Interview Question: LU, SVD, Cholesky

Sample Question #23 (applied math – linear algebra)

In linear algebra, why are we interested in matrix decompositions? Explain each of the following:

  • LU decomposition
  • Singular value decomposition (SVD)
  • Cholesky decomposition
  • QR decomposition

When and how is each of these decomposition techniques applied?

(Comment: matrix operations, including decompositions, are extremely important in applied quantitative finance – they are often the clue between modeling and implementation)

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