Python for Financial Markets Analysis from Udemy

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.

What's inside

Learning objectives

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
Show more
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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
Show more
Show less

Syllabus

Importing Financial Markets Data

Install python

Install Anaconda

Downloading and Importing finance data

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Read about what's good

what should give you pause

and possible dealbreakers

Explores industry standard libraries and module jupyter, numpy, pandas, matplotlib, statsmodels, yfinance, plotly, cufflinks and more

Beginner-friendly introduction to practical time series analysis

Covers a wide range of topics in financial markets analysis, from Python basics to advanced time series analysis

Provides opportunities for hands-on practice through interactive data apps and coding exercises

Requres learners to have a basic understanding of Python

Reviews summary

Practical python for financial markets

According to the comprehensive syllabus, learners can expect a rigorous exploration of Python for financial markets analysis, starting with Python fundamentals and progressing to advanced algorithmic trading strategies. The course appears to offer extensive coverage of key financial libraries like Pandas and Plotly, enabling students to create interactive financial charts and time series analyses. Students aiming to build practical trading strategies and interactive data applications with Streamlit and Flask may find the content highly relevant. The instructor's 17 years of experience at Bloomberg suggests a strong foundation in real-world applications, which could be a significant positive.

Starts with basics, progresses to complex topics.

"I appreciate that the course begins with Python fundamentals before diving into financial applications."

"It builds from simple data import to advanced time series and algorithmic trading."

"The structured progression from basic Python to complex financial models is very helpful."

Emphasizes real-world application for financial tasks.

"I'm keen to apply the techniques for creating trading strategies and stock screeners in real-world scenarios."

"The hands-on approach to building interactive charts and data apps is very practical."

"Learning to analyze financial data with Python for actual market insights is exactly what I need."

Covers wide range of Python, finance, and tools.

"I was impressed by the breadth of topics, from Python basics to complex algo trading concepts."

"The course covers many essential libraries and techniques needed for financial data analysis."

"It's great to see topics like Streamlit and Flask included for building full applications."

Benefits from instructor's extensive industry experience.

"I appreciate learning from someone with 17 years at Bloomberg, which adds significant real-world value."

"The instructor's background in both finance and coding gives me confidence in the course's practical insights."

"I expect the content to be directly applicable, given the instructor's experience building analytics companies."

Extensive content might require prior knowledge or faster pace.

"Given the sheer volume of topics, I wonder if each concept receives sufficient depth for mastery."

"For someone new to either Python or finance, the pace of covering so much content might be challenging."

"I might need to supplement some sections with additional learning if I'm not already familiar with the subject."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python for Financial Markets Analysis with these activities:

Time Series Analysis with Pandas

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Build a solid foundation of pandas for time series analysis.

Browse courses on Time Series Analysis

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Follow the tutorial on time series analysis with pandas.
Complete the exercises provided in the tutorial.

Financial data visualization with Plotly

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Enhance your data visualization skills for presenting financial data.

Browse courses on Data Visualization

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Follow the tutorial on financial data visualization with Plotly.
Create interactive charts and graphs to visualize your financial data.

Conduct fundamental analysis on major companies

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Develop an understanding of how to evaluate the financial health of companies.

Browse courses on Fundamental Analysis

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Gather financial statements for the target companies.
Analyze the financial ratios and metrics.
Write a report summarizing your findings.

Three other activities

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Calculate technical indicators

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Generate buy and sell signals using built-in technical indicators.

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Import the relevant Python packages.
Load the financial data.
Calculate the desired technical indicators.
Plot the calculated indicators.

Trading Simulation Project

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Test and evaluate your trading strategies in a simulated environment.

Browse courses on Technical Analysis

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Design your trading strategy.
Backtest your strategy on historical data.
Refine your strategy based on the backtesting results.

Machine Learning for Financial Data Analysis

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Explore the use of machine learning techniques for predicting financial outcomes.

Browse courses on Machine Learning

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Attend the workshop on machine learning for financial data analysis.
Apply the learned techniques to predict financial outcomes.

Career center

Learners who complete Python for Financial Markets Analysis will develop knowledge and skills that may be useful to these careers:

Financial Analyst

Financial analysts use financial data to make recommendations on investments. The skills you will build in this course are useful for financial analysts as this course will teach you to analyze financial data with Python. Furthermore, you will learn how to stream real-time data prices and build custom technical and trading strategies. This course will equip you with the knowledge needed for foundational skills in financial analysis.

