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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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Author (1)
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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Summary

In this chapter, we briefly discussed the persistence of nonlinearity in economics and finance. We looked at some nonlinear models that are commonly used in finance to explain certain aspects of data left unexplained by linear models: the Black-Scholes implied volatility model, Markov switching model, threshold model, and smooth transition models.

In Black-Scholes implied-volatility modeling, we discussed the volatility smile, which was made up of implied volatilities derived via the Black-Scholes model from the market prices of call or put options for a particular maturity. You may be interested enough to seek the lowest implied-volatility value possible, which can be useful for inferring theoretical prices and comparing against market prices for potential opportunities. However, since the curve is nonlinear, linear algebra cannot adequately solve for the optimal point...

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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