A copula is a multivariate distribution with uniform marginal distributions. Copulas are mostly used to represent/model the structure of dependence between random variables, separately from the margins.

learn more… | top users | synonyms

0
votes
1answer
36 views

How to fit a skew normal/t copula to data

I want to use either the skew normal copula or the skew t copula with a time-varying correlation matrix. But so far I haven't found any way to implement this either in R or Matlab. Would anyone be ...
2
votes
2answers
111 views

Fitting Copula and Simulation

I would greatly appreciate any insights into the problem described below, regarding using the data obtained from applying the functions of the 'rugarch' package into those from the 'copula' package. ...
0
votes
1answer
121 views

Clayton-Gumbel (BB1) and Joe-Clayton (BB7) time-varying copulas

I'm trying to estimate parameters for Mixed Dynamic Copulas (Clayton-Gumbel and Joe-Clayton) Is there any code in MATLAB? Thanks for any help.
3
votes
1answer
120 views

How to price this basket option?

Underlying assets are three global stock index : Eurostoxx 50, HSI, KOSPI 200 Maturity: 36 months with advanced redemption date in every 6 months if prices of indexes satisfy given conditions at each ...
1
vote
0answers
42 views

Problems in computing VaR with GARCH-GPD-copula approach

I use a time-varying Gaussian copula (with GARCH-filtered standardized residuals modeled semiparametrically with Gaussian kernel interior and GPD tails, i.e. generalized pareto distributed) to ...
3
votes
0answers
42 views

False warning messages in R, is it possible?

I'm modeling GARCH-filtered standardized residuals via semiparametric distribution with Gaussian kernel and GPD (generalized pareto distribution) tails with thresholds at 5% and 95%. For some series I'...
1
vote
0answers
39 views

Forecasting conditional returns in DCC-GARCH-copula approach in R

anyone who could help me interpreting and modifying this code? I have a dataset and want to reserve the last 100 returns for out-of-sample analysis. After specifying and fitting the garch-spd-copula, ...
1
vote
0answers
47 views

(Reproducible example) Conditional returns in GARCH-EVT-Copula context (with R)

I'm estimating a time-varying correlation matrix for the normal copula using the rmgarch package from R. I've found this code in the rmgarch.tests folder. I use the ...
3
votes
0answers
81 views

'GARCH - extreme value theory - copula' approach to estimate risk measures in R

I'm reading about this approach of using GARCH-EVT-copula methodology to separate univariate and joint estimation and then estimate for example VaR and ES. I wanted to try something similar, but my ...
1
vote
1answer
42 views

Relation of survival and non-survival Marshall-Olkin copula

Let us have two random variables $A$ and $B$ representing lifetimes of two elements of a system, where $A$ has cdf $F_A(x)$, $A \sim Exp(\lambda_1 + \lambda_{12})$ and $B$ has cdf $F_B(y)$, $B \sim ...
3
votes
1answer
93 views

Copulas and default probability

Assume a basket of 3 credits, each with some unconditional default probability ${q_i}(t) = \Pr [{\tau _i} \le t]$. Consider the joint CDF $H$ of the default times is given by $H(t,t,t) = \Pr [{\tau ...
1
vote
0answers
36 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_{...
1
vote
0answers
48 views

How to write time-varying functions in R? Applied example

Let's say I want to use a Gaussian copula $$C_{R_t}(\eta_1, ..., \eta_n) = N_{R_t}(N^{-1}(\eta_1), ...,N^{-1}(\eta_n))$$ with a time-varying correlation matrix $R_t$. Through DCC we model the ...
2
votes
1answer
78 views

Bivariate Gaussian copula with exponential margins

I got little bit lost in the formulas. Assume to have two random variables distributed exponentially $X_i \sim Exp(\lambda_i)$ and $X_j \sim Exp(\lambda_j)$. Thus, the distribution functions are $...
2
votes
0answers
37 views

Gaussian Copula with t margins

I am trying to fit a Gaussian Copula with t margins to my data (log returns of two stocks). It has already worked for a Gaussian Copula with normal margins with: normcopula_dist = mvdc(copula=...
4
votes
4answers
2k 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 ...
1
vote
0answers
53 views

copulas and time series

Can anbody explain how Copulas are used to describe the dependency between, for example, the return on two different stocks? I understand how Copulas are the "glue" that binds the two marginals ...
2
votes
1answer
453 views

Empirical copula

I am trying to find the empirical copula linking two random variables $X$ and $Y$. I have some data available but it's limited with respect to the variable $Y$ and I am not convinced it's enough data ...
0
votes
0answers
56 views

How to fit a copula to empirical data?

There are numerous types of Copulas one can choose to fit empirical data. My question is wow to select the 'best' copula to fit the data. More specifically, let's assume empirical data $f(x_1,y_1)f(...
2
votes
0answers
89 views

Gaussian Time-varing copula in R

I want to estimate the parameters of time-varing Normal Copula using R. A bivariate Normal copula is defined as following: The dynamic equation of dependance parameter ρ is : So I need the ...
0
votes
0answers
54 views

Estimating Credit VaR using a simulation of joint defaults with a copula

I'm trying to follow the steps Malz gives to calculate Credit VaR using simulation of joint defaults with a copula. I'm having trouble understanding some of the steps. My math knowledge is rather ...
5
votes
1answer
160 views

Simulate (imaginary) asset prices using random numbers that follow a Frank Copula

I didn't understand how to simulate asset prices by using non normal random numbers. I am assuming that it would be incorrect to use the standard Geometric Brownian Motion, since it is based solely ...
5
votes
3answers
845 views

Is there a copula that can estimate negative tail dependence?

