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Advanced Financial Analytics
Online
12 WeeksQuick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 1000 | yes | IIT Kanpur |
The Syllabus
- Data Visualization and Wrangling, working with data frames, processing large data, Statistical Inference
- Hypothesis Testing, and Confidence Intervals, Application with R
- 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
- 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
- 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
- Introduction to Volatility Modelling
- Historical volatility models, ARCH/GARCH Models, VaR/CvaR models, Implementation in R
- Linear probability models
- Logit Model and Probit Models
- ROC curve, classification matrix
- Maximum Likelihood Estimation
- Finance Use case and implementation in R
- Introduction to Panel Models
- Fixed effects, Random effects
- First difference
- LSDV estimators
- Hausman test statistics
- Finance Use case and implementation in R
- Introduction to quantile regression, regression quantiles, optimization scheme with quantile regression, theoretical underpinnings, Finance use case with R implementation
- Introduction to Markov Process
- Transient and Recurrent processes, absorption probabilities
- Convergence
- Finance use case and implementation in R
- Basics of GGPLOT, Layering, Facet wrap, aesthetics, geometric objects, Use case with R implementation
- Trend Analysis and Indicators,
- Bollinger bands, trendlines, candle stick charts,
- Dow theory, classical patterns, Momentum Indicators, R implementation
- Bond fundamentals
- G-Secs, Duration
- Convexity, application in portfolio management
- Use case with R implementation