Python for Financial Analysis


Python is most powerful tool for Financial Analysis and Data Analysis. You can use python for Machine Learning and Artificial Intelligence.

Syllabus Content

Subject Name: Python for Financial Analysis

UnitTitleDetails of Topic
Unit IGetting Started with PythonThis unit will prepare the learner to use basic python for data analytics- This foundational unit will equip the learner to use the basic syntax of Python
Unit IINumpy, General Overview of Pandas and MatplotlibNumpy for financial analysis, General overview of pandas and visualization with matplotlib and pandas. Pandas with timeseries data. Capstone stock market analysis project.
Unit IIITime series analysisTime Series basic, Introduction to basic Stat Model, ETS theory, EWMA Theory, ARIMA theory, ACF and PACF theory, ARIMA with stat model.
Unit IVPython finance fundamentals, Calculating and Comparing Rate of Returns, Measuring Investment RiskIntroduction to python finance fundamental, Shape ratio, Simple and moving average, Calculating rate of return of individual share and portfolio. Calculating rate of return of Index. Calculating risk of individual share and portfolio Calculating index risk.
Unit VUsing regression in python, Markowitz portfolio optimization, Capital Assets Pricing Model, Multivariate regression analysis, Monte Carlo Simulations. Calculation of simple regression. Calculation of Alpha, Beta and R squire in python. Markowitz portfolio optimization.  Calculation of Multivariate regression.

Lesson Plan

U. NoTitleDetails of TopicDuration
Unit 1Getting Started with PythonInstalling Python, Installing Jupyter Notebook, Introduction of Jupyter Notebook and Google colab
  Python variables, Data types, Basic Python Syntax, Python Operators. 
  Conditional statements, Python Functions, Python sequence, Iteration in Python 
  Object oriented programming, Modules and Package, Standard Library, Importing modules. 
Unit 2Numpy, General Overview of Pandas and MatplotlibIntroduction to Numpy, Numpy Array, Numpy operation, Numpy indexing
  Introduction to Pandas, Series, DataFrames, Missing Data, Groupby with Pandas, Mearging, Joining, Concatenating DataFrame, Pandas common operations, Data input and output 
  Introduction to Visualization in Python, Matplotlib 
  Pandas visualization overview, Pandas Timeseries visualization 
Unit 3Time Series AnalysisIntroduction ot data source, Note on PandasDatareader, quandl, Introduction to time Series with Pandas. Datetime Index, Time resampline, Time Shift, Pandas Rolling and Expanding.
  Introduction to time series, Time series basic, Introduction to stat models, 
  ETS theory, EWMA Theory, EWMA Code along, ETS Code along. 
  ARIMA theory, ACF and PACF, ARIMA with Statmodels, Discussion choosing PDQ. 
Unit 4Python Finance Fundamentals, Calculating and Computing Rate of Returns. Measuring Investment RiskWelcome o the Finance Fundamentals, Sharp Ratio, Portfolio Allocation Code Along, Considering Both Risk and Retrun, Calculating Security Rate of Retrun (Simple retrun and logarithmic return),
  What is a portfolio of securities and
how to calculate its rate of return, Popular stock indices that can help
us understand financial markets, Calculating the Indices’ Rate of
Return
 
  Calculating the Indices’ Rate of
Return, Calculating a Security’s Risk in
Python, The benefits of portfolio
diversification, Calculating the covariance between securities, Measuring the correlation between stocks
 
  Calculating Covariance and
Correlation, Considering the risk of multiple
securities in a portfolio, Calculating Portfolio Risk, Understanding Systematic vs. Idiosyncratic risk, Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio
 
Unit 5Using regression in python, Markowitz portfolio optimization, Capital Assets Pricing Model, Multivariate regression analysis, Monte Carlo SimulationsThe fundamentals of simple
regression analysis, Computing Alpha, Beta, and R Squared in Python
 
  Finance -Markowitz Portfolio Optimization, Obtaining the Efficient Frontier in Python 
  The intuition behind the Capital Asset Pricing Model, Understanding and calculating a security’s Beta, Calculating the Expected Return of a Stock. 
  Multivariate regression analysis – a valuable tool for finance practitioners, The essence of Monte Carlo simulations 

Batch 1: The course started on the 15th and was completed on the 20th of June 2022 and on the 11th of August 2022.

S.No.NameCertificate Link
1. Mohamed Hareesudeen
email: mohamedharees007@yahoo.com
Link
2. Dr. Mohammed Mujahed Ali
email: mubarak_mujahed@yahoo.co.in
Link
3. Md Abrar Alam
email: mdabrar1994@gmail.com
Link
4. Abuzar Nomani
email: abuzarnomani88@gmail.com
Link
5. Rithi S R
email: rithi.satheesan@gmail.com
Link
6. HARISH R
email: krharish2727@gmail.com
Link
7. Monika Mishra
email: monikabarsha200@gmail.com
Link
8. Ali Thabit Yahya Al Qaser
email: ali.ust77@gmail.com
Link
9.Tamer Elsheikh
email: tamer.elshiekh@com.kfs.adu.eg
Link
10.Faozi Abduljalil Gazem Al-Maqtari
email: faozi@umt.edu.my
Link
11.Waleed Mutahar Al-ahdal
email: wm.alahdal2011@gmail.com
Link
12.Ayesha Siddiqui
email: ayesha.siddiqui91@gmail.com
Link
13. Najib Hamood Saif Farhan
email: Najib720000@gmil.com
Link

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