Computational Intelligence Techniques For Trading And Investment
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Author | : Christian Dunis |
Publisher | : Routledge |
Total Pages | : 239 |
Release | : 2014-03-26 |
Genre | : Business & Economics |
ISBN | : 1136195114 |
Download Computational Intelligence Techniques for Trading and Investment Book in PDF, Epub and Kindle
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.
Author | : Christian Dunis |
Publisher | : Routledge |
Total Pages | : 236 |
Release | : 2014-03-26 |
Genre | : Business & Economics |
ISBN | : 1136195106 |
Download Computational Intelligence Techniques for Trading and Investment Book in PDF, Epub and Kindle
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.
Author | : Christian L. Dunis |
Publisher | : Springer |
Total Pages | : 349 |
Release | : 2016-11-21 |
Genre | : Business & Economics |
ISBN | : 1137488808 |
Download Artificial Intelligence in Financial Markets Book in PDF, Epub and Kindle
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.
Author | : Paul P. Wang |
Publisher | : Springer Science & Business Media |
Total Pages | : 232 |
Release | : 2007-07-11 |
Genre | : Computers |
ISBN | : 354072821X |
Download Computational Intelligence in Economics and Finance Book in PDF, Epub and Kindle
Readers will find, in this highly relevant and groundbreaking book, research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Author | : Ondrej Martinsky |
Publisher | : Harriman House Limited |
Total Pages | : 212 |
Release | : 2010-02-15 |
Genre | : Business & Economics |
ISBN | : 1906659532 |
Download Intelligent Trading Systems Book in PDF, Epub and Kindle
This work deals with the issue of problematic market price prediction in the context of crowd behavior. "Intelligent Trading Systems" describes technical analysis methods used to predict price movements.
Author | : Simão Moraes Sarmento |
Publisher | : Springer Nature |
Total Pages | : 108 |
Release | : 2020-07-13 |
Genre | : Technology & Engineering |
ISBN | : 3030472515 |
Download A Machine Learning based Pairs Trading Investment Strategy Book in PDF, Epub and Kindle
This book investigates the application of promising machine learning techniques to address two problems: (i) how to find profitable pairs while constraining the search space and (ii) how to avoid long decline periods due to prolonged divergent pairs. It also proposes the integration of an unsupervised learning algorithm, OPTICS, to handle problem (i), and demonstrates that the suggested technique can outperform the common pairs search methods, achieving an average portfolio Sharpe ratio of 3.79, in comparison to 3.58 and 2.59 obtained using standard approaches. For problem (ii), the authors introduce a forecasting-based trading model capable of reducing the periods of portfolio decline by 75%. However, this comes at the expense of decreasing overall profitability. The authors also test the proposed strategy using an ARMA model, an LSTM and an LSTM encoder-decoder.
Author | : Qingquan Tony Zhang |
Publisher | : Springer Nature |
Total Pages | : 340 |
Release | : 2022-10-31 |
Genre | : Business & Economics |
ISBN | : 3031116127 |
Download Alternative Data and Artificial Intelligence Techniques Book in PDF, Epub and Kindle
This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.
Author | : Cris Doloc |
Publisher | : John Wiley & Sons |
Total Pages | : 304 |
Release | : 2019-10-29 |
Genre | : Business & Economics |
ISBN | : 1119550505 |
Download Applications of Computational Intelligence in Data-Driven Trading Book in PDF, Epub and Kindle
“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
Author | : Henry E Parkins |
Publisher | : Independently Published |
Total Pages | : 0 |
Release | : 2024-03-26 |
Genre | : Business & Economics |
ISBN | : |
Download AI in Stock Trading Book in PDF, Epub and Kindle
Unveil the Secrets of Profitable Trading with "AI in Stock Trading: The Secrets of Automated Investment Strategies"! Are you ready to unlock the power of artificial intelligence and revolutionize your approach to stock trading? Look no further than "AI in Stock Trading: The Secrets of Automated Investment Strategies." Dive into this comprehensive guide and embark on a transformative journey through the dynamic world of automated investment strategies. Discover the hidden secrets that top traders and hedge funds use to gain a competitive edge in today's fast-paced financial markets. From understanding the fundamentals of stock trading to mastering advanced AI algorithms, this book is your ultimate roadmap to success in the world of automated investing. Inside, you'll explore: Cutting-edge AI techniques: Learn how to harness the latest advancements in artificial intelligence, machine learning, and deep learning to develop powerful trading algorithms that outperform the competition. Data-driven strategies: Unlock the secrets of data preprocessing, feature engineering, and model optimization to extract actionable insights from financial data and make informed trading decisions. Practical applications: Dive into real-world case studies and examples that demonstrate how AI-driven trading systems can generate alpha, manage risk, and maximize returns in diverse market conditions. Ethical considerations: Navigate the ethical and regulatory challenges of AI in finance with confidence, ensuring compliance with industry standards and maintaining trust with investors. Whether you're a seasoned trader looking to enhance your strategies or a novice investor seeking to break into the world of automated trading, "AI in Stock Trading: The Secrets of Automated Investment Strategies" is your essential companion. Packed with actionable insights, expert advice, and proven techniques, this book is your key to unlocking the secrets of profitable trading in today's digital age. Don't miss out on this opportunity to transform your trading journey and take your investment strategies to new heights. Order your copy of "AI in Stock Trading: The Secrets of Automated Investment Strategies" today and embark on a path to financial success like never before!
Author | : Michael Doumpos |
Publisher | : Springer Science & Business Media |
Total Pages | : 336 |
Release | : 2012-07-23 |
Genre | : Business & Economics |
ISBN | : 1461437733 |
Download Financial Decision Making Using Computational Intelligence Book in PDF, Epub and Kindle
The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.