Objectives-Scope and Purpose:
Optimisation technologies have become key tools in making intelligent business decisions and are often adopted in the Finance industry. Important problems of the Finance industry, such as
are well-addressed by optimisation-based models. The success of optimisation enabled solutions depends on many factors such as which modelling tools are used, integration with data sets and the selection of the most efficient solution algorithms available for the problem.
Learning Outcomes:
After successful completion of the workshop, the participants will
have acquired a good knowledge of how to embed optimisation models into applications.
This workshop series is specially designed to provide insight into the discipline of optimisation for a wide range of individuals such as OR professionals, financial quantitative analysts, risk analysts, software developers, consultants and academics.
OR professionals: This workshop series will help you to get up-to-date on the latest methodologies and receive exposure to the wide range of technologies and software now available in the field of optimisation
Quantitative analysts/Risk analysts: This workshop series gives you an overview of the wide range of technologies available, allowing you to define and conceptualise your business problems in terms of an optimisation problem.
Software developers/IT: This workshop series provides instructions on how to embed optimisation models into software applications. It will also give you all the necessary information and techniques in order to understand optimisation modelling and data modelling integration.
This workshop is modular and presented in three parts (two days x 2, plus one day). This workshop is presented in an interactive format and is split into theory and practical sessions. The participants have the opportunity to familiarise themselves with relevant software and learn some practical applications. In the afternoon of each day participants spend some time discussing their modelling and solving requirements with the expert presenters. This reinforces the theory learned and provides an excellent grounding which makes the training truly valuable and practical. Participants are encouraged to engage in general discussion and further examples of applying the lessons learned.
Practical Sessions:
Our instructors are all acknowledge subject experts and have many years’ experience in this field. They will take you through all the steps of an optimisation project using powerful optimisation tools such as the modelling language AMPL, its extension Stochastic AMPL (SAMPL), and the modelling system AMPLDev, together with the solvers CPLEX and FortMP.
Pre-requisites: This is an advanced course designed to allow individuals with various levels of optimisation knowledge to attend. Some previous exposure to optimisation theory and methods is helpful but not essential.
CPD Credits:
This program qualifies for 35 GARP CPD credit hours. If you are a certified Financial Risk Manager (FRM®) or ERP, please record this activity in your Credit Tracker at http://www.garp.org/cpd
Module Plan:
Part 1. Theory and applications of Linear and Integer Programming (Day 1 & 2)
Part 2. Optimisation under uncertainty: Stochastic Programming & Robust Optimisation (Day 3 & 4)
Part 3. Risk and return analysis for Asset Allocation (Day 5)
– Introduction and Overview
– Introduction to LP Terminology, model representation and mathematical models
– An Introduction to Modelling via AMPLDev
Participants will learn how to use various functionalities of AMPL Studio
– An Introduction to AMPL Syntax
A formal presentation of basic AMPL modelling constructs
– Efficient/Structured Modelling
A process to create an efficient model starting from the problem that is presented. [Example taken from portfolio construction.]
– Goal programming / Elastic Constraints
Presentation of an introductory financial model that includes goal programming
– Using EXCEL as data source for AMPL
How to connect an AMPL model to Excel
– Financial Models workshop
Participants investigate, formulate and solve an introductory financial model using AMPL
– Hands-on models partial description: bond stripping, portfolio construction and ALM
Description of the models to be used for the hands on session and hints for the implementation
– Hands-On Session
The attendees should form groups and implement one of the models presented in the previous
session
– Mixed Integer Programming Problems
Integer problems involving binary variables, semi-continuous variables and special ordered set variables are introduced. A few discrete programming problems are explained.
– Case Study: IP with buying threshold
An IP model illustrated for portfolios with cardinality constraints
– An Introduction to AMPL Scripting Functionalities
Introduction to AMPL’s powerful scripting functionalities
– Continuation of Hands-On Session
The groups should continue the implementation of the chosen models and prepare brief presentations of their results
– Introducing AMPL API
How to embed optimisation models in applications
– Part I: Heuristic for solving Integer Programs using AMPL Script
Different kind of heuristics to speed up solution of problems are proposed here and prototyped using AMPL scripting functionalities
– Part II: AMPL API Implementation of AMPL script procedures
Examples of integration of models and scripts into applications
– Attendees’ presentations and feedback
The groups have ten minutes each to present the model they implemented and their results.
– Stochastic Programming: optimum decision making under uncertainty-an overview
A theoretical background to decision making under uncertainty will be given, with a particular focus on stochastic programming
– Scenario Generation: Overview and Desirable Properties
– Stochastic Programming and Risk Measures
Multiple Formulations of Multiple Asset and Liability Management (ALM) Problems as Alternative Stochastic Programming Models
– Hands-on
Creation of a prototype ALM application by connecting market data, formulated model, scenario generation and results presentation
– Investigation and Simulation: Two-stage SP, ICCP and Robust Optimisation
– Formulation of SP models in SAMPL
Various SP models will be described and attendees will be helped in their implementation in SAMPL
– Stochastic Programming: optimum decision making under uncertainty-an overview
A theoretical background to decision making under uncertainty will be given, with a particular focus on stochastic programming
– Stochastic Programming and Risk Measures
Multiple Formulations of Multiple Asset and Liability Management (ALM) Problems as Alternative Stochastic Programming Models
– Hands-on: Expected Value, Wait and See and Deterministic Equivalent – an ALM model
Various models are described and attendees are helped with their implementation in AMPL
– Formulation in AMPL
AMPL extensions to represent Stochastic Programming and Robust Optimisation problems, and problems with (Integrated) Chance Constraints
– SAMPL Example: an ALM model
An ALM model will be refined by the introduction of uncertainty and expressed using AAMPL syntax
– Solution Methods for Stochastic Programming
– Introduction to Robust Optimisation Models (Family)
– Introduction and Overview
– Formulation of Quadratic Programming problems and Mean Variance Efficient Frontier
– Hands-on: Representation of Discrete Constraints in Portfolio Planning
– Hands-on: Computation of Mean Variance Efficient Frontier
– Mean Variance and CVAR: a multi-objective model
– Portfolio Construction using Stochastic Dominance and Reference Distribution
– SP Models for Portfolio Construction with Trading Constraints
– Stochastic Programming Models for ALM
To Inquire about sponsorship opportunities, write to us at shrrey.jhunjhunwalaa@unicomseminars.uk or call +91 9970 636 341
Indian Institute of Management–Udaipur (IIM–Udaipur)
