Certificate in Quantitative Financial Programming with R

How It Works

  1. 1. Select Certification & Register
  2. 2. Receive Online e-Learning Access (LMS)
  3. 3. Take exam online anywhere, anytime
  4. 4. Get certified & Increase Employability

Test Details

  • Duration: 60 minutes
  • No. of questions: 50
  • Maximum marks: 50, Passing marks: 25 (50%).
  • There is NO negative marking in this module.
  • Online exam.

Benefits of Certification


$49.00 /-
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Quantitative finance is the use of mathematical models and extremely large data sets to analyze financial markets and securities.

Only e-learning video access will be provided.

Why should one take Quantitative Financial Programming with R Certification?

Earning Vskills Certificate in Quantitative Financial Programming with R Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.

This Course is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.

Who will benefit from taking Quantitative Financial Programming with R Certification?

Job seekers looking to find employment in software development, or IT departments of various finance companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification. 

Quantitative Financial Programming with R Table of Contents

https://www.vskills.in/certification/quantitative-financial-programming-with-r-table-of-contents

Quantitative Financial Programming with R Practice Test

https://www.vskills.in/practice/quantitative-financial-programming-with-r-questions

Quantitative Financial Programming with R Interview Questions

https://www.vskills.in/interview-questions/quantitative-financial-programming-with-r-interview-questions

Companies that hire Quantitative Financial Programming with R Professionals

Compensation in the Quantitative Financial field is very high, companies require skilled professional to do the quantitative tasks. Hiring companies include, TCS, Wipro, Samsung, Flipkart, CITI, MasterCard, IBM, Dell etc.


Quantitative Financial Programming Blogs

Checkout the latest online blogs on Quantitative Financial Programming.

Quantitative Financial Programming Jobs

Checkout the various job openings for Quantitative Financial Programming, click here..

Quantitative Financial Programming Internships

Vskills runs its flagship internship programme where bright interns work with academic council, click to know more details..

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TABLE OF CONTENT


Quantitative Finance Basics

  • Fundamentals of Quantitative Finance
  • R Functions and Packages

Data Analysis using R Language

  • Introduction to Quantmod
  • Equity – Definitions and Price Download
  • Modeling Prices and Returns
  • Asset Returns Simulation
  • Financial Modeling with R: S&P500 Statistical Analysis

Fixed-Income Securities

  • Introduction to jrvFinance
  • Introduction to Fixed-Income Securities
  • The Importance of Interest Rate
  • Pricing of Fixed-Income Securities
  • Duration, Modified Duration, and Convexity
  • The Yield Curve and the Bootstrapping Approach

Derivatives

  • Introduction to fOptions
  • Working with Futures
  • European and American Options
  • Pricing European Options – The Binomial Model
  • Pricing European Options with the Black-Scholes Model

Risk Return Analysis

  • Introduction to PortfolioAnalytics
  • The Benefits of Diversification
  • Risk/Return Paradigm
  • Capital Allocation Line and Capital Market Line
  • Optimal Asset Allocation with Markowitz Framework

The CAPM Model

  • Introduction to PerformanceAnalytics
  • Idiosyncratic versus Systematic Risk
  • Risk Factors
  • The CAPM
  • Fama-French and Other Factor Models
  • Empirical Testing of the CAPM

Portfolio Risk Management

  • PerformanceAnalytics for Risk Management
  • The Value-at-Risk (VaR) Model
  • The Expected Shortfall (ES)
  • Benefits and Pitfalls of VaR Approach
  • Hedging Financial Exposure

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