The MSc Quantitative Methods for Risk Management – formerly known as MSc Risk and Stochastics – offers in-depth instruction in probabilistic, statistical, and computational methods to quantify risk arising from, but not limited to, economic, financial, and insurance applications.
This programme is LSE’s timely response to industry’s strong demand in experts with quantitative expertise in risk management, finance, insurance, and their interface.
This programme will instruct you in theoretical as well as practical aspects of various quantitative methods to measure and mitigate financial and insurance risk. It draws on diverse disciplines, from mathematical finance, actuarial science to statistics and computation. You will work with real financial data to receive hands-on training in real-world problems and case studies. This programme draws on world class research in modern financial and actuarial mathematics and statistics within the Department.
Upper second class honours (2:1) degree or equivalent in actuarial science, mathematics, statistics, or mathematical economics/finance.
Competition for places at the School is high. This means that even if you meet the minimum entry requirement, this does not guarantee you an offer of admission.
For fees and funding options please visit website to find out more
The School recognises that the cost of living in London may be higher than in your home town or country, and we provide generous scholarships each year to graduate students from the UK, EU and overseas.
This programme is eligible for needs-based awards from LSE, including the Graduate Support Scheme, Master’s Awards, and Anniversary Scholarships.
The programme offers excellent prospects for employment and further study. You can gain employment in the finance or insurance industries, or go on to do a higher degree. Our alumni have taken up positions in banks, asset management firms, insurance and reinsurance companies, data analytics companies, consulting firms, and world-wide research institutions.
Please visit website for module details
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