Abstract
https://asmeet.webex.com/asmeet/j.php?MTID=m6e0fc357ea403aa6b4ab3db025a30961
2023年6月21日星期三 上午 10:00 | 2 小時 | （UTC+08:00）台北
會議號： 2519 029 8214
密碼： WPaNJ7Za8q6
Dr. Yang was motivated by a series of questions “What are algorithms?”, “What is research?”, “Why did many good students study abroad?”, “Why did some people earn tremendous amounts of money from stock markets?” and transformed himself gradually from a software engineer to a researcher and then to a stock investor. In this talk, Dr. Yang will briefly introduce his past work on computer vision and mostly explain his findings on stock investing. 95% stock market participants are speculators, interested in short-term gain made from transactions at difference prices, which is a result of evolution, encouraging human beings to get quick and big rewards. Many scholars have documented their herd behaviors, which caused many bubbles and crashes in the history, and studied the background stimulating those activities. The studies of behavioral economics and cognitive psychology show that human beings have many judgement biases and two styles of recognition: intuition and reasoning. The former is fast and automatic, usually with strong emotional bonds, and the latter is slower and more volatile, subject to conscious judgements. Thus, in many stock participants’ minds, when they think using intuition only, stock investing has no difference from casino or lottery gambling. If they are lucky enough, they will prosper overnight. Because overlooking transaction cost and house advantage, in general they contribute their money to brokers/government/casino owners. But some successful stock investors think in other ways. Dr. Yang collects examples from four groups: value investors, bubble catchers, algorithm developers, and trend followers, and will introduce them with details in this talk.
2023年6月21日星期三 上午 10:00 | 2 小時 | （UTC+08:00）台北
會議號： 2519 029 8214
密碼： WPaNJ7Za8q6
Dr. Yang was motivated by a series of questions “What are algorithms?”, “What is research?”, “Why did many good students study abroad?”, “Why did some people earn tremendous amounts of money from stock markets?” and transformed himself gradually from a software engineer to a researcher and then to a stock investor. In this talk, Dr. Yang will briefly introduce his past work on computer vision and mostly explain his findings on stock investing. 95% stock market participants are speculators, interested in short-term gain made from transactions at difference prices, which is a result of evolution, encouraging human beings to get quick and big rewards. Many scholars have documented their herd behaviors, which caused many bubbles and crashes in the history, and studied the background stimulating those activities. The studies of behavioral economics and cognitive psychology show that human beings have many judgement biases and two styles of recognition: intuition and reasoning. The former is fast and automatic, usually with strong emotional bonds, and the latter is slower and more volatile, subject to conscious judgements. Thus, in many stock participants’ minds, when they think using intuition only, stock investing has no difference from casino or lottery gambling. If they are lucky enough, they will prosper overnight. Because overlooking transaction cost and house advantage, in general they contribute their money to brokers/government/casino owners. But some successful stock investors think in other ways. Dr. Yang collects examples from four groups: value investors, bubble catchers, algorithm developers, and trend followers, and will introduce them with details in this talk.
Bio
Dr. Chih-Yuan Yang is currently a self-supporting researcher on stock investing. He started this research since 2015 after obtaining his Ph.D. degree. In the middle of this research, he joined the NTU IoX Center as a postdoctoral researcher from 2016 to 2019 for a MOST project of robots providing services for seniors. Dr. Yang studied computer vision at UC Merced from 2009 to 2015 for the topic of single-image super-resolution and was an intern at Siemens and Google. Prior to his Ph.D. research, he gained experience of computer vision from being a research assistant at IIS, Academia Sinica, algorithm engineer at Altek Corp, master student at CSIE NTU, and software engineer at PixArt Inc.