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Trades, Quotes and Prices
A deep-dive into the heart of modern financial markets, the authors explore why and how people trade - and the consequences.
Financial Data Engineering
Today, investment in financial technology and digital transformation is reshaping the financial landscape and generating many opportunities. Too often, however, engineers and professionals in financial institutions lack a practical and comprehensive understanding of the concepts, problems, techniques, and technologies necessary to build a modern, reliable, and scalable financial data infrastructure. This is where financial data engineering is needed. A data engineer developing a data infrastructure for a financial product possesses not only technical data engineering skills but also a solid understanding of financial domain-specific challenges, methodologies, data ecosystems, providers, form...
Digital Finance in Europe: Law, Regulation, and Governance
Global finance is in the middle of a radical transformation fueled by innovative financial technologies. The coronavirus pandemic has accelerated the digitization of retail financial services in Europe. Institutional interest and digital asset markets are also growing blurring the boundaries between the token economy and traditional finance. Blockchain, AI, quantum computing and decentralised finance (DeFI) are setting the stage for a global battle of business models and philosophies. The post-Brexit EU cannot afford to ignore the promise of digital finance. But the Union is struggling to keep pace with global innovation hubs, particularly when it comes to experimenting with new digital form...
Trades, Quotes and Prices
The widespread availability of high-quality, high-frequency data has revolutionised the study of financial markets. By describing not only asset prices, but also market participants' actions and interactions, this wealth of information offers a new window into the inner workings of the financial ecosystem. In this original text, the authors discuss empirical facts of financial markets and introduce a wide range of models, from the micro-scale mechanics of individual order arrivals to the emergent, macro-scale issues of market stability. Throughout this journey, data is king. All discussions are firmly rooted in the empirical behaviour of real stocks, and all models are calibrated and evaluated using recent data from Nasdaq. By confronting theory with empirical facts, this book for practitioners, researchers and advanced students provides a fresh, new, and often surprising perspective on topics as diverse as optimal trading, price impact, the fragile nature of liquidity, and even the reasons why people trade at all.
Rough Volatility
Volatility underpins financial markets by encapsulating uncertainty about prices, individual behaviors, and decisions and has traditionally been modeled as a semimartingale, with consequent scaling properties. The mathematical description of the volatility process has been an active topic of research for decades; however, driven by empirical estimates of the scaling behavior of volatility, a new paradigm has emerged, whereby paths of volatility are rougher than those of semimartingales. According to this perspective, volatility behaves essentially as a fractional Brownian motion with a small Hurst parameter. The first book to offer a comprehensive exploration of the subject, Rough Volatility...
Proceedings of the fourth Asia-Pacific Research in Social Sciences and Humanities, Arts and Humanities Stream (AHS-APRISH 2019)
This is an open access book.According to Castells, power now rests in networks: “the logic of the network is more powerful than the powers of the network” (quoted in Weber, 2002, p. 104) – it is whether nation states or local communities are deeply affected, especially by inclusion in and exclusion from the global networks that structure a various sectors in society at any level. Thus it is also crucial look closely at exclusion from and inclusion in different kinds of social structures where connectivity and access to networks are essential, being aware that people at the bottom are those who, with nothing to offer the network, are excluded. Castells’ arguments shows us how the new ...
EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing
This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), took place on 13 – 15 December 2018 in Coimbatore, India.
Market Microstructure
The latest cutting-edge research on market microstructure Based on the December 2010 conference on market microstructure, organized with the help of the Institut Louis Bachelier, this guide brings together the leading thinkers to discuss this important field of modern finance. It provides readers with vital insight on the origin of the well-known anomalous "stylized facts" in financial prices series, namely heavy tails, volatility, and clustering, and illustrates their impact on the organization of markets, execution costs, price impact, organization liquidity in electronic markets, and other issues raised by high-frequency trading. World-class contributors cover topics including analysis of high-frequency data, statistics of high-frequency data, market impact, and optimal trading. This is a must-have guide for practitioners and academics in quantitative finance.
Limit Order Books
This text presents different models of limit order books and introduces a flexible open-source library, useful to those studying trading strategies.
AI and Financial Markets
Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
