Questions tagged [covariance]
A measure of the degree of linear association between a pair of random variables.
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How can one quantify the incremental value of better covariance matrix modeling in portfolio optimization?
Let's say we have two estimators of the covariance matrix, $\hat{C}_1$ and $\hat{C}_2$, and the latter is an improvement on the former.
Is there any measure of the improvement that can be sensibly ...
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Analyzing the angle between vector of weights and vector of returns in mean-variance optimization
I am using the paper "A Sharper Angle on Optimization" by Golts and Jones (2009) as a basis for my (minor) masters thesis in mathematical finance. The paper focuses on the mean-variance analysis of ...
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Why are thousand-ish-factor vendor risk models not extremely overfit and inaccurate?
Many vendor risk models have many hundreds, or even thousands of factors (many of which are highly correlated with each other). Underlying all these risk models is some sort of covariance matrix in ...
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Is Ledoit-Wolf Shrinkage with a Constant Correlation Prior Reasonable for a Stock/Bond Mix?
I've been looking into Ledoit-Wolf shrinkage but I've found the papers concentrate on large numbers of assets that tend to all be highly correlated. Often a universe of large cap stocks.
I'm ...
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Parametric VaR of a portfolio of a stock and an option on that stock
I understand how to calculate the parametric VaR of a stock and an option separately. But I don't understand how one can calculate the VaR of a portfolio of a stock and an option on that stock using ...
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Finding mean vector and covariance matrix for annual returns given quarterly returns
I am currently trying to calculate a vector for the mean annual returns of 4 different asset classes along with their 4x4 covariance matrix in excel. However, I am having problems since the data I ...
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How to calculate the estimation error of portfolio variance using propagation results?
I am trying to find a conservative approximation for the propagated estimation error of a investment portfolio's variance (comprising two assets), given we know the estimation error for the variance ...
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Should I use Resampling or Expectation Maximization to compute a robust covariance matrix?
I have several assets, each with different return histories.
Some of the assets have 75 days of return history, others have 40 or so days. In calculating a robust covariance matrix, should I be using ...
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Good criteria to sort state-space $\beta_{t}$ according to Kalman filter output
Let's assume the usual state-space linear model without constant term for simplicity:
$y_{t}=\beta_{t} X_{t}+\epsilon_{t}$
If we apply Gaussian Kalman filter to estimate $\beta_{t}$ we get $P_{t}$, ...
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How to reduce a covariance matrix after clustering?
I have an N = 100 covariance matrix. I am clustering the covariance matrix say into 5 clusters.
How can I compute the reduced ...
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Ledoit-Wolf, expected order of optimal shrinkage intensity
I have a question regarding the optimal shrinkage intensity derived in the Ledoit-Wolf method. Specifically, I'm referring to their version concerned with the target defined as the single index factor ...
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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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Discuss how you would allocate your budget between the two assets if their correlation is 1, 0, or -1
An asset A is expected to yield a $2\%$ return with a standard deviation of $1\%$, and another asset B is expected to yield a $1\%$ return with a standard deviation of $1\%$.
Discuss how you would ...
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Association between a random variable and Radon-Nikodym derivative
Suppose that $X$ is a random variable and $\frac{d\mathbb{Q}}{d\mathbb{P}}$ is the Radon-Nikodym derivative. The quantity under consideration is as follows:
\begin{equation}
Cov(X, \frac{d\mathbb{Q}}{...
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Disjoint covariance matrix estimation
I have always estimated correlations and variances disjointly and later combine them to construct covariance matrices. Specifically, variances are estimated in a univariate setting (only using the ...
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$n$-day ahead forecast for asymmetric DCC-GARCH model
I am working on forecasting covariances with the use of MGARCH models. I was wondering if anyone knows how to implement a n-day ahead forecast of the aDCC (asymmetric DCC) model in R. The ...
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covariance matrix in the CAPM model
I'm running a simulation for a 5 asset portfolio, calculating the optimal weights of each asset both with the statistical model (i.e. single index) and with the CAPM. my question is: how do you ...
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Is there a differentiable formulation of Prado's HRP algo?
I get the sense the algo is just a graph representation the dependency structure. Am wondering if there is anything written on learning the weights by optimizing some parameters rather than a forward ...
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One day standard deviation of a portfolio (long/short, different scalars)
I am attempting to calculate the expected one-day standard deviation of a portfolio in dollars. In other words, I am looking for the following: "I expect my portfolio to move _______ dollars on ...
