Appendix
Miquel Noguer i Alonso, Daniel Bloch and David Pacheco Aznar
Appendix
Preface
Introduction
Markov decision problems
Learning the optimal policy
Reinforcement learning revisited
Temporal difference learning revisited
Stochastic approximation in Markov decision processes
Large language models: reasoning and reinforcement learning
Deep reinforcement learning
Applications of artificial intelligence in finance
Pricing options with temporal difference backpropagation
Pricing American options
Daily price limits
Portfolio optimisation
Appendix
This appendix collects together advanced theoretical and practical details that extend the core ideas from the preceding chapters. Section A1 explores local risk minimisation, detailing portfolio evaluation, optimal hedging strategies and the construction of risk-averse prices, as well as the connection to the Black–Scholes limit. Section A2 covers diverse topics ranging from Black–Scholes expansions and the profit attribution analysis (PAA) methodology to Kolmogorov compatibility, providing deeper mathematical insights and tools. Next, Section A3 presents the parametric MixVol model, discussing both the model formulation and the computation of Greeks, alongside scenario analyses. Section A4 then revisits option pricing under daily price limits, offering an implementation-oriented perspective on geometric Brownian motion with boundaries. Sections A5 and A6 provide additional resources on reinforcement learning optimisation and an overview of Transformers (including multi-head attention and decoder structures), thus rounding out the book with further theoretical underpinnings and computational techniques.
A1 LOCAL RISK MINIMISATION
We briefly describe a local risk-minimisation
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net