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You're reading from  Learn Algorithmic Trading

Product typeBook
Published inNov 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789348347
Edition1st Edition
Languages
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Authors (2):
Sebastien Donadio
Sebastien Donadio
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Sebastien Donadio

Sebastien Donadio is the Chief Technology Officer at Tradair, responsible for leading the technology. He has a wide variety of professional experience, including being head of software engineering at HC Technologies, partner and technical director of a high-frequency FX firm, a quantitative trading strategy software developer at Sun Trading, working as project lead for the Department of Defense. He also has research experience with Bull SAS, and an IT Credit Risk Manager with Socit Gnrale while in France. He has taught various computer science courses for the past ten years in the University of Chicago, NYU and Columbia University. His main passion is technology but he is also a scuba diving instructor and an experienced rock-climber.
Read more about Sebastien Donadio

Sourav Ghosh
Sourav Ghosh
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Sourav Ghosh

Sourav Ghosh has worked in several proprietary, high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high-throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making and pairs trading strategies with the most liquid global futures contracts. He is currently the vice president at an investment bank based in São Paulo, Brazil. He holds a master's in computer science from the University of Southern California. His areas of interest include computer architecture, FinTech, probability theory and stochastic processes, statistical learning and inference methods, and natural language processing.
Read more about Sourav Ghosh

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Creating predictive models using linear classification methods

In the first part of this chapter, we reviewed trading strategies based on regression machine learning algorithms. In this second part, we will focus on the classification of machine learning algorithms and another supervised machine learning method utilizing known datasets to make predictions. Instead of the output variable of the regression being a numerical (or continuous) value, the classification output is a categorical (or discrete value). We will use the same method as the regression analysis by finding the mapping function (f) such that whenever there is new input data (x), the output variable (y) for the dataset can be predicted.

In the following subsections, we will review three classification machine learning methods:

  • K-nearest neighbors
  • Support vector machine
  • Logistic regression
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Learn Algorithmic Trading
Published in: Nov 2019Publisher: PacktISBN-13: 9781789348347

Authors (2)

author image
Sebastien Donadio

Sebastien Donadio is the Chief Technology Officer at Tradair, responsible for leading the technology. He has a wide variety of professional experience, including being head of software engineering at HC Technologies, partner and technical director of a high-frequency FX firm, a quantitative trading strategy software developer at Sun Trading, working as project lead for the Department of Defense. He also has research experience with Bull SAS, and an IT Credit Risk Manager with Socit Gnrale while in France. He has taught various computer science courses for the past ten years in the University of Chicago, NYU and Columbia University. His main passion is technology but he is also a scuba diving instructor and an experienced rock-climber.
Read more about Sebastien Donadio

author image
Sourav Ghosh

Sourav Ghosh has worked in several proprietary, high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high-throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making and pairs trading strategies with the most liquid global futures contracts. He is currently the vice president at an investment bank based in São Paulo, Brazil. He holds a master's in computer science from the University of Southern California. His areas of interest include computer architecture, FinTech, probability theory and stochastic processes, statistical learning and inference methods, and natural language processing.
Read more about Sourav Ghosh