The stagnation of dealer balance sheets that began after the financial crisis of 2007-09 has persisted, as shown in Figure 1 below. In the years running up to the crisis, dealer assets grew exponentially, peaking at around $5 trillion in early 2008. In late 2008, assets contracted sharply, to $3.5 trillion (their level in 2005) and at the end of 2016 reached $3.0 trillion.
Figure 1 Dealer balance sheets stagnated after the crisis
Note: Figure plots the total financial assets of security brokers and dealers at the subsidiary level.
Source: Board of Governors of the Federal Reserve System, Financial Accounts of the United States.
Dealer leverage (assets/equity) has followed a similar path, as seen in Figure 2. Leverage peaked at 47.9 in the first quarter of 2008, around the near-failure of Bear Stearns, and then plunged to just 25.0 in the second quarter of 2009. Leverage remained fairly steady until 2012, but has since trended down, reaching 17.6 in late 2016.
Figure 2 Leverage has continued to decline
Note: The figure shows the leverage of security brokers and dealers at the subsidiary level. Leverage is defined as (total assets)/(bank equity capital).
Source: Authors’ calculations, based on data from the Board of Governors of the Federal Reserve System, Financial Accounts of the US.
Less abundant funding liquidity.
Consistent with stagnant dealer balance sheets, arbitrage measures suggest less abundant funding liquidity. Figure 3, for example, plots the credit default swap (CDS)-bond basis, calculated as the average difference between each bond’s market CDS spread and the theoretical CDS spread implied by the bond yield. A basis different from zero suggests an arbitrage opportunity, and is indicative of dealers’ constraints, particularly funding constraints. The basis was close to zero, yet generally positive, before the crisis, but turned sharply negative during the crisis before rebounding, and has generally been moderately negative since the crisis. Boyarchenko et al. (2017) argue that increased funding costs possibly tied to regulatory constraints on dealer balance sheets can limit trading on this apparent arbitrage opportunity, as dealers must now hold more capital against such trades.
Figure 3 CDS-bond basis is negative after the crisis
Notes: The figure plots the CDS-bond basis for investment grade (orange) and high-yield (blue) corporate bonds. The CDS-bond basis is computed as the average difference between each bond’s market CDS spread (interpolated to the bond maturity) and the theoretical CDS spread implied by the bond yield.
Source: JP Morgan.
Drivers of the changes
In a recent paper (Adrian et al. (2017a), we update and unify much of our earlier work on the subject, following up on three series of earlier posts on Liberty Street Economics (Adrian et al. 2015a,b, 2016a). Many commentators attribute the funding market pressures and purportedly reduced market liquidity to the Dodd-Frank Act and the Basel III regulatory framework. Those regulatory reforms include higher bank capital requirements, new leverage ratios, and liquidity requirements. While these regulations are intended to make the US and the global financial system more resilient, some market participants argue that they also hinder market making by raising the cost of capital and restricting dealer risk taking.
While it’s reasonable to think that regulations have affected both funding and market liquidity, the effects are difficult to pinpoint given various other factors affecting dealer balance sheets and liquidity in the post-crisis era. Such factors include voluntary changes in dealer risk management practices and balance sheet composition since the crisis, the growth of electronic trading, the evolving liquidity demands of large asset managers and changes in expected returns associated with the economic environment. Identifying how any one factor affects dealer balance sheets and liquidity must account for these other factors, which is especially difficult given that many are highly interrelated and driven by other developments.
Evolution of market liquidity
Turning to market liquidity, we find mixed evidence for the Treasury market. As of late 2016, average bid-ask spreads for benchmark notes in the interdealer market were narrow and stable – and comparable to pre-crisis levels, as shown in Figure 4 below. In contrast, Figure 5 reveals that ‘Treasury depth’ – the average quantity of securities that can be traded at the best bid and offer prices – remains below levels seen right before the crisis and the 2013 sell-off in fixed income markets, albeit well above crisis levels. The evolution of the price impact of trades, shown in Adrian et al (2015c), similarly suggests a modest deterioration in liquidity since early 2013.
Figure 4 Treasury bid-ask spreads are narrow and stable
Notes: The figure plots 21-day moving averages of average daily bid-ask spreads for the on-the-run notes in the interdealer market. Spreads are measured in 32nds of a point where a point equals 1% of par.
Source: Authors’ calculations, based on data from BrokerTec.
Figure 5 Treasury depth is below all-time high
Notes: The figure plots 21-day moving averages of average daily depth for the on-the-run notes in the interdealer market. Depth is summed across the top five levels of both sides of the order book.
Source: Authors’ calculations, based on data from BrokerTec.
In the corporate bond market, liquidity appears to have diverged depending on trade size, which is often associated with investor type. Figure 6 below thus shows that average realised bid-ask spreads (which are based on transaction data), have fallen below pre-crisis levels for retail-sized trades, but remain above pre-crisis levels for institutional-sized trades. Regardless, corporate bond trading and issuance volume have been robust, reaching record highs in 2016.
Figure 6 Corporate bond bid-ask spreads have diverged
Notes: The chart shows the 21-day moving average of realised bid-ask spreads for retail (under $100,000) and institutional ($100,000 and greater) trades of corporate bonds. The spreads are computed daily for each bond. Trade size grouping are calculated as the difference between the average (volume-weighted) dealer-to-client buy price and the average (volume-weighted) dealer-to-client sell price, and then averaged across bonds using equal weighting.
Source: Authors’ calculations, based on data from the Financial Industry Regulatory Authority, Trade Reporting and Compliance Engine supervisory database.
Liquidity case studies
Although liquidity under normal market conditions may not have significantly worsened, it might be that it has become more fragile, or prone to disappearing under stress (see, for example, Powell 2016). To address that prospect, we consider three case studies on the resilience of market liquidity since the crisis. Adrian et al. (2013) analyse dealer balance sheet behaviour during the 2013 Treasury sell-off – the ‘taper tantrum’ when yields rose over 100 basis points over ten weeks. Ahmed et al. (2015) look at the October 2014 ‘flash rally’ in the Treasury market, when yields rose and fell sharply within a 12-minute window. Adrian et al. (2016b) review how the liquidation of Third Avenue’s high-yield bond fund in December 2015 affected market liquidity. In all three instances, the degree of deterioration in market liquidity was within historical norms, suggesting that liquidity remained resilient even during stress events.
While we do not find clear indications of a widespread worsening of bond market liquidity, our analysis faces several limitations, including important limits to available data. For example, our Treasury market metrics are from the interdealer market, and hence do not gauge liquidity in the dealer-to-customer market. Moreover, our corporate metrics are based on transactions data, and cannot account for the time required to trade or the liquidity of bonds that do not trade. To overcome these shortcomings, future work should consider a wider range of data to illuminate these ‘blind spots’. Indeed, as discussed in Fleming (2017), regulators will soon have access to a broader set of transactions data for the US Treasury market.
In addition, dealer balance sheets have changed dramatically, and some funding cost metrics, such as the CDS-bond basis, imply increased balance sheet costs, suggesting important changes in dealer behaviour. Exploring the determinants of such behaviour and how dealer attributes affect market liquidity is a promising avenue of future work. Adrian et al. (2017), for example, link changes in the liquidity of individual corporate bonds to financial institutions’ balance sheet constraints and find that bonds traded by more levered institutions are less liquid, especially after the financial crisis.
Authors’ note: The views expressed here are those of the authors and do not necessarily represent those of the institutions with which they are affiliated.
-Tobias Adrian, Michael J. Fleming, Or Shachar