Python for Finance – Financial Analysis

The Finance and Investment Industry is experiencing rapid change due to the rapid advancement of processing power, connectivity, and machine learning tools. Not only this, Finance and Investment are increasingly becoming a data-driven business, shifting from a math/formula-based business.

Intermediate 0(0 Ratings) 9 Students enrolled English-hindi
Created by Jobaaj Learnings
Last updated Wed, 27-Oct-2021
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Course overview

Why do you need to take this Python for Finance Course? The Finance and Investment Industry is experiencing rapid change due to the rapid advancement of processing power, connectivity, and machine learning tools. Not only this, Finance and Investment are increasingly becoming a data-driven business, shifting from a math/formula-based business.

How can you keep up?
You need to leave Excel behind to manage your Financial Data. Python and Pandas offer the opportunity for deep dives into Machine Learning, as well as becoming more efficient at work when you are dealing with Financial Data.
Learning Pandas from scratch is nearly as easy as learning Excel. Pandas is like Excel for Python. Due to its many features, Pandas appears to be more complicated than other tools. As you practice, you will become familiar with pandas and will be able to use them for managing financial data, for meeting the same goal Jobaaj Learnings introduced Advanced Python for Finance Course.

Significant Highlights of The Course

  • Deep Dive in Pandas, Financial Data, and Financial Concepts
  • Online video lectures
  • Quizzes for Practice
  • Taught by qualified Python professional
  • Projects at the end of the course

 

Why learn Pandas?

The workflows you usually carry out with Excel can be more efficiently done with Pandas. There may be dozens of lines of coding running automatically behind the scenes of Pandas, which is a high-level coding library. Pandas operations are typically wiped out in one line of code! However, you must learn and master Pandas in an order that enables you to understand more about what’s going on and realize the pitfalls (Don’ts) and remain compliant (DOs). Python/Panda coding is one of the most in-demand skills in Finance.

The difficulty level can be selected from the Python courses we offer:-

For getting started with Python you can choose our Python for Finance Level – 1 Course, there is no prior knowledge needed. In Python for Finance Level – 2 you’ll be learning to Import Financial Data from Free Web Sources, CSV, and Excel Files. Calculate Returns, Risks, and Correlations of Stocks, Indexes, and Portfolios. Calculate Simple Returns, Log Returns, and Annualized Returns and Risks. Learn how to construct your financial index (price, equal, or value-based). Optimize your stock portfolio Calculate Sharpe Ratio, Systematic Risk, Unsystematic Risk, Beta, and Alpha for stocks, indexes, and portfolios. Understanding Modern Portfolio Theory and Risk Diversification, thus allowing for Capital Asset Pricing Model (CAPM). Insight into Mean-Variance Optimization (MVO) and how it is used in Real World (and why it is not used in many cases). Create customized charting with technical indicators (SMA, Candle Stick, Bollinger Bands, etc.) for the financial performance (e.g. Rolling Statistics, Simple Moving Averages, etc.)

What else do we offer?

  • Practical-oriented course
    There is a strong practical focus to the course lessons, and students work only with the existing programs to demonstrate the concepts. Every module ends with a Quiz containing practical questions related to the course, and students are encouraged to answer the questions before moving forward.
  • Quizzes for practice
    A quiz is also included at the end of every section of this course and the module end questions. We have also provided worksheets, assignments, and projects for practice.
  • Instructor support for questions
    Connect with Instructor via WhatsApp/Mail. Jobaaj understands that students will have questions about the course. It is also necessary for a healthy learning process, so we encourage students to ask their questions in the videos discussion forum. Every question will be answered as soon as possible.

 

Who can take this Course?

  • For Investment & Finance Professionals who are interested in transitioning from Excel to Python to boost their careers and work efficiency.
  • Finance Students and Researchers who learned to handle large datasets and reached the limits of Excel.
  • Data Scientists who want to improve their data handling/manipulation skills (in particular for statistical data).
  • Anyone interested in data science (financial).
  • Anybody who is interested in how Financial Performance is measured and how indices (stock) and portfolios are created, analyzed, visualized, and optimized. By using data examples instead of theories and formulas, it is easier to understand the concepts.

