Neural Network Solutions For Trading In Financial Markets
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Neural Network Solutions For Trading In Financial Markets
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Author : Dirk Emma Baestaens
language : en
Publisher: Pitman Publishing
Release Date : 1994
Neural Network Solutions For Trading In Financial Markets written by Dirk Emma Baestaens and has been published by Pitman Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Business & Economics categories.
Offers an alternative technique in forecasting to the traditional techniques used in trading and dealing. The book explains the shortcomings of traditional techniques and shows how neural networks overcome many of the disadvantages of these traditional systems.
Artificial Intelligence In Financial Markets
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Author : Christian L. Dunis
language : en
Publisher: Springer
Release Date : 2016-11-21
Artificial Intelligence In Financial Markets written by Christian L. Dunis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Business & Economics categories.
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Neural Networks And The Financial Markets
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Author : Jimmy Shadbolt
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Networks And The Financial Markets written by Jimmy Shadbolt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.
Ai In The Financial Markets
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Author : Federico Cecconi
language : en
Publisher: Springer Nature
Release Date : 2023-03-24
Ai In The Financial Markets written by Federico Cecconi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-24 with Computers categories.
This book is divided into two parts, the first of which describes AI as we know it today, in particular the Fintech-related applications. In turn, the second part explores AI models in financial markets: both regarding applications that are already available (e.g. the blockchain supply chain, learning through big data, understanding natural language, or the valuation of complex bonds) and more futuristic solutions (e.g. models based on artificial agents that interact by buying and selling stocks within simulated worlds). The effects of the COVID-19 pandemic are starting to show their financial effects: more companies in a liquidity crisis; more unstable debt positions; and more loans from international institutions for states and large companies. At the same time, we are witnessing a growth of AI technologies in all fields, from the production of goods and services, to the management of socio-economic infrastructures: in medicine, communications, education, and security. The question then becomes: could we imagine integrating AI technologies into the financial markets, in order to improve their performance? And not just limited to using AI to improve performance in high-frequency trading or in the study of trends. Could we imagine AI technologies that make financial markets safer, more stable, and more comprehensible? The book explores these questions, pursuing an approach closely linked to real-world applications. The book is intended for three main categories of readers: (1) management-level employees of companies operating in the financial markets, banks, insurance operators, portfolio managers, brokers, risk assessors, investment managers, and debt managers; (2) policymakers and regulators for financial markets, from government technicians to politicians; and (3) readers curious about technology, both for professional and private purposes, as well as those involved in innovation and research in the private and public spheres.
Virtual Trading
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Author : Robert Arnold Klein
language : en
Publisher: Irwin Professional Publishing
Release Date : 1995
Virtual Trading written by Robert Arnold Klein and has been published by Irwin Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business & Economics categories.
In plain language, Virtual Trading, shows you how to proceed from data collection to system development to actual trading. For traders who want to stay on the cutting edge of market technology, Virtual Trading is a must read. Featuring contributions from the leading experts in the field, Virtual Trading provides in-depth information on every important aspect of artificial intelligence in trading. Highlights include: Synergistic market analysis using neural networks by Lou Mendelsohn; Developing a market-timing system using genetic algorithms by Casimir Klimasauskas; Neural networkds and stock market valuation by John Keal; Applying chaos theory to a neural network by Joseph Shepard; Developing a trading system that uses Al by Mark Jurik; Neural network techniques for time series analysis by Peter Davies.
Artificial Neural Networks
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Author : Ali Roghani
language : en
Publisher: CreateSpace
Release Date : 2015-04-17
Artificial Neural Networks written by Ali Roghani and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-17 with categories.
Neural networks are state-of-the-art, trainable algorithms that emulate certain major aspects in the functioning of the human brain. This gives them a unique, self-training ability, the ability to formalize unclassified information and, most importantly, the ability to make forecasts based on the historical information they have at their disposal. Neural networks have been used increasingly in a variety of business applications, including forecasting and marketing research solutions. In some areas, such as fraud detection or risk assessment, they are the indisputable leaders. The major fields in which neural networks have found application are financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks can be applied gainfully by all kinds of traders, so if you're a trader and you haven't yet been introduced to neural networks, we'll take you through this method of technical analysis and show you how to apply it to your trading style. Neural networks have been touted as all-powerful tools in stock-market prediction. Companies such as MJ Futures claim amazing 199.2% returns over a 2-year period using their neural network prediction methods. They also claim great ease of use; as technical editor John Sweeney said in a 1995 issue of "Technical Analysis of Stocks and Commodities," "you can skip developing complex rules (and redeveloping them as their effectiveness fades) . . . just define the price series and indicators you want to use, and the neural network does the rest."
Computational Intelligence Techniques For Trading And Investment
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Author : Christian Dunis
language : en
Publisher: Routledge
Release Date : 2014-03-26
Computational Intelligence Techniques For Trading And Investment written by Christian Dunis and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-26 with Business & Economics categories.
Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment. The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading. This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.
Neural Networks In Finance
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Author : Paul D. McNelis
language : en
Publisher: Academic Press
Release Date : 2005-01-05
Neural Networks In Finance written by Paul D. McNelis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-05 with Business & Economics categories.
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website
Developing An Effective Model For Detecting Trade Based Market Manipulation
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Author : Jose Joy Thoppan
language : en
Publisher: Emerald Group Publishing
Release Date : 2021-05-05
Developing An Effective Model For Detecting Trade Based Market Manipulation written by Jose Joy Thoppan and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-05 with Business & Economics categories.
Developing an Effective Model for Detecting Trade-Based Market Manipulation determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.
Artificial Neural Networks
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Author : Ali Roghani
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016-08-09
Artificial Neural Networks written by Ali Roghani and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-09 with categories.
Neural networks are state-of-the-art, trainable algorithms that emulate certain major aspects in the functioning of the human brain. This gives them a unique, self-training ability, the ability to formalize unclassified information and, most importantly, the ability to make forecasts based on the historical information they have at their disposal. Neural networks have been used increasingly in a variety of business applications, including forecasting and marketing research solutions. In some areas, such as fraud detection or risk assessment, they are the indisputable leaders. The major fields in which neural networks have found application are financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks can be applied gainfully by all kinds of traders, so if you're a trader and you haven't yet been introduced to neural networks, we'll take you through this method of technical analysis and show you how to apply it to your trading style. Neural networks have been touted as all-powerful tools in stock-market prediction. Companies such as MJ Futures claim amazing 199.2% returns over a 2-year period using their neural network prediction methods. They also claim great ease of use; as technical editor John Sweeney said in a 1995 issue of "Technical Analysis of Stocks and Commodities," "you can skip developing complex rules (and redeveloping them as their effectiveness fades) . . . just define the price series and indicators you want to use, and the neural network does the rest."