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E-MailRawley Heimer is Assistant Professor at the Boston College Carroll School of Management and Alp Simsek is Rudi Dornbusch Career Development Associate Professor of Economics at Massachusetts Institute of Technology. This post is based on their recent article, forthcoming in the Journal of Financial Economics.
Financial markets feature considerable speculative trading that can harm uninformed investors. Consequently, financial market regulators have long grappled with how to prevent investors from making harmful speculative trades, while preserving markets for useful trades. Leverage is a major catalyst for speculative trading. Our article examines the impact of leverage limits on the retail foreign exchange (forex) market. We find that leverage limits result in smaller losses for the most aggressive traders without harming market liquidity. Further, the policy improves belief-neutral welfare and reduces excessive financial intermediation. Our approach can be applied to other markets, and will be a useful framework for regulators as they try to curb speculation without impeding well-functioning markets.
The retail forex market is an ideal venue for our analysis because leverage limits in this market are new (introduced in 2010, compared to e.g. the market for U.S. equities, which has had a leverage limit of 2:1 since 1934). In October 2010, under the authority of the Dodd-Frank Act, the Commodity Futures Trading Commission (CFTC) capped the amount of leverage brokers can provide to U.S. traders at 50:1 on all major currency pairs and 20:1 on others. Meanwhile, European regulators did not impose any leverage limits, and the maximum leverage available almost always exceeded 50:1. These market features—time-series variation in available leverage and a suitable control group of unregulated traders—allow us to use a difference-in-differences design to evaluate the costs and benefits of the leverage-constraint policy.
We inform our empirical analysis with a stylized model that captures key aspects of the retail forex market. The model features traders with heterogeneous and dogmatic beliefs that reflect behavioral distortions (such as overconfidence), but these traders can also have some information about asset returns. Traders take positions based on their beliefs, and a competitive retail broker intermediates these positions. The broker sets bid-ask spreads that reflect intermediation costs and that protect the broker against informed trading. The model predicts that a leverage-constraint policy will reduce trading volume. Because traders lose money on average (due to the intermediation costs that they ultimately pay), the decline in volume improves traders’ expected return. The decline in trading volume also shrinks the intermediation revenues, as well as the size of the brokerage sector. Moreover, as in Brunnermeier, Simsek, and Xiong (2014), these effects represent belief-neutral improvements in social welfare. Intuitively, restricting trade in this market is beneficial because it reduces speculation, which is harmful because it lowers aggregate wealth due to intermediation costs. Less obviously, the policy might remove less-than-average quality trades from the market. In this case, brokers would need to charge a larger bid-ask spread to protect themselves from losses to more informed traders. Hence, the leverage-constraint policy represents a trade off: It reduces speculation and economizes on socially inefficient intermediation, but it can increase bid-ask spreads and worsen market liquidity.
Our empirical analysis comes in three parts. First, we investigate the effect of the policy on trader- level outcomes: their trading volume and portfolio returns. We compare American and European traders’ activities before and after the leverage constraint. We find that leverage limits reduce monthly trading volume by 23 percent. The policy improves traders’ average monthly returns, with stronger effects for traders that use more leverage. Prior to the policy, the average high-leverage U.S. trader loses 44 percent per month. The leverage constraint policy reduces these traders’ losses by about 40 percent. Second, we investigate the policy’s effect on the brokerage sector. We compare the excess capital (capital in excess of the regulatory requirement) of brokerages that have retail forex obligations to a control group of brokerages that are regulated by the CFTC, but do not offer retail forex accounts. The excess capital of the affected brokerages falls by about 25 percent. The reduction in excess capital is most pronounced for brokerages that offered traders more leverage prior to the CFTC regulation, precisely the brokerages we expect to be most sensitive to leverage restrictions. Third, we examine market liquidity, by testing the execution prices paid by traders in this market, relative to bid and ask prices in the interbank market. We find no evidence that brokerages charged higher spreads as a result of the CFTC regulation. These results suggest that the leverage-constraint policy improves social welfare by reducing excessive intermediation, without impairing market liquidity.
A plausible alternative mechanism for regulators to curtail speculation is to issue warnings about the use of leverage. In January 2010, several months before it imposed the leverage-constraint regulation, the CFTC announced that it wanted to restrict leverage to protect traders’ welfare. The announcement brought about protest from market participants, but it did not significantly affect trading volume, traders’ demand for leverage, or their returns; nor did it affect brokerages’ capital or bid-ask spreads. These results suggest that the physical leverage-constraint is the most effective policy. This finding is consistent with our model, since we assume that traders have dogmatic beliefs (e.g., due to overconfidence) and therefore are not easily deterred by announcements or warnings.
We have shown that leverage restrictions can reduce speculation without imposing costs (in fact, according to Brunnermeier et al.’s definition, the restrictions actually increase welfare). In addition to this belief-neutral welfare improvement, regulators might have other motivations for curbing speculation. The financial sector has recently experienced extraordinary growth, and this growth might in part reflect activities that do not benefit society (Zingales, 2015). Our evidence suggests that the growth of the forex brokerage market has been excessive, and a leverage-constraint policy is an effective tool to reduce this excess. More broadly, trading volumes have ballooned in recent decades, largely as a result of speculative trading, as evidenced by the recent trading frenzies in cryptocurrencies and retail structured products. Our results suggest that speculative trading could have inefficiently increased the size of the financial sector, and policies that target speculative trading can address this inefficiency without hurting market liquidity. Our analysis can easily be extended to other markets and other anti-speculation policies (such as financial transaction taxes), and we hope that policymakers perform similar welfare analyses before deciding on a regulatory framework.
The complete article is available here.
References
Markus K Brunnermeier, Alp Simsek, and Wei Xiong. A welfare criterion for models with distorted beliefs. The Quarterly Journal of Economics, 129(4):1753–1797, 2014.
Luigi Zingales. Presidential address: Does finance benefit society? The Journal of Finance, 70(4):1327–1363, 2015.
