A measure of the degree of linear association between a pair of random variables.

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Correlation Multiple Currencies

If i have a portfolio of stocks from different currencies and i want to generate a correlation matrix from the stocks, how is the correct procedure ? Imagine a portfolio which the base currency is ...
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Does the correlation of matrices has explanatory power when building a pattern recognition model?

I'm using 8 different variables (with daily observations) with the purpose to compare different months across the historical data. For that purpose I calculate the correlation between each month and ...
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177 views

Stress testing covariance

Going one level beyond stressed scenarios, to parameters e.g. for a VaR measure: what are the most common approaches for stressing a covariance/correlation matrix, especially taking portfolio exposure ...
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309 views

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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96 views

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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138 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 ...
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Taking into account the correlation in Barrier options on a Basket

In a Barrier option (where the contract cancels when the underlying hits the barrier) I succesfully found the way to compute the probability of a single underlying touching the barrier (with constant ...
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Correlation between idiosyncratic residuals and forward returns

The classic mean-reversion strategy is to calculate an "expected return" (alpha) by computing the raw return for each security and then remove the part which you think is market driven. Statistically ...
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Potential pitfalls in the use of correlation

Background: The red line is an index, which goes from 0 to 100, measuring uncertainty in the markets. The dark blue line is a price index, which has a lower bound at 0, and virtually no upper bound. ...
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how to identify similar assets based only on a few price samples

Using quantitative finances techniques on limited information, how might one go about finding similar(highly correlated) assets whose public information is available? The only data offered on a list ...
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61 views

Correlating random numbers seems to skew the data

First off, apologies for the cross-post from mathematics, but I found this site later and think it would be a better fit for the question (besides, there has been no comments/answers on mathematics ...
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124 views

Is there a Newey West like correction for overlapping data correlation estimates?

I already posted a related question a while ago but was unsure if I should post within the same question. I want to estimate mulitperiod asset return correlations and test if there are significant ...
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UAC- Unbiased Average Correlation for a Matrix of stocks

Once I have computed a correlation matrix for a portfolio of stocks, how do I calculate the UAC for the correlation matrix? ie, how do I strip out any auto correlation among the names?
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Time-varying correlation via state-space representation and Kalman filter

Let a linear time-varying mode like this one: $y_{t}=\alpha_{t}+\beta_{t}x_{t}+\epsilon_{t}$. You can also suppress the constant term to simplify this example: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
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Correlation Sensitivity

Suppose I have 2 stocks $S_{1}$ and $S_{2}$: \begin{align} & dS_{1}=rS_{1}dt+\sigma_{1}S_{1}dB_{1}\\ & dS_{2}=rS_{2}dt+\sigma_{2}S_{2}dB_{2}\\ & dB_{1}dB_{2}=\rho dt \end{align} Then I ...