Department of Mathematics

Financial Engineering and Risk Management

Our program – your future

Financial Engineering is a multidisciplinary field involving financial theory, the methods of engineering, the tools of mathematics and the practice of programming.

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Objectives

Our graduates will be equipped with solid understandings in mathematics and able to apply modern tools and techniques in financial engineering and risk management. They would also be qualified for positions in the insurance industry, banking and financial management. They can work as quantitative analysts in corporate treasury and finance departments as well as in the investment industry.

Job opportunity

After graduating from our program FERM, students can find jobs at International financial organizations such as World Bank, International Monetary Fund (IMF), International Finance Corporation (IFC), and many others national and international financial organizations in Vietnam and in other countries.
Our program, however, mainly trains students so that they can possess the ability to work as experts in economics/finance analyst at financial investment companies, stock companies, …
Students are equipped with knowledges and skills in porfolio management, financial market analysis, and so, they have ability to work and support financial organizations, funds, banks, companies that supply financial services.
After graduating from our program, students can be officers or managers for the (or local) government(s), or for projects, working on the areas financial engineering and risk management.
Our graduates also can become lecturers at colleges or universities, or financial institutes and can continue the academic rout by continuing their study for a Master or PhD degree.

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Experts opinions

"I am in a world of data, and I build all sorts of models for banks. For instance, one that helps a bank decide whom to lend a mortgage to. You have all this data about the person who is applying, and then the model works out the risk of lending to that person. You look at both the probability of this happening, and at the size of the loss in such an event"

In “Voice of finance: quant” by Joris Luyendijk
http://www.theguardian.com/commentisfree/2011/dec/01/quant-voice-of-finance

“From the start, one of the aims of the world of finance consisted in managing and reducing risks as much as possible. During the late 1980s, a quantum leap was achieved thanks to the quick development of dynamic strategies, as opposed to techniques that had previously been applied by ensuring an average risk through the weighting of different asset classes. During the development of financial mathematics in the early 1990s, the first challenge was to implement a dynamic hedging, supported by increasingly sophisticated mathematical models. And as the models strengthened, researchers and practitioners started to examine more closely, not only the models themselves, but the disruptive factors, the random elements that distorted curves.”

From “The future of financial mathematics” ParisTech Review .
Nicole El Karoui / Professor of Applied Mathematics, Pierre et Marie Curie University (Paris VI), Research Director, Center for Applied Mathematics, Ecole Polytechnique / September 6th, 2013

“The world in which we live today does not know the same expansion as the years 1990-2000. Moreover, the crisis has highlighted the importance of the hidden, implicit links, and more generally of what we call the “systemic risk”. To put things simply, until 2008 the focus was set on the “risk of noise”. Since 2008, we are learning to manage the risk of chaos.”

“In terms of risk management, this implies especially a stronger consideration of collateralization. In this context, financial mathematics are set to undergo an inflection. Earlier systems need to integrate different techniques: collateral management requires to follow several curves at the same time; taking into account the systemic risk poses considerable problems, since it requires both a better understanding and to prevent the creation of systems that by responding to signals from systemic risk, will increase this risk.”

From “The future of financial mathematics” ParisTech Review (by Nicole El Karoui).