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

To know more about the Python and it use in Financial Analysis, learn Python from expert. The online batch will start from 15th November, 2021. The classes will be through Microsoft Team. The couse fee is Rs. 4,900 only.

Following content will be discussed in the class.

Subject Name: Python for Financial Analysis

Unit	Title	Details of Topic
Unit I	Getting Started with Python	This unit will prepare the learner to use basic of python for data analytics- This foundational unit will equip the learner to use the basic syntax of Python
Unit II	Numpy, General Overview of Pandas and Matplotlib	Numpy for financial analysis, General overview of pandas and visualization with matplotlib and pandas. Pandas with timeseries data. Capstone stock market analysis project.
Unit III	Time series analysis	Time Series basic, Introduction to basic Stat Model, ETS theory, EWMA Theory, ARIMA theory, ACF and PACF theory, ARIMA with stat model.
Unit IV	Python finance fundamentals, Calculating and Comparing Rate of Returns, Measuring Investment Risk	Introduction 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 V	Using 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.

Fill the form at the end of this page to register in the course.

Lesson Plan

U. No	Title	Details of Topic	Duration
Unit 1	Getting Started with Python	Installing Python, Installing Jupyter Notebook, Introduction of Jupyter Notebook and Google colab	9 Hours
		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 2	Numpy, General Overview of Pandas and Matplotlib	Introduction to Numpy, Numpy Array, Numpy operation, Numpy indexing	9 Hours
		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 3	Time Series Analysis	Introduction ot data source, Note on PandasDatareader, quandl, Introduction to time Series with Pandas. Datetime Index, Time resampline, Time Shift, Pandas Rolling and Expanding.	9 Hours
		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 4	Python Finance Fundamentals, Calculating and Computing Rate of Returns. Measuring Investment Risk	Welcome 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),	9Hours
		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 5	Using regression in python, Markowitz portfolio optimization, Capital Assets Pricing Model, Multivariate regression analysis, Monte Carlo Simulations	The fundamentals of simple regression analysis, Computing Alpha, Beta, and R Squared in Python	9 Hours
		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

Participant who will complete the course successfully their name will appear in the website and they will get the completion cirtificate. if you are interested to take course fill the following form. The Class will start from 15th November 2021. The class Time will be Monday to Friday 9.00 pm to 10.00 pm.

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