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RebellionResearch.com White Paper - Volume 1.0

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RebellionResearch.com White Paper - Volume 1.0

Some investors profit in the stock market whereas others sustain a loss. What accounts for the difference in performance among investors? If the random walk hypothesis and efficient market hypothesis hold in market, the differences of performance of investors only can be explained by the degree of luck of the investor. But there are some theoretical approaches explaining the difference of performance of investors and some empirical evidence supports the theories by which the random walk hypothesis and efficient market hypothesis are challenged.

The first approach is relevant to information the investor might possess. Market microstructure assumes three types of investors: informed investors, uninformed noise investors, market maker.

Friedman (1953) and Kyle (1985) argue that the informed investor can make positive profit in their separate way, by exploiting arbitrage opportunity caused by mis pricing (Friedman(1953)), and by exploiting his monopoly power optimally (Kyle(1985)) . For uninformed noise investors, after defining the noise trading as “trading on noise as if it were information”, Black (1986) argue that “most of time, the noise traders as a group will lose money by trading, while the information traders as a group will make money.”

Barberis and Thaler (2005) say that the individual investor usually belongs to uninformed noise investors and many empirical study support the argument by showing that individual investors have poor performance relative to institution.

So we can say that individual investors usually belong to uninformed noise investor, whereas institutions usually belong to informed investor so that institutions usually show superior performance than individuals.
 

The second approach focuses on the skill of the investor. Many empirical studies shows that there are some skilled fund managers possessing abilities such as stock-picking and market timing who make superior performance than other fund managers. But, these two approaches have some limit in explaining the difference of performance of investors. For the first approach, since it analyzes the data in investor type level (individual and institution and so on,), it can not explain the difference of performance of investors within a same investor type. In fact, among institutions, since there are large difference in information possessing, it can make the difference of performance between institutions. And there is also probability that some individual have high quality information for some special reason.

For the second approach, the approach focus on so small subset of investors, fund managers that it can not explain the difference of performance between general investors. But more fundamental matter is the fact that quality of information and skill investor having is relative. Although the quality of information is so high, if the majority of investors also have the same information, the investors having the information can not make profit from the information. Similarly, although an investor’s investing skill is so nice, if the majority of investors also have the similar investing skill, the investor can not make profit from the investing skill. These simple idea imply the importance of the number of buyers and sellers in predicting the performance of an investment.
 

The price increase of a stock in intraday is induced by buyer-initiated trade whereas the price decrease of a stock in intraday is induced by seller-initiated trades. An investor (buyer) initiating price-increasing trade expect that the price of the stock will increase continuously and the performance of the investor (buyer) depends on the degree of correctness of his expectation. Our hypothesis is that the degree of correctness of investor’s expectation depends on ‘the role of each buyer’ in increasing the stock return. In more detail, the bigger the role of each buyer in increasing a stock return is (equivalently, the smaller the ratio of buyers1 involved in increasing the stock return is), the larger the return of the stock in next period is.

In this paper, we use the transaction level data from KRX over a 2 – year period to examine our hypothesis. Among the raw data, we only use the data of stocks hitting the upper price limit as close price (hereafter, we use the shorter expression ‘hit the upper price limit’ for meaning ‘hit the upper price limit as end price’) because it make it easy for us to compare stocks with same increasing rate. So, we use the ratio of buyer relative to seller of a stock hitting the upper price limit as the measure of ‘the role of each buyer’ and use the overnight return of the stock as the measure of the performance of the stock return.

We find the three main results from our study. First, mostly, the more the role of each.

The meaning of ‘the ratio of buyer’ will be clear in next paragraph.

The buyer of a stock is, the higher the performance of the stock is and the stock with extremely large role of each buyer shows the extremely high performance.

Second, if a role of each buyer of a stock is extremely small, then the performance of the stock is also extremely high.

Third, although stocks with two extreme case, extremely large role of each buyer, and extremely small role of each buyer, show the extremely high performance, the process of these stocks with two extreme cases realizing high performance is so different.: whereas relatively larger exiting investors (buyer and seller) of a stock with small role of each buyer involve in realizing high performance of the stock in the next period, relatively smaller exiting investors of a stock with larger role of each buyer involve in realizing high performance of the stock in the next day premarket. That is, relatively larger herding occurs at next day premarket in the stock with large role of each buyer in next period than the stock with small role of each buyer.

Edited by Alexander Fleiss

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