UCLA

This dissertation consists of three chapters that study dealer's endogenous search effort in over-the-counter (OTC) financial markets and its effect on asset's liquidity risk in U.S. corporate bond markets. In Chapter 1, I study dealer's search intensity using a transaction-level data set on U.S. corporate bonds. The main target of this chapter is to test whether dealer's search intensity is endogenously determined by their idiosyncratic states and how search intensity affects market efficiency. Existing literatures commonly do not consider dealer's continuous adjustment of search intensity in search-and-match models and there is no paper using transaction-level data to estimate the dealer-level state-dependent search intensity. In this paper, I propose a search-and-match model with dealers' endogeneous and state-dependent search intensity and estimate it using the TRACE data for the U.S. corporate bond market. I find that: [1] if we rank all dealers by their private valuations for holding the bond, the dealer of the middle-level private valuation will choose the highest level of search intensity, and she works as the "dealer of dealers" to reallocate bond positions from the low-type dealers to the high-type dealers; [2] the estimated model gives us a quantitative evaluation of the inefficiency due to the decentralized market structure. At the average level across all sub-markets in our sample, the model estimates that dealers' search cost is 0.75% of bond's face value, and there is on average 8.64% of bond positions being misallocated, comparing with a counterfactual frictionless market. In conclusion, the decentralized market structure generates 8.96% welfare loss relative to the frictionless one.

In Chapter 2, I study the correlation between corporate bond's misallocation among dealers and liquidity risk. This chapter bridges the literature on search-and-match models and the literature on explaining the non-default component of corporate bond's credit spread variations. In this paper, I propose a measure of bond's misallocation among dealers. This measure is based on a structural search-and-match model, and is defined as the cross-sectional covariance of dealers' idiosyncratic private valuations for holding the bond and their actual inventory positions in the bond. Using the TRACE data for the U.S. corporate bond market, I construct a panel data which contains yearly series of empirical estimates of bond's misallocation and liquidity risk, and verify that: at the bond level, a higher magnitude of misallocation among the dealers is associated with a higher magnitude of liquidity risk. This finding gives a preliminary market microstructural evidence supporting that: the distribution of market maker's states correlates with the magnitude of asset's liquidity risk.

In Chapter 3, I theoretically study the social optimal policy function of dealer's meeting technology in over-the-counter markets. This chapter contributes to the existing literature by considering the dealer-level state-dependent meeting technology in a random search model and obtaining explicit-form solutions of the social optimal policy functions. In the model, I allow the agents (dealers) to freely adjust their meeting technologies based on two types of idiosyncratic states: asset position and liquidity need. I find that in the social optimal policy functions, there is no intermediation in the sense that no dealer will choose to search simultaneously on both the buy side and sell side of the market. This result applies for a general form of search-cost function.