I have encountered numerous copula estimators that can estimate time-invariant and time-varying linear and non-linear correlations on the interval $[-1,1]$, and these estimators are fully consistent ...
1
vote
0answers
104 views

Time-Varying Copulas (GAUSS)

Could anyone suggest me how to begin with Time-varying Copulas or Stochastic Copulas? I'm looking for the GAUSS code, however it seems there are only MATLAB code available over the internet. I'm ...
1
vote
1answer
143 views

Simulate from time-dependent copula in MatLab using COPULARND

I would like to simulate from a t-copula with time-dependent correlation matrices. Say I have a series of 2000 correlation matrices (obtained from a copula-DCC model for data consisting of 2000 ...
14
votes
2answers
1k views

Copula models and the distribution of the sum of random variables without Monte Carlo

There is a vast literature on copula modelling. Using copulas I can describe the joint law of two (and more) random variables $X$ and $Y$, i.e. $F_{X,Y}(x,y)$. Very often in risk management (credit ...
4
votes
1answer
191 views

Portfolio VaR with Copula?

Let the portfolio be given by: $$X=X_1+X_2$$ $(X_1,X_2)$ are dependent through a Copula function $C(u_1,u_2)$, such that the joint distribution is given by: $$F(x_1,x_2)=C(F(x_1),F(x_2))$$ What is ...
3
votes
0answers
152 views

how to apply a simple copula model

I'm playing around with copulas and wanted to generate some sample based on copula techniques in R. For this purpose I applied the following algorithm: Generate three sample vectors coming from ...
3
votes
1answer
114 views

Ito integrals and copulas

Let $X_{t}$ and $Y_{t}$ be two brownian motions and let their joint distribution be given by $F$. So in regularly correlated BM's where $dX_{t}dY_{t}=\rho dt$, we have a bivariate normal distribution ...
1
vote
2answers
390 views

How to combine Gaussian marginals with Gaussian copula to obtain multivariate normals?

in the book "Numerical Methods and Optimization in Finance" I red the following: "Combining the Gaussian copula with Gaussian marginal gives a fancy way of expressing multivariate normals. However, ...
3
votes
1answer
86 views

Copula- AR simulation

I am estimating different copulas for bond factors that i also fit AR(1) models on. Now i would like to test and compare durations and VaRs with my model vs empiric. But how can i simulate AR(1) ...
3
votes
1answer
88 views

Properties of a Symmetric Copula

I am working with the following copula, and have a few questions about it: $C(x,y) = xy + \theta (1-x)(1-y)xy$ Here $\theta \in [-1,1]$ and $x,y \in [0,1]$ First, I am trying to show this copula is ...
1
vote
0answers
55 views

Effect of kernel smoothing on correlation

Instead of deriving correlation matrix on standardized returns (z scores) would it not be more accurate to kernel smooth the cdf and then norminv the cdf values for the return z score and then ...
1
vote
1answer
505 views

Where can I find implementations of the time-varying copula (BBX) in Matlab or R?

I want to construct some time-varying BBX copulas, however, I found that patron's package does not contain time-varying BBX copula. Anybody know where I can download them?
3
votes
1answer
172 views

Convolution copula?

Using copula formulation for the following probability: $$\mathbb{P}(X\leq x,y_{1}\leq Y\leq y_{2})=\mathbb{P}(X\leq x,Y\leq y_{2})-\mathbb{P}(X\leq x,Y\leq y_{1})$$ $$=C(F_{X}(x),F_{Y}(y_{2}))-C(F_{...
2
votes
1answer
132 views

Where does this copula come from?

In a paper I encountered the following notation $$P(Z\leq z,u\leq Y\leq v)=C(F_{Z}(z),F_{Y}(v)-F_{Y}(u))$$ However I don't see why this holds in relation to uniform random variables. Usually $$P(Z\...
0
votes
0answers
330 views

Copula Value At Risk

Let's suppose I have two asset in my portfolio. I want to compute Copula Value At Risk. Can you help me? This is the code I wrote: ...
2
votes
1answer
96 views

What are the general limitations of Gaussian copulas with regards to the range of joint pdf's it can approximate?

I'm working with the nataf transformation - AkA Gaussian copula - and trying to establish the range of joint bivariate pdf's it can approximate, and what limitations it puts on those joint pdf's. I've ...
2
votes
1answer
79 views

Creditworthiness indicator for copula one-factor model

In this paper in equation 15 on page 261 dealing with one factor copula model, one is using creditworthiness indicator as one of a variables. It is defined as \begin{equation} Y_c = \sqrt{\rho_c} Z +...
4
votes
0answers
222 views

Estimation of ranks of log-returns via copula

I have successfully chosen and estimate a copula for the ranks of the log-returns of my actions. My question is, since I have worked with the ranks instead of directly the log-returns (in order to be ...
5
votes
2answers
581 views

Generate correlated random variables from Normal and Gamma distributions

I want to generate a random vector $z$ of dimension $k+m$ with some given correlation matrix $\Sigma$, such that the first $k$ elements of the vector are distributed normally and the last $m$ elements ...
3
votes
3answers
1k views

Do I need a copula to accurately estimate the VaR of a portfolio of risky assets?

I need to estimate the daily VaR of a portfolio of various exposures in $n$ risky assets (say equity futures). The simplest approach, I think, would be to just estimate VaR from a multivariate normal ...
9
votes
1answer
474 views

copula-marginal algorithm

has there been any interesting work or advances on the copula-marginal algorithm (CMA) as proposed by Attilio Meucci. I am unable to find anything on the web other then the original article, here is ...