Jun Chen

This book is concerned with the historical fact of overseas Chinese and ethnic Chinese living in Myanmar, Thailand, Vietnam and Laos before 1949. Against the social background of acute class and ethnic conflicts in Yunnan in modern times, many Chinese people had immigrated. The immigration of overseas Chinese of Yunnan origin was influenced by the condition of transportation. There were economic and political reasons for the immigration, and the former was the chief reason. Myanmar was a preferred destination for emigration. The Chinese immigrants of Yunnan origin there were mainly engaged in business and mining, supplemented by agriculture and handicraft. Overseas Chinese received different treatments by different countries in different periods: sometimes they were well-received and accepted, while sometimes isolated, suppressed, and cracked down. Overseas Chinese had made indelible contributions to the agriculture, industry, commerce, culture, and education in both their adopted homeland and their country of origin. In the Ming and Qing Dynasties and the Republic of China, the central government and the local government of Yunnan implemented different overseas Chinese policies. The overseas Chinese policy of the Yunnan government in the Republican Era were all in all a success. They were a foundation of the overseas Chinese policy adopted by the government of the People's Republic of China.

Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithmsIt will be of great interest to researchers in computational finance, machine learning and data science.About the AuthorsJun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019.Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.