Web Scraping Market, Financial and Economic Data Using Python 3, REST Web Servic

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pdf, azw | 155.14 MB | English | Lee, John | 2020

Book Description :

FREE FREE

There are two main things you will learn from this book. The first main theme is that there are a lot of FREE market, financial, market, and other types of data on the internet. This book will tell you will where to go to get the FREE data. A lot of time was spent hunting for the FREE data. This hunt has brought me to many unexpected places on internet. Below is the outline of the book. Each chapter tells you where to go to get the FREE data. The second main theme is it gives you the Python code to retrieve the free data. A lot of time was spent developing the Python code. This will save you a lot of headaches.

This book uses Python 3.7 and beautifulsoup to retrieve many different types of market, financial and economic data. The types of market, financial and economic data we will retrieve are stock, market index, currency rates, bonds, futures, mutual funds, electronic traded funds (ETF), commodities, balance sheet, income, statement of cash flow, GDP, consumer price index, unemployment rate, household income, and money supply. This book also sho how to retrieve free weather and zip code data.

There are two ways to retrieve market data; one of them is web scraping the data; the other is to use the REST web service or REST API that is provided by the web site. When web scraping, we will use the beautifulsoup Python library.

Table of Contents
---------------------
1 Introduction
1.1 Target Audience
1.2 Official Python Website
1.3 Anaconda and Python 3.7
1.4 Python (IDE)
2Market Indexes
2.1Dow Jones Industrial Average
2.2S&P 500 Index
2.3Nasdaq Composite Index
3Mutual Funds
3.1Credit Rating Agencies and the SEC
3.2Mutual Fund Python Code.
3.325 Largest Mutual Funds
3.4Risk Measure - Beta of 1.0
3.5Risk Measure - Alpha
3.6S&P 500
3.7NASDAQ Index Mutual Funds
4Electronic Traded Funds (ETF)
4.1ETF Python Code
4.2Top 6 S&P 500 ETF
4.3Dow Jones Industrial Average ETF Fund
5Stocks
5.1Stock Exchanges
5.2Plotting historical/Time-series Data
5.3Microsoft (MSFT) and Market Indexes
5.4High, Low, Negative Beta Stocks
6Call and Put Options on Stock
6.1Python Code
6.2Call Stock Options
6.3Put Stock Options
7Currency
7.1Latest FX Rates
7.2Major Currencies
7.3Minor Currencies
7.4Exotic Currencies
7.518 Python Code - Major, Minor, Exotic
7.618 Python Output - Major, Minor, Exotic
7.7Currency Pairs
7.8Plotting Historical Currency Rates
8Bonds
8.1U.S. Treasuries
8.2Corporate Bonds
8.3World Government Bonds
8.4Regional Government Bonds
9Credit Ratings
10Central Bank Rates
11Sovereign Credit Default Swaps (CDS)
12Dividends
12.1History
12.2Dividend Payment Dates
12.3Mutual Funds
13Financial Statements
13.1Microsoft Peers
13.2Balance Sheet
13.3Income Statement
13.4Statement of Cash Flo
14Financial Ratios
14.1Investment Valuation Ratios
14.2Profitability Indicator Ratios
14.3Operating Performance Ratio
14.4Liquidity Measurement Ratios
14.5Debt Ratios
14.6Cash Flow Indicator Ratios
15Measuring Market Volatility
15.1COBE Volatility Index (^VIX)
15.2S&P 500 VIX Futures Contracts
16NYSE Holidays
16.1Python Code
16.2Python Output
17S&P 500 Sector Performance
17.1Python Code
17.2Python Output
18Federal Reserve Economic Data (FRED)
18.1QUANDL Data Provider
18.2Gross Domestic Product
18.3Consumer Price Index
18.4M1 Money Stock
18.5Unemployment Rate
18.6Real Median Household Income
19Commodities
19.1Energy
19.2Metals
19.3Agriculture
19.4Meat & Livestock
19.5Consumer
19.6Python Code
19.7Python Output
19.8Historical Commodity Prices
20Zip Codes
20.1City
20.2Zip Code of City
21Weather
21.1Current Forecast
22References

Category : | Python Computer Programming, Macroeconomics, Macroeconomics

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