During financial crises, distressed companies often hold the troubled assets for a long time. For example, years after the crisis started since 2007, there is little sign that major banks have offloaded much of the alphabet soup of debt that caused repeated write-downs, including the mortgage-backed securities (MBS), collateralized debt obligations (CDO), etc. The inability or unwillingness to sell via the market channel raises the concern with market liquidity. Curiously, the banks’ burdens of troubled assets coexist with large amount of outside capital that can be a potential source of liquidity yet, for some reasons, has not stepped in. For example, as of the first quarter of 2008, there are $3.4 trillion, $5.3 trillion, and $7.8 trillion of money market funds, Treasuries (excluding Agency and Government Sponsored Enterprise (GSE)), and time/saving deposits respectively, according to the Federal Reserve statistical release (2008). As of the second half of 2007, the notional amount of interest rate/foreign exchange derivatives and equity derivatives totaled $382 trillion and $10 trillion respectively (International Swaps and Derivatives Association (2007)). Although many of the derivatives positions are for hedge purposes, the data suggest neither a lack of capital nor a lack of appetite for risk. What reasons then delay the capital from flowing to the trouble assets?
This paper uses a dynamic model of heterogeneous beliefs to study the provision of market liquidity. In this model, investors have different priors at the start of a downturn and update their beliefs based on Bayesian learning from common information. In another word, the investors agree to disagree (Aumann (1976)). Trade (liquidity provision) opportunity arrives when beliefs cross, i.e., when an initial pessimist becomes more optimistic than an initial optimist that holds the troubled asset.
Sovereign debt crises in emerging markets are usually associated with liquidity and banking crises. The conventional view is that such domestic financial turmoil is caused by foreign retaliation, as trade sanctions or exclusion from international financial markets. Yet, this interpretation is controversial. First, there is no clear-cut empirical evidence supporting the application of “classic” penalties. Second, in recent sovereign crises (e.g. Argentina 2001 and Russia 1998) government default had a direct “balance-sheet” effect on domestic financial institutions, since a large fraction of public debt was held domestically (see Mishkin (2006)). In this paper, I study the connection between sovereign defaults and liquidity crises in absence of external penalties.
The model builds on two natural assumptions for emerging markets. First, public debt represents a source of liquidity for the private sector. Indeed, limited enforcement restricts the access to spot credit markets and induces firms to save in government bonds (either directly or indirectly through the banking sector) as a financial buffer that can be drawn in case of unexpected investment opportunities. This is consistent with the negative correlation between creditor rights protection and banks’ holdings of government debt observed in the data. Second, the government cannot discriminate between domestic and foreign bond holders in the event of default. This assumption, which stems from the increasing integration of domestic financial markets, is consistent with the large haircuts suffered by domestic financial institutions on their government debt holdings observed in recent debt crises.
Much recent attention has focused on modeling high frequency stock price behavior. On the theoretical side, the blossoming area of market microstructure is providing valuable insights into the trade by trade stock price process. On the empirical side, a wealth of research has focused on capturing salient features of calendar period stock data, including conditional heteroskedasticity in calendar period price changes, or stochastic volatility. We provide a theory based link among asymmetric information, the behavior of market participants, and stochastic volatility through a market microstructure model of securities markets.
Our work follows on from Kelly and Steigerwald (2000), in which the stochastic properties of calendar period trades and squared price changes are derived from a market microstructure model. In the current paper, we make two principle contributions. First, we consider a model in which trade occurs in an options market as well as the stock market. Working from the microstructure model of Easley, OGHara, and Srinivas (1998) we derive the dynamic pattern of trade across markets as well as the stochastic properties of trades and squared price changes for each market. Second, we obtain analytic expressions for the serial correlation in calendar period squared price changes and so can directly relate stochastic volatility to the parameters of the underlying model.
