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