What will i learn?

Requirements
  • Python for Finance
Curriculum for this course
118 Lessons 01:58:45 Hours
Deep Dive in Pandas
15 Lessons 01:58:45 Hours
  • Creating an Equal-Weighted Stock Index with Python
    .
  • Beta and Alpha
    .
  • Dropping Rows and Columns using Pandas
    00:25:26
  • Adding new Columns using Square Brackets
    00:11:00
  • Case study for Arithmetic Operations on NITI Ayog Data
    00:35:12
  • Best possible ways to create a DataFrame
    00:18:11
  • Adding new Rows (Custom Data)
    00:15:24
  • Merging, Joining and Concatenating Dataframes
    00:13:32
  • Manipulating Elements in a DataFrame
    .
  • Introduction to GroupBy Operations
    .
  • Splitting with many Keys
    .
  • split-apply-combine
    .
  • split-apply-combine applied
    .
  • Hierarchical Indexing with Groupby
    .
  • stack() and unstack()
    .
Time Series in Pandas
9 Lessons 00:00:00 Hours
  • Importing Time Series Data from csv-files
    .
  • Converting strings to datetime objects with pd.to_datetime()
    .
  • Initial Analysis / Visualization of Time Series
    .
  • Indexing and Slicing Time Series
    .
  • Creating a customized DatetimeIndex with pd.date_range()
    .
  • More on pd.date_range()
    .
  • Downsampling Time Series with resample()
    .
  • The PeriodIndex object
    .
  • Advanced Indexing with reindex()
    .
Importing Financial Data from Yahoo Finance
11 Lessons 00:00:00 Hours
  • Getting Data of TESLA Stock by YFinance
    .
  • Customising the Stock Data by YFinance
    .
  • Stock Split and Dividends by YFinance
    .
  • Exporting to CSV/ Excel File by YFinance
    .
  • Importing multiples stocks and Financial Indexes Data by YFinance
    .
  • Importing Currency Exchange & CryptoCurrency Data by YFinance
    .
  • Importing Mutual Funds, ETFs & Treasury Yields Data by YFinance
    .
  • Stock Fundamentals, Meta Info and Performance Metrics by YFinance
    .
  • Financials (Balancesheet, Cashflows, P&L) by YFinance
    .
  • Put and Call Options by YFinance
    .
  • Stream Real Time data from YFinance by YFinance
    .
Importing Financial Data from Alpha Vantage
9 Lessons 00:00:00 Hours
  • Register and get your API Key on Alpha Vantage
    .
  • Hands on API
    .
  • Getting Data of TESLA Stock by Alpha Vantage
    .
  • Setting specific Time Period
    .
  • Stock Split and Dividends by Alpha Vantage
    .
  • Converting to DatetimeIndex
    .
  • Frequency Setting
    .
  • Real time data and Technical Indicators
    .
  • Importing Currency Exchange & CryptoCurrency Data by Alpha Vantage
    .
Importing Financial Data from FXCM
6 Lessons 00:00:00 Hours
  • Register and get your API Key on FXCM
    .
  • Hands on API
    .
  • Hands on API
    .
  • Setting Specific Time Period and Frequency
    .
  • Stock Indexes, Commodities & Cryptocurrencies
    .
  • Streaming High Frequency Real time Data By FXCM
    .
Importing Financial Data from OANDA (for US & Canadian Residents)
4 Lessons 00:00:00 Hours
  • Register and get your API Key on OANDA
    .
  • Hands on API
    .
  • Get Historical Data
    .
  • Streaming High Frequency Real time Data By OANDA
    .
Importing Financial Data from EOD
12 Lessons 00:00:00 Hours
  • Getting Data of TESLA Stock by EOD
    .
  • Customising the Stock Data by EOD
    .
  • Stock Split and Dividends by EOD
    .
  • Importing multiples stocks and Financial Indexes Data by EOD
    .
  • Importing Mutual Funds, ETFs & Treasury Yields Data by EOD
    .
  • Importing Currency Exchange & CryptoCurrency Data by EOD
    .
  • Stock Fundamentals, Meta Info and Performance Metrics by EOD
    .
  • Financials (Balancesheet, Cashflows, P&L) by EOD
