Questions tagged [dependence]
The dependence tag has no usage guidance.
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I.I.D log returns. What about their square?
If one assumes the underlying return process is I.I.D, is there a solution to the question of the autocorrelation of squared returns?
Thanks.
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Finding a representation for Joint probability density function of dependent random variables
Suppose that $\underline{\mathbf{X}}=(X_1, X_2, ..., X_n)$ is a vector of independent random variables. Then, we know that the joint probability density function $f_{\underline{\mathbf{X}}}(x_1, x_2, ....
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Hierarchical copula vs. vine copula
Vine copulas are a sequential cascade of bivariate copulas meant to capture the hierarchical structure in the dependence structure of random variables. How does this relate or differ from the concept ...
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Does the $t$-copula or Clayton copula capture the dependence structure of empirical returns better?
Which copula captures the dependence structure of empirical asset returns better? the $t$-copula, which has symmetric tail dependence, or the Clayton copula, which has asymmetric tail dependence, and ...
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Correlation vs. dependence in finance
I found an example that shows how two uncorrelated random variables can be dependent: a normally distributed variable $X$ is not correlated with its square $Y=X^2$. What can be $X$ and what can be $Y$ ...
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Patton Copula model code and significance of parameters
I am trying to implement a copula model using the Patton (2006) Matlab code. I am unable to determine the significance of the parameters. Does anyone know how i can generate the standard errors from ...
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Positive quadrant dependence
Gijbels et. al. Positive quadrant dependence tests for copulas (25 page PDF)
What could potentially be application of this concept in economics and finance? From what I read from a couple of papers, ...
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Alternatives to Elliptical and Archimedean copulas for modelling dependency structure between stocks
Except from the well-know and well-documented Elliptical (i.e. Gaussian, Student-t) and Archimedean (i.e. Frank, Clayton, Gumbel) copulas used to model the dependency structure between stock returns, ...
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Double knockout binary pricing?
I'm studying the pricing of a Double-Barrier binary option on the price of $S$. By this I mean an option that pays $X$ at maturity $T$ if the lower ($H1$) or upper barriers ($H2$) are not hit during ...
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tail dependency for portfolio optimization
This question pops up in my head every few weeks and I'm struggling to really understand the concept / theory behind it.
We all know there are different kind of measures of dependencies out there. ...
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What is the most stable, non-trivial dependence structure in finance?
The highest rated answer to the question on What concepts are the most dangerous ones in quantitative finance work? is this one:
Correlation
Correlations are notoriously unstable in ...
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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_{...
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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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Applications of distance correlation
This question mentions distance correlation.
Where has this concept been applied to financial data and provided new insight?
Do you know any examples or references?
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Credit spreads vs default events dependence
Reading this note it strikes me that credit spreads and defaults seem not to be commonly modeled jointly (e.g. more or less directly in structural models), but at best with some kind of "ex post" ...
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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 ...
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Alternative ways to understand time-varying comovement between two time-series?
I have been looking into ways to better understand how the dependencies/correlations/etc between two time series can vary over time.
I first thought about using a Kalman/particle filter over a ...
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Most natural generalization of covariance/correlation to model dependence of extreme events
One of the most serious shortcomings of covariance/correlation are the assumptions of linearity and normality.
What is the most natural generalization of these measures of dependence when you want to ...