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Author: Universidad Nacional de Tucumán
Publisher:
ISBN:
Category : Mathematical physics
Languages : en
Pages : 474

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Author: Benjamin Franklin Library (Mexico City, Mexico)
Publisher:
ISBN:
Category :
Languages : en
Pages : 230

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Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 546

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Author: Zura Kakushadze
Publisher: Springer
ISBN: 3030027929
Category : Business & Economics
Languages : en
Pages : 480

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Book Description
The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.

Author:
Publisher:
ISBN:
Category : Libraries
Languages : un
Pages : 1026

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Author: Kenneth Train
Publisher: MIT Press
ISBN: 9780262200554
Category : Business & Economics
Languages : en
Pages : 282

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This book addresses two significant research areas in an interdependent fashion. It is first of all a comprehensive but concise text that covers the recently developed and widely applicable methods of qualitative choice analysis, illustrating the general theory through simulation models of automobile demand and use. It is also a detailed study of automobile demand and use, presenting forecasts based on these powerful new techniques. The book develops the general principles that underlie qualitative choice models that are now being applied in numerous fields in addition to transportation, such as housing, labor, energy, communications, and criminology. The general form, derivation, and estimation of qualitative choice models are explained, and the major models - logit, probit, and GEV - are discussed in detail. And continuous/discrete models are introduced. In these, qualitative choice methods and standard regression techniques are combined to analyze situations that neither alone can accurately forecast. Summarizing previous research on auto demand, the book shows how qualitative choice methods can be used by applying them to specific auto-related decisions as the aggregate of individuals' choices. The simulation model that is constructed is a significant improvement over older models, and should prove more useful to agencies and organizations requiring accurate forecasting of auto demand and use for planning and policy development. The book concludes with an actual case study based on a model designed for the investigations of the California Energy Commission. Kenneth Train is Visiting Associate Professor in Economics at the University of California, Berkeley, and Director of Economic Research at Cambridge Systematics, Inc., also in Berkeley. Qualitative Choice Analysisis included in The MIT Press Transportation Studies Series, edited by Marvin L. Manheim.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 2562

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Author: Kenneth Train
Publisher: Mit Press
ISBN: 9780262200844
Category : Business & Economics
Languages : en
Pages : 338

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Optimal Regulation addresses the central issue of regulatory economics - how toregulate firms in a way that induces them to produce and price "optimally." It synthesizes the majorfindings of an extensive theoretical literature on what constitutes optimality in various situationsand which regulatory mechanisms can be used to achieve it. It is the first text to provide aunified, modern, and nontechnical treatment of the field.The book includes models for regulatingoptimal output, tariffs, and surplus subsidy schemes, and presents all of the material graphically,with clear explanations of often highly technical topics.Kenneth E. Train is Associate AdjunctProfessor in the Department of Economics and Graduate School of Public Policy at the University ofCalifornia, Berkeley. He is also Principal of the firm Cambridge Systematics.Topics include: Thecost structure of natural monopoly (economies of scale and scope). Characterization of firstandsecond-best optimality. Surplus subsidy schemes for attaining first-best optimality. Ramsey pricesand the Vogelsang-Finsinger mechanism for attaining them. Time-ofuse (TOU) prices and Riordan'smechanisms for attaining the optimal TOU prices' Multipart and self-selecting tariffs, and Sibley'smethod for using self-selecting tariffs to achieve optimality. The Averch-Johnson model of howrate-of-return regulation induces inefficiencies. Analysis of regulation based on the firm's returnon Output, costs, or sales. Price-cap regulation. Regulatory treatment of uncertainty and its impacton the firm's behavior. Methods of attaining optimality without direct regulation (contestability,auctioning the monopoly franchise.)

Author:
Publisher:
ISBN:
Category : America
Languages : es
Pages : 692

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Author: Carlos N. Bouza-Herrera
Publisher:
ISBN: 9781799875567
Category : Ranking and selection (Statistics)
Languages : en
Pages : 305

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Book Description
When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research. This type of sampling is an alternative to simple random sampling and can offer substantial improvements in precision and efficient estimation. There are different methods within RSS that can be further explored and discussed. On top of being efficient, RSS is cost-efficient and can be used in situations where sample units are difficult to obtain. With new results in modeling and applications, and a growing importance in theory and practice, it is essential for modeling to be further explored and developed through research. Ranked Set Sampling Models and Methods presents an innovative look at modeling survey sampling research and new models of RSS along with the future potentials of it. The book provides a panoramic view of the state of the art of RSS by presenting some previously known and new models. The chapters illustrate how the modeling is to be developed and how they improve the efficiency of the inferences. The chapters highlight topics such as bootstrap methods, fuzzy weight ranked set sampling method, item count technique, stratified ranked set sampling, and more. This book is essential for statisticians, social and natural science scientists, physicians and all the persons involved with the use of sampling theory in their research along with practitioners, researchers, academicians, and students interested in the latest models and methods for ranked set sampling.