Training course by Adnane Moulim, Senior Quantitative Modeler, Morocco

December 19, 2020 (3 p.m., Rabat) 

Short Bio: Graduated in Financial Engineering from ENSIMAG: National School of Computer Science and Applied Mathematics of Grenoble. Adnane Moulim joined CIC bank in 2004 as Quantitative Analyst on Equity derivatives, then in 2006 Natexis Banque Populaire as Quantitative Analyst on Forex derivatives before joining Natixis CIB in 2007. From 2007 to 2016, Adnane has held several positions within Natixis Paris and London, Senior Quantitative Analyst on Equities and Commodities in the Risk Department, Head of Quantitative Research and Financial Engineering of the Commodities Trading Desks and Head of the Modeling Team within of the Global Portfolio Management department. Adnane has joined OCP Group in 2016 and he is principal in charge of the Modeling practice within the consulting firm OCP Solutions for 4 years.

Title: International Commodity Market Structures, Modeling & Risk Management

 Abstract: Commodity Markets are at the heart of economic activity. From natural gas to petroleum or renewable, from soybean oil to wheat, from aluminum to coffee or rubber, we are all, in one way or another and to varying degrees, dependent on Commodity Markets. Different in their physical properties but governed by the dynamics of common physical markets (known as Spot), traded on complex and oligopolistic global markets, subject to intense competitive pressure and speculative betting.

Often marked by very volatile prices and little correlated with other financial assets such as stocks, bonds or interest rates, We will present in this presentation the different structures of the financialized commodity markets (Energy (oil & gas), Base metals, Precious metals), but also the modeling of the stochastic dynamics of the commodity markets (on future curve basic) as well as examples of hedging and risk management for producers and consumers of raw materials.

Exhaustive modeling of the futures curve for derivatives pricing is a difficult task. It involves the modeling of each future as a particular asset. Therefore, it transforms a mono underlying derivative contract into a multi-dimensional problem with a large correlation matrix. It is then for reasons imperative to reduce the dimension of the problem.