Zobrazeno 1 - 10
of 531
pro vyhledávání: '"BRIGO, DAMIANO"'
Deep learning methods have become a widespread toolbox for pricing and calibration of financial models. While they often provide new directions and research results, their `black box' nature also results in a lack of interpretability. We provide a de
Externí odkaz:
http://arxiv.org/abs/2411.19317
Autor:
Brigo, Damiano
We present the two new notions of projection of a stochastic differential equation (SDE) onto a submanifold, as developed in Armstrong, Brigo e Rossi Ferrucci (2019, 2018): the Ito-vector and Ito-jet projections. This allows one to systematically and
Externí odkaz:
http://arxiv.org/abs/2205.01594
We extend the valuation of contingent claims in presence of default, collateral and funding to a random functional setting and characterise pre-default value processes by martingales. Pre-default value semimartingales can also be described by BSDEs w
Externí odkaz:
http://arxiv.org/abs/2112.11808
We present a measurement of price impact in order-driven markets that does not require averages across executions or scenarios. Given the order book data associated with one single execution of a sell metaorder, we measure its contribution to price d
Externí odkaz:
http://arxiv.org/abs/2110.00771
Deep learning is a powerful tool whose applications in quantitative finance are growing every day. Yet, artificial neural networks behave as black boxes and this hinders validation and accountability processes. Being able to interpret the inner funct
Externí odkaz:
http://arxiv.org/abs/2104.09476
We introduce a first theory of price impact in presence of an interest-rates term structure. We explain how one can formulate instantaneous and transient price impact on bonds with different maturities, including a cross price impact that is endogeno
Externí odkaz:
http://arxiv.org/abs/2011.10113