Prof. Mu-En Wu (Prof. Mu-En Wu)
Professor, Department of Information and Finance Management (IFM)
National Taipei University of Technology (NTUT), Taipei, Taiwan
Research Group：iLoveTradingLab
Biography
Mu-En Wu is a Professor in the Department of Information and Finance Management at National Taipei University of Technology. He holds a Ph.D. in Computer Science from National Tsing Hua University, where his early work was in cryptography and information theory. He later carried that mathematical and computational training into finance, and has since worked on money management, the Kelly criterion, quantitative trading and financial data analysis.
His work spans mathematics, computer science and finance: mathematics as the theory, computation as the tool, and market strategy design and risk control as the application. He has published more than a hundred papers in international journals and conferences, and works to make the mathematical basis of trading better understood, against the popular belief in stock tips and trading holy grails. He runs the iLoveTradingLab research group and writes for financial media under the pen name Mu Ching-Hua.
He was the founding president of the Taiwan Quantitative Trading Association, and president of the Taiwan Data Science and Business Application Association and of the Chinese R Software Association. He was at the Institute of Information Science, Academia Sinica from 2009 to 2014, and taught in the Department of Mathematics at Soochow University from 2014 to 2017.
Research Interests
Money management, the Kelly criterion, portfolio optimization, quantitative trading, financial data analysis, information theory, cryptography, decentralized finance and digital currency.
Book
The Rich Man Inside the Formula: Money Management and the Kelly Criterion (in Chinese)
A mathematical treatment of money management and a full account of the Kelly criterion. Starting from betting games, the book asks how to size a bet so as to maximize capital over the long run. It contains no stock tips and no discretionary technical analysis — only mathematical reasoning, simulation and backtesting, letting the statistics speak. R code is included.
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