Following trend is the key to successful investing. For over a century, from Charles H. Dow to Ralph N. Elliott, much research has been conducted to seek early signs when a market trend changes. The Dow theory assumes that the market discounts everything. The primary trend will be irregular. The objective is to tell when either a bull or a bear market has terminated. The theory focuses on market indexes, not individual stocks.

Prior to the Capital Market Behavior Theory, other most notable theories are briefly summarized as follows:

Elliott Wave Theory

Key Point – It uses a five-wave sequence to predict when market turns.

Limitation – Like many other technical analysis tools, two followers of the theory may see different results.

Capital Market Theory

Key Point – Market is efficient and random (normal distribution). Prices reflect all available information and have no memory. There is no way to predict market trend.

Limitation – The reality is that nonrandom opportunities are everywhere. Stock prices behave often as non-symmetric (fat-tailed and skewed distributions).

Contrarian Theory

Key Point – The public is always wrong. Success in investing can be achieved by acting the opposite by recognizing the extremes of crowd psychology.

Limitation – No proven quantitative evidence.

Since 1996, Dr. Charlie Q. Yang has devoted his spare time in investor sentiment index research. Specifically, he has focused on statistical data processing of human emotion, leading to defining the foundation of the Capital Market Behavior Theory:

Key Point – A stock’s daily price movement is primarily driven by human emotion. After all market information is known, the fundamental of a company does not change even when its stock price is fluctuating. However, over a longer time period, a company’s fundamental does change. Again, human emotion is driving the stock price trend up or down. By properly capturing and measuring variations in crowd emotion, primary trend reversals can often be identified in its initial stage. Human emotion analysis challenges the conventional methods of fundamental analysis and technical analysis, allowing us to quantitatively explore the third dimension of stock market behavior.

Foundation of Capital Market Behavior Theory

The mathematical foundation of Capital Market Behavior Theory was established in 1996 with the discovery of Q-Distributions. Q-Distributions, for the first time in history, enabled researchers to generate a family of fat-tailed and skewed probability distributions for modeling stock prices and asset return statistics (shown below). This later evolved to systematic implementation of Investor Sentiment Index capturing and measuring variations in crowd emotion.