Description: Are you a machine learning enthusiast looking for a practical day to day application? Or are you just trying to incorporate machine learning software in your trading decisions? This book is your answer. While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day trading scenario, or to determine the long term value of a stock; financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine learning algorithms like clustering and regression? When would be the best time to use these? While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day trading scenario, or to determine the long term value of a stock; financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine learning algorithms like clustering and regression? When would be the best time to use these? What's Included In This Book: What is Financial Machine LearningDeveloping a Trading Strategy for StocksMachine Learning to Determine Current Value of StocksOptimal Time to Buy StocksMachine Learning Algorithm to Predict When to Sell a StockDetermine Value of a Penny StockTrading Automation SoftwareConclusion
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EAN: 9781922300058
UPC: 9781922300058
ISBN: 9781922300058
MPN: N/A
Book Title: Machine Learning in Finance: Use Machine Learning
Item Length: 21 cm
Publisher: Bob Mather
Item Height: 210 mm
Subject: Finance, Computer Science
Publication Year: 2019
Number of Pages: 90 Pages
Publication Name: Machine Learning in Finance: Use Machine Learning Techniques for Day Trading and Value Trading in the Stock Market
Language: English
Type: Textbook
Item Weight: 118 g
Author: Bob Mather
Item Width: 148 mm
Format: Paperback