Illustrating Finance Policy with Mathematica (Paperback, Softcover reprint of the original 1st ed. 2018)


Students in various disciplines-from law and government to business and health policy-need to understand several quantitative aspects of finance (such as the capital asset pricing model or financial options) and policy analysis (e.g., assessing the weight of probabilistic evidence) but often have little quantitative background. This book illustrates those phenomena and explains how to illustrate them using the powerful visuals that computing can produce. Of particular interest to graduate students and scholars in need of sharper quantitative methods, this book introduces the reader to Mathematica, enables readers to use Mathematica to produce their own illustrations, and places specific emphasis on finance and policy as well as the foundations of probability theory.

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Product Description

Students in various disciplines-from law and government to business and health policy-need to understand several quantitative aspects of finance (such as the capital asset pricing model or financial options) and policy analysis (e.g., assessing the weight of probabilistic evidence) but often have little quantitative background. This book illustrates those phenomena and explains how to illustrate them using the powerful visuals that computing can produce. Of particular interest to graduate students and scholars in need of sharper quantitative methods, this book introduces the reader to Mathematica, enables readers to use Mathematica to produce their own illustrations, and places specific emphasis on finance and policy as well as the foundations of probability theory.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Quantitative Perspectives on Behavioral Economics and Finance

Release date

December 2018

Availability

Expected to ship within 10 - 15 working days

First published

2018

Authors

Dimensions

210 x 148 x 14mm (L x W x T)

Format

Paperback

Pages

226

Edition

Softcover reprint of the original 1st ed. 2018

ISBN-13

978-3-03-007022-9

Barcode

9783030070229

Categories

LSN

3-03-007022-0



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