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Covariance time frequency
I have rolling 3-year returns for an asset and a benchmark.
I want to compare the covariance of the asset and benchmark, should I use the covariance of the rolling 3-year returns or the covariance ...
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Deriving Cox, Ingersoll and Ross expression for the relationship between forwards and futures, how do they conclude a specific step?
I'm trying to derive a specific relationship about the relationship between forwards and futures from "The relationship between forward and futures prices", written 1981 by Cox, Ingersoll and Ross (...
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Marchenko–Pastur, Student distribution and returns
I have a question regarding random matrix theory. I've been studying various papers and I found some confusing definitions of Marchenko-Pastur law. The most clear was the one on wiki:
wiki-Pastur-...
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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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Portfolio Hedging under Uncertain Correlations
I have a portfolio ($w_0=1$) and two hedging assets ($w_1,w_2$) and a co-variance matrix for the three $\Sigma$. However the co-variance $\Sigma$ is only an estimate.
For fairly well behaved assets (...
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How to calculate beta against a multi-asset benchmark
Lets say that I have a benchmark, $BM$ that consists of 3 assets- 30% asset $A$, 30% asset $B$ and 40% asset $C$. Now, lets further assume I am trying to construct a portfolio that uses $BM$ as its ...
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modeling regime switching for Correlation matrix
I am trying to estimate covariance in multiple time series. However, I want to do this using a regime-switching framework. So, I start with fitting a GARCH(1,1) model and then de-volatalize the series....
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How to prove that the feasible set of a two-asset portfolio is a hyperbola?
The question comes from ‘Mathematics for Finance: An Introduction to Financial Engineering’ by Marek Capiński (Author), Tomasz Zastawniak. The book does not give a complete proof, and I did not find a ...
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GARCH for Mean Variance Optimization
I am currently trying to carry out a mean variance optimisation, with the implementation of GARCH. I'm not sure if this is going to make complete sense as my understanding of GARCH is limited.
In the ...
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Scaling returns to use PCA?
Many machine learning techniques perform better, if the data is preprocessed - either by normalization (MaxMin Scaler) or standardization (Standard Scaler). But that comes with a lack of ...
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Covariance Matrix of Correlated Random Variable
Suppose I know or have estimated the covariance matrix for one random variable (for example an asset) and have:
$$
\begin{bmatrix}
<\text{spot, spot}> & <\text{atmv, spot}> \\
<\...
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"fix" a sample covariance matrix which is not positive semidefinite by using daily returns instead of monthly
In the portfolio optimization problem at hand, one of the constraints is that the tracking error should not be greater than $\gamma$.
The constraint is therefore:
$(\textbf{x}-\textbf{w})^\mathrm{T}\...
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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 ...
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What is the difference between np.cov(array) and array.cov()?
I'm trying to find a covariance matrix, so when i use returns.cov() on my returns variable, I get a good result. Unfortunately, when i want to use ...
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Interpreting factor coefficients when correlation flips
I am looking at mainly value and growth factor coefficients of a fund during the recent Covid market “crisis”.
I have found that said fund had a negative coefficient to value at the start of 2020 (let’...
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Covariance of Individual Return and Portfolio Return
Hi guys,
Is it possible to get the covariance between the individual return and portfolio return given the correlation matrix, volatility matrix, weights matrix and return matrix?
I know how to get ...
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Can I build an efficient frontier using matrix algebra?
If i have a vector of expected returns $A$, a covariance matrix $C$ and a vector of the corresponding weights $W$ for each investment, is it possible to generate the efficient frontier with vector ...
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Decomposition of Contribution to Variance
$C$ is a $N\times N$ covariance matrix of stock returns. Assuming $w$ is a vector of positions in each asset, the total variance of the portfolio is
$$w^TCw$$
The contribution to total variance of the ...
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Decomposing Co-variance of Two Assets Terminal Prices into Forward measures
Let $X_T,Y_T$ be the terminal values of two price processes following Continuous Gaussian Motion (I.E.) let us assume no jumps. Further assume the correct forwards/futures price is given by $F^X_{t,T} ...
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Factor Models: uncorrelated errors don't impact covariances of assets
This question stems from time series factor models (e.g., CAPM, Fama-French, etc.), but is a broader idea.
I am trying to comprehend how adding noise to a time series (e.g., error/residual from a ...
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