Advanced Financial Analytics

Offered byNPTEL
Public/Government Institute

Advanced Financial Analytics
at
NPTEL
Overview

Duration	12 weeks
Mode of learning	Online
Official Website	Go to Website
Credential	Certificate

Advanced Financial Analytics

Table of content

Overview
Highlights
Course Details
Curriculum
Faculty

Advanced Financial Analytics
at
NPTEL
Highlights

Earn a certificate after completion of course

Advanced Financial Analytics
at
NPTEL
Course details

Skills you will learn

R Risk Management

Who should do this course?

Management students

Commerce students

Chartered Accountants

Engineering students

Finance professionals (Investment analysts, banking professionals, accountants, credit analysts)

Data Scientists

More about this course

This program has been carefully designed to help future analysts, traders, brokers, consultants and other industry professionals who are either currently exposed to or foresee data science proliferate their work environment

The operating environment for investment management firms continues to evolve, with technological innovations and shifting investor preferences at the heart of this change

In that context, Data Analytics is providing new opportunities to both professionals and investors

The objective of this course is to understand the application of Data Analytics in financial markets, trading, and asset management, also called Financial Analytics

This program aims to demonstrate the applications of data analytics in the finance domain

Advanced Financial Analytics
at
NPTEL
Curriculum

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

Advanced Financial Analytics
at
NPTEL
Faculty details

Prof. Abhinava Tripathi

Prof. Abhinava Tripathi is a Faculty of Finance and Accounting at IME, Indian Institute of Technology, Kanpur. Previously, he was working at DOMS, IIT Roorkee. He has completed his Ph.D. degree from Indian Institute of Management, Lucknow. He has done his B-Tech. from Indian Institute of Technology, Roorkee and MBA from Indian Institute of Management, Kozhikode.