Intelligent Banking
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Victor J. Valcarcel
About this book
Traditional money and banking textbooks establish the central tenets of the economics of financial markets in a theoretical, academic fashion and rarely offer any knowledge of computer skills. Intelligent Banking bridges this gap by introducing the fundamentals of finance in tandem with the development of programming skills. This book leans heavily on Python programming, while teaching fundamental concepts of money and banking to undergraduate and masters level students.
Along with discussions on the fundamentals, including topics like debt measurement, monetary aggregates and money supply, asset value, risk management, bonds and stocks, the book also teaches the basics of coding and machine learning.
Intelligent Banking is a one-stop-shop for learning first-principle financial concepts with direct coding applications within the span of a college term. The detailed glossaries at the end of chapters and the Python code examples and coursework will help students be better prepared to meet the demands of today’s banking and financial companies who are increasingly demanding these skills from their job applicants.
- Provides a hybrid experience between the traditional money and banking textbook and the finance trade book
Author / Editor information
Victor J. Valcarcel is Professor of Economics at the University of Texas at Dallas, USA. He teaches courses at all levels within the intersection of banking, finance, and macroeconomics. He is the Treasurer Secretary of the Society for Economic Measurement. He has been a visiting research scholar at the Federal Reserve Bank of Kansas City. He previously taught in various capacities at Texas Tech University and the University of Kansas. He is an irredeemable dog lover.
Topics
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Frontmatter
I -
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Dedication
V -
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Acknowledgments
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Contents
IX -
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List of Figures
XIII -
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List of Tables
XVII -
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Introduction
XIX - Part I Money and the Government
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1 Debt and the U. S. Treasury
3 -
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2 Money and the Federal Reserve
11 - Part II Time, Probability, and Risk
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3 Time Value of Money
41 -
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4 Primer on Probability Theory
54 -
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5 The Fundamentals of Risk
65 - Part III Financial Markets
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6 The Bond Market
81 -
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7 Interest Rates
107 -
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8 Equities and the Stock Market
129 - Part IV Machine Learning
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9 The Basics of Machine Learning
161 -
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Index
197
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10785 Berlin
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