Advanced Risk Management Professional


A sound and robust risk management in organizations is considered a sine qua non for corporate success.

The ARMP or Advanced Risk Management Professional is a certification designed based on ISO 31000 Risk Management International Standard, the Basel Accords and the COSO framework.

This  advanced certification provides  the advanced skills needed to manage risks effectively. It impacts skills to establish  clear vision to untangle the complexities in organizations  and execute strategies more effectively.

Course Modules

Risk in Perspective

  • Introduction and Need for Risk Management
  • Risk and Randomness
  • Financial Risk
  • Measurement and Management of Risk
  • A Brief History of Risk Management
  • From Babylon to Wall Street
  • The Road of Regulation
  • The New Regulatory Framework: (Basel Accords & Solvency 2)
  • Why Manage Financial Risk?: Societal View & Shareholders View
  • Economic Capital
  • Quantitative Risk Management [QRM]: The Nature of the Challenge
  • QRM for the Future

Basic Concepts in Risk Management

  • Risk Factors and Loss Distribution
  • General Definitions
  • Conditional and Unconditional Loss Distribution
  • Mapping of Risk
  • Risk Measurement
  • Approaches to Risk Measurement
  • Value-at-Risk [VaR]
  • Further Comments on VaR
  • Other Risk Measure Based on Loss Distribution
  • Standard Method for Market Risk
  • Variance-Covariance Method for Market Risk
  • Historical Simulation
  • Monte Carlo Losses over Several Periods and Scaling Back testing

 Multivariate Models

  • Basic of Multivariate Modelling
  • Random Vectors and their Distributions
  • Standard Estimators of Covariance and Correlation
  • The Multivariate Normal Distribution
  • Testing Normality and Multivariate Normality
  • Normal Mixture Distribution
  • Normal Variance Mixtures
  • Normal Mean-Variance Mixtures
  • Generalized Hyperbolic Distributions
  • Fitting Generalized Hyperbolic Distribution to Data
  • Empirical Examples
  • Spherical and Elliptical Symmetry
  • Dimension Reduction Techniques
  • Factor Models
  • Statistical Calibration Strategies
  • Regression Analysis of Factor Models
  • Principal Component Analysis

Financial Time Series

  • Empirical Analysis of Finance Time Series
  • Stylized Facts
  • Multivariate Stylized Facts
  • Fundamentals of Time Series Analysis
  • Basic Definitions
  • ARMA Processes
  • Analysis in the Time Domain
  • Statistical Analysis of Time Series
  • Prediction GARCH Models for changing Volatility
  • ARCH Processes
  • GARCH Processes
  • Simple Extensions of the GARCH Models
  • Fitting GARCH Models to Data
  • Volatility Models and Risk Extension
  • Fundamentals of Multivariate Time Series
  • Analysis in the Time Domain
  • Multivariate ARMA Processes
  • Multivariate GARCH Processes
  • General Structure of Models
  • Models for Conditional Correlation
  • Models for Conditional Covariance
  • Fitting Multivariate GARCH Models
  • Dimension Reduction in MGARCH
  • MGARCH and Conditional Risk Measurement

 Copulas and Dependence

  • Copulas
  • Basic Properties
  • Examples of Copulas
  • Meta Distribution
  • Simulation of Copulas and Meta Distribution
  • Further Properties of Copulas
  • Perfect Dependence
  • Dependence Measures
  • Liner Correlation
  • Bank Correlation and Coefficient of Tall Dependence
  • Normal Mixture Copulas
  • Bank Correlation
  • Skewed Normal Mixture Copulas
  • Grouped Normal Mixture Copulas
  • Archimedean Copulas
  • Bivariate Archimedean Copulas
  • Multivariate Archimedean Copulas
  • Non-exchangeable Archimedean Copulas
  • Fitting Copulas to Data
  • Methods-of-Moments using Rank Correlation
  • Forming a Pseudo-sample from the Copula
  • Maximum Likelihood Estimation

