Neural Networks In Finance

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Neural Networks in Finance

Paul D. McNelis
Neural Networks in Finance Book PDF

Author : Paul D. McNelis
Publisher : Academic Press
Page : 262 pages
File Size : 53,5 Mb
Release : 2005-01-05
Category : Business & Economics
ISBN : 9780124859678

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Neural Networks in Finance by Paul D. McNelis Pdf

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

Artificial Neural Networks in Finance and Manufacturing

Kamruzzaman, Joarder,Begg, Rezaul,Sarker, Ruhul
Artificial Neural Networks in Finance and Manufacturing Book PDF

Author : Kamruzzaman, Joarder,Begg, Rezaul,Sarker, Ruhul
Publisher : IGI Global
Page : 299 pages
File Size : 41,6 Mb
Release : 2006-03-31
Category : Computers
ISBN : 9781591406723

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Artificial Neural Networks in Finance and Manufacturing by Kamruzzaman, Joarder,Begg, Rezaul,Sarker, Ruhul Pdf

"This book presents a variety of practical applications of neural networks in two important domains of economic activity: finance and manufacturing"--Provided by publisher.

Neural Networks in Finance and Investing

Robert R. Trippi,Efraim Turban
Neural Networks in Finance and Investing Book PDF

Author : Robert R. Trippi,Efraim Turban
Publisher : Irwin Professional Publishing
Page : 872 pages
File Size : 48,9 Mb
Release : 1996
Category : Artificial intelligence
ISBN : UCSD:31822025890054

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Neural Networks in Finance and Investing by Robert R. Trippi,Efraim Turban Pdf

This completely updated version of the classic first edition offers a wealth of new material reflecting the latest developments in teh field. For investment professionals seeking to maximize this exciting new technology, this handbook is the definitive information source.

Machine Learning in Finance

Matthew F. Dixon,Igor Halperin,Paul Bilokon
Machine Learning in Finance Book PDF

Author : Matthew F. Dixon,Igor Halperin,Paul Bilokon
Publisher : Springer Nature
Page : 565 pages
File Size : 44,9 Mb
Release : 2020-07-01
Category : Business & Economics
ISBN : 9783030410681

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Machine Learning in Finance by Matthew F. Dixon,Igor Halperin,Paul Bilokon Pdf

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.

Neural Networks in Finance

Paul D. McNelis
Neural Networks in Finance Book PDF

Author : Paul D. McNelis
Publisher : Elsevier
Page : 256 pages
File Size : 40,8 Mb
Release : 2005-01-20
Category : Computers
ISBN : 9780080479651

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Neural Networks in Finance by Paul D. McNelis Pdf

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

Financial Prediction Using Neural Networks

Joseph S. Zirilli
Financial Prediction Using Neural Networks Book PDF

Author : Joseph S. Zirilli
Publisher : Unknown
Page : 168 pages
File Size : 40,8 Mb
Release : 1997
Category : Business & Economics
ISBN : UOM:39015041905558

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Financial Prediction Using Neural Networks by Joseph S. Zirilli Pdf

Focusing on approaches to performing trend analysis through the use of neural nets, this book comparess the results of experiments on various types of markets, and includes a review of current work in the area. It appeals to students in both neural computing and finance as well as to financial analysts and academic and professional researchers in the field of neural network applications.

Neural Network Time Series

E. Michael Azoff
Neural Network Time Series Book PDF

Author : E. Michael Azoff
Publisher : Unknown
Page : 224 pages
File Size : 44,9 Mb
Release : 1994-09-27
Category : Business & Economics
ISBN : UOM:39076001958839

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Neural Network Time Series by E. Michael Azoff Pdf

Comprehensively specified benchmarks are provided (including weight values), drawn from time series examples in chaos theory and financial futures. The book covers data preprocessing, random walk theory, trading systems and risk analysis. It also provides a literature review, a tutorial on backpropagation, and a chapter on further reading and software.

Neural Networks and the Financial Markets

Jimmy Shadbolt
Neural Networks and the Financial Markets Book PDF

Author : Jimmy Shadbolt
Publisher : Springer Science & Business Media
Page : 273 pages
File Size : 45,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447101512

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Neural Networks and the Financial Markets by Jimmy Shadbolt Pdf

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.

