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Working papers

I propose a search-based model with dealers' endogeneous and state dependent search intensity and estimate it using the TRACE data for the U.S. corporate bond market. Theoretically and empirically, I find that: [1] dealers with a middle level of private valuation choose higher search intensities than other dealers and intermediate shares of bonds from low-type to high-type dealers and/or customers; [2] the estimated model indicates nontrivial market inefficiency that, taking the average across all markets in our sample, shows dealers' search cost is 0.75% of bonds' face value and for each bond there is on average 8.64% of total shares being mis-allocated to market participants with private valuations lower than the marginal investor in a frictionless market. The decentralized market structure generates an 8.96% welfare loss compared with the frictionless one; and [3] for each bond, the average level of search intensity across all dealers depends on how misallocated the bond is among the dealers in the cross section, which is measured by the covariance between dealers' private valuation and holding position. Across different bonds higher average search intensity implies higher exposure of bonds' yield spread to systemic search frictions.

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: [1] 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; [2] 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.