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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf StudyVideo and Text Based

Important dates

Course Commencement Date

Start Date : 20 Jan, 2025

End Date : 11 Apr, 2025

Enrollment Date

End Date : 27 Jan, 2025

Certificate Exam Date

Start Date : 04 May, 2025

Other

End Date : 14 Feb, 2025

Courses and Certificate Fees

Fees InformationsCertificate AvailabilityCertificate Providing Authority
INR 1000yesIIT 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

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