Andrei Goloubentsev
MatLogica
Andrei Goloubentsev is a PhD-quant and Data Scientist, with an outstanding record of developing quantitative, data science, and machine learning modelling solutions for global leaders in the banking and financial services industries. Rich experience in experimental research, data analysis and modelling. Co-author of more than 20 papers and software packages in the physics and financial industry. Practical application of various machine learning techniques.
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Articles by Andrei Goloubentsev
Automatic adjoint differentiation for special functions involving expectations
The authors put forward AAD algorithms for functions involving expectations and use their technique to calibrate European options.
Adjoint differentiation for generic matrix functions
The authors develop and apply a formula to derive closed-form expressions in particular quantitative finance cases.