Real World Examples of Singular Matrices in Finance

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In summary, the conversation discusses the rarity of singular matrices in real world applications, with the more common occurrence being badly conditioned matrices. The speaker is specifically looking for financial applications that yield ill-conditioned matrices. The determining factor for singularity or ill-conditioning is the values of the elements, and any application can have these types of matrices depending on the data.
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Homework Statement



Hi, no variables, eqns or any of that here:) I was hoping some of you brilliant people could help me in finding some real world examples of where singular matrices occur. I do know that most real world problems yield matrices that are singular and therefore not invertible. We can use a generalized inverse on these problems, but I am finding it difficult to find some real world examples of this, specifically in the field of finance.

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The Attempt at a Solution

 
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In real world applications singular matrices occur very seldom, since the elements are real numbers.
What is common is badly conditioned matrices: matrices whose determinant is not zero, but is very close to. In this case, small fluctuations in any parameter yields enormous variations in the result.
 
  • #3
singularity

hey thanks so much.

I have been looking at ill-conditioned matrices. I was hoping to find some specific financial application that yields ill-conditioned matrices. (i.e. there condition number is very large)
 
  • #4
calli said:
hey thanks so much.

I have been looking at ill-conditioned matrices. I was hoping to find some specific financial application that yields ill-conditioned matrices. (i.e. there condition number is very large)

What makes a matrix singular or ill-conditioned is the value of the elements. Any application can have those types of matrices, depending on the data.
 

1. What are singular matrices?

Singular matrices are square matrices that do not have an inverse. This means that there is no matrix that can be multiplied with the singular matrix to give the identity matrix. In simpler terms, the determinant of a singular matrix is equal to zero.

2. How are singular matrices used in finance?

Singular matrices are used in finance to model and analyze systems with multiple variables and equations. They are especially useful in risk management and portfolio optimization, where they can help identify potential problems or inefficiencies in a financial system.

3. Can you provide a real-world example of a singular matrix in finance?

One example of a singular matrix in finance is the covariance matrix, which is used to measure the risk and return of a portfolio. If the assets in the portfolio are highly correlated, the covariance matrix will be singular, indicating that the portfolio is not well-diversified and carries a higher level of risk.

4. How do singular matrices affect financial calculations?

Singular matrices can greatly impact financial calculations, as they can lead to incorrect or undefined results. For example, if a singular matrix is used to calculate the optimal portfolio weights for minimizing risk, the resulting portfolio may not actually be optimal due to the lack of an inverse.

5. Are there any limitations to using singular matrices in finance?

Yes, there are limitations to using singular matrices in finance. As mentioned before, they can lead to incorrect or undefined results if not used correctly. Additionally, singular matrices may not be able to accurately model complex financial systems with non-linear relationships between variables.

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