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2
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0answers
50 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
votes
0answers
96 views
+100

Correctly applying GARCH in Python

Problem: Correct usage of GARCH(1,1) Aim of research: Forecasting volatility/variance. Tools used: Python Instrument: SPX (specifically adjusted close prices) Reference material: On Estimation of ...
0
votes
1answer
11 views

When the two time series with different length, how could we analysis them with a bivariate GARCH model?

At this moment, i need to do the analysis of rouble/us dollars exchange rate and the stock market index in Russia, I prefer to do that in a multivariate GARCH model. However, I have a question about ...
2
votes
0answers
31 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
vote
0answers
29 views

Why random walk Metropolis Hasting algorithm works bad on GARCH(1,1) parameters estimation

I am trying to estimate the parameters of the GARCH(1,1) model with MCMC method, firstly, I read the paper: http://mpra.ub.uni-muenchen.de/12985/1/MPRA_paper_12985.pdf Metropolis Hasting method is ...
2
votes
4answers
189 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: ...
1
vote
1answer
66 views

Log returns and GARCH models

I try to model currency rates volatility using GARCH models through the RUGARCH package in R. Starting from the observed currency rate series, I compute the log-return through: ...
2
votes
2answers
118 views

How to find the best fitting GARCH model for a portfolio composed of 3 ETFs in R?

I am doing a project for my class Financial Time Series in which I am trying to forecast my portfolio log returns using a GARCH fit. I am having a bit of trouble determining the best way to fit this ...
0
votes
2answers
112 views

what volatility do we calculate using GARCH model

what volatility do we calculate using GARCH model, Historical vol or Implied vol or Future Vol or Actual vol.
3
votes
0answers
67 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 ...
1
vote
0answers
54 views

GARCH parameters

I'm trying to estimate parameters of GARCH(p,q) model. I tried p=1, q=1 with t-distribution errors. Ljung-Box showed no correlation in residuals and squared residual. But the null hypothesis that ...
0
votes
0answers
33 views

Dummy variable and negative estimation in GARCH (1.1)

I am trying to use GARCH model for my research. However, when I am running them, I see negative value for alpha and beta. How I can restrict them so that they do not provide me any negative value. Is ...
0
votes
0answers
18 views

garchOxFit in R-oxo file does not match

Could someone please help me with trying to get the Ox interface to work in R. I get the following errors as output: This version may be used for academic research and teaching only Link error: ...
2
votes
1answer
84 views

Volatility estimation: sampling frequency and scaling

I have a year long stock data sampled at 5 min frequency and would like to estimate monthly volatility using it. I am thinking using GARCH or TGARCH for volatility estimation. However, I am not sure ...
2
votes
2answers
140 views

Is there a way to adjust R PerformanceAnalytics function VaR with EWMA or GARCH method?

Is there a way to upgrade R PerformanceAnalytics function VaR with more risk sensitive approaches like EWMA or GARCH? Or is there another R package which can handle the issue?
1
vote
1answer
178 views

HAR-RV, realized GARCH and HEAVY model for realized volatility

I don't have much experience with volatility modeling using intraday data but I'm in the process of collecting 5mins data. Currently I have ~6 months of data. Is it enough to use these models with ...
2
votes
2answers
142 views

Understanding the conditioning in a GARCH process

In a GARCH model like the following $$y_t=\sigma_tz_t,\\ \sigma_t^2=\omega(1-\alpha-\beta)+\alpha y_{t-1}^2+\beta \sigma_{t-1}^2$$ where $z_t$ is assumed to be iidN(0,1), we say that conditional on ...
3
votes
2answers
148 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 $ ...
1
vote
0answers
54 views

volume augmented garch(1,1) model in matlab

Actually I want to add volume traded of a stock in my Garch(1,1) model to forecast the volatility.In Matlab I can specify the model as garch(1,1) and then use estimate and forecast commands.But I am ...
0
votes
0answers
67 views

Volatility clustering but (G)ARCH not good fit

I'm looking at a time series that appears to be white noise. The ACF/PACF are in the test bounds. Applying the Ljung-Box test for various (maximum) lags gives me high p-values (i. e. I cannot reject ...
1
vote
0answers
56 views

rugarch and rolling estimation

I use Rugarch for a long time in order to calibrate GARCH models on FX rates time series and perform simulations. I am trying to understand the ugarchroll method. However even if I can find plenty of ...
4
votes
0answers
88 views

Does GARCH derived variance explain the auto-correlation in a time series?

Given a time series of $u_i$ returns where i=1 to t. $\sigma_i$ is calculated from GARCH(1,1) as $\sigma_i^2=w+\alpha u_{i-1}^2 +\beta \sigma_{i-1}^2$ . What is the mathematical basis to say that ...
2
votes
1answer
1k views

GARCH model and prediction

I have a question about the prediction of volatility and returns of a time series. Basically it is a question about prediction in the ...
3
votes
1answer
957 views

GARCH(1,1) good fit found, how to predict one day volatility ahead?

I used SPY data to fit GARCH(1,1) in my model. My data starts from Jan, 2000 until Dec, 2013. I compared the volatility using runSD on the 21 rolling window and GARCH(1,1). It looks a pretty good fit ...
1
vote
1answer
162 views

How would you correct a GARCH model to deal with non mean reverting volatility?

