Quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …
computers and have a transformative impact on numerous industry sectors. We present a …
Recent advances in reinforcement learning in finance
The rapid changes in the finance industry due to the increasing amount of data have
revolutionized the techniques on data processing and data analysis and brought new …
revolutionized the techniques on data processing and data analysis and brought new …
[BOOK][B] Machine learning in finance
MF Dixon, I Halperin, P Bilokon - 2020 - Springer
Machine learning in finance sits at the intersection of a number of emergent and established
disciplines including pattern recognition, financial econometrics, statistical computing …
disciplines including pattern recognition, financial econometrics, statistical computing …
Neural networks for option pricing and hedging: a literature review
Neural networks have been used as a nonparametric method for option pricing and hedging
since the early 1990s. Far over a hundred papers have been published on this topic. This …
since the early 1990s. Far over a hundred papers have been published on this topic. This …
Deep hedging of derivatives using reinforcement learning
J Cao, J Chen, J Hull, Z Poulos - arXiv preprint arXiv:2103.16409, 2021 - arxiv.org
This paper shows how reinforcement learning can be used to derive optimal hedging
strategies for derivatives when there are transaction costs. The paper illustrates the …
strategies for derivatives when there are transaction costs. The paper illustrates the …
Machine learning solutions to challenges in finance: An application to the pricing of financial products
The recent fast development of machine learning provides new tools to solve challenges in
many areas. In finance, average options are popular financial products among corporations …
many areas. In finance, average options are popular financial products among corporations …
Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions
Financial regulation is the basic requirement for financial stability. Recently, regulatory
technology (Reg-Tech) has become one of the main research topics in financial stability …
technology (Reg-Tech) has become one of the main research topics in financial stability …
[PDF][PDF] Dynamic replication and hedging: A reinforcement learning approach
◮ More recently, several studies have considered option pricing and hedging subject to both
permanent and temporary market impact in the spirit of Almgren and Chriss (1999) …
permanent and temporary market impact in the spirit of Almgren and Chriss (1999) …
Deep learning calibration of option pricing models: some pitfalls and solutions
A Itkin - arXiv preprint arXiv:1906.03507, 2019 - arxiv.org
Recent progress in the field of artificial intelligence, machine learning and also in computer
industry resulted in the ongoing boom of using these techniques as applied to solving …
industry resulted in the ongoing boom of using these techniques as applied to solving …
Model-free reinforcement learning for financial portfolios: a brief survey
Y Sato - arXiv preprint arXiv:1904.04973, 2019 - arxiv.org
Financial portfolio management is one of the problems that are most frequently encountered
in the investment industry. Nevertheless, it is not widely recognized that both Kelly Criterion …
in the investment industry. Nevertheless, it is not widely recognized that both Kelly Criterion …