: so if you turn your non-stationary time series into a stationary process, you'll probably see that it is not periodic.. This is an issue for Fourier-based techniques because ...
6
votes
2answers
196 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 ...
5
votes
6answers
1k views

Find the order of an ARMA model (q & p )

I fit an ARMA model in Matlab and before I calculate the predicted value with the prediction error I set the order $(p,q)$ to some random value. But how can I determine the number of AR (p) and MA ...
5
votes
1answer
2k views

Mean reverting strategies

I would like to take advantage of a volatile market by selling highs and buying lows. As we all know the RSI indicator is very bad and I want to create a superior strategy for this purpose. I have ...
5
votes
1answer
149 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 ...
5
votes
2answers
232 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 $ ...
5
votes
0answers
281 views

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 ...
4
votes
1answer
422 views

How is the MA (moving average model) useful?

How is the MA model useful in modeling financial data, for example the stock indices? For example, from what i understand in the AR (auto-regressive) model portion, we can use the ADF test to check ...
4
votes
1answer
1k 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 ...
4
votes
1answer
206 views

ARIMA model, cannot get rid of low order ACF spike

I've gone through all the steps to fit a good ARIMA model - I plotted the data, I looked at the ADF tests, I looked at the ACF plot with no AR and MA terms just a constants. I came up with an ...
4
votes
1answer
101 views

Is that a good way to work with the ARMA model?

I would like to share with you what I am doing to get your point of view, and to make a better trading system in collaboration. I am working on EURUSD forex, and I am trying to find a way to place ...
4
votes
0answers
53 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 ...
2
votes
1answer
45 views

Estimating Carma(2,1) parameters (using yuima package)

I am very new to R, and particularly to the yuima package, so I was hoping someone would be able to help me. I have some data (daily prices) that I wish to fit to ...
2
votes
1answer
75 views

Define polynomials of an ARMA process

I just started out with financial time series and I'm a bit stuck with ARMA models. I have the following ARMA process: $-4X_t + X_{t-2} = Z_t + 0.2 Z_{t-1}$ Now I am being asked for the polynomials ...
2
votes
0answers
120 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 ...
1
vote
1answer
43 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 ...
1
vote
1answer
134 views

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 ...