Rats Handbook To Accompany Introductory Econometrics For Finance

Written to complement the second edition of best-selling textbook Introductory Econometrics for Finance, this book provides a comprehensive introduction to the use of the Regression Analysis of Time Series (RATS) software for modelling in finance and beyond. It provides numerous worked examples with carefully annotated code and detailed explanations of the outputs, giving readers the knowledge and confidence to use the software for their own research and to interpret their own results. A wide variety of important modelling approaches are covered, including such topics as time-series analysis and forecasting, volatility modelling, limited dependent variable and panel methods, switching models and simulations methods. The book is supported by an accompanying website containing freely downloadable data and RATS instructions.

This best-selling introduction to econometrics is specifically written for finance students. The new edition builds on the successful data- and problem-driven approach of the first edition, giving students the skills to estimate and interpret models while developing an intuitive grasp of underlying theoretical concepts.

This free software guide for R with freely downloadable datasets brings the econometric techniques to life, showing readers how to implement the approaches presented in Introductory Econometrics for Finance using this highly popular software package. Designed to be used alongside the main textbook, the guide will give readers the confidence and skills to estimate and interpret their own models while the textbook will ensure that they have a thorough understanding of the conceptual underpinnings.

A workbook/disk on performing estimations with RATS 4.0 or later, with overviews of topics in time-series analysis; discussion of RATS instructions and procedures relevant to each topic; sample programs; discussion of output; and exercises. After an introduction to RATS, topics include stationary time-series; modeling volatility; and cointegration and error correction. For students in statistical analysis. The accompanying disk contains data sets for estimations described in the text. No index. Annotation copyright by Book News, Inc., Portland, OR

This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations, this uncertainty has to be taken into account. In the past, most related research results were based on using traditional techniques from probability and statistics, such as p-value-based hypothesis testing. These techniques led to numerous successful applications, but in the last decades, several examples have emerged showing that these techniques often lead to unreliable and inaccurate predictions. It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques. This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.

This proceedings volume presents the latest trends in innovative business development theory and practice from a global, interdisciplinary perspective. Featuring selected contributions from the 25th International Economic Conference Sibiu (IECS 2018) held in Sibiu, Romania, it explores various topics in the areas of economics, business, finance and accounting, including tourism, marketing and Islamic banking and finance. Written by researchers from different regions and sectors around the world, it offers significant insights into the emerging shifts that characterize the fields of innovative economics and global development, innovative business practices, as well as innovative finance and banking, and provides organizations, managers and policy makers with new reliable solutions and opportunities for innovative development and growth within and between organizations around the globe.

As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.

This book presents papers from the 11th Sustainable Education and Development Research Conference on the theme: "Build Resilient Infrastructure, Promote Inclusive and Sustainable Industrialization, and Foster Innovation." Papers related to the sub-themes were presented: i. Develop quality, reliable, sustainable, and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all. ii. Promote inclusive and sustainable industrialization and, by 2030, significantly raise industry's share of employment and gross domestic product, in line with national circumstances, and double its share in the least developed countries. iii. Increase the access of small-scale industrial and other enterprises, in particular in developing countries, to financial services, including affordable credit, and their integration into value chains and markets. iv. By 2030, upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes, with all countries taking action in accordance with their respective capabilities. v. Enhance scientific research and upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries, including, by 2030, encouraging innovation and substantially increasing productivity. SEDRC gathers papers that explain how key education on the Sustainable Development Goals is transforming lives, eradicating poverty, professing solutions to the infrastructural deficit in Africa, and providing innovative ways to provide affordable housing in Africa. This book will be of interest to academics, postgraduate students, and industry professionals.