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2
votes
2answers
83 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 ...
2
votes
2answers
109 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?
2
votes
1answer
73 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 ...
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 ...
4
votes
0answers
84 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 ...
4
votes
0answers
141 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
3
votes
0answers
48 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 ...
3
votes
0answers
173 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
0answers
591 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 ...
2
votes
0answers
767 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 ...
2
votes
0answers
242 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
votes
0answers
124 views

What does negative gamma mean in APGARCH model?

I got a gamma of -0.1321677. ...
2
votes
0answers
413 views

Markov-Switching E-GARCH with R

I am looking for a R library for modeling a Markov-Switching E-GARCH process. In other questions at StackExchange related to GARCH models, the package rugarch is often mentionned. Do you recommend it ...
1
vote
0answers
24 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: ...
1
vote
0answers
52 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 ...
1
vote
0answers
50 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 ...
1
vote
0answers
326 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 ...
0
votes
0answers
39 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
25 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
16 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: ...
0
votes
0answers
59 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 ...
0
votes
0answers
145 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 ...
-1
votes
0answers
14 views

garchFit formula problems in R

I am working on a Financial Time Series project in R. I am using GMVP.R which has this line: m1=garchFit(~1+garch(1,2),data=rtn[1:t,i],trace=F) I am trying to understand what the 1 before ...