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    Quick Facts

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

    Important dates

    Certificate Exam Date

    Start Date : 19 Apr, 2026

    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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