Python for Financial Markets Analysis

Python for Financial Markets Analysis, available at $69.99, has an average rating of 4.65, with 120 lectures, based on 93 reviews, and has 1046 subscribers.

You will learn about Create interactive data apps with Streamlit Simple to advance practical time series analysis Create trading strategies with technical indicators signals Algo trading with Buy Low and Sell High Strategies Create a stock screener Create a web based (flask) candlesticks pattern screener Calculate Return, Risk, Correlation and Rolling Statistics for Stocks, Indexes and Portfolios Create Financial Indexes with price, equal and value weighted formations Portfolio analysis with pyfolio Finding Higher High and Lower Lows in time series Get 40+ technical indicators and create custom indicators This course is ideal for individuals who are This course is designed for anyone interested in using AI tools like ChatGPT and more to create amazing content, regardless of their background or experience. or Whether you're an entrepreneur, student, professional, or just a curious learner, this course is accessible, engaging, and empowering for everyone. or Anyone who want to explore the world of financial markets or Anyone who want to transition from Excel into Python or Anyone who want to step into Financial Data Science by learning Pandas and more or Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more or Everyone who wants to learn how to code and apply their skills in practice in financial world It is particularly useful for This course is designed for anyone interested in using AI tools like ChatGPT and more to create amazing content, regardless of their background or experience. or Whether you're an entrepreneur, student, professional, or just a curious learner, this course is accessible, engaging, and empowering for everyone. or Anyone who want to explore the world of financial markets or Anyone who want to transition from Excel into Python or Anyone who want to step into Financial Data Science by learning Pandas and more or Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more or Everyone who wants to learn how to code and apply their skills in practice in financial world.

Enroll now: Python for Financial Markets Analysis

Summary

Title: Python for Financial Markets Analysis

Price: $69.99

Average Rating: 4.65

Number of Lectures: 120

Number of Published Lectures: 120

Number of Curriculum Items: 120

Number of Published Curriculum Objects: 120

Original Price: $84.99

Quality Status: approved

Status: Live

What You Will Learn

Create interactive data apps with Streamlit
Simple to advance practical time series analysis
Create trading strategies with technical indicators signals
Algo trading with Buy Low and Sell High Strategies
Create a stock screener
Create a web based (flask) candlesticks pattern screener
Calculate Return, Risk, Correlation and Rolling Statistics for Stocks, Indexes and Portfolios
Create Financial Indexes with price, equal and value weighted formations
Portfolio analysis with pyfolio
Finding Higher High and Lower Lows in time series
Get 40+ technical indicators and create custom indicators

Who Should Attend

This course is designed for anyone interested in using AI tools like ChatGPT and more to create amazing content, regardless of their background or experience.
Whether you're an entrepreneur, student, professional, or just a curious learner, this course is accessible, engaging, and empowering for everyone.
Anyone who want to explore the world of financial markets
Anyone who want to transition from Excel into Python
Anyone who want to step into Financial Data Science by learning Pandas and more
Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more
Everyone who wants to learn how to code and apply their skills in practice in financial world

Target Audiences

This course is designed for anyone interested in using AI tools like ChatGPT and more to create amazing content, regardless of their background or experience.
Whether you're an entrepreneur, student, professional, or just a curious learner, this course is accessible, engaging, and empowering for everyone.
Anyone who want to explore the world of financial markets
Anyone who want to transition from Excel into Python
Anyone who want to step into Financial Data Science by learning Pandas and more
Anyone who want to learn how to do time series analysis on any global financial market instruments. i.e. Stocks, Indexes, Crypto and more
Everyone who wants to learn how to code and apply their skills in practice in financial world

Welcome to Python for Financial Markets Analysis!

Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you!

This course will guide you through everything you need to know to use Python for analyzing financial markets data! I’ve worked for Bloomberg for 17+ years and will present the knowledge to help you in this course.

We’ll start off by learning the fundamentals of financial market data, importing large datasets and then proceed to learn about the various core libraries used in the Finance world including jupyter, numpy, pandas, matplotlib, statsmodels, yfinance, plotly, cufflinks and much more. We will use jupyter notebooks, google colabs and visual studio to write our python apps for finance.

We’ll cover the following topics:

Python Fundamentals
NumPy for High Speed Numerical Processing
Pandas for Efficient Data Analysis
Matplotlib for Data Visualization
Pandas Time Series Analysis Techniques
Statsmodels
Importing financial markets data
Working with single and multiple stocks with prices, fundamental data
Streaming real-time data prices
Create interactive financial charts with plotly, cuffllinks
Using annotation to tell the data story
Simple to advanced time series analysis
Time series analysis with indexing, filling and resampling
Rate of returns analysis for stocks, crypto and indexes
Create Financial Indexes with price, equal and value weighted formations
Create custom technical indicators – Squeeze momentum, point and figure and more
Create trading strategies with technical indicators
Explore stock statistics with peer analysis, returns rates, and heatmaps
Find best and worst returns months for any global instruments
Create your very own stock screen
Create your very own web based (flask) candlestick pattern screener
Algo trading with Buy Low and Sell High Strategies
Portfolio analysis with pyfolio
Create interactive data apps with streamlit
and much more…

Why you should listen to me…

In my career, I have built an extensive level of expertise and experience in both areas: Finance and Coding

Finance:

17 years experience in Bloomberg for the Finance and Investment Industry…
Build various financial markets analytics companies like
- KlickAnalytics,
- ClickAPIs and more

Python & Pandas:

My existing companies extensively used python based models and algorithms
Code, models, and workflows are Real World Project-proven

Best Seller author on Udemy

e.g. PostgreSQL Bootcamp: Go from Beginner to Advanced, 60+ Hours course
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What are you waiting for? Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.

