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Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios book cover by Tshepo Chris Nokeri
Paperback

Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios

by Tshepo Chris Nokeri

$38.49 / copy at 25+ copies As low as $34.09 at 1,000+Your best volume price

Total $962.25

Paperback · 182 pages Apress · 2021

Format

Paperback
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About the book

Implementing Machine Learning for Finance

Bring together machine learning (ML) and deep learning (DL) in financial trading, with an emphasis on investment management. This book explains systematic approaches to investment portfolio management, risk analysis, and performance analysis, including predictive analytics using data science procedures.

The book introduces pattern recognition and future price forecasting that exerts effects on time series analysis models, such as the Autoregressive Integrated Moving Average (ARIMA) model, Seasonal ARIMA (SARIMA) model, and Additive model, and it covers the Least Squares model and the Long Short-Term Memory (LSTM) model. It presents hidden pattern recognition and market regime prediction applying the Gaussian Hidden Markov Model. The book covers the practical application of the K-Means model in stock clustering. It establishes the practical application of the Variance-Covariance method and Simulation method (using Monte Carlo Simulation) for value at risk estimation. It also includes market direction classification using both the Logistic classifier and the Multilayer Perceptron classifier. Finally, the book presents performance and risk analysis for investment portfolios.

By the end of this book, you should be able to explain how algorithmic trading works and its practical application in the real world, and know how to apply supervised and unsupervised ML and DL models to bolster investment decision making and implement and optimize investment strategies and systems.


What You Will Learn
  • Understand the fundamentals of the financial market and algorithmic trading, as well as supervised and unsupervised learning models that are appropriate for systematic investment portfolio management
  • Know the concepts of feature engineering, data visualization, and hyperparameter optimization
  • Design, build, and test supervised and unsupervised ML and DL models
  • Discover seasonality, trends, and market regimes, simulating a change in the market and investment strategy problems and predicting market direction and prices
  • Structure and optimize an investment portfolio with preeminent asset classes and measure the underlying risk


Who This Book Is For

Beginning and intermediate data scientists, machine learning engineers, business executives, and finance professionals (such as investment analysts and traders)


The book, Implementing Machine Learning for Finance: A Systematic Approach to Predictive Risk and Performance Analysis for Investment Portfolios [Bulk, Wholesale, Quantity] ISBN#9781484271094 in Paperback by Tshepo Chris Nokeri may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.

Details

Publisher
Apress
Author
Tshepo Chris Nokeri
Format
Paperback
Published
May 27, 2021
ISBN-13
9781484271094
Pages
182
Printing
Printed on demand
Buying for a group

Implementing Machine Learning for Finance in bulk: pricing

Volume pricing applies automatically in your cart. No codes, no account needed.

CopiesPrice per copyYou save
25 – 99 $38.49 30% off list
100 – 249 $37.39 32% off list
250 – 499 $36.29 34% off list
500 – 999 $35.19 36% off list
1,000+ $34.09 38% off list
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