Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios
Author:   Tshepo Chris Nokeri
Publisher:   APress
Edition:   1st ed.
ISBN:  

9781484271094


Pages:   182
Publication Date:   27 May 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios


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Author:   Tshepo Chris Nokeri
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.454kg
ISBN:  

9781484271094


ISBN 10:   1484271092
Pages:   182
Publication Date:   27 May 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Introduction to Financial Markets and Algorithmic Trading.- Chapter 2: Forecasting Using ARIMA, SARIMA, and the Additive Model .- Chapter 3: Univariate Time Series Using Recurrent Neural Nets .- Chapter 4: Discover Market Regimes .- Chapter 5: Stock Clustering.- Chapter 6: Future Price Prediction Using Linear Regression.- Chapter 7: Stock Market Simulation.- Chapter 8: Market Trend Classification Using ML and DL.- Chapter 9: Investment Portfolio and Risk Analysis.

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Author Information

Tshepo Chris Nokeri harnesses big data, advanced analytics, and artificial intelligence to foster innovation and optimize business performance. In his functional work, he has delivered complex solutions to companies in the mining, petroleum, and manufacturing industries. He initially completed a bachelor’s degree in information management. He then graduated with an honors degree in business science at the University of the Witwatersrand on a TATA Prestigious Scholarship and a Wits Postgraduate Merit Award. They unanimously awarded him the Oxford University Press Prize. He has authored the Apress book Data Science Revealed: With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning.

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