A number of important theorems in finance rely on the ability of investors to trade any amount of a security without affecting the price. However, there exist several frictions, such as trading costs, short sale restrictions, circuit breakers, etc. that impact price formation. The influence of market imperfections on security pricing has long been recognized. Liquidity, in particular, has attracted a lot of attention from traders, regulators, exchange officials as well as academics.
Liquidity, a fundamental concept in finance, can be defined as the ability to buy or sell large quantities of an asset quickly and at low cost. The vast majority of equilibrium asset pricing models do not consider trading and thus ignore the time and cost of transforming cash into financial assets or vice versa. Recent financial crises, however, suggest that, at times, market conditions can be severe and liquidity can decline or even disappear. Such liquidity shocks are a potential channel through which asset prices are influenced by liquidity. Amihud and Mendelson (1986) and Jacoby, Fowler, and Gottesman (2000) provide theoretical arguments to show how liquidity impacts financial market prices. Jones (2001) and Amihud (2002) show that liquidity predicts expected returns in the time-series. Pastor and Stambaugh (2003) find that expected stock returns are cross sectionally related to liquidity risk.
Until recently, studies on liquidity were focused principally on its cross sectional determinants, and were restricted to equity markets (e.g., Benston and Hagerman, 1974, and Stoll, 1978). As more data has become available, recent work has shifted focus on studying time-series properties of liquidity in equity markets as well as in fixed-income markets. Hasbrouck and Seppi (2001), Huberman and Halka (2001), and Chordia, Roll and Subrahmanyam (2000) document commonality in trading activity and liquidity in the equity markets. Chordia, Roll, and Subrahmanyam (2001) study daily aggregate equity market spreads, depths and trading activity over an extended period to document weekly regularities in equity liquidity and the influence of market returns, volatility and interest rates on liquidity. For U.S. Treasury Bond markets, Fleming (2001) examines the time-series of a set of liquidity measures, Huang, Cai, and Song (2001) relate liquidity to return volatility, while Brandt and Kavajecz (2002) study the relationship between liquidity, order flow and the yield curve. Fleming and Remolona (1999) and Balduzzi, Elton, and Green (2001) analyze returns, spreads, and trading volume in bond markets around economic announcements.
So far, the literature on stock and bond market liquidity has developed in separate strands. There is good reason, however, to believe that liquidity in the stock and bond markets covaries. Although the unconditional correlation between stock and bond returns is low (Campbell and Ammer, 1993), there are strong volatility linkages between the two markets (Fleming, Kirby and Ostdiek, 1998), which can affect liquidity in both markets by altering the inventory risk borne by market making agents (Ho and Stoll, 1983, and O’Hara and Oldfield, 1986). Second, stock and bond market liquidity may interact via trading activity. In practice, a number of asset allocation strategies shift wealth between stock and bond markets. A negative information shock in stocks often causes a “flight to quality” as investors substitute safe assets for risky assets.
The resulting outflow from stocks into Treasury bonds may cause price pressures and also impact stock and bond liquidity. In other situations, stock and bond order flows may be complementary. For example, if the Federal Reserve pursues an expansionary monetary policy, the increase in funds could cause higher order inflows into both stocks and government bonds and potential changes in their liquidity. Further, systematic wealth or informational shocks could induce positively correlated trading activity across equity and fixed income securities, and, in turn, cause co-movements in liquidities across these markets. Overall, the preceding discussion implies that liquidity can exhibit co-movement across asset classes and also can be driven by common influences such as monetary shocks.
Motivated by these observations, in this paper we study the joint dynamics of liquidity, trading activity, returns, and volatility in stock and U.S. Treasury bond markets. While the extant literature has examined the dynamic interaction of liquidity and returns in stock markets (Hasbrouck, 1991) and time-varying liquidity in Treasury bond markets (Krishnamurthy, 2002), the intertemporal interactions of liquidity proxies with returns and volatility across these asset classes have not been examined. Our structural model allows us to distinguish the relative importance of order flow and return variability in affecting liquidity as well as price formation in the stock and Treasury bond markets.
We also seek to identify primitive factors that generate order flow in stock and bond markets and, possibly, induce correlated movements in liquidity. We examine the notion (Garcia, 1989) that the monetary stance of the Fed can affect liquidity by altering the terms of margin borrowing and alleviating borrowing constraints of dealers, and also consider the idea that fund flows into stock and bond markets can affect trading activity, and thereby influence liquidity. Earlier work has analyzed the effects of monetary policy and fund flows on financial markets, but has not directly addressed their impact on liquidity. For example, Fleming and Remolona (1997) and Fair (2002) document that monetary shocks are associated with large changes in bond and stock prices. For fund flows, Edelen and Warner (2001) and Boyer and Zheng (2002) show a positive association between aggregate flow and concurrent market returns, while Goetzmann and Massa (2002) document that fund flows affect price formation in equity markets. These findings indicate that fund flows and monetary factors can affect returns and volatility in addition to liquidity. Therefore, we explore the interaction of monetary factors and fund flows with liquidity, returns, volatility and order flow. Our analysis thus allows us to link microstructure liquidity (in the sense of transaction costs) and “macro liquidity” (in the sense of fund flows between sectors of the economy).
The results indicate that the time series properties of stock and bond liquidity possess similarities, such as common calendar regularities. There are cross-market dynamics flowing from volatility to liquidity. Further, we find that the correlations in liquidity and volatility innovations between bond and stock markets are positive and significantly different from zero, pointing to common influences across the markets.
Innovations to net borrowed reserves are contemporaneously associated with increased liquidity and also have modest ability to predict liquidity during periods of crises, suggesting that monetary loosening is associated with increased liquidity. We also find that innovations to flows to the stock and government bond sectors play a key role in forecasting liquidity. Overall, our results support the notion that money flows (in the form of bank reserves and mutual fund investments) account for part of the commonality in stock and bond market liquidity.
The rest of the paper is organized as follows. Section 2 describes how the liquidity data is generated, while Section 3 presents basic time-series properties of the data, and describes the adjustment process to stationarize the series. Section 4 performs daily vector autoregressions. Section 5 presents the analysis of monetary policy and mutual fund flows. Section 6 concludes.
Download
PDF Ebook An Empirical Analysis of Stock and Bond Market Liquidity
