Importing Finance Data with Python from Free Web Sources
What you’ll learn
Importing free / low-priced Financial Data from the Web with Python
Installing the required Libraries and Packages
Working with powerful APIs and Python wrapper packages
Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETF´s
Downloading Historical Prices for Currencies (FOREX), Cryptocurrencies, Bonds & more
Saving / Storing the Data locally
Pandas Coding Crash Course
Requirements
Some Python Basics
A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
An internet connection capable of streaming videos and downloading data
Ideally first experience with Pandas Library (not necessary, a Pandas crash course is included in the course)
Description
What can be the most critical and most expensive part when working with financial data?Pandas coding? Creating some advanced Algorithms to analyse and optimize portfolios? Building solutions for Algorithmic Trading and Robo Advising? Maybe! But very often it is … getting the Data!Financial Data is scarce and Premium Data Providers typically charge $20,000 p.a. and more! However, in 95% of all cases where Finance Professionals or Researchers require Financial Data, it can actually be obtained from Free or low-priced web sources. Some of them provide powerful APIs and Python wrapper packages, which makes it easy and comfortable to import the data with and into Python. +++ This course shows you how to get massive amounts of Financial Data from the web and provides downloadable Python coding templates (Jupyter Notebooks) for your convenience! +++ This course covers four different data sources and explains in detail how to install required Libraries and how to download and import the data with few lines of Python Code. You will have access to60+ Exchanges all around the world120,000+ Symbols/InstrumentsHistorical Price and Volume Data for thousands of Stocks, Indexes, Mutual Funds and ETFsForeign Exchange (FOREX): 150+ Physical Currencies / Currency Pairs500+ Digital- / CryptocurrenciesFundamentals, Ratings, Historical Prices and Yields for Corporate BondsCommodities (Crude Oil, Gold, Silver, etc.)Stock Options for 4,500 US StocksFundamentals, Metrics and Ratios for thousands of Stocks, Indexes, Mutual Funds and ETFsBalance SheetsProfit and Loss Statements (P&L)Cashflow Statements50+ Technical Indicators (e.g. SMA, Bollinger Bands)Real-time and Historical Data (back to 1960s)Streaming high-frequency real-time DataStock Splits and Dividends and how these are reflected in Stock PricesLearn how Stock Prices are adjusted for Stock Splits and Dividends…… and use appropriately adjusted data for your tasks! (avoid the Pitfalls!) Build your own Financial Databases…… And save thousands of USDs!What are you waiting for? As always, I provide a 30-Days-Money-Back Guarantee. So, there is no risk for you!Looking forward to seeing you in the course!
Overview
Section 1: Getting Started
Lecture 1 Tips: How to get the most out of this Course
Lecture 2 Course Overview
Lecture 3 Hands-on: Downloading CSV-files and import to Python
Section 2: Importing Financial Data from Web Source 1
Lecture 4 Intro
Lecture 5 Installing the required Package
Lecture 6 Historical Price and Volume Data for one Stock
Lecture 7 Setting specific Time Periods
Lecture 8 Frequency Settings (Intraday)
Lecture 9 Stock Splits and Dividends
Lecture 10 Exporting to CSV / Excel
Lecture 11 Importing many Stocks
Lecture 12 Financial Indexes
Lecture 13 Currencies / FX
Lecture 14 Cryptocurrencies
Lecture 15 Mutual Funds & ETFs
Lecture 16 Treasury Yields
Lecture 17 The Ticker Object
Lecture 18 *** UPDATE March 2023*** the yahooquery alternative
Lecture 19 *** Updated Notebooks March 2023***
Lecture 20 Stock Fundamentals, Meta Info and Performance Metrics
Lecture 21 Financials (Balance Sheet, Cashflows, P&L)
Lecture 22 Put / Call Options
Lecture 23 Streaming Real-time Data
