In quantitative finance academic researchers and leading practitioners are publishing distinguished models and methodologies for the pricing and analytics of instruments and portfolios. To implement them properly, you need to know a lot about models for underlyings, stochastic calculus, numerical schemes for PDE and PIDE treatment , parameter identification, Montecarlo simulation and Longstaff Schwartz, global optimization, inverse problems, …
To validate valuation and calibration engines in HPC environments, combine them with transaction processing and deploy risk analytics tasks over the web, you need to drive generic sw technologies additionally, and understand them deeply.
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