Financial institutions are highly leveraged due to the extremely low interest rates of the past decade. However, interest rates are now rising worldwide due to inflationary pressures, which can lead to plunging stock markets and significant deleveraging of financial institutions. Policymakers, academics, and practitioners are concerned about the impact of deleveraging. In our recent paper, we study the effect of deleveraging on the market liquidity of high-embedded-leverage securities issued by deleveraging institutions and on the funding liquidity of such institutions in one of the most important capital markets of the world, China.
Many investors (e.g., individual investors, mutual funds, pension funds, and even hedge funds) face significant leverage constraints and hence cannot reach desired leverage levels in their portfolios. Thus, to achieve high expected returns from using leverage, they prefer securities with high levels of embedded leverage and thus high beta (e.g., leveraged ETFs, options, stocks of highly leveraged firms, etc.), and overweight such securities in their portfolios. It is known that this investor preference for high-embedded-leverage and high-beta securities increases the prices of such securities, leading to low risk-adjusted returns.
If due to operational loss or other funding shocks, issuers of such high-embedded-leverage securities are forced to deleverage to protect debtholder interests, deleveraging can make these originally high-beta securities much less attractive to leverage-constrained investors. This can result in a substantial reduction in investor demand for these deleveraged securities and thus a significant deterioration in the market liquidity of these securities, which may then amplify the initial funding shocks and further tighten issuer funding constraints.
To the best of our knowledge, no study empirically documents the impact of deleveraging on the market liquidity and funding liquidity of financial institutions. The lack of empirical evidence on this important issue likely reflects two challenges. First, the leverage of a financial institution is generally unobservable in real time. Second, when financial institutions are forced to deleverage due to an initial trading or operational loss, it is difficult, if not impossible, to isolate the impact of pure leverage changes from that of the loss. Moreover, other observable or unobservable factors (such as changes in market conditions or implementation of new investment strategies) can lead financial institutions to actively adjust their leverage levels. Since such factors can also affect the market liquidity of securities issued by financial institutions and the funding constraints of these institutions, causality is difficult to establish.
We tackle these two challenges by using the forced deleveraging of some structured mutual funds during the 2015 Chinese stock market crash as a natural experiment to isolate the effect of deleveraging (i.e., the treatment) on market liquidity, funding constraints, and performance of the treatment funds. Our dataset allows us to observe the leverage levels of structured mutual funds daily. Because some structured funds crossed the preset leverage limit during the market crash and were subsequently forced to deleverage, these forced deleveraging events provide us with an ideal natural experiment to examine the impact of deleveraging.
For those fund-day observations with actual leverage near the preset deleveraging threshold, the deleveraging treatment can be viewed as random. We thus employ a regression discontinuity design (RDD) to study the impact of deleveraging on the market liquidity of the treatment funds’ equity shares. RDD is a powerful identification strategy. Its premise is that except for the assignment of treatment, which is discontinuous at the deleveraging threshold, the impact of other observable/unobservable factors on the market liquidity of a fund’s equity shares is similar near the threshold. Hence, by estimating the local average treatment effect around the threshold, we can cleanly rule out the influence of other confounding factors and estimate the causal impact of deleveraging on the market liquidity of fund equity shares.
Like other mutual funds in China, structured mutual funds (hereafter, structured funds) raise money from investors by issuing fund units and then using the raised money to invest in stocks and other financial securities such as bonds. Unlike other Chinese mutual funds whose assets-to-equity ratio (i.e., leverage) cannot exceed 1.4, structured funds are allowed to use much higher leverage. What makes structured funds special is that they issue two tranches of fund units. Holders of tranche A debt units receive fixed interest payments, while holders of tranche B equity units receive all the residual income after the deduction of fixed interest payments to tranche A debtholders, fund fees, other expenses, and investment losses. In essence, structured funds effectively borrow from tranche A debtholders to increase the expected returns of their tranche B equity holders.
This high-embedded-leverage feature of tranche B equity units made them very popular among investors who prefer high expected returns. The China Securities Regulatory Commission (CSRC) mandates that when a structured fund is raised, the initial leverage should not exceed two, and subsequent leverage should be maintained below six. This leverage limit is much higher than the leverage limit for other mutual funds. Structured funds usually specify in their prospectus a threshold (minimum) net asset value of the tranche B equity unit that will trigger deleveraging. Once the fund’s actual net asset value per equity unit falls below this deleveraging threshold and the actual leverage level exceeds the preset leverage limit, the fund will then be forced to (i.e., in the next two trading days) bring its leverage back down to the initial leverage level to protect the interests of tranche A debtholders. The fund will publicly announce the coming deleveraging. It will then recalculate/reduce the number of tranche B equity units so that each equity unit’s value is returned to its initial value. To reduce the fund’s debt value, the fund will convert a large portion of tranche A debt units into parent units. These parent units can then be paid back to tranche A debtholders in cash (i.e., redemption) or, if desired by tranche A holders, split equally into tranche A and B units and sold to the market.