I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals ...
2
votes
2answers
119 views

What impact does arbitrage have on realised volatility estimates?

Doing some research modeling/estimating volatility in the bitcoin market. There is quite a bit of scope for arbitrage within crypto-currency markets. Wonder if this has any impact on my volatility ...
0
votes
2answers
646 views

Optimal lag length selection criterion in GARCH(p,q) model using MATLAB

As assessed by the title, I'm trying to estimate a GARCH(p,q) model to forecast stock market volatility and, in order to be able to do that, I've to identify the optimal number of lags, p and q, to ...
0
votes
0answers
152 views

Monte Carlo American Option Pricing under GARCH(1,1) volatitliy

I am attempting to price a couple of at-the-money American option using the LSM algorithm and GARCH(1,1) volatility. The LSM code I have works correctly for constant volatility, however, when I switch ...
3
votes
1answer
175 views

What return equation is Engle referring to in his Nobel lecture?

Engle comments in "Risk and Volatility: Econometric models and Financial Practice" that If the price of risk were constant over time, then rising conditional variances would translate linearly ...
2
votes
1answer
62 views

How come the existence of ARCH effect is not a violation of Random Walk Hypothesis 3?

An ARCH (autoregressive conditional heteroscedastic) (1) model is: $r_t=\mu +a_t$, where $a_t=$return residual, and $\mu$ is the drift of the stock return $a_t=\sigma_t\epsilon_t$, where ...
3
votes
1answer
92 views

Time-Varying Volatility and Conditional Likelihood

Engle's comment in his seminal paper "Risk and Volatility: Econometric models and Financial Practice" mentions that I had recently worked extensively with the Kalman Filter and knew that a ...
0
votes
1answer
84 views

Can we model components in a set of multivariate multi-period time-series data?

There are N data sets in periods occurring weekly/monthly, across a 10-year historical timeline. In each period, five dates are observed (labelled a to e), where a denotes the day the period ...
1
vote
3answers
800 views

How to trade volatility?

I am analyzing the volatility of financial stock returns and let's say I have a pretty good model to forecast tomorrows volatility of the stock returns. So let's say for simplicity reasons I have a ...
3
votes
0answers
182 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 ...
3
votes
1answer
219 views

Evaluation volatility with Garch model

I want to forecast the volatility (with Garch) of a canadian stock in 5 months with daily returns. How many data do I have to collect ? Thanks.
3
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1answer
145 views

Cross validation of a garch model

Suppose I divide a time series into 10 sequential time windows, where each window contains 1000 data points. I want to do test 5 different garch models using cross validation. So for each model, I ...
5
votes
0answers
1k 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 ...
3
votes
2answers
337 views

How to compare volatility models?

What are the most popular ways to compare volatility models? Suppose I wanted to compare the forecasting accuracy of a GARCH(1,1) model with the historic 30 day volatility. What method should I use? ...
2
votes
1answer
553 views

GARCH(1,1) prediction in R - Basic Questions

Background to question: Hi, I was trying to fit a GARCH(1,1) model to the variance of log returns of a series, and ARMA(0,0) for the mean. I was using the fGarch package to do this. The aim of the ...
3
votes
1answer
604 views

Fitting a GARCH BEKK model

I am trying to find whether there is significant volatility transmission between two price series (t=1000). A literature review learned me that the GARCH BEKK model is suitable for this. The SAS ...
3
votes
0answers
630 views

FIGARCH estimation in R

I am trying to estimate a FIGARCH(1,1) model in R for Value-at-Risk purposes. As I understand it, the rugarch package does not support FIGARCH or FIEGARCH. To that end, I used the garchOxFit function ...
0
votes
2answers
385 views

garchOxFit in R

Could someone please help me with trying to get the Ox interface to work in R. I followed the steps outlined in this paper (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1752095), but I get the ...
1
vote
0answers
361 views

GJR-GARCH modeling in stata

I am wanting to run a GJR-Garch model in stata and I am having problems identifying what command I need to put into the system. When using the commands I receive two different ways to do so and I am ...
2
votes
0answers
831 views

How to calculate the conditional variance of a time series?

I am reading a paper where the term conditional variance is mentioned, but I am not really sure what is meant by this and how this can be calculated: Fig. 2 shows the conditional variances of the ...
3
votes
1answer
312 views

Volatility Return Distribution/Garch Modeling

For simplicity sake, if stock returns are normally distrusted, would that imply that second moment, variance/volatility, is chi-squared distrusted? If so wouldn't that imply the statistics(employed to ...
11
votes
1answer
849 views

So many volatility models. Any comparisons of them?

Are there any papers that make an explicit contrast/comparison of the following (or other) vol models in terms of the suitability for addressing some empirical problem? Wavelet multiresolution ...
6
votes
1answer
2k views

Forecasting using rugarch package

I want to do one step ahead in-sample forecasts. My data can be found here. This is just a data frame with the date as the rownames. I specify my model and do the fit and show the plots with ...
9
votes
1answer
307 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: ...
2
votes
0answers
260 views

Error term/Innovation process in ARCH/GARCH processes?

I am wondering about the distribution of the error term/innovation process in a ARCH/GARCH process and its implementation, I am not sure about some points. The basic assumption is ...
2
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0answers
125 views

What does negative gamma mean in APGARCH model?

I got a gamma of -0.1321677. ...