Section 3: Importing Financial Data from Web Source 2
Lecture 24 Intro / Get your API Key
Lecture 25 Installing the required Package
Lecture 26 Historical Price and Volume Data for one Stock
Lecture 27 Setting specific Time Periods
Lecture 28 Stock Splits and Dividends
Lecture 29 Converting to DatetimeIndex
Lecture 30 Frequency Settings (Intraday)
Lecture 31 Technical Indicators
Lecture 32 Currencies / FX
Lecture 33 Cryptocurrencies
Section 4: Importing Financial Data from Web Source 3
Lecture 34 Intro / Register and get your API Key
Lecture 35 Commands to install required packages
Lecture 36 Installing the required Package
Lecture 37 Connecting to the API/Server
Lecture 38 Currencies / FX (incl. Bid/Ask)
Lecture 39 Frequency Settings (Intraday)
Lecture 40 Setting specific Time Periods
Lecture 41 Stock Indexes (incl. Bid/Ask)
Lecture 42 Commodities (incl. Bid/Ask)
Lecture 43 Cryptocurrencies (incl. Bid/Ask)
Lecture 44 Streaming high-frequency real-time Data (Part 1)
Lecture 45 Streaming high-frequency real-time Data (Part 2)
Section 5: Web Source 3b (for US and Canadian Residents)
Lecture 46 Intro / Register
Lecture 47 Commands to install required packages
Lecture 48 Installing the required Packages
Lecture 49 Get your API Key and connect to the Server
Lecture 50 Getting Historical Data
Lecture 51 Frequency Settings (high-frequency Intraday Data)
Lecture 52 Streaming high-frequency real-time Data
Section 6: Importing Financial Data from Web Source 4
Lecture 53 Intro / Register and get your API Key
Lecture 54 Introduction to the API (hands-on)
Lecture 55 Getting Historical Stock Prices and Volume Data
Lecture 56 Stock Splits and Dividends
Lecture 57 Financial Indexes
Lecture 58 Currencies / FX
Lecture 59 Cryptocurrencies
Lecture 60 Commodities
Lecture 61 Mutual Funds & ETFs
Lecture 62 Treasury Yields
Lecture 63 Stock Fundamentals, Meta Info and Performance Metrics
Lecture 64 Financials (Balance Sheet, Cashflows, P&L)
Lecture 65 Fundamentals and Performance Metrics for Funds & ETFs
Lecture 66 Bond Data: Fundamentals
Lecture 67 Bonda Data: Ratings
Lecture 68 Bond Data: Historical Prices and Yields
Lecture 69 Bulk Download of Ticker Symbols for entire Exchanges
Lecture 70 Bulk Download of Stock Prices, Stock Splits and Dividends
Section 7: Installing Python and Download/Working with Templates
Lecture 71 Installing Anaconda
Lecture 72 How to open a Jupyter Notebook
Lecture 73 Working with Jupyter Notebooks
Lecture 74 Downloading and Working with Templates (***Updated March 2023***)
Section 8: Appendix 1: Pandas Crash Course
Lecture 75 Intro to Tabular Data / Pandas
Lecture 76 Tabular Data Cheat Sheets
Lecture 77 Download of Datasets (csv files)
Lecture 78 First Steps (Inspection of Data, Part 1)
Lecture 79 First Steps (Inspection of Data, Part 2)
Lecture 80 Built-in Functions, Attributes and Methods
Lecture 81 Make it easy: TAB Completion and Tooltip
Lecture 82 Selecting Columns
Lecture 83 Selecting Rows with iloc
Lecture 84 Selecting Rows with loc
Lecture 85 Pandas Series
Lecture 86 Importing Time Series Data from csv-files
Lecture 87 Converting strings to datetime objects with pd.to_datetime()
Lecture 88 Initial Analysis / Visualization of Time Series
Lecture 89 Indexing and Slicing Time Series
Lecture 90 Initial Inspection and Visualization of Financial Time Series
Lecture 91 Normalizing Time Series to a Base Value (100)
Lecture 92 Hands-on: Importing Excel-Files to Python
Section 9: What´s next? (outlook and additional resources)
Lecture 93 Bonus Lecture
Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data.,(Finance) Students and Researchers who need to work with large financial datasets with only small budgets.,Everybody working occasionally with Financial Data.
Course Information:
Udemy | English | 7h 49m | 3.03 GB
Created by: Alexander Hagmann
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