Revise and Resubmit at the Journal of Financial Economics
We estimate the liquidity multiplier and individual banks’
contribution to systemic risk in an interbank network using a structural model. Banks borrow liquidity
from neighbors and update their valuation based on neighbors' actions. When
the former (latter) motive dominates, the equilibrium exhibits strategic substitution (complementarity) of liquidity holdings, and a reduced (increased) liquidity
multiplier dampening (amplifying) shocks. Empirically, we find substantial and
procyclical network-generated risks driven mostly by changes of equilibrium
type rather than network topology. We identify the banks that generate most systemic risk and solve the
planner's problem, providing guidance to macro-prudential policies.
NBER SI 2018, Macro Finance Society, Bank of England, Cass Business School, Duisenberg School of Finance, Koc University, London School of Economics, Stockholm School of Economics, OSU Fisher
WFA , 5th Joint Bank of Canada / Payments Canada Workshop on Payment Systems, 2018 Fed/OFR Financial Stability: Markets and Spillovers
Jan 20, 2019 New Version!
Abstract: This paper analyzes the endogenous risk in economies where intangible capital is essential and its limited pledgeability induces firms' liquidity demand. Banks emerge to intermediate the liquidity supply by holding claims on firms' tangible capital and issuing deposits that firms hold to pay for intangible investment. A bubbly value of tangible capital arises and increases in banks' balance-sheet capacity. Its procyclicality induces firms' investment and savings waves, which feed into banks' risk-taking and amplify downside risks. The model produces stagnant crises and replicates several trends in the decades leading up to the Great Recession: (1) the rise of intangible capital; (2) the increase of firms' cash holdings; (3) the growth of financial intermediation; (4) the declining real interest rate; (5) the rising prices of collateral assets.
Presentations: WFA (Western Finance Association), European Winter Finance Summit (Best Paper Award), EFA (European Finance Association),
CEPR ESSFM Gerzensee, Society for Economic Dynamics, Econometric Society (North America), 7th HKUST Macro Workshop, CMU/OSU/Pittsburgh/Penn State conference; earlier version at:
Columbia University, Federal Reserve Bank of New York, Finance Theory
Group (parallel session), LBS Trans-Atlantic Doctoral Conference
We provide a dynamic asset-pricing model of cryptocurrencies/tokens on platforms and highlight their roles on endogenous user adoption. Tokens facilitate transactions among decentralized users and allows them to capitalize future growth of promising platforms. Tokens thus can accelerate adoption, reduce user-base volatility, and improve welfare. Token price increases non-linearly in platform productivity, users' heterogeneous transaction needs, and endogenous network size. The growth of user base starts slow, becomes explosive and volatile, and eventually tapers off. Our model can be extended to discuss platform token supply, cryptocurrency competition, and pricing assets under network externality.
Presentations: 2018 AAM-CAMRI-CFA Institute Prize in Asset Management, 2019 RCFS/RAPS Conf. at Baha Mar, CEPR ESSFM Gerzensee Workshop, Chicago Booth, City University of Hong Kong International Finance Conference, Emerging Trends in Entrepreneurial Finance Conference (Best Paper Award), Finance UC 14th International Conference, Georgetown University, HKUST Finance Symposium 2018, JOIM Conference on FinTech, London Finance Theory Group Summer Conference, MFA 2019 Norwegian School of Economics, Rome Junior Finance Conference, SEC DERA, Shanghai Forum, Stanford SITE, U Washington Foster School of Business, and UT Dallas Finance Conference
Abstract: The ratio of long- to short-term dividend prices, "price ratio" (pr), predicts one-year stock market return with an out-of-sample R2 of 19%. It subsumes the predictive power of price-to-dividend ratio (pd). The residual from regressing pd on pr predicts one-year dividend with an out-of-sample R2 of 30%. Our results hold outside the U.S. In an exponential-affine model, we show the key to understand these findings is the (lack of) persistence of expected dividend growth. We also characterize the risk of time-varying expected return: (1) the expected return is countercyclical; (2) the response of expected return (rather than expected dividend growth) accounts for the impact of monetary policy on stock price; (3) shocks to pr are priced in the cross-section, which serves as an ICAPM test of pr as an adequate proxy for the expected return.
Presentations: 16th Paris December Finance Meeting (Best Paper Award), 2019 RCFS/RAPS Conf. at Baha Mar, Econometric Society (North America), Fall Finance Conference at UT Dallas, HKUST Finance Symposium, Northern Finance Association (NFA), Örebro Workshop on Predicting Asset Returns
with Chen Wang, Nov 19, 2018
Abstract: Delegation bears an intrinsic form of uncertainty. Investors hire managers for their superior models of asset markets, but delegation outcome is uncertain precisely because managers' model is unknown to investors. We model investors' delegation decision as a trade-off between asset return uncertainty and delegation uncertainty. Our theory explains several puzzles on fund performances. It also delivers asset pricing implications supported by our empirical analysis: (1) because investors partially delegate and hedge against delegation uncertainty, CAPM alpha arises; (2) the cross-section dispersion of alpha increases in uncertainty; (3) managers bet on alpha, engaging in factor timing, but factors' alpha is immune to the rise of their arbitrage capital - when investors delegate more, delegation hedging becomes stronger. Finally, we offer a novel approach to extract model uncertainty from asset returns, delegation, and survey expectations.
Presentations: 2019 ASU Sonoran Winter Finance, CEPR ESSFM Gerzensee, Chinese University of Hong Kong, European Winter Finance Summit (EWFS), Geneva Workshop on Financial Stability, INSEAD, MFA 2019, University of Zurich
Abstract: As transaction and data hubs, e-commerce platforms are uniquely positioned to extend credit to users and have become leading players in FinTech. This paper provides the first evidence on how platform credit shapes the e-commerce market structure. Using data from Alibaba, we estimate the effects of platform credit to e-commerce merchants on the allocation of customer attention and the sales distribution of merchants. We explore two semi-experimental settings created respectively by the platform's algorithmic lending rules and shopping holidays. We find that platform credit accelerates the selection of merchants by customers, and thus, may help the platform attract more customers. Therefore, different from traditional lenders, a platform may extend credit not only for the loan profits but also to boost online activities.
Presentations: 2018 Finance, Organizations, and Markets (FOM) Conference, AFA 2019, Bank of Canada, FDIC Annual Bank Research Conference, Fed Board, NTU, NUS, MIT Econ, OSU Fisher