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CQRM - Certified in Quantitative Risk Management - December 2019

Training Course
  • London and Home Counties
  • <p>Energy Institute</p> <p>61 New Cavendish Street</p> <p>W1G 7AR, London</p>
  • 3-12-2019
    /
    6-12-2019
  • 09:00 - 17:30
  • Non-Member - 2600.00
    Member - 2400.00
    + VAT
  • Available in-house
  • Book now

This 4-day CQRM - Certified in Quantitative Risk Management training course will teach delegates how to acquire updated and practical knowledge in risk management from a quantitative approach to measure, analyse and make decisions.

Become part of the global network of Quantitative Risk Management professionals. The CQRM (Certified in Quantitative Risk Management) is an International Certification awarded by the International Institute of Professional Education and Research (IIPER). It is aimed at managers, directors and analysts of the governmental, business, financial and academic sectors interested in acquiring updated and practical knowledge in risk management from a quantitative approach to measure, analyse and make decisions.

The certification will last four days in which the participants will learn from global experts, advanced topics and practical applications of risk management. Upon completion, a validation of knowledge will be conducted to obtain the CQRM title.

By participating in the certification, attendees will have elements to analyse and interpret data for risk measurement, understand the results obtained as well as suggest and make decisions based on the Monte Carlo risk simulations, statistics and econometric analysis, optimisation and real options applicable to their projects or investments.

Why attend this certification?

  • To be certified internationally as a Quantitative Risk Manager (CQRM-IIPER).
  • The opportunity to learn from world experts who have outstanding credentials and extensive practical experience.
  • Understand how to make more informed decisions in times of uncertainty and achieve better business outcomes.
  • Learn about the latest theoretical approaches and practical applications for risk analysis and management.
  • Update and immerse yourself in techniques that allow you to understand the past, the present and more accurately forecast the future.
  • To model industry-specific problems and implement risk analysis using Risk Simulator, Real Options SLS, and PEAT tools, capable of analysing large volumes of information and working with the latest implementation of risk management analytics.

Who should attend?

The CQRM course is aimed towards any managerial or professional occupation, including engineers, managers, directors, analysts, entrepreneurs, and so forth, who are interested in acquiring updated and practical knowledge in risk management from a quantitative approach to measure, analyse and make decisions. Therefore, this accreditation suits any governmental, business, energy, logistics, financial or academic sectors, at any professional level.

General prerequisites (recommended)

  • A bachelor’s degree or in the final year (preferably, but not necessarily, in engineering, management, business, or economics), or equivalent training plus at least two years of working experience.
  • Basic knowledge of Excel as well as a basic understanding of mathematics and statistics at a bachelor’s degree level. Access to pre-recorded webinars will be provided.
  • Very good spoken and reading English proficiency (B2)

Course Overview

MODULE 1: Introduction to Risk Analysis

  • Chapter 1: Introduction to the Training and What to Expect
  • Chapter 2: How Are Business Decisions Made?
  • Chapter 3: What is Risk and Why Should Risk be Considered?
  • Chapter 4: Overview of Risk Analysis Software Applications.

MODULE 2: Monte Carlo Simulation with Risk Simulator

  • Chapter 1: Overview of Risk Simulator Software
  • Chapter 2: Profiling, Assumptions, Forecasts and Running Simulations
  • Chapter 3: Interpreting the Forecast Statistics
  • Chapter 4: Simulation Run Preferences and Seed Values
  • Chapter 5: Running Reports, Saving and Extracting Simulation Data

MODULE 3: Advanced Simulation Techniques

  • Chapter 1: Correlating and Truncating Distributions
  • Chapter 2: Alternate Parameters
  • Chapter 3: Multidimensional Simulations
  • Chapter 4: Distributional Fitting
  • Chapter 5: Due Diligence and Pitfalls in Simulation

MODULE 4 Simulation and Analytical Tools

  • Chapter 1: Static Tornado and Spider Charts
  • Chapter 2: Dynamic Sensitivity Analysis and Scenario Analysis
  • Chapter 3: Hypothesis Test on Different Distributions
  • Chapter 4: Nonparametric Bootstrap Simulation

MODULE 5: Optimization with Risk Simulator

  • Chapter 1: Introduction to Optimisation
  • Chapter 2: Continuous Optimisation
  • Chapter 3: Integer Optimisation

MODULE 6: Forecasting

  • Chapter 1: Overview of Forecasting Techniques and Data Types
  • Chapter 4: Nonlinear Extrapolation
  • Chapter 5: Multivariate Linear and Nonlinear Regression Analysis
  • Chapter 6: Stochastic Processes
  • Chapter 7: Advanced Forecasting: Box-Jenkins ARIMA and Auto ARIMA, GARCH, J-Curve, S-Curves, Markov Chains, Data Diagnostics, Statistical Properties, Basic Econometrics

MODULE 7: Real Options Analysis: Theory and Background

  • Chapter 1: Real Options: What, Where, Who, When, How, and Why?
  • Chapter 2: Sample Applied Business Cases
  • Chapter 3: Overview of Different Options Valuation Techniques
  • Chapter 4: Risk-Neutral Probability Technique
  • Chapter 5: Solving a Basic European and American Call Option
  • Chapter 6: Using Excel to Solve a Basic European and American Call Option
  • Chapter 7: Abandonment, Expansion, Contraction, and Chooser Options

MODULE 8: Real Options Analysis: SLS (Super Lattice Solver) Application

  • Chapter 1: Overview of the Different SLS Modules and Volatility Estimates
  • Chapter 2: Volatility Estimates
  • Chapter 3: Options with Changing Inputs and Customised Exotic Options
  • Chapter 4: MSLS: Multiple Sequential Compound Options
  • Chapter 5: MNLS: Solving Mean-Reverting, Jump-Diffusion, and Dual-Asset Rainbow
  • Options using Trinomial, Quadranomial, and Pentanomial Lattices
  • Chapter 6: Framing Real Options-Structuring the Problem
  • Chapter 7: The Next Steps...

CQRM REVIEW FOR THE EXAMINATION

CQRM EXAM

Tutor profile:

Prof. Dr Elvis Hernandez-Perdomo is a Senior IIPER-CQRM Certifed Trainer with over eighteen years of experience in risk management, project management, corporate governance, economic valuations, and real options in energy-related companies. Director of OSL Risk Management (UK), Senior Risk Specialist at OSL Consulting Engineering, and Senior Executive Consultant at Real Options Valuations, Inc. (ROV - USA) working on real options, risk management, Monte Carlo Risk Simulation, optimisation, and business intelligence analytics.

Dr Elvis has a PhD in Finance (University of Hull), PhD in Engineering Science, MSc In Finance, MSc in Operational Research & Statistics, and BS in Economics, is CQRM Accredited and Associated in Business ERP by SAP Corporation. He is also Visiting Professor and Associate Fellow the Academy of Higher Education in the UK, with Academic articles published in international peer-review journals in reliability systems, energy markets, engineering, risk, uncertainty, and so forth.

CPD hours:

30

Contact details:

Book now