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

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230 views

Multifractal Model, Generating Sample Paths with Correlations between Assets

I have studied option pricing using Geometric Brownian Motion to generate sample paths. Because of the normal distribution, it is easy to create a covariance matrix and get correlated asset returns. ...
2
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0answers
181 views

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. ...
2
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2answers
2k views

Why do stocks with a negative beta return less than the risk free rate?

Let's say we have two stocks, Stock A and Stock B. Both of them have the same standard deviation $\sigma$, and therefore have the same risk. The only difference is that Stock A has a perfect ...
4
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1answer
105 views

tail correlation during crisis

I am seeking a recommendation for an empirical paper on increased correlations of returns during the 2008 financial crisis, or 'tail correlation' during the crisis, if that is different, or whatever ...
2
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2answers
1k views

Are two stocks with the same beta have a correlation of 1?

If two stocks have the same beta over same time period, does it mean they are 100% correlated over that time period? In a CAPM framework, a stock's beta is defined as $$\beta_1={\rm Cov} (R_1, M) / ...
2
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2answers
298 views

Correlated Wiener processes of different factors

I'm relatively new in this field, so I have a couple of points that I need to clarify. I would like to know how I can estimate the correlation matrix necessary to implement a Cholesky decomposition ...
5
votes
1answer
408 views

When does the Epps effect start?

Wikipedia defines the Epps effect as follows: In econometrics and time series analysis, the Epps effect, named after T. W. Epps, is the phenomenon that the empirical correlation between the returns ...
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0answers
122 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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2answers
139 views

how to extend lognormal model so that $\sigma$ is correlated to $\mu$?

Consider a log-normal model, $dx / x = \mu dt + \sigma dW$, where $W(t)$ is a Wiener process. Let's say $\mu$ and $\sigma$ change with time, slowly, so we note them by $\mu(t)$ and $\sigma(t)$. ...
4
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2answers
475 views

Average correlation of index/portfolio

We try to analyze the average correlation of a portfolio as it can be found here in section 2 b), the same formula which is also used by the CBOE to calculate implied correlations: $$ \rho_{av(2)} = ...
0
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0answers
303 views

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: $y_{t}=\beta_{t}x_{t}+\epsilon_{t}$. ...
1
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1answer
294 views

Help with understanding a normal distribution/probability question

Could someone please help me translate what this is saying on page P15, section 4.2: http://www.ntuzov.com/Nik_Site/Niks_files/Research/papers/stat_arb/Ahmed_2009.pdf Specifically: When the ...
0
votes
1answer
389 views

Non-intuitive correlation between S&P sector indexes and economic indicators

I am trying to understand how changes in economic indicators like Unemployment Rate, Inflation Rate, and Consumer Sentiment affect the portfolio values. For that I want to measure the correlation ...
2
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1answer
970 views

Counterintuitive time varying Beta with Kalman filter

If you're used to play with R, you'll enjoy the following reproducible code: ...
6
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2answers
271 views

How to deal with zeroes in returns?

Suppose there are two time series that I want to analyze and compare. However, many, or most, of the data are zeroes for some reason. For example, consider a pair of intraday trading returns time ...
6
votes
2answers
1k views

Principle Component Analysis vs. Cholesky Decomposition for MonteCarlo

Let's assume we have a portfolio containing large number (~500) of risk factors. We want to simulate the portfolio dynamics. PCA based simulation would be faster as we can reduce the dimensionality. ...
4
votes
1answer
3k views

When the Inverse Correlation between the SPX and VIX breaks down

As we all know the S&P and its implied vol, the VIX, generally move in opposite direction. To a large extent, the correlations makes sense. IV is one of the main drivers of the price of options, ...
5
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0answers
214 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 ...
1
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1answer
414 views

Testing Significance of Correlation

Lets say I have the returns of two stocks(stock1 and stock2). Now without running a regression, I lag one of the variables, calculate the correlation between the two stocks and repeat this process as ...
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0answers
307 views

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 ...
5
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2answers
444 views

Correlation decay in lognormal distribution

I noticed that if you use two correlated geometric brownian motions, the correlation structure decays in time pretty fast even for really high correlation values. I think that is not replicating ...
4
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1answer
574 views

Stability of correlations and volatility

I had a discussion recently about the stability of volatilities and correlations. If we take for example stocks and bonds (think of DAX and Bund) then I have seen changing volatilities (something like ...
3
votes
1answer
110 views

How can I evaluate how poor a fit a parametric VaR result would be for a given holding?

I'm currently working on an application that, among other things, computes a one-day parametric VaR for security positions. I understand that the parametric method of computing VaR is a poor fit for ...
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2answers
357 views

What stock market indicators to model based on twitter feed? [closed]

We are developing an algorithm that models twitter users and groups of words that may indicate real world events. One application is modelling elections, i.e which party is likely going to win. ...
5
votes
3answers
618 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 ...
8
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0answers
441 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 ...
5
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2answers
319 views

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 ...
3
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1answer
313 views

Rank Correlation Based Prediction

Are there any methods of prediction (machine learning, regression, etc.) which are designed to maximize the rank correlation (spearman correlation, kendall's tau, etc.) of your prediction with your ...
4
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0answers
156 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 ...
2
votes
1answer
228 views

Combining covariances?

