Download or read book An Algorithmic Crystal Ball Forecasts based on Machine Learning written by Jin-Kyu Jung and published by International Monetary Fund. This book was released on 2018-11-01 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting macroeconomic variables is key to developing a view on a country's economic outlook. Most traditional forecasting models rely on fitting data to a pre-specified relationship between input and output variables, thereby assuming a specific functional and stochastic process underlying that process. We pursue a new approach to forecasting by employing a number of machine learning algorithms, a method that is data driven, and imposing limited restrictions on the nature of the true relationship between input and output variables. We apply the Elastic Net, SuperLearner, and Recurring Neural Network algorithms on macro data of seven, broadly representative, advanced and emerging economies and find that these algorithms can outperform traditional statistical models, thereby offering a relevant addition to the field of economic forecasting.
Download or read book Deus ex Machina A Framework for Macro Forecasting with Machine Learning written by Marijn A. Bolhuis and published by International Monetary Fund. This book was released on 2020-02-28 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast errors than traditional models. By combining multiple machine learning models into ensembles, we lower forecast errors even further. We also identify measures of variable importance to help improve the transparency of machine learning-based forecasts. Applying the framework to Turkey reduces forecast errors by at least 30 percent relative to traditional models. The framework also better predicts economic volatility, suggesting that machine learning techniques could be an important part of the macro forecasting toolkit of many countries.
Download or read book Overfitting in Judgment based Economic Forecasts The Case of IMF Growth Projections written by Klaus-Peter Hellwig and published by International Monetary Fund. This book was released on 2018-12-07 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: I regress real GDP growth rates on the IMF’s growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I identify several such variables that explain forecasts well but are not predictors of actual growth. I show that, at long horizons, IMF forecasts are little better than a forecasting rule that uses no information other than the historical global sample average growth rate (i.e., a constant). Given the large noise component in forecasts, particularly at longer horizons, the paper calls into question the usefulness of judgment-based medium and long-run forecasts for policy analysis, including for debt sustainability assessments, and points to statistical methods to improve forecast accuracy by taking into account the risk of overfitting.
Download or read book Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems written by Mohammed A. Al-Sharafi and published by Springer Nature. This book was released on 2022-12-12 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sheds light on the recent research directions in intelligent systems and their applications. It involves four main themes: artificial intelligence and data science, recent trends in software engineering, emerging technologies in education, and intelligent health informatics. The discussion of the most recent designs, advancements, and modifications of intelligent systems, as well as their applications, is a key component of the chapters contributed to the aforementioned subjects.
Download or read book Integrated Uncertainty in Knowledge Modelling and Decision Making written by Van-Nam Huynh and published by Springer Nature. This book was released on 2023-10-26 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.
Download or read book International Conference on Advanced Intelligent Systems for Sustainable Development written by Janusz Kacprzyk and published by Springer Nature. This book was released on 2023-06-09 with total page 995 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the potential contributions of emerging technologies in different fields as well as the opportunities and challenges related to the integration of these technologies in the socio-economic sector. In this book, many latest technologies are addressed, particularly in the fields of computer science and engineering. The expected scientific papers covered state-of-the-art technologies, theoretical concepts, standards, product implementation, ongoing research projects, and innovative applications of Sustainable Development. This new technology highlights, the guiding principle of innovation for harnessing frontier technologies and taking full profit from the current technological revolution to reduce gaps that hold back truly inclusive and sustainable development. The fundamental and specific topics are Big Data Analytics, Wireless sensors, IoT, Geospatial technology, Engineering and Mechanization, Modeling Tools, Risk analytics, and preventive systems.
Download or read book Internet Science written by Samira El Yacoubi and published by Springer Nature. This book was released on 2019-11-25 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 6th International Conference on Internet Science held in Perpignan, France, in December 2019. The 30 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers detail a multidisciplinary understanding of the development of the Internet as a societal and technological artefact which increasingly evolves with human societies.
Download or read book Forecasting with Artificial Intelligence written by Mohsen Hamoudia and published by Springer Nature. This book was released on 2023-10-22 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field. The book contains fourteen chapters covering a wide range of topics, including the concept of AI, its impact on economic decision-making, traditional and machine learning-based forecasting methods, challenges in demand forecasting, global forecasting models, meta-learning and feature-based forecasting, ensembling, deep learning, scalability in industrial and optimization applications, and forecasting performance evaluation. With key illustrations, state-of-the-art implementations, best practices, and notable advances, this book offers practical insights into the theory and practice of AI-based forecasting. This book is a valuable resource for anyone involved in forecasting, including forecasters, statisticians, data scientists, business analysts, or decision-makers.