China’s stock market crashed in mid-2015. The Shanghai Stock Exchange (SSE) composite index steadily increased from 2,038 at the beginning of June 2014 to 5,166 on June 12, 2015. Then, the SSE index went into a free fall to 2,655 in January 2016 and fluctuated at around 3,000. During this boom-and-bust process, the total assets under management (AUM) of structured funds exponentially increased from ¥70 billion in June 2014 to ¥460 billion in June 2015 (a 657% increase) and then decreased to ¥229 billion in the first quarter of 2016 (a decrease of more than 50%). By contrast, non-structured mutual funds did not experience such dramatic changes in AUM. Structured fund deleveraging did not occur before the 2015 market crash. However, during the 2015 crash, 78 of the 183 structured funds in our sample crossed the preset leverage limit and were forced to deleverage to the initial leverage level.
Empirical Evidence on the Effects of Deleveraging
We begin our analysis by documenting a positive relationship between fund leverage and the market liquidity of structured funds’ equity units before the market crash. Funds with greater leverage have significantly higher order imbalances, narrower effective spreads, greater trading volumes, and higher turnover for their equity units. This finding is robust after controlling for various fund characteristics, year-day fixed effects, and fund fixed effects, indicating that greater leverage attracts investors seeking high expected returns. We conjecture that when a fund’s leverage exceeds the preset limit, the fund’s equity units will become much less attractive to these investors (due to the expectation of subsequent deleveraging). The loss of investors’ interest and the associated reduction in investor demand will cause a significant deterioration of the equity units’ market liquidity.
Results from our RDD analysis clearly show a large and statistically significant impact of deleveraging on the market liquidity of a fund’s equity units. Compared to the control group (i.e., fund-day observations with just-below-threshold leverage, which have very similar performance and other characteristics as the treatment group), when a treatment fund crosses the deleveraging threshold (and is thus expected to subsequently deleverage to its initial leverage in the next two trading days), its order imbalance decreases on average 2.1 times, the effective spread increases 5.8 times, and trading volume decreases by 43%, relative to their respective sample standard deviations. These results lend strong support to our conjecture. Additional empirical evidence further rules out several alternative explanations and suggests that deleveraging negatively impacts the market liquidity of treatment funds’ equity units due to investors’ preferences for high-embedded-leverage securities.
Deleveraging results in a large portion of tranche A debt units being converted into parent units. The latter can then be paid back to tranche A debtholders in cash (i.e., redemption) or, if desired by tranche A holders, split equally into tranche A and B units and sold to the market. Because of the significant reduction in the market liquidity of its tranche B equity units (e.g., high effective spread and low trading volume) after a fund crosses the deleveraging threshold, most, if not all, tranche A investors will go to redeem their investment and demand cash from the treatment fund (rather than splitting their parent units into A and B units and sell them to the market at a discount due to the low B unit market liquidity). Moreover, due to the low embedded leverage of the B units after deleveraging, many investors of B units no longer want to hold these securities and, due to the deteriorated B unit market liquidity, may also choose to exit through redemption. Significant redemption pressures can lead to funding liquidity crises of these treatment funds. These redemption pressures can cause the treatment funds to have a fire sale of their stock holdings and produce low relative fund performance.
We use data on quarterly fund flows and portfolio holdings around the deleveraging events to examine the impact of deleveraging on the funding constraints of the treatment funds. We employ the event-window cohort approach in a difference-in-differences (DID) regression framework. A potential concern for the DID analysis is that the treatment (i.e., deleveraging) may be driven by recent fund performance and/or correlate with other fund characteristics and hence may not be random. To alleviate this concern, we use propensity score matching (PSM) to select the control group (i.e., fund-quarter observations of structured funds that did not deleverage during the sample period) with no observable difference in ex-ante fund characteristics compared with the treatment group. We then construct event-window cohorts from the PSM sample for our DID analysis. The results clearly show that, compared with structured funds that did not deleverage, the treatment funds saw large redemption outflows and large reductions in stock holdings, cash holdings, and fund returns in subsequent quarters. These results indicate that these funds experienced severe funding liquidity crises.
We further examine whether the large reduction in market liquidity of their equity units after crossing the deleveraging thresholds causes the treatment funds’ funding liquidity crises. Due to this significant reduction in market liquidity, investors choose to redeem their investment rather than sell their fund units at a discount to the market. Our results show that the larger the reduction in the market liquidity of the equity units around deleveraging, the greater the impact of deleveraging on subsequent outflows, stock holdings, cash holdings, and fund returns. Thus, our empirical evidence suggests that deleveraging results in a loss of leverage-constrained investors’ interests and demand for the treatment funds’ equity units. This significantly decreases the market liquidity of the equity units, which in turn leads investors to redeem their investment from these funds, thus causing their funding liquidity crises.
Now that interest rates are rising rapidly, policymakers should be on alert for potential deleveraging in structured products with high embedded leverage and the knock-impacts this will have for market liquidity of such securities and financial firms’ funding liquidity.
Buhui Qiu is an Associate Professor of Finance and Director of Doctoral Studies at the University of Sydney Business School, The University of Sydney.
Gary Tian is a Professor of Finance at the Macquarie Business School, Macquarie University.
Haijian Zeng is a Professor of Finance at the Guangxi University School of Business, Guangxi University.