The process of fitting mathematical finance (MF) models for option pricing — known as calibration — is expensive because evaluating the pricing function usually requires Monte-Carlo sampling. Inspired by the success of deep learning for simulation, we present a hypernetwork based approach to...

We present a mixture of normalizing flows (MoNF) approach to European option pricing with guarantees that its estimations are free from static arbitrage. In contrast to many existing methods that meet economic rationality constraints (e.g., non-arbitrage) by introducing auxiliary losses, our...

Partial index tracking aims to cost effectively replicate the performance of a benchmark index by using a small number of assets. It is usually formulated as a regression problem, but solving it subject to real-world constraints is non-trivial. For example, the common L1 regularised model for...

Recently self-supervised learning (SSL) has achieved impressive performance in computer vision (CV) and natural language processing (NLP) tasks, and some early attempts are made in the area of finance. In this paper, we apply SSL to extract features from financial time series data, and use those...

China Versus the West is an innovative book. The author, a leading specialist on the international and Asian economy and business, presents the most comprehensive picture of the changing power balance between the emerging superpower China and the "old" developed economies of the West: mainly the...