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Questions tagged [arma]

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0answers
80 views

White noise process common in daily return series

When I fit an ARMA-GARCH in some financial time series, I often observe through the ACF/PACF that the daily return series shows a white noise process at once, especially in Forex time series. In ...
0
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0answers
107 views

ARMA model Excel

I am working for a company and they ask me to forecast the cashflow for 12 months. Therefore, I am doing an ARMA model on excel. I have already modelled the AR model. Nevertheless, when I try to code ...
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0answers
26 views

Chances a forecasting model exceeds/deceeds a specified threshold

I am interested in determining the confidence of a forecasting model with applications to quantitative finance. I have the following multivariate data $X$: \begin{align} X(t) \sim F_{X}(t) \end{...
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0answers
116 views

What can cause autocorrelation in higher lag orders of returns?

I am fitting an AR(p) model to the daily time series of S&P500 returns. I have examined AIC/BIC up to 5 lags and both show that model with 2 lags is optimal. However, when I examine the residuals ...
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0answers
107 views

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 ...
1
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1answer
236 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 ...
2
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0answers
191 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 ...
4
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1answer
322 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 ...
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0answers
114 views

Estimating time-varying tail dependence for Archimedean copulas

Patton (2006) defines the upper tail dependence coefficient for a time-varying bivariate SJC copula as $$\tau^u_t=\Lambda \left(\omega_u + \beta_u \tau^u_{t-1}+\alpha_u \frac{1}{10}\sum^{10}_{i=1}|u_{...
2
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1answer
390 views

Python regenerating ARMA params using statsmodels

I am trying to regenerate the ARMA parameters from statsmodel in python. The code I am using is: ...
0
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1answer
160 views

Python statsmodel ARMA question

I am reading through the documentation of statsmodel package in python from the link The (p,q) order of the model for the number of AR parameters, differences, and MA parameters to use. How do I ...
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0answers
58 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 - \...
2
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1answer
243 views

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 ...
1
vote
1answer
656 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 ...
4
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1answer
317 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 ...
10
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1answer
2k 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 (...
2
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1answer
195 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
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1answer
91 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
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0answers
760 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-...
6
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2answers
1k 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 ...
6
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0answers
114 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 ...
4
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1answer
850 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 ARMA(0,1,...
6
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1answer
349 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 ...
7
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6answers
8k 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
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2answers
517 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 $ ...
4
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1answer
2k 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 ...
5
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0answers
875 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 ...
20
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1answer
6k 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 ...
12
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1answer
836 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: ...
4
votes
1answer
4k 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 ...
8
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3answers
868 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 ...
8
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1answer
3k 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 ...