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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Introduction to portfolio theory

The keyword for the portfolio theory is diversification, while the keyword for diversification is correlation. In other words, correlation is used to measure how closely two stocks or portfolios are moving together. The objective of portfolio theory is to allocate our assets optimally with respect to risk and return. Markowitz (1952) argues that we should consider only the first two moments of a security's return distribution: mean and variance. For financial markets, several important assumptions are made, such as stock markets are inefficient, a typical investor is rational, and an arbitrage opportunity would not last long. For the preferences between two stocks, for a given risk, a rational investor would prefer stock with a higher expected return; for a given return, a rational investor prefers stock with a lower risk level. Sometimes, a single period portfolio optimization is called Markowitz Portfolio Optimization. The input includes a return...

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