Industry Expertise (1)
Areas of Expertise (6)
The Alexander Henderson Award for Excellence in Economic Theory
William Larimer Mellon Fellowship
Marc Vellrath Fellowship
Carnegie Mellon University, Tepper School of Business: Ph.D., Economics 2014
Carnegie Mellon University, Tepper School of Business: M.S., Economics 2010
Indiana University, Bloomington: B.A., Economics 2006
Indiana University, Bloomington: B.S., Mathematics 2006
Artem Neklyudov, Batchimeg Sambalaibat
OTC markets exhibit a core-periphery network: 10-30 central dealers trade frequently and with many dealers, while hundreds of peripheral dealers trade sparsely and with few dealers. Existing work rationalize this phenomenon with exogenous dealer heterogeneity. We build a search-based model of network formation and propose that a core-periphery network arises from specialization. Dealers endogenously specialize in different clients with different liquidity needs. The clientele difference across dealers, in turn, generates dealer heterogeneity and the core-periphery network: The dealers specializing in clients who trade frequently form the core, while the dealers specializing in buy-and-hold investors form the periphery.
I build a dynamic search model of bond and CDS markets and show that allowing short positions through CDS contracts increases liquidity of the underlying bond market. This result contrasts with existing theories on derivatives, which show that derivatives fragment traders across the derivative and underlying markets and thereby decrease liquidity in the underlying cash market. I reach the opposite conclusion by endogenizing the aggregate number of investors. My results help explain how sovereign bond markets reacted to a naked CDS ban.
Federico Gavazzoni, Batchimeg Sambalaibat, Chris Telmer
A basic tenet of lognormal asset pricing models is that a risky currency is associated with low pricing kernel volatility. Empirical evidence indicates that a risky currency is associated with a relatively high interest rate. Taken together, these two statements associate high-interest-rate currencies with low pricing kernel volatility. We document evidence suggesting that the opposite is true, thus contradicting a fundamental empirical restriction of lognormal models. Our identification strategy revolves around using interest rate volatility differentials to make inferences about pricing kernel volatility differentials. In most lognormal models the two are monotonic functions of one another. A risky currency, therefore, is one with relatively low pricing kernel volatility and relatively low interest rate volatility. In the data, however, we see the opposite. High interest rates are associated with high interest rate volatility. This indicates that lognormal models of currency risk are inadequate and that future work should emphasize distributions in which higher moments play an important role. Our results apply to a fairly broad class of models, including Gaussian affine term structure models and many recent consumption-based models.
A defining friction of sovereign debt is the lack of collateral that can back sovereign borrowing. This paper shows that credit default swaps (CDS) can serve as collateral and thereby support more sovereign borrowing. By giving more bargaining power to lenders in ex-post debt renegotiations, CDS becomes a commitment device for lenders to extract more repayment from the debtor country. This ex-post disciplining effect during debt renegotiations better aligns the sovereign's ex-ante incentives with that of the lender. CDS alleviates agency frictions that are present in any lending contracts but are particularly difficult to mitigate in sovereign debt context. As a result, CDS enables the borrower to raise more external capital.