Consider an economy with assets with return processes $A$, $B$, $C$, $D$. Consider a weighted index with return process $I=aA + bB + cC + dD$ where $a,b,c,d$ are coefficients, and $a+b+c+d = 1$. ...
11
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1answer
596 views

Meta-view of different time-series similarity measures?

While I spend most of my StackExchange time on MathematicaSE, I'm in the business and follow the questions and answers on this site with great interest. Recently questions like the following (and ...
6
votes
1answer
321 views

Measuring co-movement at non-constant intervals

Correlation measures how much two series move together over a fixed interval. Are there any techniques that measure co-movement over a variable time frame? One technique I am aware of is concordance.
7
votes
3answers
897 views

cointegration applied to Portfolio Construction & Risk management

There are all sorts of applications of cointegration to generating alpha on mean-reverting timeseries: comparing spot vs. futures, bond spreads, identifying mean-reverting residuals, etc. But there ...
3
votes
1answer
249 views

Does the correlation amongst stocks rise when stock values decline?

Is there any research on whether the correlations among stocks rise when stock indices decline? Which model could account and test for that effect ? Maybe GARCH-BEKK, or some models using copulas?
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331 views

Correlation: Test for linear dependence

Setting the scene: Assume a multivariate GBM with correlation matrix $\Sigma$. Further, one want to estimate the correlation between two of the assets. Assume one has a suitable estimator of the ...
4
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2answers
241 views

Can we explain physical similarities between Black Scholes PDE and the Mass Balance PDE (e.g. Advection-Diffusion equation)?

Both the Black-Scholes PDE and the Mass/Material Balance PDE have similar mathematical form of the PDE which is evident from the fact that on change of variables from Black-Scholes PDE we derive the ...
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0answers
90 views

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 ...
7
votes
3answers
306 views

age-sensitive correlation measurements in finances

When it comes to comparing returns or prices of instruments like stocks/ETFs, are there any well-established formulas, or ones in common use, that place stronger emphasis on recent correlations more ...
3
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3answers
611 views

portfolio diversification tester

Are there any online tools (optionally with developer API, to spare me the scraping) that given an existing portfolio, calculate how well a new candidate position would score to increase combined ...
2
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2answers
531 views

How to calculate cumulative loss from two factors that have negative correlation?

I went through the most advanced books on statistics and still can't find an answer. There is a well known formula for combining volatility of two correlating variables, but what about adding the ...
5
votes
1answer
1k views

How to simulate correlated assets for illustrating portfolio diversification?

I have seen multiple instances where people try to explain the diversification effects of having assets with a certain level of correlation, especially in the "most diversified portfolio" literature. ...
5
votes
1answer
263 views

RMT (Random Matrix Theory) issue with callibrating MP distribution -

I am seeing an issue when callibrating an MP distribution. Assume a log return series for the SP500 with the following dimensions dim(xts.sp500.ret.stocksonly) ==> [1] 1133 478 ...
7
votes
3answers
725 views

Does random matrix theory (RMT) for returns' correlation matrices apply if there are high correlations?

Steps to replicate: Take the correlation matrix of a sample of stocks in the SP500, or a set of ETF's that are include some that are highly correlated (0.7 and above). Problem observed: I observe ...
1
vote
2answers
138 views

Buying one company or index against another, is this readily possible with options, with an accurate return (also Alpha Indexes)

There's a relatively new product in the market / on the Nasdaq called Alpha Indexes. It lets one own a company -- e.g. Apple, GE, Google, etc -- as the difference between how that company does (the ...
11
votes
6answers
2k views

How to generate a random price series with a specified range and correlation with an actual price?

I want to generate a mock price series. I want it to be within a certain range and have a defined correlation with the original price series. If I choose, say, oil, I want as many time series which ...
4
votes
0answers
211 views

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 ...
10
votes
1answer
436 views

What weights should be used when adjusting a correlation matrix to be positive definite?

I have a correlation matrix $A$ for an equity market that is not positive definite. Higham (2002) proposes the Alternating Projections Method, minimising the weighted Frobenius norm $||A-X||_W$ where ...
12
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2answers
1k views

Cleansing covariance matrices via Random matrix theory

I am exploring de-noising and cleansing of covariance matrices via Random Matrix Theory. RMT is a competitor to shrinkage methods of covariance estimation. There are various methods expressed usually ...
11
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3answers
1k views

How to detect regime change when estimating asset correlation from historical time series?

Suppose I have two asset time series, $X_t$ and $Y_t$, and I'm estimating their correlation from historical data. I'd like to apply some systematic criterion to estimate what time window I should use ...
21
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4answers
8k views

What is the best way to “fix” a covariance matrix that is not positive semi-definite?

I have a sample covariance matrix of S&P 500 security returns where the smallest k-th eigenvalues are negative and quite small (reflecting noise and some high correlations in the matrix). I am ...