NOC:Advanced Financial Analytics

Lecture 1 - Introduction to Teaching Assistants (TA)

Lecture 2 - Introduction to R

Lecture 3 - Data Cleaning with R

Lecture 4 - Data Visualization

Lecture 5 - Data Visualization with GGPLOT

Lecture 6 - Regression Modelling - Part 1

Lecture 7 - Regression Modelling - Part 2

Lecture 8 - Regression Algorithm : Application - Part 1

Lecture 9 - Regression Algorithm : Application - Part 2

Lecture 10 - Introduction to Market Microstructure

Lecture 11 - Introduction to Risk and Return

Lecture 12 - Portfolio Theory and Asset Pricing Models

Lecture 13 - Introduction to Portfolio Construction

Lecture 14 - Advanced Portfolio Optimization - Part 1

Lecture 15 - Advanced Portfolio Optimization - Part 2

Lecture 16 - Portfolio Construction with R - Part 1

Lecture 17 - Portfolio Construction with R - Part 2

Lecture 18 - Portfolio Construction with R - Part 3

Lecture 19 - Tutorial on Data Visualization

Lecture 20 - Tutorial on Portfolio Construction with Advanced Financial Market Instruments - Part 1

Lecture 21 - Tutorial on Portfolio Construction with Advanced Financial Market Instruments - Part 2

Lecture 22 - Introduction to Univariate Models - Part 1

Lecture 23 - Introduction to Univariate Models - Part 2

Lecture 24 - Introduction to ARMA Process

Lecture 25 - Non-Stationarity, Cointegration, and Error Correction Models - Part 1

Lecture 26 - Non-Stationarity, Cointegration, and Error Correction Models - Part 2

Lecture 27 - Volatility Modelling

Lecture 28 - Tail Risk Measurement: VaR and CVaR (or ES) models

Lecture 29 - Advanced Financial Markets Instruments: Return and Volatility Modelling and Forecasting

Lecture 30 - Classification Algorithms: Logit/Probit Regression - Part 1

Lecture 31 - Classification Algorithms: Logit/Probit Regression - Part 2

Lecture 32 - Classification Algorithms: Application - Part 1

Lecture 33 - Classification Algorithms: Application - Part 2

Lecture 34 - Introduction to Panel Data Modelling

Lecture 35 - Panel Data Application and Implementation with R

Lecture 36 - Maximum Likelihood Estimation (MLE)

Lecture 37 - Quantile Regression - Part 1

Lecture 38 - Quantile Regression - Part 2

Lecture 39 - Quantile Regression: Income Expenditure Case Study

Lecture 40 - Trend Determining Techniques

Lecture 41 - Moving Average Indicators

Lecture 42 - Momentum Indicators - Part 1

Lecture 43 - Momentum Indicators - Part 2

Lecture 44 - R Application for Technical Analysis and Algorithmic Trading - Part 1

Lecture 45 - R Application for Technical Analysis and Algorithmic Trading - Part 2

Lecture 46 - Valuation of Fixed Income Securities

Lecture 47 - Valuation of Common Stocks

Lecture 48 - Cost of Capital

Lecture 49 - Yield to Maturity and Theories of Term Structure of Interest Rates - Part 1

Lecture 50 - Yield to Maturity and Theories of Term Structure of Interest Rates - Part 2

Lecture 51 - Duration and Convexity