Author: Jörg SommerPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
An Artificial Stock Market: Asset Pricing and Endogenous Expectations Using Neural Nets
Author: Jörg SommerAsset Pricing Under Endogenous Expectations in an Artificial Stock Market
Author: Asset Pricing Under Endogenous Expectations in an Artificial Stock Market
Author: Asset Pricing Under Endogenous Expectations in an Artificial Stock Market
Author: Artificial Higher Order Neural Networks for Economics and Business
Author: Zhang, MingPublisher: IGI Global
ISBN: 1599048981
Category : Computers
Languages : en
Pages : 542
Book Description
"This book is the first book to provide opportunities for millions working in economics, accounting, finance and other business areas education on HONNs, the ease of their usage, and directions on how to obtain more accurate application results. It provides significant, informative advancements in the subject and introduces the HONN group models and adaptive HONNs"--Provided by publisher.
Information Computing And Automation (In 3 Volumes) - Proceedings Of The International Conference
Author: Jian Ping LiPublisher: World Scientific
ISBN: 9814471380
Category : Computers
Languages : en
Pages : 1645
Book Description
Wavelet analysis and its applications have become one of the fastest growing research areas in the past several years. Wavelet theory has been employed in many fields and applications, such as signal and image processing, communication systems, biomedical imaging, radar, air acoustics, and endless other areas. Active media technology is concerned with the development of autonomous computational or physical entities capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic environment.This book consists of carefully selected and received papers presented at the conference, and is an attempt to capture the essence of the current state-of-the-art in wavelet analysis and active media technology. Invited papers included in this proceedings includes contributions from Prof P Zhang, T D Bui, and C Y Suen from Concordia University, Canada; Prof N A Strelkov and V L Dol'nikov from Yaroslavl State University, Russia; Prof Chin-Chen Chang and Ching-Yun Chang from Taiwan; Prof S S Pandey from R D University, India; and Prof I L Bloshanskii from Moscow State Regional University, Russia.
Machine Learning in Asset Pricing
Author: Stefan NagelPublisher: Princeton University Press
ISBN: 0691218706
Category : Business & Economics
Languages : en
Pages : 156
Book Description
A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network
Author: Joish BoscoPublisher: GRIN Verlag
ISBN: 3668800456
Category : Computers
Languages : en
Pages : 82
Book Description
Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.
Zeitreihenanalyse in der empirischen Wirtschaftsforschung
Author: Rainer MetzPublisher: Lucius & Lucius DE
ISBN: 9783828202443
Category : Econometrics
Languages : en
Pages : 264
Book Description
Transactions on Computational Collective Intelligence VI
Author: Ngoc-Thanh NguyenPublisher: Springer
ISBN: 3642293565
Category : Computers
Languages : en
Pages : 232
Book Description
The LNCS journal Transactions on Computational Collective Intelligence (TCCI) focuses on all facets of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This, the sixth issue of Transactions on Computational Collective Intelligence contains 10 selected papers, focusing on the topics of classification, agent cooperation, paraconsistent reasoning and agent distributed mobile interaction.