Download or read book Searching for a Crystal Ball written by Michael Dardia and published by . This book was released on 2001 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improving Accuracy Without Losing Interpretability written by Yiqi Sun and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In time series forecasting, decomposition-based algorithms break aggregate data into meaningful components and are therefore appreciated for their particular advantages in interpretability. Recent algorithms often combine machine learning (hereafter ML) methodology with decomposition to improve prediction accuracy. However, incorporating ML is generally considered to sacrifice interpretability inevitably. In addition, existing hybrid algorithms usually rely on theoretical models with statistical assumptions and focus only on the accuracy of aggregate predictions, and thus suffer from accuracy problems, especially in component estimates. In response to the above issues, this research explores the possibility of improving accuracy without losing interpretability in time series forecasting. We first quantitatively define interpretability for data-driven forecasts and systematically review the existing forecasting algorithms from the perspective of interpretability. Accordingly, we propose the W-R algorithm, a hybrid algorithm that combines decomposition and ML from a novel perspective. Specifically, the W-R algorithm uses ML to modify the estimates of all components simultaneously, while other algorithms predict the components only by individual ML modules. We mathematically analyze the theoretical basis of the algorithm and validate its performance through extensive numerical experiments. In general, the W-R algorithm outperforms all decomposition-based and ML benchmarks. Based on P50_QL, a common evaluation indicator for quantile prediction, the algorithm relatively improves by 8.76% in accuracy on the practical sales forecasts of JD.com and 77.99% on a public dataset of electricity loads. This research offers an innovative perspective to combine the statistical and ML algorithms, and JD.com has implemented the W-R algorithm to make accurate sales predictions and guide its marketing activities.
Download or read book Time Series Prediction and Applications written by Amit Konar and published by Springer. This book was released on 2017-03-25 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.
Download or read book The Crystal Ball Instruction Manual Volume One written by Stephen Davies and published by . This book was released on 2021-03-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
Download or read book Graphcore written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on with total page 81 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the power of next-generation weather forecasting with Graphcore's cutting-edge technology. Our AI-powered solutions leverage the latest advancements in machine learning and the revolutionary Intelligence Processing Unit (IPU) to deliver unprecedented accuracy, speed, and granularity in weather predictions. Move beyond traditional forecasting methods limited by point-to-point analysis. Graphcore's technology empowers meteorologists to identify hidden relationships within weather data, leading to a more comprehensive understanding of atmospheric behavior. This holistic approach enables the creation of highly accurate forecasts, from days to weeks in advance, allowing businesses and individuals to make informed decisions and proactively prepare for weather events.
Download or read book Artificial Intelligence in Forecasting written by Sachi Nandan Mohanty and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Importance of forecasting is to deal with the uncertainty of the future. An accurate Forecasting should be timely available, accurate, reliable and compatible with existing database. Accurate projection of the future is highly demanding for supply chain management, inventory control, economic condition, technology, growth trend, social change, political change, business, weather forecasting, stock price prediction, earth quake prediction and many more. In this direction AI powered tools and techniques of forecasting plays a major role to improve the projection accuracy. AI powered forecasting software uses machine learning techniques to improve accuracy. The software can analyse the past data and can make better prediction about the future trends with higher accuracy and confidence that favours for making proper future planning and decision. Moreover, AI forecasting tools are better in a sense that it can gradually improve its accuracy. In other words, accurate forecasting requires more than just the fitting of models to historical data. Inside, readers will find the latest techniques used by managers in business today, discover the importance of forecasting and learn how it's accomplished. And readers will develop the necessary skills to meet the increased demand for thoughtful and realistic forecasts"--
Download or read book Long range Forecasting from Crystal Ball to Computer written by Georgii Ivanovich Petrashen and published by . This book was released on 1978 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Completing the Market Generating Shadow CDS Spreads by Machine Learning written by Nan Hu and published by International Monetary Fund. This book was released on 2019-12-27 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms’ accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.