    .
  • Put and Call Options by EOD
    .
  • Stream Real Time data from YFinance by EOD
    .
  • All about Bond Data – Fundamentals, Ratings, Historical Prices and Yields
    .
  • Bulk Data Download by EOD
    .
Financial Data - Essential Workflows (Risk, Return & Correlation)
8 Lessons 00:00:00 Hours
  • Importing Stock Price Data from Yahoo Finance (it still works!)
    .
  • Initial Inspection and Visualization
    .
  • Normalizing Time Series to a Base Value (100)
    .
  • The shift() method
    .
  • The methods diff() and pct_change()
    .
  • Measuring Stock Performance with MEAN Returns and STD of Returns
    .
  • Financial Time Series – Return and Risk
    .
  • Financial Time Series – Covariance and Correlation
    .
Advanced Techniques (Rolling Statistics & Reporting) on Financial Data
14 Lessons 00:00:00 Hours
  • Importing Financial Data from Excel
    .
  • Simple Moving Averages (SMA) with rolling()
    .
  • Momentum Trading Strategies with SMAs
    .
  • S&P 500 Performance Reporting – rolling risk and return
    .
  • S&P 500: Investment Horizon and Performance
    .
  • Simple Returns vs. Log Returns
    .
  • The S&P 500 Return Triangle
    .
  • The S&P 500 Dollar Triangle
    .
  • The S&P 500 “Weather Radar”
    .
  • Exponentially-weighted Moving Averages (EWMA)
    .
  • Expanding Windows
    .
  • Rolling Correlation
    .
  • rollling() with fixed-sized time offsets
    .
  • Merging / Aligning Financial Time Series (hands-on)
    .
Creating and Analysing Financial Indexes
9 Lessons 00:00:00 Hours
  • Financial Indexes
    .
  • Getting the Data
    .
  • Price-Weighted Index – Theory
    .
  • Creating a Price-Weighted Stock Index with Python
    .
  • Equal-Weighted Index
    .
  • Market Value-Weighted Index – Theory
    .
  • Creating a Market Value-Weighted Stock Index with Python
    .
  • Comparison of weighting methods
    .
  • Price Index vs. Performance/Total Return Index
    .
Create, Analyze and Optimize Financial Portfolios
5 Lessons 00:00:00 Hours
  • Getting the Data
    .
  • Creating many random Portfolios with Python
    .
  • What is the Sharpe Ratio and a Risk Free Asset?
    .
  • Finding the Optimal Portfolio
    .
  • Sharpe Ratio – visualized and explained
    .
Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)
5 Lessons 00:00:00 Hours
  • Capital Market Line (CML) & Two-Fund-Theorem
    .
  • The Portfolio Diversification Effect
    .
  • Systematic vs. unsystematic Risk
    .
  • video coming soon
    .
  • video coming soon
    .
Forward-looking Mean-Variance Optimization & Asset Allocation
5 Lessons 00:00:00 Hours
  • Mean-Variance Optimization (MVO)
    .
  • It´s not that simple – Part 1 (Investments 101 vs. Real World)
    .
  • Changing Expected Returns
    .
  • It´s not that simple – Part 2 (Investments 101 vs. Real World)
    .
  • Cyclical vs. non-cyclical Stocks – another Intuition on Beta
    .
Interactive Financial Charts with Plotly and Cufflinks
6 Lessons 00:00:00 Hours
  • Creating Graphs
    .
  • Interactive Price Charts with Plotly
    .
  • Customizing Plotly Charts
    .
  • Interactive Histograms with Plotly
    .
  • Candle-Stick and OHLC Charts with Plotly
    .
  • SMA and Bollinger Bands with Plotly
    .
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Jobaaj Learnings

We Believe in Practical Learning!

110 Reviews | 389 Students | 29 Courses
Jobaaj Learnings is the EduTech arm of Jobaaj.com which trains professionals by focusing only on practical exposure and thus making them industry ready. It offers several certif...
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