Applied Quantitative Finance: Using Python for Financial Analysis

Introduction
Contents
About the Author
List of Figures
List of Tables
List of Equations
Why Python?
	Abstract
	Installing Python in the Computer
	Using Jupyter Notebooks with Python
		Understanding Jupyter Notebooks
	Using Google Colab
	References
Learning to Use Python: The Basic Aspects
	Abstract
	Understanding Numbers in Python
	Understanding Numbers in Python
	Using Data Structures in Python
		What Is a List?
		How to Create a List?
		Measuring a List
		Indexing and Cutting a List
		Appending Lists
		Arranging Lists
		From List to Matrices
		From List to Dictionaries
		Modifying a Dictionary
		Other Interesting Functions of a Dictionary
		The DataFrame
		Boolean, Loops and Other Features
		If, Else and Elif in Python
	Loops
		For Loop
		While Loop
	List Comprehension
	References
Using FRED® API for Economic Indicators and Data (Example)
	Abstract
	Installing the FRED® API
	Using the FRED® API to Retrieve Data
		First Step
		Second Step
		Third Step
		The Gross Domestic Product
		The Gross Domestic Product Price Deflator
		Understanding the Process into the Basics
		Comparing GDP
Using Stock Market Data in Python
	Abstract
	API Sources
	Most Important Libraries for Using Data in Python in the Present Book
	Other Important Libraries Not Used in This Book
	Suggestion of Libraries for Other Applications
	Using Python with Yahoo Finance API
	Using Python with Quandl API
	Using f.fn( ) for Retreiving Information
	Using Python with Excel
	Conclusion Regarding Using Data in Python
Statistical Methods Using Python for Analyzing Stocks
	Abstract
	The Central Limit Theorem
	Creating a Histogram
	Creating a Histogram with Line Plots
		Histograms Using f.fn()
	Histogram (Percent Change) with Two Variables
	Histogram (Logarithmic Return) with Two Variables
	Interquartile Range and Boxplots
	Boxplot with Two Variables
	Kernel Density Plot and Volatility
	Kernel Density Plot (Percent Change) with Two Variables
	Covariance and Correlation
	Scatterplots and Heatmaps
	Works Cited
Elements for Technical Analysis Using Python
	Abstract
	The Linear Plot with One Stock Price (Max & Min Values and the Range)
	When to Use Linear Plots in Finance
	The Linear Plot with Two or More Stock Price
	Linear Plot with Volume
	Volume of Trade
	Comparison of Securities with Volume Plots and Closing Prices
	Candlestick Charts
	Candlestick Charts and Volume
	Customizing Candlestick Charts and Volume with **Kwargs
	OHLC Charts with Volume
	Line Charts with Volume
	Moving Average with Matplotlib
	Moving Average with Mplfinance
	The Exponential Moving Average (EMA)
	The Moving Average Convergence Divergence (MACD) with Baseline
	The Moving Average Convergence Divergence (MACD) with Signal Line
	Bollinger Bands ®
	Backtesting Strategies for Trading
		Parabolic SAR
		Fast and Slow Stochastic Oscillators
	References
Valuation and Risk Models with Stocks
	Abstract
	Creating a Portfolio
	Calculating Statistical Measures on a Portfolio
	The Capital Asset Pricing Model
		The Beta
		The Beta and the CAPM
	Sharpe Ratio
	Traynor Ratio
	Jensen’s Measure
	Information Ratio
	References
Value at Risk
	Abstract
	Historical VaR(95)
	Historical VaR(99)
	VaR for the Next 10 Days
	Historical Drawdown
	Wrapping Up the Book—Understanding Performance
		Portfolio Performance using f.fn()
		Fund Performance using f.fn()
	Works Cited
Works Cited
Index