Week 1: Fundamentals of R Programming and Introduction to Business Statistics: Data Visualization and Wrangling, working with data frames, processing large data, Statistical Inference, Hypothesis Testing, and Confidence Intervals, Application with R
Week 2: Time-Series Analytics: Introduction to Stationarity, ARMA/ARIMA Modelling, ACF/PACF, Model Building and Goodness-of-Fit, Modelling Non-stationary process, Cointegration and VECM Models, Time-series forecasting, Implementation in R
Week 3: Portfolio Analytics: Portfolio Optimization with two securities and multiple securities, Construction of efficient frontier and market portfolio, Portfolio performance evaluation and construction of market portfolio, Asset Pricing Models, Implementation in R
Week 4: Application of Regression: Introduction to regression modelling, Simple and Multiple Linear Regression, Assumptions of classical linear regression model and its violations, issues of heteroscedasticity, multicollinearity, autocorrelation, Application with asset pricing models, and implementation with R
Week 5: Risk Analytics: Introduction to Volatility Modelling, Historical volatility models, ARCH/GARCH Models, VaR/CvaR models, Implementation in R
Week 6: Logistic Regression: Linear probability models, Logit Model and Probit Models, ROC curve, classification matrix, Maximum Likelihood Estimation, Finance Use case and implementation in R
Week 7: Panel Data Regression: Introduction to Panel Models, Fixed effects, Random effects, First difference, LSDV estimators, Hausman test statistics, Finance Use case and implementation in R
Week 8: Quantile Regression: Introduction to quantile regression, regression quantiles, optimization scheme with quantile regression, theoretical underpinnings, Finance use case with R implementation
Week 9: Markov Regime Switching Regression: Introduction to Markov Process, Transient and Recurrent processes, absorption probabilities, Convergence, Finance use case and implementation in R
Week 10: Financial Markets Data Visualization with GGPLOT: Basics of GGPLOT, Layering, Facet wrap, aesthetics, geometric objects, Use case with R implementation
Week 11: Technical Analysis: Trend Analysis and Indicators, Bollinger bands, trendlines, candle stick charts, Dow theory, classical patterns, Momentum Indicators, R implementation
Week 12: Fixed Income securities: Bond fundamentals, G-Secs, Duration, Convexity, application in portfolio management, Use case with R implementation
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