Download or read book Forecasting commodity prices using long short term memory neural networks written by Ly, Racine and published by Intl Food Policy Res Inst. This book was released on 2021-02-10 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper applies a recurrent neural network (RNN) method to forecast cotton and oil prices. We show how these new tools from machine learning, particularly Long-Short Term Memory (LSTM) models, complement traditional methods. Our results show that machine learning methods fit reasonably well with the data but do not outperform systematically classical methods such as Autoregressive Integrated Moving Average (ARIMA) or the naïve models in terms of out of sample forecasts. However, averaging the forecasts from the two type of models provide better results compared to either method. Compared to the ARIMA and the LSTM, the Root Mean Squared Error (RMSE) of the average forecast was 0.21 and 21.49 percent lower, respectively, for cotton. For oil, the forecast averaging does not provide improvements in terms of RMSE. We suggest using a forecast averaging method and extending our analysis to a wide range of commodity prices.
Download or read book Innovative Mobile and Internet Services in Ubiquitous Computing written by Leonard Barolli and published by Springer. This book was released on 2018-06-07 with total page 987 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research findings, methods and development techniques related to Ubiquitous and Pervasive Computing (UPC) as well as challenges and solutions from both theoretical and practical perspectives with an emphasis on innovative, mobile and internet services. With the proliferation of wireless technologies and electronic devices, there is a rapidly growing interest in Ubiquitous and Pervasive Computing (UPC). UPC makes it possible to create a human-oriented computing environment where computer chips are embedded in everyday objects and interact with physical world. It also allows users to be online even while moving around, providing them with almost permanent access to their preferred services. Along with a great potential to revolutionize our lives, UPC also poses new research challenges.
Download or read book Recurrent Neural Networks for Short Term Load Forecasting written by Filippo Maria Bianchi and published by Springer. This book was released on 2017-11-09 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series.
Download or read book Applied Soft Computing and Communication Networks written by Sabu M. Thampi and published by Springer Nature. This book was released on 2021-07-01 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes thoroughly refereed post-conference proceedings of the International Applied Soft Computing and Communication Networks (ACN 2020) held in VIT, Chennai, India, during October 14–17, 2020. The research papers presented were carefully reviewed and selected from several initial submissions. The book is directed to the researchers and scientists engaged in various fields of intelligent systems.
Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Download or read book Deep Learning written by Josh Patterson and published by "O'Reilly Media, Inc.". This book was released on 2017-07-28 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop
Download or read book Modeling and Forecasting Primary Commodity Prices written by Walter C. Labys and published by Routledge. This book was released on 2017-03-02 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.
Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.
Download or read book Neural Networks in Finance and Investing written by Robert R. Trippi and published by Irwin Professional Publishing. This book was released on 1996 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Time Series and Panel Data Econometrics written by M. Hashem Pesaran and published by Oxford University Press, USA. This book was released on 2015 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
Download or read book Information and Communication Technologies written by Jorge Herrera-Tapia and published by Springer Nature. This book was released on 2022-09-30 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the 10th Ecuadorian Conference on Information and Communication Technologies, TICEC 2022, held in Manta, Ecuador, in October 2022. The 20 full papers were carefully reviewed and selected from 150 qualified submissions. The papers cover a great variety of topics, such as wireless communication, immersive environments, artificial intelligence, data mining, neural networks, augmented reality, cyberphysical systems, telemedicine, cybersecurity, software architecture, data processing, software development, and others. The contributions are divided into the following thematic blocks: ICT ́s Applications; Data Science; Software Development.
Download or read book Proceedings of the 3rd International Conference on Smart and Innovative Agriculture ICoSIA 2022 written by Josaphat Tetuko Sri Sumantyo and published by Springer Nature. This book was released on 2023-04-16 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. Held as part of the Universitas Gadjah Mada Annual Scientific Conferences (UASC 2022) series, the 3rd International Conference on Smart and Innovative Agriculture (ICoSIA 2022) provides an ideal academic platform for researchers to present the latest research findings and describe emerging technologies and directions in agriculture. This year, the conference will take the theme “Digital transformation, technology, and its solution for agriculture” with seven symposia: Agricultural Big Data Analysis symposium; Agricultural Geography symposium; Land and Environmental Management symposium; Precision Nutrition Technology symposium; Smart and Precision Farming symposium; Smart Genetics Resource Management and Utilization symposium; and Sustainable Food Production symposium.
Download or read book Applications of Computing and Communication Technologies written by Ganesh Chandra Deka and published by Springer. This book was released on 2018-08-29 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book (CCIS 899) constitutes the refereed proceedings of the First International Conference on Applications of Computing and Communication Technologies, ICACCT 2018, held in Delhi, India, in March 2018. The 30 full papers were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on communication and system technologies, computing and network technologies, application and services.
Download or read book Time Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space
Download or read book Advances in Data Computing Communication and Security written by Pankaj Verma and published by Springer Nature. This book was released on 2022-03-28 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of high-quality peer reviewed contributions from the academicians, researchers, practitioners, and industry professionals, accepted in the International Conference on Advances in Data Computing, Communication and Security (I3CS2021) organized by the Department of Electronics and Communication Engineering in collaboration with the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India during 08-10 Sep 2021. The fast pace of advancing technologies and growing expectations of the next-generation requires that the researchers must continuously reinvent themselves through new investigations and development of the new products. The theme of this conference is devised as "Embracing Innovations" for the next-generation data computing and secure communication system.
Download or read book AI and Financial Markets written by Shigeyuki Hamori and published by MDPI. This book was released on 2020-07-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
Download or read book Technological and Industrial Applications Associated with Intelligent Logistics written by Alberto Ochoa-Zezzatti and published by Springer Nature. This book was released on 2021-09-08 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book helps the reader to identify how different organizations in the context of diverse societies deploy their resources and leverage their capabilities to achieve better performance of its various labor skills, marketing, social responsibility and management capacity. Intelligent Logistics is a complex phenomenon that has become critical for companies to reach their development locally and internationally. On the one hand, macro-factors and market structure influence in business competitiveness, but also in a regional or sector context. The internal aspects and the use of various business tools contribute to the ability to create value in an organization. It is of utmost importance to understand the relevance of crucial aspects in the technological future that should be known and implemented by the Z generation of its incidence in the use of organizational models linked to artificial intelligence. Every innovative aspect in the use of new technologies for the distribution of goods and services will be crucial in a globalized world. An avant-garde society will require improved decision-making regarding Logistics 4.0 and its implementation in our lives respecting the environment and being sustainable together with invaluable principles of generating tacit knowledge for future generations.
