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You're reading from  Mastering Python for Finance. - Second Edition

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789346466
Edition2nd Edition
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James Ma Weiming
James Ma Weiming
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James Ma Weiming

James Ma Weiming is a software engineer based in Singapore. His studies and research are focused on financial technology, machine learning, data sciences, and computational finance. James started his career in financial services working with treasury fixed income and foreign exchange products, and fund distribution. His interests in derivatives led him to Chicago, where he worked with veteran traders of the Chicago Board of Trade to devise high-frequency, low-latency strategies to game the market. He holds an MS degree in finance from Illinois Tech's Stuart School of Business in the United States and a bachelor's degree in computer engineering from Nanyang Technological University.
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The LU decomposition

The LU decomposition, or also known as lower-upper factorization, is one of the methods that solve square systems of linear equations. As its name implies, the LU factorization decomposes the A matrix into a product of two matrices: a lower triangular matrix, L, and an upper triangular matrix, U. The decomposition can be represented as follows:

Here, we can see a=l11u11, b=l11u12, and so on. A lower triangular matrix is a matrix that contains values in its lower triangle with the remaining upper triangle populated with zeros. The converse is true for an upper triangular matrix.

The definite advantage of the LU decomposition method over the Cholesky decomposition method is that it works for any square matrices. The latter only works for symmetric and positive definite matrices.

Think back to the previous example in Solving linear equations using matrices...

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Mastering Python for Finance. - Second Edition
Published in: Apr 2019Publisher: PacktISBN-13: 9781789346466

Author (1)

author image
James Ma Weiming

James Ma Weiming is a software engineer based in Singapore. His studies and research are focused on financial technology, machine learning, data sciences, and computational finance. James started his career in financial services working with treasury fixed income and foreign exchange products, and fund distribution. His interests in derivatives led him to Chicago, where he worked with veteran traders of the Chicago Board of Trade to devise high-frequency, low-latency strategies to game the market. He holds an MS degree in finance from Illinois Tech's Stuart School of Business in the United States and a bachelor's degree in computer engineering from Nanyang Technological University.
Read more about James Ma Weiming