HPCFINANCE · Training in Modern Quantitative Methods and High-Performance Computing for Finance

HPCFinance, a 4-year multi-site Marie Curie Initial Training Network in modern quantitative methods and High-Performance Computing for Finance, provides solutions to managing financial risks by high-performance computing. HPCFinance will help improve the financial strength of banks, pension funds, insurance companies, other financial institutions and households in Europe. The main goal of the network is to enhance the career development of 12 early-stage researchers and 2 experienced ones in finance-related sectors.Currently, while recovering from the financial crisis, the European financial world and academic researchers are facing major challenges to create and apply more reliable quantitative models and methods to manage risks. Simultaneously, computationally challenging new hybrid products combining traditional financial investments with insurance policies are gaining popularity. Consequently, demand for experts in finance with superior computing skills is growing rapidly.HPCFinance consists of 7 universities and 8 companies, representing investment and insurance companies, banks, consultants, and high-performance computing solution providers. The network’s US partners provide invaluable experience for benchmarking and knowledge transfer into Europe. This world-class network provides training in robust financial models and numerical methods on high-performance computing platforms with emphasis on variable annuities and asset and liability management. The intended research is not only academically but also practically relevant as the program is built around real life challenges identified together by the academic and private sector partners. To bridge research and practice, all researchers contribute to the private sector via secondments. The major societal impacts of HPCFinance are to provide the European finance community with specialists with state-of-the-art skills in computational finance and to ease the adoption of reliable models in the industry.