In the financial market, there are so many investment forecasting institutions which are providing various forecasting information for its members only. Sometimes it is difficult to get unless you join the institutions. Once you have paid the fee and become one of their members, the manager of the institution will give you their studies, the information about the assets. With this information in mind, you come to the market and try to find a best chance to trade. However, what the information points may not like the current trends in the market. The traders will consider these two indices carefully under this circumstance and then make the right decisions under rationality. As you can imagine, there are a lot of traders with their private information on the market, some are the members of institutions and others are not.
In this paper, we try to find out that under what kind of conditions, the members will earn more than the traders who do not join the institutions in the financial market.
Banerjee [1] showed that individuals make a onetime decision under incomplete and asymmetric information sequentially. Glosten and Milgrom [10] set a trading market with heterogeneous informed traders. Following the spirits of them, we construct a sequential trading line market which is trading by the traders with heterogeneous information in this paper.
For simplicity, there is only one institution on the market and traders are separating into two groups. One group is consisted of traders who join the institution in order to get extra information, and the other group is consisted of traders who need to collect information by their own. When traders come to the market with their own information, after the observations of the past actions, they can make their decisions.
‧
Bikhchandani, Hirshleifer, and Welch [19] found that individuals rationally ignore their own information and imitate their predecessors, a phenomenon of herding. In this model through our mechanism, the herding will not persist which is equal to the result of Cipriani and Guarino [17] because of the adjustment of asset price.
Rational herds, defined by Bikhchandani and Sharma [20], occur when sequential individuals make identical decisions and they do not give their private information up necessarily. Celen and Kariv [4] gave a clear definition between informational cascade and herd behavior. In this paper, traders observe the past actions and will compare the history trend to their private information, and then the herds may occur.
If the institution is trying to influence the price to the value they set, it is not enough to reach the target price by their own power of its members. The institution needs to guarantee that the non-members will be infected. Since the members have extra information, if they can influence the decisions made by non-members through price, they can have better profits.
The mechanism of asset price in this paper is not using the recently popular method of Brown motion. We believe that the price connection between two days is not independent. Traders bring their private information and observe the public history, and then make their decisions. In some sense, the private information reveals the value of the asset, and it is like the fundamental analysis; in another sense, the public information affects the private information and it is like the technical analysis.
Traders will use both of them as their judgments when they are trading. A lot of papers ignore this point.
The aim of this paper is trying to find out if there is any benefit for traders to join the institutions. Hence we need to compare the performance of the members and the non-members. We set a lot of parameters to see that what conditions make the performance of the members better through simulation.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
3
In chapter 3, we introduce the set up of this paper. In chapter 4, we are starting to describe the calculation of performance and the method of simulation. Also we use two examples to explain our simulation. In chapter 5, we list ten different cases to contrast the performance with these two groups. Finally, we make our conclusions.
‧
signals would be randomly drawn from two states. If you had drawn a good signal, you could guess that the value of the asset would be high, and then you probably would call a buy order. On the contrary, if you had drawn a bad signal, you would put a sell order. Scharfstein and Stein [7] used this assumption to observe the herd behaviors. Anderson and Holt [11] set another mechanism to observe the information cascades in the laboratory. Alevy, Haigh, and List [9] were experimented the information cascades in the laboratory. The asset value was simply becoming dichotomy and could not sophisticated deal with.Park and Sabourian [3] assumed that there are two types of traders, informed and noise. A lot of papers assumed the comparative traders trade for liquidity, but in fact most traders come to the market for profits. They are not just trading for liquidity, if we had made this assumption, we would underestimate the ability of noise traders.
In recent paper, Amador and Weill [13] assumed there are a public and a noisy signal and they wanted to see the speed of learning through observing other’s actions. We made the assumption further: there are two private signals and one public signal.
Traders will act dependent on the weighted averages method of these three signals.
Also the aim of analysis would be different, what we measured and interested is the relative performance between these two subgroups.