See salaries and explore the career path for Financial Analyst

Investment Analyst

Investment analysts evaluate and make recommendations on investment opportunities. This course will teach you how to import financial markets data. You will also learn how to calculate return, risk, correlation, and rolling statistics for stocks, indexes, and portfolios. This can help you make informed recommendations on investment opportunities.

See salaries and explore the career path for Investment Analyst

Portfolio Manager

Portfolio managers oversee the investment portfolios of their clients. This course will teach you how to import financial markets data and how to calculate return, risk, correlation, and rolling statistics for stocks, indexes, and portfolios. This can help you make informed investment decisions as a portfolio manager.

See salaries and explore the career path for Portfolio Manager

Financial Risk Manager

Financial risk managers use their knowledge of finance and risk management to help companies identify, assess, and manage financial risks. This course can help you understand how to import financial markets data and how to calculate return, risk, correlation, and rolling statistics for stocks, indexes, and portfolios. This can be helpful in identifying and quantifying financial risks in the real world.

See salaries and explore the career path for Financial Risk Manager

Risk Analyst

Risk analysts identify, assess, and manage financial risks. This course will help you learn how to import financial markets data and how to calculate return, risk, correlation, and rolling statistics for stocks, indexes, and portfolios. This can help you understand and communicate financial risks more effectively as a risk analyst.

See salaries and explore the career path for Risk Analyst

Data Analyst

Data analysts collect, clean, analyze, and interpret data to help businesses make informed decisions. Since you'll learn how to use the fundamental tools used for data analysis (Python, NumPy, Pandas, etc) in this course, it can help equip you with valuable skills for working as a data analyst. You will learn how to import, manipulate, and visualize large datasets. The course even covers creating interactive data apps with Streamlit, which may be useful in this role depending on the company you work for.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course may be a good foundation for understanding how to analyze financial data with programming and building quantitative models. You will learn how to build trading strategies based on technical indicators, which may be of particular interest to this role.

See salaries and explore the career path for Quantitative Analyst

Quantitative Researcher

Quantitative researchers use mathematical and statistical models to develop investment strategies. This course will help you learn how to analyze financial data with Python and how to build custom technical and trading strategies. This can help you develop more informed investment strategies as a quantitative researcher.

See salaries and explore the career path for Quantitative Researcher

Hedge Fund Manager

Hedge fund managers use a variety of investment strategies to generate high returns for their clients. This course will teach you how to analyze financial data with Python and how to build custom technical and trading strategies. This can help you make informed investment decisions as a hedge fund manager.

See salaries and explore the career path for Hedge Fund Manager

Investment Banker

Investment bankers provide financial advice and services to corporations and governments. This course will teach you how to import financial markets data. This can help you understand the financial markets and make informed recommendations to your clients as an investment banker.

See salaries and explore the career path for Investment Banker

Data Scientist

Data scientists use their knowledge of math, statistics, and computer science to solve business problems. This course can help data scientists learn about financial data analysis with Python. It covers installing Python and Anaconda, downloading and importing finance data, and using popular Python libraries for data analysis. However, it may be important to supplement this course with additional coursework or practical experience to gain a more comprehensive foundation for working as a data scientist in the financial industry.

See salaries and explore the career path for Data Scientist

Actuary

Actuaries use mathematical and statistical models to assess financial risks and make recommendations on how to manage them. This course will teach you how to import financial markets data and how to calculate return, risk, correlation, and rolling statistics for stocks, indexes, and portfolios. This can help you understand and communicate financial risks more effectively as an actuary.

See salaries and explore the career path for Actuary

Financial Consultant

Financial consultants provide advice and guidance to individuals and businesses on financial matters. This course can help financial consultants learn how to analyze financial data with Python. It covers installing Python and Anaconda, downloading and importing finance data, and using popular Python libraries for data analysis.

See salaries and explore the career path for Financial Consultant

Business Analyst

Business analysts use data to solve business problems and improve decision-making. This course can help business analysts learn about financial data analysis with Python. Since you'll learn how to import, manipulate, and analyze financial data with Python, this may be useful in this role, depending on the company you work for.

See salaries and explore the career path for Business Analyst

Software Engineer

Software engineers design, develop, and maintain software systems. This course can help software engineers learn about financial data analysis with Python. It covers installing Python and Anaconda, downloading and importing finance data, and using popular Python libraries for data analysis. This may be helpful for software engineers who want to work on financial software or who want to gain a better understanding of how financial data is analyzed and used.

See salaries and explore the career path for Software Engineer