Corporate insiders engage in “shadow trading” when they use private information about their own firm to trade in the shares of economically connected companies such as suppliers, customers, or competitors. While legal scholars have long recognized that shadow trading can be profitable, SEC v. Panuwat (a recent case in which the head of business development at a pharmaceutical company traded in the stocks of a competitor) has reinvigorated the debate on the consequences of shadow trading and the extent to which it ought to be regulated. We investigate these issues in a pair of forthcoming papers. In the first paper, we study the consequences of shadow trading on corporate investment choices. In the second paper, we focus on the macroeconomic consequences of shadow trading.
Our first paper develops a formal model to analyze the incentives created by shadow trading – specifically, how shadow trading might affect corporate investment choices. To begin with, we show that shadow trading can allow a firm to offload some of the cost of its insiders’ compensation onto the shareholders of economically connected companies. The intuition is that if shadow trading is freely permitted, corporate insiders can profit from trading in the shares of these connected companies, and therefore in a competitive labor market, they will be willing to accept lower salaries or performance-based compensation.
In addition, we also show that the possibility of engaging in shadow trading can increase managers’ appetite for risk. Imagine that the CEO of a major corporation must decide between two corporate investments. One project is risky and can either increase the company’s stock price by 5 percent or decrease it by 10 percent, with equal probability. The other project is safe and would result in a relatively small increase in the stock price. Thus, the safe project is superior in the sense of being more more predictable. Nevertheless, the CEO may still prefer the risky option. Because the risky project can result in significant fluctuations in the stock price of her company, and consequently in those of connected companies, the CEO can potentially use her privileged position to gain early access to information on the direction of these swings and engage in profitable shadow trades for herself. Importantly, the CEO can profit from her trades regardless of the outcome of the project. If the project looks to be successful, the CEO can profit by buying shares of other companies that would be positively affected by the news of its success, while selling short the shares of companies that would be negatively affected. On the other hand, if the project looks to be unsuccessful, the CEO can profit by using the opposite trading strategies. In these instances, the magnitude of the CEO’s profit just depends on the magnitude (not the direction) of the swing, and thus, the CEO would prefer the riskier project.
This is not necessarily undesirable from the shareholders’ perspective. Indeed, one argument for allowing insiders to trade in the stock of their own company based on private material information is that it would reduce the chances that managers’ private risk aversion would push them toward more conservative investments than shareholders would prefer (Bebchuk & Fershtman, 1994).
However, as we discuss in our second paper, combining the model’s results with the findings from the macroeconomic literature leads to the worrisome conclusion that shadow trading can increase the level of macroeconomic risk for the economy. On the one hand, the macroeconomic literature has shown that a subset of “central” firms can impose large externalities on the economy and also trigger aggregate fluctuations in production (Gabaix 2011; Acemoglu et al. 2012). On the other hand, because shocks at these firms also tend to have a larger impact on connected companies’ stock prices (Aobdia et al., 2014), insiders of central firms can reap larger profits than can those at other firms by creating risk and engaging in shadow trading. Put differently, the possibility of engaging in shadow trading gives insiders at firms with a significant economic impact greater incentives to pursue risky investments.
Another important insight of our model is that in some cases shadow trading can lead insiders and shareholders to prefer money-losing risky projects to profitable safe ones. This is because shareholders can profit in two ways from shadow trading when their firm invests in risky projects. On one hand, their corporation can profit by engaging in shadow trading in the stocks of connected companies. On the other hand, shareholders can save on the manager’s compensation if the manager is allowed to engage in shadow trading. This contrasts with a standard conclusion about classical insider trading: In that scenario, shareholders would not prefer projects expected to have a negative value even when a manager’s compensation includes profits from insider trading. (Bebchuk & Fershtman, 1994).
Our model also considers the case in which shareholders do not anticipate that the manager may engage in shadow trading. In this scenario, a manager can strategically thwart the expectation of shareholders about what project the manager will pursue — to create an opportunity for profitable shadow trades. The manager’s seemingly irrational choice of project can then become a surprise, which in turn results in a further change in the firm’s value. In these instances, shadow trading can increase market volatility, a finding that confirms that allowing shadow trading can result in negative externalities on economically connected firms and markets in general. Finally, we consider a perfect Bayesian equilibrium under which the manager uses a mixed strategy in choosing between a risky project and a safe project, and the shareholders form a consistent belief regarding the manager’s project choice.
As for policy implications, our model provides a normative reason for making shadow trading illegal when the firm has an explicit prohibition against it. As noted above, by allowing insiders to engage in shadow trading, a firm can benefit from, in effect, offloading part of its insiders’ compensation onto related companies. However, allowing shadow trading can also affect the insiders’ propensity for risk and the corporation’s investment strategies. Thus, a firm’s choice to ban shadow trading can be read as a reasoned decision to forego the savings associated with offloading insiders’ compensation, presumably because it considers the incentives from shadow trades too costly on balance. At the same time, the results of our model do not compel a specific conclusion regarding how shadow trading ought to be regulated in cases where firms do not themselves ban shadow trades.
The picture changes significantly, however, when one also considers the macroeconomic consequences of shadow trading, which we discuss in our second paper. If shadow trading can create macroeconomic externalities, the decision as to whether to regulate shadow trading should not depend only on the impact that shadow trading can have on a firm. Indeed, if shadow trading at some firms can have negative macroeconomic consequences, the case for regulating shadow trading (at least within such firms) appears much more compelling. At a minimum, we believe there should be greater transparency regarding firms’ shadow trading policies for their employees as well as their policies for corporate purchases and sales of stocks in other companies.
REFERENCES
Acemoglu, Daron, et al. “The network origins of aggregate fluctuations.” Econometrica 80.5 (2012): 1977-2016.
Aobdia, Daniel, Judson Caskey, and N. Bugra Ozel. “Inter-industry network structure and the cross-predictability of earnings and stock returns.” Review of Accounting Studies 19 (2014): 1191-1224.
Bebchuk, Lucian Arye, and Chaim Fershtman. “Insider trading and the managerial choice among risky projects.” Journal of Financial and Quantitative Analysis 29.1 (1994): 1-14.
Gabaix, Xavier. “The granular origins of aggregate fluctuations.” Econometrica 79.3 (2011): 733-772.
This post comes to us from Yoon-Ho Alex Lee at Northwestern University’s Pritzker School of Law, Lawrence Liu at the University of Southern California, and Alessandro Romano at Bocconi University – Department of Law. It is based on their recent papers, “Shadow Trading and Corporate Investments,” available here, and “Shadow Trading and Macroeconomic Risk,” available here. A version of this post appeared on the Oxford Business Law Blog, here.