Questions tagged [covariance-estimation]
The covariance-estimation tag has no usage guidance.
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What is special about covariance estimation from statistical factor models?
If you were to compare the usual sample covariance estimate to a robust covariance estimate (such as MCD), you can say that the robust estimate is more tolerant to outliers in the data and will not be ...
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Fourier transform covariance estimator
I am estimating realized variance and covariance by the estimator described in this paper, and relying on Fourier Transform.
Now, as my data is one day of data in ultra high frequency, so that the ...
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OHLC Covarianc Estimation
Is there an R package which can estimate a covariance matrix using OHLC (Open/High/Low/Close) share prices for upwards of 40 shares using the Yang & Zhang method using daily data? I google ...
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Implementation of Ledoit Wolf shrinkage estimator within R package tawny
I want to implement the shrinkage intensity given by Ledoit and Wolf, see here page 13. They define $y_{it}$ with $1\le i\le N$ and $1\le t\le t$ be the return on stock $i$ at time $t$. Moreover, $z_i:...
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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 ...
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MLE estimate of normal distribution
Probably a naive question. I am quoting this from Greene's econometrics book:
"The occasional statement that the properties of the MLE are only optimal in large samples is not true, however. It can ...
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Bayes Stein Porfolio Implementation
From this paper from Jorion.
Has anyone implemented this? How is the Covariance matrix estimated? It needs to estimate also the conditional distribution of the returns?
Best
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How to get Multivariate Betas from an Estimated EWMA co variance Matrix?
I have a portfolio of 4 assets. I also have returns for 3 indices. I want to get the multivariate betas for these 4 assets-based on these assets. I only have the 7 x 7 covariance matrix estimated by a ...
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Portfolio Optimization : Shrinkage of Covariance Matrix when data is available
It seems that shrinking the covariance matrix is especially useful if the number of individual stocks is greater than the number of data points. However is there any special gain if you're not ...
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Explanation or implementation of Ledoit-Wolf estimator (without math packages)
I have calculated weights of selected assets in a market-neutral portfolio (presumably with min variance) using PCA and simple data covariance matrix.
The question is :
It is obvious that Cov Matrix ...
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Step-by-Step PCA algorithm (checking correctness without math packages)
I would appreciate if someone could correct me if i am wrong in my suggestion.
I am using PCA to :
find measure of cointegration between selected assets
find the eigenvector and its portfolio with ...
- 415
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Shrinkage Estimator for Newey-West Covariance Matrix
I like to apply the Newey-West covariance estimator for portfolio optmization which is given by
$$
\Sigma = \Sigma(0) + \frac12 \left (\Sigma(1) + \Sigma(1)^T \right),
$$
where $\Sigma(i)$ is the lag ...
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Covariance estimation: shrinkage, random matrix theory, what else?
Shrinkage was much en-vogue before random matrix theory (RMT) took everybody's attention in covariance matrix estimation, however the latter also showed its limits. A plethora of other estimators has ...
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