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0answers
17 views

VEC GARCH (1,1) for 4 time series

I have to estimate a VEC GARCH(1,1) model in R. I already tried rmgarch, fGarch, ccgarch, mgarch, tsDyn. Has somebody estimated a model like that? ...
2
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2answers
89 views

Augmented Dickey-Fuller Test/ Unit Root test on multiple time series dataframe in R

I have a dataset/dataframe in which I have calculated the daily log returns of five thousand companies and these companies are as column as well. I want carry out ADF test on this dataframe. I have ...
0
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0answers
31 views

CCC-Garch predict

So I'm trying to measure the VaR of 2 stock with a multivariate GARCH model, so im using the CCC model. I need to predict the standard-diviation and the mean but the ...
6
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2answers
189 views

What is the preferred GARCH method in practice?

My advance apologies, if this question is too naive or basic. Please be patient with my first experiences with SE; ask for clarification, if needed. I recognize there are many (often-criticized) ...
2
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2answers
167 views

Multivariate GARCH in Python

Is there a package to run simplified multivariate GARCH models in Python? I found the Arch package but that seems to work on only univariate models. I'd like to test out some of the more simple ...
3
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3answers
351 views

Any package to run VAR-GARCH or VECM-GARCH models in R?

I need to estimate a multivariate VECM-GARCH (or simply VAR-GARCH) in R. Browsing on the internet, I did not find anything yet. Do you know if such kind of packages exists? Please, note that a BEKK ...
3
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4answers
1k views

Copulas simply explained

I try to understand the basic idea of copulas, however I am still struggling and hope that someone can help me. I understood that in general a copula is a function which links several marginal ...
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0answers
51 views

How to estimate constrained a constrained VAR(1) with MATLAB?

Suppose I want to estimate the following VAR(1) model: $$ Y_t = \mu + \Phi Y_{t-1} + \varepsilon_t $$ where $Y_t=(y_{1t}, y_{2t},…,y_{kt})'$, $\mu=(\mu_1,…,\mu_{k})’$ and $\Phi$ a matrix of ...
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1answer
31 views

Spread options on prices or returns?

I need some clarifications regarding spread options. I have always found them characterized as paying, at maturity, the difference between the prices of two underlying assets: $$ (S_1(T)-S_2(T)-K)^+ ...
3
votes
1answer
50 views

Basket Default Swap (BDS)

I would like to understand better the $n^{th}$ to default pair spreads of a basket default swap containing $m>n$ entities. For example, consider 2 single name CDS's with same spread and same ...
6
votes
1answer
74 views

Mutivariate t markets

We know that some markets exhibit marginals well approximated by Student t distributions. But what is the dependence structure? Is the multivariate density really elliptical (as we all wish for) or ...
2
votes
1answer
215 views

How to see the impact of one variable on a set of other variables?

Editing my question: I have decided to use multiple factor model to model my stress test. I am using factor shock method to implement the propagation of shocks. I am doing this according to a book ...
0
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2answers
209 views

Interpretation of PCs

I have computed PC1 and PC2 wts on future contracts derived from cumulative log differences. How can I use them to get back the theoretical price of each contract using those 2 pcs? Thanks in ...
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0answers
104 views

Estimating two normal random numbers with one equation

Subtitle: Estimating the correlation of the shocks driving two commodities in two multi-factor models I am fitting two 2-factor models to electricity and gas futures, respectively. In order to ...
5
votes
1answer
416 views

Major FX pairs - Pentahedron Data Structure

I read an interview today with Stephane Coquillaud. He talked about this idea of formulating a data set of the G5 currencies as a pentahedron. The obvious benefit is the fact that there is more ...
7
votes
3answers
1k views

Using rolling returns in a multivariate linear regression?

I am trying to use fundamental factors such as PE, BV, & CFO in a multivariate linear regression with the response variable being the rolling 1 month returns. But this approach seems flawed as the ...
9
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1answer
2k views

Time series price prediction and linear regression: using high/low rather than last quotes price

Discrete time series regression models, like ARIMA, are usually built around the assumption that we only have 1 available price for each period t, which I will call the Close. In reality asset time ...
6
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0answers
627 views

Alternative to Block Bootstrap for Multivariate Time Series

I currently use the following process for bootstrapping a multivariate time series in R: Determine block sizes - run the function b.star in the np package which produces a block size for each series ...