Financial Analytics

Paper Code: 
MBB 426
Credits: 
4
Contact Hours: 
90.00
Max. Marks: 
100.00
Objective: 

Course outcome

Learning and

teaching strategies

Assessment

Strategies

On completion of this course, the students will be able to;

CO 1.Read financial documents and compute basic financial statistics using R.

CO 2.Import data sets and apply various visualization techniques.

CO 3.Recognize and relate the concept of Risk Diversification and management through different portfolio models.

CO 4. Apply the simulating trading strategies.

CO 5.Comprehend and apply the Option pricing models.

CO 6.Analyze the  utility  of  implied

volatility in price models.

Approach in teaching: Interactive Lectures, GroupDiscussion, Tutorials, Case Study

Learning activities for thestudents: Self-learning assignments, presentations

Class test, Semester end examinations, Quiz, Assignments, Presentation

 

18.00
Unit I: 

Introduction: Meaning-Importance of Financial Analytics, Documents used in Financial Analytics: Balance Sheet, Income Statement, Cash flow statement, Elements of Financial Health: Liquidity, Leverage, Profitability.

Financial Statistics: Concept and mathematical expectation, Probability, Mean, SD and Variance, Skewness and Kurtosis, Covariance and correlation, Financial Returns, Capital Asset Pricing model.

 

18.00
Unit II: 

Financial Securities: Bond Investments, Stock Investments, Securities Data Sets and visualization, Securities data set importing and cleansing, Plotting multiple series, adjusting for stock splits & Mergers, generating prices from log returns.

Application of Sharpe Ratio using R

 

18.00
Unit III: 

Markowitz means - variance optimization: Optimal Portfolio of two risky assets, Data mining with Portfolio optimization.

Gauging the market Sentiment: Markov Regime Switching model, Reading the market data, Bayesian reasoning, Beta distribution, Prior and posterior distributions, Momentum graphs

 

18.00
Unit IV: 

Simulating Trading Strategies: Foreign exchange markets, Chart analytics, Initialization and finalization

- Bayesian Reasoning within Positions, Entries, Exits, Profitability, Short term volatility, The State Machine

 

18.00
Unit V: 

Binomial Model for Options: Applying computational finance, Rsik Neutral Pricing and No Arbitrage, High Risk Free Rate Environment, Put Call Parity, From Binomial to Log-normal.

Black - Scholes model and option - Implied volatility: Black - Scholes model: Concept and applications, Derivation - Algorithm for Implied volatility.

*Case studies related to entire topics are to be taught.

Essential Readings: 
Essential readings
  • Mark J. Bennett, Dirk L. Hugen, Financial Analytics with R, Cambridge University Press
  • Vikas Raj, Business Analytics and Financial Planning, TV18 Broadcast Ltd

 

Suggested readings
  • James, E.R. (2017). Business Analytics. UK: Pearson Education Limited

 

References: 

 

E-RESOURCES:

 

JOURNALS:

 

Academic Year: 
2023-2024
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