Are dealers' search efforts endogeneous in decentralized markets? How do dealers' search efforts affect market efficiency? We propose a model with dealers choosing idiosyncratic search intensities, and estimate the model using transaction data on U.S. corporate bonds. We find that:  with dealers ranked by their private valuations for a bond, the middle-type dealer chooses the highest search intensity, and she reallocates bond positions from lower-type dealers to higher-type dealers;  the estimated model predicts that the search costs and bond misallocation in current OTC markets generate 13.7% welfare loss relative to a counterfactual frictionless market.
Agents' Meeting Technology in Over-The-Counter Market
This paper constructs a theoretical search model to study how agents (dealers) ex-post choose their meeting technologies, at both intensive and extensive margins, in a random search environment, and how the equilibrium solutions change with market friction. We find that: in market with higher level of search friction, dealers with extreme valuation types (either very high or very low) will choose to invest in more advanced meeting technology thus becoming the core dealers in the inter-dealer network; in market with lower level of search friction, dealers with intermediate valuation types will choose to become the core dealers. One policy implication is: in response to a certain form of aggregate liquidity shock, when systemic search friction is low, it is optimal to give priority funding-liquidity support to the periphery dealers in the inter-dealer network instead of the core dealers, which minimizes the decline in total market liquidity and maintains stability; when systemic search friction is high, it is instead optimal to give priority support to the core dealers. In social welfare analysis, we obtain a closed-form solution which gives the social optimal policy function of dealers' meeting technology. This policy function implies that it is social optimal to let dealer-owners with valuation types higher than a pre-determined marginal level to stop searching and also let dealer-nonowners with valuation types lower than that marginal level to stop searching.
Work in progress
Financial Intermediation and Risk Sharing among Heterogeneous Investors
This paper investigates how financial intermediary prices Arrow-Debru securities in an endowment economy with both centralized stock market and decentralized Arrow-Debru securities market. In this economy, investors are heterogeneous in both risk aversion and endowments of a risky stock which can be traded in the centralized stock market. To faciliate risk sharing, investors can also trade Arrow-Debru securities directly with financial intermediary, but not with each other. This paper gives explicit solutions to financial intermediary's optimal quoting strategy for Arrow-Debru securities and her maximized utility under different constraints. This paper mainly establishes:  financial intermediary's main sources of profit are monopoly power to quote bid and ask for Arrow-Debru securities due to entry barrier to the intermediary sector and also the characteristic of being risk neutral;  investors' total gain from risk sharing through Arrow-Debru securities market is larger when there is larger share of risky stock initially endowed to the more risk averse investor and/or the gap of stock dividend between good and bad states is larger. Finally, this paper characterizes the feedback effect of Arrow-Debru securities' prices in decentralized market on the stock price in centralized market.
Adverse Selection in Venture Capital Market
(with Mengbo Zhang)
This paper investigates the relationship between adverse selection and funding resource allocation in venture capital market. By using micro-level data of all rounds of venture capital funding in the U.S. between 1980 and 2017, we find that: the start-up firms that get first-round funding at an older age are more likely to raise a larger amount of money, but have worse ex-post performances by different measures. This result implies that the adverse selection problem is significant for a start-up firm's first-round funding in the U.S. venture capital market. To explain the empirical facts, we build a competitive search model in which VC investors can enter a series of submarkets to screen the unobserved qualities of start-up firms. The model predicts that start-up firms of high quality prefer the matching speed with VC investors to the amount of funds raised, which makes high-quality firms more likely complete first-round funding at their earlier ages than low-quality firms.