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Financial Analytics
Course Objectives: The course aims to Course Outcomes (COs): Course Course outcome (at course level) Learning and teaching strategies Assessment Strategies Paper Code Paper Title CLO 162.Read financial documents and compute basic financial statistics using R. CLO 163.Import data sets and apply various visualization techniques. CLO 164.Recognize and relate the concept of Risk Diversification and management through different portfolio models. CLO 165. Apply the simulating trading strategies. CLO 166.Comprehend and apply the Option pricing models. CLO 167.Analyze the utility of implied volatility in price models. Approach in teaching: Interactive Lectures, Group Discussion, Tutorials, Case Study Learning activities for the students: Self-learning assignments, presentations Class test, Semester end examinations, Quiz, Assignments, Presentation MBB 423 Financial Analytics
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.
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
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
Simulating Trading Strategies: Foreign exchange markets, Chart analytics, Initialization and finalization - Bayesian Reasoning within Positions, Entries, Exits, Profitability, Short term volatility, The State Machine
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.
