According to the Securities and Exchange Commission website, "'Illegal insider trading' refers generally to buying or selling a security, in breach of a fiduciary duty or other relationship of trust and confidence, while in possession of material, nonpublic information about the security.
"Insider trading violations may include 'tipping' such information, securities trading by the person(s) "tipped," and securities trading by those who misappropriate such information. Examples of insider trading cases that have been brought by the SEC are cases against: Friends, business associates, family members, and other "tippees" of such officers, directors, and employees, who traded the securities after receiving such information."
***
During the latter part of the last weekend, I read a riveting Behavioral Finance paper, authored by Messr. Jing Chen, that is entitled An Entropy Theory of Psychology and its Implication to Behavioral Finance. The paper struck me with an immense force of insight that changed the way in which I perceive insider trading.
In the paper Messr. Jing Chen asserts that "patterns in financial markets reflect the patterns of information processing by the investment public."
Generally, information is the reduction of entropy in a system, and all human activities are essentially entropy processes. Thus, this means that models from entropy theory, cast within a game theory framework, can be used to explain why hedge fund managers sometimes resort to insider trading.
Within the context of financial markets, the value of an information piece (to you) is a function of the probability that other market players, who have investment strategies that overlap with yours (and thus, are best positioned to replicate your portfolio positions), have accessed the alpha enhancing information piece before you.
According to the tenets of Information Theory, information satisfies the following properties (these properties are a verbatim quotation of a section of Jing's paper):
Where b is greater than zero, and constant.
Equation 1 represents the level of uncertainty in an open system. When a signal is received from the environment, there is a reduction of uncertainty in the system, which, in essence, is the mathematical definition of information.
Now, let us suppose that a random event denoted by the letter X, has n discrete states, x1, x2, x3 …,xn; each discrete state has a corresponding discrete probability that expresses the likelihood of other market players discerning the respective state before you detect it. The probabilities are denoted by p1, p2,…,pn, respectively. (Note: Here I have departed from the syntax in Jing's paper to advance my assertion with clarity).
Therefore, the informational value of event X is the aggregate information value of each and every one of its discrete states. Thus, this gives us Equation 2 below:
In the paper Messr. Jing Chen asserts that "patterns in financial markets reflect the patterns of information processing by the investment public."
Generally, information is the reduction of entropy in a system, and all human activities are essentially entropy processes. Thus, this means that models from entropy theory, cast within a game theory framework, can be used to explain why hedge fund managers sometimes resort to insider trading.
Within the context of financial markets, the value of an information piece (to you) is a function of the probability that other market players, who have investment strategies that overlap with yours (and thus, are best positioned to replicate your portfolio positions), have accessed the alpha enhancing information piece before you.
According to the tenets of Information Theory, information satisfies the following properties (these properties are a verbatim quotation of a section of Jing's paper):
- The information value of two events is higher than the value of each of them.
- If two events are independent, the information value of the two events will be
the sum of the two. - The information value of any event is non-negative.
H(P) = -log_b P
Where b is greater than zero, and constant.
Equation 1 represents the level of uncertainty in an open system. When a signal is received from the environment, there is a reduction of uncertainty in the system, which, in essence, is the mathematical definition of information.
Now, let us suppose that a random event denoted by the letter X, has n discrete states, x1, x2, x3 …,xn; each discrete state has a corresponding discrete probability that expresses the likelihood of other market players discerning the respective state before you detect it. The probabilities are denoted by p1, p2,…,pn, respectively. (Note: Here I have departed from the syntax in Jing's paper to advance my assertion with clarity).
Therefore, the informational value of event X is the aggregate information value of each and every one of its discrete states. Thus, this gives us Equation 2 below:
H(X)=-/sum_{j=1}^{n}p_jlog(p_j)
The right hand side of Equation 2 is the entropy function first posited by Messr. Boltzmann in 1870s. This is the general form for information. (Shannon, 1948)
Therefore, If your adversaries were to understand the all the discrete states of an alpha enhancing information piece before you do, then all of the individual probabilities from p1 to pn =1. This means that when you plug the value (i.e 1 for each of the probabilities) into Equation 2 to compute the summation of the discrete probabilities, your end result will be: H(X) = 0. Therefore, this means that the information value of potentially profitable events already discerned by a fund manager's adversaries is zero.
Whereas, if a fund manager's adversaries fail to discern all of the discrete states of an alpha enhancing event, its information value is at its maximum. Thus, this implies that as pj approaches zero, the information value of an event tends towards a maximum.
Thus, If we assume that fund managers are rational, profit maximizing individuals, we can conclude that they have an implicit incentive to trade on information that other fund managers don't have access to.
By definition, information that other fund managers don't have access to, does not exist in the public domain; it is privileged, sequestered and confidential information; and, acting on it is tantamount to insider trading. Otherwise put, trading on such information prejudices market outcomes in favor of a few, and undermines the credibility of the markets.
Hence, we can conclude that insider trading is an adaptive function that helps fund managers to outperform in forbidding market conditions, i.e. conditions in which crowding in strategies exists, and an environment in which replication of a fund manager's trades, by his/her adversaries, is rife.
Whereas, if a fund manager's adversaries fail to discern all of the discrete states of an alpha enhancing event, its information value is at its maximum. Thus, this implies that as pj approaches zero, the information value of an event tends towards a maximum.
The probability of other market players discerning alpha enhancing information increases as the number of market players (with strategies that overlap with your's) increases. Therefore if NMp is the number of market players, we can safely assert that as NMp increases pj approaches 1, and thus H(X) approches 0.
Thus, If we assume that fund managers are rational, profit maximizing individuals, we can conclude that they have an implicit incentive to trade on information that other fund managers don't have access to.
By definition, information that other fund managers don't have access to, does not exist in the public domain; it is privileged, sequestered and confidential information; and, acting on it is tantamount to insider trading. Otherwise put, trading on such information prejudices market outcomes in favor of a few, and undermines the credibility of the markets.
Hence, we can conclude that insider trading is an adaptive function that helps fund managers to outperform in forbidding market conditions, i.e. conditions in which crowding in strategies exists, and an environment in which replication of a fund manager's trades, by his/her adversaries, is rife.
Thus the answer to answer to the question: Why do fund managers engage in insider trading?, is; to survive.