Looking Forward to seeing you in the Course!

LETS GET STARTED!

Course Curriculum

Chapter 1: Importing Financial Markets Data

Lecture 1: Install python

Lecture 2: Install Anaconda

Lecture 3: Downloading and Importing finance data

Lecture 4: Installing required package

Lecture 5: Download OHLC price for single stock

Lecture 6: Get specfic time range data

Lecture 7: Get Intra-day data

Lecture 8: Get Pre and Post Market Data

Lecture 9: Fundamentals, Dividends, Splits and News

Lecture 10: Splits and Dividends

Lecture 11: Import multiple stocks

Lecture 12: Export Data to CSV and Excel

Lecture 13: From Dictionary > Series > Frame

Lecture 14: Get Stock Earnings Information

Lecture 15: Get Stock Analyst Recommendations

Lecture 16: Get Stock Options Data

Lecture 17: Get Stock Shareholders

Lecture 18: Import and normalize Financial Indexes

Lecture 19: Import ETFs and Mutual Fund Data

Lecture 20: Import currency data

Lecture 21: Import Cryptocurrencies

Lecture 22: Import Treasury Yields Data

Lecture 23: Streaming real-time data

Chapter 2: Python Basic 101

Lecture 1: Data types and Numbers

Lecture 2: Variables

Lecture 3: Integers and Float

Lecture 4: Strings

Lecture 5: Lists

Lecture 6: Dictionaries

Lecture 7: For loops

Lecture 8: If conditions

Lecture 9: Functions

Chapter 3: Creating Interactive Financial Charts

Lecture 1: Explore Plotly and cufflinks

Lecture 2: Customizing charts

Lecture 3: Spread Charts

Lecture 4: Interactive Histogram

Lecture 5: Candle and OHLC Charts

Lecture 6: Technical Indicators : SMA and Bollinger Bands

Lecture 7: Adding Volume and MACD Indicators

Lecture 8: Using annotation to tell the story

Lecture 9: Create an interactive candle chart + technical indicators

Chapter 4: Time Series Analysis

Lecture 1: The power of index()

Lecture 2: Handling missing data in time series

Lecture 3: Creating new data frame and using reindex

Lecture 4: Using bfill and ffill methods

Lecture 5: Resample time series

Lecture 6: Timezone travel with time series

Lecture 7: Shifting dates

Lecture 8: Find largest and smallest numbers

Lecture 9: Pandas profiling library

Chapter 5: Translating SQL style queries

Lecture 1: Calculate Boolean statistics

Lecture 2: Construct multiple boolean conditions

Lecture 3: Translate SQL where clauses

Chapter 6: Rate of Returns Analysis

Lecture 1: Calculate rate of returns

Lecture 2: Log returns of a security

Lecture 3: Rate of return for a portfolio

Lecture 4: Rate of returns for major indices

Lecture 5: Calculate Annualize Returns

Chapter 7: Exploring Risk Analysis

Lecture 1: Calculating a security risk

Chapter 8: Creating weighted indexes

Lecture 1: Prepare data, normalize data

Lecture 2: Calculate Price Weighted Index

Lecture 3: Calculate weights of constituents over time

Lecture 4: Calculate Equal Weighted Index

Chapter 9: Point and figure charts

Lecture 1: Create point and figure charts

Chapter 10: Quick Stock Analysis

Lecture 1: Exploring Rolling Mean, Returns Deviations

Lecture 2: Exploring Peer Analysis

Lecture 3: Returns Rates and Risk with heat map

Lecture 4: Find best and worst returns by months

Chapter 11: Explore Stock Statistics

Lecture 1: Calculate SMA on the fly

Lecture 2: Calculate technical indicators with custom values

Lecture 3: Calculate custom up and down days

Lecture 4: Min, max and delta changes

Chapter 12: Crypto vs Stock Market correlations

Lecture 1: Is crypto market is correlation to stock market?

Chapter 13: Exploring Technical Indicators

Lecture 1: Introduction to technical indicators

Lecture 2: Simple Moving Averages (SMA)

Lecture 3: Exponential Moving Averages (EMA)

Lecture 4: Bollinger Bands

Lecture 5: MACD

Lecture 6: Create technical indicator manually – MACD

Lecture 7: Create technical indicator manually – MACD – Part 2

Lecture 8: Relative Strength Index (RSI)

Lecture 9: RSI – Overbought / Oversold Signals

Lecture 10: Calculate pivot points

Lecture 11: Getting 40+ technical indicators…

Chapter 14: Technical Indicators Signals

Lecture 1: Simple Moving Averages – Setting up data, and strategy

Lecture 2: Visualization

Instructors

Adnan Waheed
Founder KlickAnalytics and ex-Bloomberg employee

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 8 votes
4 stars: 25 votes
5 stars: 58 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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