Gautam Mitra – författare

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike.

Features

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike.

Features

The First Collection That Covers This Field at the Dynamic Strategic and One-Period Tactical Levels. Addressing the imbalance between research and practice, Quantitative Fund Management presents leading-edge theory and methods, along with their application in practical problems encountered in the fund management industry. A Current Snapshot of State-of-the-Art Applications of Dynamic Stochastic Optimization Techniques to Long-Term Financial Planning - The first part of the book initially looks at how the quantitative techniques of the equity industry are shifting from basic Markowitz mean-variance portfolio optimization to risk management and trading applications. This section also explores novel aspects of lifetime individual consumption investment problems, fixed-mix portfolio rebalancing allocation strategies, debt management for funding mortgages and national debt, and guaranteed return fund construction. Up-to-Date Overview of Tactical Financial Planning and Risk Management - The second section covers nontrivial computational approaches to tactical fund management. This part focuses on portfolio construction and risk management at the individual security or fund manager level over the period up to the next portfolio rebalance. It discusses non-Gaussian returns, new risk-return tradeoffs, and the robustness of benchmarks and portfolio decisions. The Future Use of Quantitative Techniques in Fund Management - With contributions from well-known academics and practitioners, this volume will undoubtedly foster the recognition and wider acceptance of stochastic optimization techniques in financial practice.

 The content of the Hand Book is organised to provide a rapid yet comprehensive understanding of this topic. Chapter 1 sets out an overview of News Analytics (NA) with an explanation of the technology and applications. The rest of the chapters are presented in four parts. Part 1 contains an explanation of methods and models which are used to measure and quantify news sentiment. In Part 2 the relationship between news events and discovery of abnormal returns (the elusive alpha) is discussed in detail by the leading researchers and industry experts. The material in this part also covers potential application of NA to trading and fund management. Part 3 covers the use of quantified news for the purpose of monitoring, early diagnostics and risk control. Part 4 is entirely industry focused; it contains insights of experts from leading technology (content) vendors. It also contains a discussion of technologies and finally a compact directory of content vendor and financial analytics companies in the marketplace of NA.  The book draws equally upon the expertise of academics and practitioners who have developed these models and is supported by two major content vendors - RavenPack and Thomson Reuters - leading providers of news analytics software and machine readable news.   The book will appeal to decision makers in the banking, finance and insurance services industry.  In particular: asset managers; quantitative fund managers; hedge fund managers; algorithmic traders; proprietary (program) trading desks; sell-side firms; brokerage houses; risk managers and research departments will benefit from the unique insights into this new and pertinent area of financial modelling.

The First Collection That Covers This Field at the Dynamic Strategic and One-Period Tactical Levels. Addressing the imbalance between research and practice, Quantitative Fund Management presents leading-edge theory and methods, along with their application in practical problems encountered in the fund management industry. A Current Snapshot of State-of-the-Art Applications of Dynamic Stochastic Optimization Techniques to Long-Term Financial Planning - The first part of the book initially looks at how the quantitative techniques of the equity industry are shifting from basic Markowitz mean-variance portfolio optimization to risk management and trading applications. This section also explores novel aspects of lifetime individual consumption investment problems, fixed-mix portfolio rebalancing allocation strategies, debt management for funding mortgages and national debt, and guaranteed return fund construction. Up-to-Date Overview of Tactical Financial Planning and Risk Management - The second section covers nontrivial computational approaches to tactical fund management. This part focuses on portfolio construction and risk management at the individual security or fund manager level over the period up to the next portfolio rebalance. It discusses non-Gaussian returns, new risk-return tradeoffs, and the robustness of benchmarks and portfolio decisions. The Future Use of Quantitative Techniques in Fund Management - With contributions from well-known academics and practitioners, this volume will undoubtedly foster the recognition and wider acceptance of stochastic optimization techniques in financial practice.

In Decision Modelling And Information Systems: The Information Value Chain the authors explain the interrelationships between the decision support, decision modelling, and information systems.

The first two parts of the book focus on the interdisciplinary decision support framework, in which mathematical programming (optimization) is taken as the inference engine. The role of business analytics and its relationship with recent developments in organisational theory, decision modelling, information systems and information technology are considered in depth. Part three of the book includes a carefully chosen selection of invited contributions from internationally-known researchers. These contributions are thought-provoking and cover key decision modelling and information systems issues.

The final part of the book covers contemporary developments in the related area of business intelligence considered within an organizational context. The topics cover computing delivered across the web, management decision-making, and socio-economic challenges that lie ahead. It is now well accepted that globalisation and the impact of digital economy are profound; and the role of e-business and the delivery of decision models (business analytics) across the net lead to a challenging business environment. In this dynamic setting, decision support is one of the few interdisciplinary frameworks that can be rapidly adopted and deployed to so that businesses can survive and prosper by meeting these new challenges.