Implementing Machine Learning For Finance: A Systematic Approach To Predict...

Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Implementing Machine Learning For Finance: A Systematic Approach To Predictive Risk And Performance Analysis For Investment PortfoliosISBN13:9781484271094ISBN10:1484271092Author:Nokeri, Tshepo Chris (Author)Description: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 Learnunderstand The Fundamentals Of The Financial Market And Algorithmic Trading, As Well As Supervised And Unsupervised Learning Models That Are Appropriate For Systematic Investment Portfolio Managementknow The Concepts Of Feature Engineering, Data Visualization, And Hyperparameter Optimizationdesign, Build, And Test Supervised And Unsupervised Ml And Dl Modelsdiscover Seasonality, Trends, And Market Regimes, Simulating A Change In The Market And Investment Strategy Problems And Predicting Market Direction And Pricesstructure And Optimize An Investment Portfolio With Preeminent Asset Classes And Measure The Underlying Risk Who This Book Is Forbeginning And Intermediate Data Scientists, Machine Learning Engineers, Business Executives, And Finance Professionals (Such As Investment Analysts And Traders) Binding:Paperback, PaperbackPublisher:ApressPublication Date:2021-09-29Weight:0 lbsDimensions:Number of Pages:155Language:English

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Book Title: Implementing Machine Learning For Finance: A Systematic Appr...

Item Length: 9.3in

Item Width: 6.1in

Author: Tshepo Chris Nokeri

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

Format: Trade Paperback

Language: English

Publisher: Apress L. P.

Publication Year: 2021

Type: Textbook

Item Weight: 16 Oz

Number of Pages: Xviii, 182 Pages