Monte Carlo Modelling for Multi-Asset Portfolios: Building an Economic Scenario Generator

Course overview This 3 day training will provide participants with a solid understanding of the technicalities involved when modeling multi asset portfolios under a Monte Carlo engine, including modeling the impact of derivative strategies as an overlay hedge for Multi Asset portfolios. A foundation is built by investigating the dynamics of interest rate modeling (all excel sheet / VBA based) and Equity modeling and the importance of modeling interest rates for long dated equity options. From here participants will be introduced to Property modeling and modeling Credit Spreads for different credit qualities. Stochastic volatility models are also covered. No experience in VBA coding is required. Complex math will be avoided to maintain a high level of practicality without losing sight of the underlying theory. View our 60 Second Interview with the Course Director - Mark C. Hoogendijk We took the opportunity to ask our expert Course Director a few questions on the current market challenges and how he became involved in this exciting industry. This is what he had to say. 4 Reasons Must Attend: 2 for 1 Training: As option pricing is the basis for multi-asset portfolio modelling, you will leave the course with an understanding of both If your organisation is considering purchasing a capital intensive ESG engine, you need to know which areas to focus on to ensure a sufficient return on investment If they are not, you can learn how to build a simple ESG engine for your organisation yourself Euromoney and the Course Director’s goal is that you leave the course knowing how to implement the analysis in practice. There will be plenty of take-away models Methodology The training will be complemented with a list of research, reference materials and excel sheets to provide the participants with a solid understanding of the technicalities involved when modeling portfolios under a Monte Carlo engine. The participants will also be guided through the VBA code behind all the excel sheets. Who should attend People working in the Investment Department, Risk Management, and Analytics teams in the following types of organisations: Asset Management companies that run multi-asset portfolios Sovereign Wealth Funds Life Insurance Companies Re-insurance Companies Pension Funds Family Offices Regulators who provide oversight for the insurance and asset management sectors Computer-based exercises All delegates should bring a laptop loaded with Microsoft Excel 2007 or later to facilitate in-class studies and exercises. Take-away In addition to exclusive documentation, participants will receive copies of Excel models and templates to support their analysis.
Day 1 A bird’s eye view of the ESG engine dynamics Starting with the End Result: An ESG Engine in full motion Explanation & Benefit of running 50 different Strategic Asset Allocation (SAA)’s Risk Neutral & Real World Engines A detailed view of the ESG engine dynamics Random Number Generators (RNG), Pseudo & Quasi Exercise: Analyzing the Randomness of a RNG in excel/vba & Halton in Excel/VBA Inversion methods Discretization techniques Variance Reduction strategies Economic Variables and their relation to the ESG Engine Review of the current literature; Macro Economic Theory Detailed Analysis of the US Interest Rate market Understanding the three drivers for the Interest Rate Curve Dynamics Swaption & Cap Volatility Structures; Equity & Interest Rate Correlation Dynamics Interest Rate Modeling Review of “well known” Interest Rate models Calibration of the Vasicek & Hull-White One Factor model to Historical Data Comparing Monte Carlo Simulations of Rates under the HW1F, CIR1F & Black-Karasinski models Limitation of 1 Factor models Exercise: Estimating the parameters of the 1 Factor models. Participants will receive different Interest Rate models with full VBA code and work on understanding the parameters of the models Exercise: Understanding the 1 Factor models and implied Spread Dynamics Implied Volatility Term-structures of Interest Rate Derivatives under 1 Factor model Day 2 Interest Rate Modeling continued: 2 Factor Model – Hull & White Understanding the parameters of the Hull White 2 Factor model Switching between the G2++ model and HW2F model Monte Carlo simulation with the HW2F model Exercise: Running different Monte Carlo simulations with the HW2F model, explanation of the VBA code Equity modeling under stochastic volatility & interest rates The case for long dated Equity Options Review of different volatility models; Understanding the correlation dynamics; Brief review of Historical Return distributions for equities & rates, and proposed correlation structures Exercise: Monte Carlo Simulation of the Equity Process under stochastic rates Incorporating Equity Risk premium into the Equity model. Review of research on this topic Implied Volatility Term-structures of Equity Derivatives Day 3 Credit modeling Overview of commonly used models and implementation in excel Real Estate modeling Understanding the de-smoothing process of property indices Review of different property investment classes Comparison analysis of Commercial & Residential indices Exercise: Property Modeling within Monte Carlo set-up. Seeing the link with Long Dated Equity Option pricing Correlation structures for Multi Asset portfolios Understanding Cholesky factorization and implementation in Excel/VBA Exercise: Calculating 2 x 2 Cholesky factorization Exercise: Running Correlated Random Variables within a Monte Carlo set-up