This book provides an updated, concise summary of forecasting air travel demand methodology. It looks at air travel demand forecasting research and attempts to outline the whole intellectual landscape of demand forecasting. It helps readers to understand the basic idea of TEI@I methodology used in forecasting air travel demand and how it is used in developing air travel demand forecasting methods. The book also discusses what to do when facing different forecasting problems making it a useful reference for business practitioners in the industry.
This book provides insights into China’s energy consumption and pollution as well as its energy saving policies. It explores energy saving ways and argues for an energy consumption revolution, which includes technologies to improve transportation resource efficiency, modification of existing transportation infrastructure and structure. This book uses various analytical models to study the relationships within the transportation system. It also includes comparative analysis of China, Japan, the US and developing countries on traffic demand and transportation energy consumption. This book highlights the urgent need to review China’s current transportation policies in order to secure a breakthrough in energy saving and emissions reduction.
With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.
This book helps to solve the problem of substantial waste and inefficiency in port production by analyzing operational efficiency at more than 30 Chinese and Korean leading container ports using three types of DEA model. In addition it offers a returns-to-scale analysis, which is particularly useful for port managers or policy makers deciding on the scale of production. The results provide port managers and relevant scholars with insights into resource allocation and operating performance optimization. This book was supported by the National Science and Technology Academic Publications Fund of China in 2015.
Candlestick charts are often used in speculative markets to describe and forecast asset price movements. This book is the first of its kind to investigate candlestick charts and their statistical properties. It provides an empirical evaluation of candlestick forecasting. The book proposes a novel technique to obtain the statistical properties of candlestick charts. The technique, which is known as the range decomposition technique, shows how security price is approximately logged into two ranges, i.e. technical range and Parkinson range. Through decomposition-based modeling techniques and empirical datasets, the book investigates the power of, and establishes the statistical foundation of, candlestick forecasting.
This book studies the information spillover among financial markets and explores the intraday effect and ACD models with high frequency data. This book also contributes theoretically by providing a new statistical methodology with comparative advantages for analyzing comovements between two time series. It explores this new method by testing the information spillover between the Chinese stock market and the international market, futures market and spot market. Using the high frequency data, this book investigates the intraday effect and examines which type of ACD model is particularly suited in capturing financial duration dynamics. The book will be of invaluable use to scholars and graduate students interested in comovements among different financial markets and financial market microstructure and to investors and regulation departments looking to improve their risk management.
This book is a comparative study of the critical factors in berth productivity in Chinese and South Korean container terminals. It first defines the concept of berth productivity, and then establishes a regression model to evaluate the productivity factor. With the results obtained for the leading Asian container terminals it identifies the relationship between critical factors for berth productivity and their order of importance. The findings provide guidelines for terminal operators to improve berth productivity.
With the internationalization of Renminbi (RMB), the gradual liberalization of China's capital account and the recent reform of the RMB pricing mechanism, the RMB exchange rate has been volatile. This book examines how we can forecast exchange rate reliably. It explains how we can do so through a new methodology for exchange rate forecasting. The book also analyzes the dynamic relationship between exchange rate and the exchange rate data decomposition and integration, the domestic economic situation, the international economic situation and the public’s expectations and how these interactions would affect the exchange rate. The book also explains why this comprehensive integrated approach is the best model for optimizing accuracy in exchange rate forecasting.
This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges.
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
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