Biologically Inspired Algorithms for Financial Modelling

Anthony Brabazon,Michael O'Neill
Biologically Inspired Algorithms for Financial Modelling Book PDF

Author : Anthony Brabazon,Michael O'Neill
Publisher : Springer Science & Business Media
Page : 276 pages
File Size : 42,9 Mb
Release : 2006-03-28
Category : Computers
ISBN : 9783540313076

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Biologically Inspired Algorithms for Financial Modelling by Anthony Brabazon,Michael O'Neill Pdf

Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures. The book was written for those in the finance community who want to apply BIAs in financial modelling, and for computer scientists who want an introduction to this growing application domain.

Advances in Financial Machine Learning

Marcos Lopez de Prado
Advances in Financial Machine Learning Book PDF

Author : Marcos Lopez de Prado
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 42,6 Mb
Release : 2018-01-23
Category : Business & Economics
ISBN : 9781119482116

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Advances in Financial Machine Learning by Marcos Lopez de Prado Pdf

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Artificial Intelligence in Finance

Yves Hilpisch
Artificial Intelligence in Finance Book PDF

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 478 pages
File Size : 53,5 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055389

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Artificial Intelligence in Finance by Yves Hilpisch Pdf

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Data Mining in Finance

Boris Kovalerchuk,Evgenii Vityaev
Data Mining in Finance Book PDF

Author : Boris Kovalerchuk,Evgenii Vityaev
Publisher : Springer Science & Business Media
Page : 308 pages
File Size : 42,5 Mb
Release : 2006-04-18
Category : Computers
ISBN : 9780306470189

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Data Mining in Finance by Boris Kovalerchuk,Evgenii Vityaev Pdf

Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book focuses specifically on relational data mining (RDM), which is a learning method able to learn more expressive rules than other symbolic approaches. RDM is thus better suited for financial mining, because it is able to make greater use of underlying domain knowledge. Relational data mining also has a better ability to explain the discovered rules - an ability critical for avoiding spurious patterns which inevitably arise when the number of variables examined is very large. The earlier algorithms for relational data mining, also known as inductive logic programming (ILP), suffer from a relative computational inefficiency and have rather limited tools for processing numerical data. Data Mining in Finance introduces a new approach, combining relational data mining with the analysis of statistical significance of discovered rules. This reduces the search space and speeds up the algorithms. The book also presents interactive and fuzzy-logic tools for `mining' the knowledge from the experts, further reducing the search space. Data Mining in Finance contains a number of practical examples of forecasting S&P 500, exchange rates, stock directions, and rating stocks for portfolio, allowing interested readers to start building their own models. This book is an excellent reference for researchers and professionals in the fields of artificial intelligence, machine learning, data mining, knowledge discovery, and applied mathematics.

Artificial Intelligence in Asset Management

Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Artificial Intelligence in Asset Management Book PDF

Author : Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Publisher : CFA Institute Research Foundation
Page : 95 pages
File Size : 50,5 Mb
Release : 2020-08-28
Category : Business & Economics
ISBN : 9781952927034

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Artificial Intelligence in Asset Management by Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari Pdf

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Neural Network Solutions for Trading in Financial Markets

Dirk Emma Baestaens,Willem Max van den Bergh,Douglas Wood
Neural Network Solutions for Trading in Financial Markets Book PDF

Author : Dirk Emma Baestaens,Willem Max van den Bergh,Douglas Wood
Publisher : Pitman Publishing
Page : 274 pages
File Size : 50,9 Mb
Release : 1994
Category : Neural networks (Computer science)
ISBN : CORNELL:31924075313316

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Neural Network Solutions for Trading in Financial Markets by Dirk Emma Baestaens,Willem Max van den Bergh,Douglas Wood Pdf

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.

Neural Networks for Economic and Financial Modelling

Andrea Beltratti,Sergio Margarita,Pietro Terna
Neural Networks for Economic and Financial Modelling Book PDF

Author : Andrea Beltratti,Sergio Margarita,Pietro Terna
Publisher : Unknown
Page : 314 pages
File Size : 52,8 Mb
Release : 1996
Category : Computers
ISBN : STANFORD:36105018465802

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Neural Networks for Economic and Financial Modelling by Andrea Beltratti,Sergio Margarita,Pietro Terna Pdf

The field of economics and finance is one of the few areas where the need for neural network applications is increasing. This book investigates the use of neural networks in developing real-world applications to help economists and financial strategists predict the movement of the markets.