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Title2017 Erp Part II Practice Exam
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Page 1

ERP® Part II
Practice Exam

2017

Page 2

Energy Risk Professional (ERP) Part II Practice Exam








© 2017 Global Association of Risk Professionals. All rights reserved. It is illegal to reproduce this material
in any format without prior written approval of GARP, Global Association of Risk Professionals, Inc.








1

!"#$%&'(#)%"*
The ERP Exam is a practice-oriented examination. Its questions are derived from a combination of theory, as
set forth in the core readings, and “real-world” work experience. Candidates are expected to understand
energy risk management concepts and approaches and how they would apply to an energy risk manager’s
day-to-day activities.

The ERP Exam is also a comprehensive examination, testing an energy risk professional on a number of
risk management concepts and approaches. It is very rare that an energy risk manager will be faced with
an issue that can immediately be slotted into just one category. In the real world, an energy risk manager
must be able to identify any number of risk-related issues across the physical and financial energy markets
and be able to deal with them effectively.

The 2017 ERP Part I and Part II Practice Exams have been developed to aid candidates in their preparation for
the ERP Exam in May and November 2017. These practice exams are based on a sample of actual questions
from past ERP Exams and is suggestive of the questions that will be in the 2017 ERP Exam.

The 2017 ERP Part I Practice Exam contains 80 multiple choice questions and the 2017 ERP Part II Practice
Exam contains 60 multiple-choice questions, the same number of questions that the actual 2017 ERP Exam
Part I and 2017 ERP Exam Part II will contain. As such, the Practice Exams were designed to allow candidates
to calibrate their preparedness both in terms of material and time.

The 2017 ERP Practice Exams do not necessarily cover all topics to be tested in the 2017 ERP Exam as any test
samples from the universe of testable possible knowledge points. However, the questions selected for
inclusion in the Practice Exams were chosen to be broadly reflective of the material assigned for 2017 as well
as to represent the style of question that the Energy Oversight Committee considers appropriate based on
assigned material.

For a complete list of current topics, core readings, and key learning objectives candidates should refer to the
2017 ERP Exam Study Guide and 2017 ERP Learning Objectives.

Core readings were selected in conjunction with the Energy Oversight Committee to assist candidates in their
review of the subjects covered by the Exam. Questions for the ERP Exam are derived from the core readings.
It is strongly suggested that candidates study these readings in depth prior to sitting for the Exam.*

Page 43

Energy Risk Professional (ERP) Part II Practice Exam






© 2017 Global Association of Risk Professionals. All rights reserved. It is illegal to reproduce this material
in any format without prior written approval of GARP, Global Association of Risk Professionals, Inc.






42

6V7 A separate estimate of correlation between risk factors is typically not required when applying which of the
following VaR methodologies?

A7 Delta-gamma
D7 Delta-normal
C7 Historical Simulation
E7 Monte Carlo Simulation

C%$$-(#*2".X-$d C

34;82"2#)%"d An historical simulation based VaR methodology relies on historical data that typically
incorporates the underlying correlation between risk factors. The Delta-gamma, Delta-normal, and Monte
Carlo methodologies require a separate estimate of volatilities and correlation between risk factors.

B-2&)",*$-0-$-"(-d Les Clewlow and Chris Strickland. Energy Derivatives: Pricing and Risk Management,
Chapter 10.

Page 44

Energy Risk Professional (ERP) Part II Practice Exam






© 2017 Global Association of Risk Professionals. All rights reserved. It is illegal to reproduce this material
in any format without prior written approval of GARP, Global Association of Risk Professionals, Inc.






43

6^7 A credit analyst is assessing a USD 16,000,000 credit exposure related to a 10-year, fixed rate bond issued by
a Baa1/BBB+ rated midstream oil and gas company. The bond has a par value of USD 15,600,000, an
estimated recovery rate of 63%, and an expected loss of USD 720,000 in the event of default. Calculate the
implied default probability on the bond?

A7 9.20%
D7 10.86%
C7 12.16%
E7 16.90%

C%$$-(#*2".X-$d C

34;82"2#)%"d The implied default probability can be derived using the following relationship: Expected loss
(EL) = Loss Given Default (LGD) x probability of default.

In this example LGD is derived by multiplying the Credit Exposure by (1-Recovery Rate) = USD 5,920,000.

The implied default probability is then the EL of USD 720,000 divided by the LGD USD 5,920,000 or 12.16%.

Note: The par value of the bonds is not used in the calculation.

B-2&)",*$-0-$-"(-d Markus Burger, Bernhard Graeber, and Gero Schindlmayr. Managing Energy Risk: An
Integrated View on Power and Other Energy Markets, 2nd Edition, Chapter 3 (Section 3.4 Credit
Risk only).

Page 85

Energy Risk Professional (ERP) Part II Practice Exam






© 2017 Global Association of Risk Professionals. All rights reserved. It is illegal to reproduce this material
in any format without prior written approval of GARP, Global Association of Risk Professionals, Inc.






84

]U7 A risk analyst at a refinery is calculating the 10-day, 95% VaR on a 100,000 barrel Brent crude oil position
currently valued at USD 3,250,000. Using a daily returns for Brent crude oil prices over the past 12 months,
the analyst applies a simple moving average to estimate the volatility factor used in the VaR model. Noticing
higher crude oil price volatility over the past month, the analyst applies an EWMA with a lambda of 0.99 to
adjust the volatility factor used in the VaR model. Applying the new volatility estimate will most likely cause
the new VaR amount to:


A7 Increase slightly relative to the original VaR.
D7 Increase sharply relative to the original VaR.
C7 Decrease slightly relative to the original VaR.
E7 Decrease sharply relative to the original VaR.

C%$$-(#*2".X-$d*A

34;82"2#)%"d*Applying a decay factor of 0.99 will place a slightly greater weight on more recent observations.
Therefore, the standard deviation and VaR should increase only slightly.
*
B-2&)",*$-0-$-"(-d*John C. Hull. Risk Management and Financial Institutions, 4th Edition, Chapter 12.

Page 86

© 2017 Global Association of Risk Professionals. All rights reserved. (01.30.17)

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