All Questions
Tagged with covariance-estimation covariance-matrix
20
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Excess Return Covariance Matrix is Singular - Cash return and risk free rate are the same [closed]
I've created a three asset excess return covariance matrix. The assets are; equity, bonds, and cash. However, my cash return is the same as my risk free rate ( i.e. 3 month Euribor). This is leaving ...
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Distribution of sample covariance times inverse covariance times sample covariance
I want to understand the distribution of the random variable:
$$S_n = \frac{1}{n^2} 1'\hat \Sigma \Sigma ^{-1} \hat \Sigma 1$$.
1 is a vector of ones of size n, and the variance is of size nxn. $\hat \...
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Reliability of R Package on Covariance Matrix Shrinkage
I recently used a R package CovTools in R with the command CovEst.2003LW(X), where X is your sample covariance matrix as an input, to compute the shrunk covariance matrix (an estimate that is closest ...
- 1,595
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Calculating Portfolios Covariance via Bilinearity with Log or Simple Returns
I'm wanting to calculate the covariance between two portfolios $A$ and $B$ which are allocated to assets $X_i$ (where $i \in \left[1, 2, \cdots, N \right]$) with weights $\vec{w_A}$ and $\vec{w_B}$, ...
- 128
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Estimating covariance with intraday data
I have intraday (30 min) data for a number of stocks, and I would like to calculate the covariance matrix of returns.
For the purpose of calculating the covariance matrix, is it better/more correct to ...
- 136
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What does a non-stochastic limiting shrinkage function mean?
I'm reading the paper "The Power of (Non-)Linear Shrinking: A Review and Guide to Covariance Matrix Estimation" by Ledoit and Wolf (2020). When a function that is used to transform the ...
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Sample Variance of Portfolio
Let $w$ denote a vector of portfolio weights, $r_i$ denote the $i$th return vector, $\Sigma$ denote the Covariance matrix of $r_i$ and let $\hat{\Sigma}$ denote the sample covariance matrix of $r_i$.
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833
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Number of Observations for Non-Singular Covariance Matrix Estimation
Marcos López de Prado writes the following in his book Advances in Financial Machine Learning:
In general, we need at least \frac{1}{2} N (N+1) independent and ...
- 66
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Odd Result from Computing Correlation Matrix from Kalman Filter Posteriori Covariance Estimate
I am using a Kalman Filter to estimate the return dynamics of a forwards curve on a particular commodity. My state space is the initial forwards values, and an initial guess of the drift functions for ...
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Can the covariance matrix be represented as a scalar or something similarly small, instead of a large pair-wise grid?
The covariance matrix tabulates pair-wise interactions between variables (assets) one-at-a-time into a grid, which can quickly become large as the number of assets included in a portfolio, for example,...
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Meaning of an identity matrix for the covariance in portfolio optimization
Instead of using a sample covariance matrix for portfolio optimization, Ledoit and Wolf use an estimator that is the weighted average of the sample covariance matrix and the identity matrix, $I$. This ...
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Effective Time Length of Exponentially Weighted Covariance Matrix Estimate
In [1] Pafka, Potters and Kondor mention the following in section 2:
In contrast, if this covariance matrix estimate is used for portfolio optimization (i.e.
for selecting the portfolio in a ...
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2
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Creating a Covariance Matrix
Lets say that you have the correlation of x,y and you have the standard deviations of x and y , how would you then find the covariance of x,y using the correlation of x,y and and the standard ...
- 339
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6
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Is a more robust Covariance estimation possible?
I'm working on a mean-variance optimization problem, but instead of financial securities I'm choosing a 'portfolio' of N athletes. It is a 1-period optimization problem over one generic statistic ...
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Black Litterman - numerical instability
I am trying to work out the formula for the posterior mean in Black Litterman's model assuming 100% confidence :
Ref: https://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAssociates/...
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