FMA-EMBA-BA-19

FMA-EMBA-BA-19
MBA(Exe.)-BA-2019-20: Term-IV

Course Name: Financial and Market Analytics

Credits	3
Faculty Name*	Prof. Plavini Punyatoya (2 credits); Prof. Ameet Kumar Banerjee (1 credit)
Program	EMBA-BA
Academic Year and Term	2019-20, Term IV

Note:*Prof. Plavini will take the Market Analytics portion (2 credits: First 13 sessions). Prof. A. K. Banerjee will take the Financial analytics portion (1 credit: 7 sessions).

1. About the Course

There is widespread information deluge as a result of exponential growth in computing power in the information technology space. Which has made available loads of data generated from various sources, streamlined into gold mines of information which can help in the decision-making process? Though demystifying the information content of this data is somewhat challenging, but with more significant strides made in IT, the analysis of this data has become manageable, can be used to predict and drew newer insights to improve upon the real-time decision making. Thus, financial analytics helps in understanding, forecasting marketing movements, future market prices, firm profitability, and in cases of firm bankruptcy.

The course blends statistical tools and sophisticated machine learning tools to equip the students with the requisite skills to handle different types of data with powerful tools like R and Python.

2. Pedagogue and learning outcomes

· The course will include lecture sessions, discussion on articles relating to the subject.
· Students will get equipped with the latest development happening in the area of finance with the help of analytical tools

3. Reading materials

· Provide with necessary course materials as per requirement

4. Session Plan of Financial Analytics

Session No.
TOPIC
Pedagogue

1-2
· Understanding the necessary foundation of Market Microstructure.
· A basic introduction to different asset classes and it’s characteristics
· Different types of markets and participants
Class lectures and Reading materials.

2
· Understanding data in finance and sources of data
· Cleaning and processing of data with R
do

3
· Principal Component Analysis and Exploratory Factor Analysis for financial data using R
do

4-5
· Non-linear time series analysis with a special discussion on neural networks and genetic algorithms.
· Application of the genetic algorithm to portfolio management.
· Forecasting of asset prices
do

6-7
· Discussion on MCDM techniques of Particle Swarm Optimization, Simulated Annealing and TOPSIS using financial data with R/Python
· A brief discussion about sentiment analysis
do

5. Evaluation

Components Weightage (in %)

Class Participation and In-class Exercise 20

Midterm 40

End-Term Exam 40

Total 100

6. Academic Integrity

Students are required to maintain the best ethical practices during the entire session.

Created By: Alora Kar on 05/06/2020 at 01:35 PM
Category: MBA(Exe.)BA-2019-20 T-IV Doctype: Document

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Session No.	TOPIC	Pedagogue
1-2	· Understanding the necessary foundation of Market Microstructure. · A basic introduction to different asset classes and it’s characteristics · Different types of markets and participants	Class lectures and Reading materials.
2	· Understanding data in finance and sources of data · Cleaning and processing of data with R	do
3	· Principal Component Analysis and Exploratory Factor Analysis for financial data using R	do
4-5	· Non-linear time series analysis with a special discussion on neural networks and genetic algorithms. · Application of the genetic algorithm to portfolio management. · Forecasting of asset prices	do
6-7	· Discussion on MCDM techniques of Particle Swarm Optimization, Simulated Annealing and TOPSIS using financial data with R/Python · A brief discussion about sentiment analysis	do

Components	Weightage (in %)
Class Participation and In-class Exercise	20
Midterm	40
End-Term Exam	40
Total	100