Value at Risk Methods Using R

Analysts, portfolio managers, and risk managers need the ability to analyze data and apply various methodologies for evaluation of risks. In this course, we cover various modern statistical methods for analysis of risks.
Course Period: February 13 - March 25, 2024
Lessons Launch: Each Tuesday
Instructor Access:  February 13 - March 25, 2024


  Presented By:
Elena Goldman, Ph.D.
Professor of Finance and Graduate Economics
Pace University

  Session Length:
6 lessons, plus exercises
Lessons vary in length (see Outline)


About This Course
This course will teach estimation and forecasting of time series models. Methods will be applied to modeling and forecasting dynamic volatility and correlations, Value at Risk, Expected Shortfall, and Systemic Risk. Also, the course will teach estimation, Monte Carlo simulations, and programming in R/RStudio. An introduction to R/RStudio and a review of basic statistics will be provided.

Learning Objectives

  • Estimate and forecast time-varying volatility
  • Apply various methods for tail risk measurement, including Value at Risk and Expected Shortfall
  • Analyze backtesting
  • Review Systemic Risk


This course begins with the fundamentals of installing R/RStudio and coding. It then moves into intermediate topics, formulas, and coding.


Foundations of finance and a familiarity with simple probability and statistics including least squares regression
Participants must be able to download R and RStudio for this course. Instructions are provided in the course. If necessary, please work with your IT department to ensure you can download this free, open source software or use a personal device.

How It Works

Each Tuesday a lesson launches with access to videos, exercises, and knowledge checks, as well as downloadable slide decks. During the course, you have access to the instructor, Elena Goldman, Ph.D., to ask questions or seek assistance through the online learning platform. You can interact with other participants as well. Once you have completed the course, you can download/print a certificate of completion and provide us with your feedback via a survey.

 Week  Lesson (Lecture time in parentheses) Topic
 February 13
 Lesson 1   Fundamentals 
    Lesson 1.1 (1:06)
 Lesson 1.2 (1:15)
 Lesson 1.3 (:39)

  • Introduction to R/RStudio 
  • Financial Returns 
  • Monte Carlo Simulations 


 February 20  Lesson 2  Univariate Time Series Volatility
   Lesson 2.1 (:24)
 Lesson 2.2 (1:00)
  • Historical Volatility
  • EWMA Volatility Estimator
  • ARCH/GARCH Models with Extensions
February 27  Lesson 3  Estimation of Variance-Covariance Matrix
    Lesson 3.1 (:17)
 Lesson 3.2 (1:11)
 Lesson 3.3 (:45)
  •  EWMA, DCC, Factor Models


March 5  Lesson 4  Value at Risk, Expected Shortfall
   Lesson 4.1A (1:02)
 Lesson 4.1B (:54)
 Lesson 4.2 (:28)
  • Historical
  • Variance-Covariance
  • Filtered Historical Simulations
  • Monte Carlo
 March 12  Lesson 5 (:57)  Backtesting
  •  Kupiec and other Backtests
 March 19  Lesson 6 (:50)  Systemic Risk
  •  SRisk on VLAB

Who Should Attend

This course is intended for practitioners in banks and other financial companies in the areas of:

  • Risk management
  • Portfolio management
  • Finance
  • Business analytics

About Our Expert

  Elena Goldman, PhD, is a Professor of Finance and Graduate Economics at the Lubin School of Business at Pace University. Her research and teaching are in the fields of Financial Econometrics, Bayesian Econometrics, Risk Management, and International Finance. Goldman’s recent academic publications include "Regimes and Long Memory in Realized Volatility," Studies in Nonlinear Dynamics and Econometrics and “Internal Capital Markets and Dividend Policy: Evidence from Indian Corporates," Journal of Financial Research. Her current working papers are on systemic risk, asymmetric GARCH volatility models, and margin models for Central Clearing Counterparties (CCPs).

Elena currently serves on the Education Committee for PRMIA. She was a fellow at the SEC in 2016. She holds a Ph.D. in Economics from Rutgers University.

Continued Risk Learning Credits:  14

PRMIA Continued Risk Learning (CRL) programs provide you with the opportunity to formally recognize your professional development, documenting your evolution as a risk professional. Employers can see that you are not static, making you a highly valued, dynamic, and desirable employee. The CRL program is open to all Contributing, Sustaining, and Risk Leader members, providing a convenient and easily accessible way to submit, manage, track and document your activities online through the PRMIA CRL Center. To request CRL credits, please email [email protected].

 Membership Type Price
 All Member Types $ 799
 Non Members $ 899

If this is your first time accessing the PRMIA website you will need to create a short user profile to register. Save on registration by becoming a member.


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2/13/2024 - 3/25/2024
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