Quantitative Asset Management

Augment your asset allocation strategy with machine learning and factor investing for unprecedented returns and growth

Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well.

This book explores the emerging field of risk management and risk analysis of cryptocurrencies, an area that has been generating considerable research. It begins by providing an introduction to digital finance and the concept of cryptocurrencies and blockchain technologies. It then describes in detail the intrinsic risks involved in cryptocurrencies, an area that, to date, has not been fully documented or investigated. Lastly, it discusses the various types of risk, with a focus on design, operational, market and quantitative risks.