Yale School of Management

Working Papers

The Macroeconomics of Shadow Banking

(Local copy)

(with Alexi Savov)

Vox column

We build a macro-finance model in which intermediaries issue equity without friction. In normal times, they maximize liquidity creation by levering up the collateral value of their assets, a process we call shadow banking. A rise in uncertainty causes investors to demand liquidity in bad states, which forces intermediaries to delever and substitute toward safe liabilities; shadow banking shuts down, prices and investment fall. The model is consistent with a slow economic recovery especially when intermediary capital is high. It features collateral runs and flight to quality, and it provides a framework for analyzing unconventional monetary policy and regulatory reform proposals.

News Implied Volatility and Disasters Concerns

(with Asaf Manela)

We extend back to 1890 the volatility implied by options index (VIX), available only since 1986, using the frequency of words on the front-page of the Wall Street Journal. News implied volatility (NVIX) captures well the disaster concerns of the average investor over this longer history. NVIX is particularly high during stock market crashes, times of policy-related uncertainty, world wars and financial crises. We find that periods when people are more concerned with a rare disaster, as proxied by news, are either followed by periods of above average stock returns, or followed by periods of large economic disasters. We estimate that the disaster probability has a half-life of four to eight months and annual volatility of 4% to 6%. Our findings are consistent with the view that hard to measure time-varying rare disaster risk is an important driver behind asset prices.

Limits to Arbitrage and Lockup Maturities

This paper studies the interaction between a fund manager who has information regarding a long-term opportunity and investors who are uncertain about their manager. Investor behavior determines the fund liquidation risk. Manager portfolio decisions interact with investor behavior through the learning channel. A loop between limits to arbitrage and liquidation arises: higher liquidation risk pushes the manager to invest less in the long-term opportunity, which leads investors to liquidate the manager earlier, which feeds back into higher liquidation risk. The introduction of a lockup reduces limits to arbitrage, but also leads to managerial entrenchment. The optimal lockup maturity balances these two forces. For a calibration that matches moments of a hedge fund database, the model produces quantitatively large limits to arbitrage distortions and lockup maturities consistent with the data.

A Reputation Based Model of Limited Arbitrage

My model shows how limits to arbitrage arises endogenously from a positive self-enforcing feed-back between fund investors' liquidation decisions and manager's portfolio choice. A higher risk of fund liquidation leads managers to favor strategies that pay out quickly. Rational investors anticipate the managers' incentives, learn more from short-term performance and liquidate funds earlier. Investor's decisions feed back into the manager's portfolio through an additional reduction in the manager horizon, further amplifying the initial distortion. Equilibrium pricing reflects this fundamental delegation friction with mispricing becoming more severe as reputational capital becomes scarce.