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Author: David M. Drukker
Publisher: Emerald Group Publishing
ISBN: 1780525265
Category : Business & Economics
Languages : en
Pages : 262
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Book Description
Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.
Author: David M. Drukker
Publisher: Emerald Group Publishing
ISBN: 1780525265
Category : Business & Economics
Languages : en
Pages : 262
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Book Description
Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 1482240564
Category : Computers
Languages : en
Pages : 478
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Book Description
As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre
Author:
Publisher:
ISBN:
Category : Business
Languages : en
Pages : 2838
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Book Description
Author: Charles Lee
Publisher: Now Publishers
ISBN: 9781601988928
Category : Business & Economics
Languages : en
Pages : 212
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Book Description
Alphanomics: The Informational Underpinnings of Market Efficiency is intended to be a compact introduction to academic research on market efficiency, behavioral finance, and fundamental analysis and is dedicated to the kind of decision-driven and prospectively-focused research that is much needed in a market constantly seeking to become more efficient. The authors refer to this type of research as Alphanomics, the informational economics behind market efficiency. Alpha refers to the abnormal returns, which provide the incentive for some subpopulation of investors to engage in information acquisition and costly arbitrage activities. Nomics refers to the economics of alpha extraction, which encompasses the costs and incentives of informational arbitrage as a sustainable business proposition. Some of the questions that are addressed include: why do we believe markets are efficient?; what problems have this belief engendered?; what factors can impede and/or facilitate market efficiency?; what roles do investor sentiment and costly arbitrage play in determining an equilibrium level of informational efficiency?; what is the essence of value investing?; how is it related to fundamental analysis (the study of historical financial data)?; and how might we distinguish between risk and mispricing based explanations for predictability patterns in returns? The first two sections review the evolution of academic thinking on market efficiency and introduce the noise trader model as a rational alternative. Section 3 surveys the literature on investor sentiment and its role as a source of both risks and returns. Section 4 discusses the role of fundamental analysis in value investing. Section 5 reviews the literature on limits to arbitrage, and section 6 discusses research methodology issues associated with the need to distinguish mispricing from risk.
Author: Robert A. Meyers
Publisher: Springer Science & Business Media
ISBN: 1441977007
Category : Business & Economics
Languages : en
Pages : 919
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Book Description
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Author: Leonard C. MacLean
Publisher: World Scientific
ISBN: 9814417351
Category : Business & Economics
Languages : en
Pages : 941
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Book Description
This handbook in two parts covers key topics of the theory of financial decision making. Some of the papers discuss real applications or case studies as well. There are a number of new papers that have never been published before especially in Part II.Part I is concerned with Decision Making Under Uncertainty. This includes subsections on Arbitrage, Utility Theory, Risk Aversion and Static Portfolio Theory, and Stochastic Dominance. Part II is concerned with Dynamic Modeling that is the transition for static decision making to multiperiod decision making. The analysis starts with Risk Measures and then discusses Dynamic Portfolio Theory, Tactical Asset Allocation and Asset-Liability Management Using Utility and Goal Based Consumption-Investment Decision Models.A comprehensive set of problems both computational and review and mind expanding with many unsolved problems are in an accompanying problems book. The handbook plus the book of problems form a very strong set of materials for PhD and Masters courses both as the main or as supplementary text in finance theory, financial decision making and portfolio theory. For researchers, it is a valuable resource being an up to date treatment of topics in the classic books on these topics by Johnathan Ingersoll in 1988, and William Ziemba and Raymond Vickson in 1975 (updated 2 nd edition published in 2006).
Author: Matthew F. Dixon
Publisher: Springer Nature
ISBN: 3030410684
Category : Business & Economics
Languages : en
Pages : 565
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Book Description
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Author: Sitabhra Sinha
Publisher: John Wiley & Sons
ISBN: 3527408150
Category : Science
Languages : en
Pages : 371
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Book Description
Filling the gap for an up-to-date textbook in this relatively new interdisciplinary research field, this volume provides readers with a thorough and comprehensive introduction. Based on extensive teaching experience, it includes numerous worked examples and highlights in special biographical boxes some of the most outstanding personalities and their contributions to both physics and economics. The whole is rounded off by several appendices containing important background material.
Author: S.J. Bartlett
Publisher: Springer Science & Business Media
ISBN: 940093551X
Category : Philosophy
Languages : en
Pages : 365
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Book Description
Self-reference, although a topic studied by some philosophers and known to a number of other disciplines, has received comparatively little explicit attention. For the most part the focus of studies of self-reference has been on its logical and linguistic aspects, with perhaps disproportionate emphasis placed on the reflexive paradoxes. The eight-volume Macmillan Encyclopedia of Philosophy, for example, does not contain a single entry in its index under "self-reference", and in connection with "reflexivity" mentions only "relations", "classes", and "sets". Yet, in this volume, the introductory essay identifies some 75 varieties and occurrences of self-reference in a wide range of disciplines, and the bibliography contains more than 1,200 citations to English language works about reflexivity. The contributed papers investigate a number of forms and applications of self-reference, and examine some of the challenges posed by its difficult temperament. The editors hope that readers of this volume will gain a richer sense of the sti11largely unexplored frontiers of reflexivity, and of the indispensability of reflexive concepts and methods to foundational inquiries in philosophy, logic, language, and into the freedom, personality and intelligence of persons.
Author: Khalid Rehman Hakeem
Publisher: Springer
ISBN: 3319138472
Category : Nature
Languages : en
Pages : 508
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Book Description
Agricultural biomass is abundant worldwide and it can be considered as alternative source of renewable and sustainable materials which can be used as potential materials for different applications. Despite this enormous production of agricultural biomass, only a small fraction of the total biomass is utilized for different applications. Industry must be prepared to take advantage of the situation and utilize the available biomass in the best possible manner. Agricultural biomass such as natural fibres has been successfully investigated as a great potential to be used as a renewable and sustainable materials for the production of composite materials. Natural fibres offer excellent specific properties and have potential as outstanding reinforcing fillers in the matrix and can be used as an alternative material for biocomposites, hybrid composites, pulp, and paper industries. Natural fibre based polymer composites made of jute, oil palm, flex, hemp, kenaf have a low market cost, attractive with respect to global sustainability and find increasing commercial use in different applications. Agricultural biomass based composites find applications in a number of fields viz., automotive industry and construction industry. Future research on agricultural biomass-natural fibre based composites should not only be limited to its automotive applications but can be explored for its application in aircraft components, construction industry, rural housing and biomedical applications. In this book we will cover the chemical, physical, thermal, electrical, and biodegradability properties of agricultural biomass based composite materials and its different potential applications. The main goal of this volume is to familiarize researchers, scientists and engineers with the unique research opportunities and potentials of agricultural biomass based materials. Up-to-date information on alternative biomass utilization Academic and industry leaders discuss unique properties of biomass based composite materials Direct application of agricultural biomass materials as sustainable and renewable alternatives