 Aggregate Risk

  • Coherent Measure of Risk
  • The Axioms of Coherence
  • Value-at-Risk
  • Coherent Risk Measures based on Loss Distribution
  • Coherent Risk Measures as Generalized Scenarios
  • Mean-VaR Portfolio Optimization
  • Bounds of Aggregate Risk
  • The General Freshet Problem
  • The Case of VaR Capital Allocation
  • The Allocation Problem
  • The Euler Principle
  • Economic Justification of the Euler Principle

Credit Risk Management

  • Introduction to Credit Risk Modelling
  • Credit Risk Models
  • The Nature of the Challenge
  • Structural Models of Default
  • The Merton Model
  • Pricing in Merton’s Model
  • The KMV Model
  • Model Based on Credit Migration
  • Multivariate Firm-value Models
  • Threshold Models
  • Notation for One-Period Portfolio Models
  • Threshold Models and Copulas
  • Model Based on alternative Copulas
  • Model Risk Issues
  • The Mixture Model Approach
  • One-factor Bernoulli Mixture Models
  • Credit Risk
  • Asymptotic for large Portfolios
  • Threshold Models as Mixture Models
  • Model-Theoretic Aspects of Basel II
  • Model Risk Issues
  • Monte Carlo Methods
  • Basics of Important Sampling: Application to Bernoulli-Mixture Models
  • Mixture Models as GLMMs
  • One-Factor Model with Rating Effect

 Dynamic Credit Risk Models

  • Credit Derivatives
  • Single-name Credit Derivatives
  • Portfolios Credit Derivatives
  • Mathematical Tools
  • Random Time and Hazard Rates
  • Modelling Additional Information
  • Double Stochastic Random Times
  • Financial and Actual Pricing of Credit Risk
  • Physical and Risk-Natural Probability Measures
  • Risk-Neutral Pricing and Market Competencies
  • Martingale Modelling
  • The Actuarial Approach to Credit Risk Pricing
  • Pricing with Double Stochastic Default Times
  • Recovery Payment of Corporate Bonds
  • The Model Pricing Formula
  • Affine Models
  • The CR Square-Root Diffusion
  • Conditionally Independent Defaults
  • Reduced-form Models for Portfolio Credit Risk
  • Definition and General Properties
  • Factor Copula Models
  • Default Contagion in Reduced-Form Models
  • Default Contagion and Default Dependence
  • Information-Based Default Contagion
  • Interacting Intensities 

Operational Risk and Insurance Analysis

  • Operational Risk in Perspective
  • The Elementary Approaches
  • Advanced Measurement Approaches
  • Operational Loss Data
  • Elements of Insurance Analytics
  • The Case for Actuarial Methodology
  • The Total Loss Amount
  • Approximation and Panjer Recursion
  • Poisson Mixture
  • Tails of Aggregate Loss Distributions
  • The Homogeneous Poisson Process
  • Process related to the Poisson Process

ISO 31000: 2018 ERM

This module will help you to:

Understand the principles, framework and process described in ISO 31000:2018

Create and protect value in your organization by managing risks, making decisions, setting and achieving objectives and improving performance

Understand governance and leadership role in managing risk at all levels

Module Highlight

  • Key terms and definitions
  • Importance and benefits of ISO 31000:2018
  • Introduction to risk management principles and framework based on ISO 31000
  • Risk management process based on ISO 31000
  • Risk assessment techniques based on IEC/ISO 31010

WHO Can Sit for the Exam?

  • Directors and top officials in both the private and public sectors with over 10 years experience
  • Chief Risk Officers
  • Chief Compliance Officers
  • Risk Management Professionals
  • Practitioners and professionals in risk management  with over 8 years cognate experience
  •,, P.hD holders in relevant discipline with over 6 years experience.
  • Auditors
  • Consultants
  • Chartered Bankers
  • Chartered Accountants