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Quick Facts

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

Courses and Certificate Fees

Fees InformationsCertificate AvailabilityCertificate Providing Authority
INR 1000yesIIT Kanpur

The Syllabus

  • Introduction to R Programming
  • R Fundamentals
  • Basic mathematical and logical operations with R, working with different data-types in R, wrangling with data frames
  • Exploratory data analysis and data visualization with R.

  • Introduction to Portfolio Construction
  • Risk-return framework in financial markets, risk diversification with portfolios, portfolio optimization in mean-variance framework, concept of market risk and beta
  • Portfolio Possibility curve
  • Efficient frontier, Minimum Variance portfolios
  • Introduction to risk-free lending and borrowing

  • Asset Pricing Models
  • Capital Asset Pricing Model (CAPM)
  • Capital Market Line, Security Market Line
  • Fallings of CAPM
  • Single-Index and Multi-Index models
  • Expected Risk and Return with Index models
  • 3-Factor Fama-French Model

  • Portfolio Management and Performance Evaluation
  • Portfolio Management strategies
  • Active vs Passive Portfolio Management
  • Value vs Growth investing
  • One-parameter performance measures Timing & Selection performance measures, application of asset pricing models in performance management

  • Introduction to Algorithmic Trading
  • Technical analysis and trend determination
  • Dow Theory
  • Moving averages
  • Momentum indicators
  • Classical price patterns.

  • Advanced time-series regression algorithms
  • ARMA/ARIMA models
  • Mean reverting trading strategies with vector error correction models and cointegration, model risk management, back testing, model validation, and stress testing with R

  • Advanced time-series algorithms for financial risk-management
  • Value-at-risk
  • Expected Shortfall
  • ARCH/GARCH models, implementation with R

  • Advanced topics
  • Alternative versions of CAPM
  • Delineating Efficient Frontier
  • Performance Evaluation with Multi-index models
  • Portfolio construction, optimization, back-testing, and visualization with R

Instructors

Articles

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