We present a theory of financial intermediary leverage cycles within a dynamic model of the macroeconomy. Intermediaries face risk based funding constraints that give rise to procyclical leverage and a procyclical share of intermediated credit. The pricing of risk varies as a function of intermediary leverage, and asset return exposure to intermediary leverage shocks earns a positive risk premium. Relative to an economy with constant leverage, financial intermediaries generate higher consumption growth and lower consumption volatility in normal times, at the cost of endogenous systemic financial risk. The severity of systemic crisis depends on intermediaries ’ leverage and net worth. Regulations that tighten funding constraints affect the systemic risk-return trade-off by lowering the likelihood of systemic crises at the cost of higher pricing of risk.

We propose a rational theory of momentum and reversal based on delegated portfolio management. A competitive investor can invest through an index fund or an active fund run by a manager with unknown ability. Following a negative cashflow shock to assets held by the active fund, the investor updates negatively about the manager’s ability and migrates to the index fund. While prices of assets held by the active fund drop in anticipation of the investor’s outflows, the drop is expected to continue, leading to momentum. Because outflows push prices below fundamental values, expected returns eventually rise, leading to reversal. Fund flows generate comovement and lead-lag effects, with predictability being stronger for assets with high idiosyncratic risk. We derive explicit solutions for asset prices, within a continuous-time normal-linear equilibrium.

This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in the paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Risk Appetite and Exchange Rates

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This paper provides a theory of money, whose value depends on the functioning of the intermediary sector, and a unified framework for analyzing the interaction between price and financial stability. Households that happen to be productive in this period finance their capital purchases with credit from intermediaries and from their own savings. Less productive household save by holding deposits with intermediaries (inside money) or outside money. Intermediation involves risk-taking, and intermediaries’ ability to lend is compromised when they suffer losses. After an adverse productivity shock, credit and inside money shrink, and the value of (outside) money increases, causing deflation that hurts borrowers even further. An accommodating monetary policy in downturns can mitigate these destabilizing adverse feedback effects. Lowering short-term interest rates increases the value of long-term bonds, recapitalizes the intermediaries by redistributes wealth. While this policy helps the economy ex-post, ex-ante it can lead to excessive risk-taking by the intermediary sector. Preliminary and Incomplete. We are grateful to comments by seminar participants at Princeton, Bank

This paper argues that the capacity of financial markets to aggregate information is diminished in times of distress, resulting in countercyclical economic uncertainty. I build upon a rational expectations equilibrium model that delivers this result from the combination of (i) countercyclical funding constraints faced by informed financial intermediaries, and (ii) the dispersed nature of information in the economy. During downturns, informed traders become increasingly exposed to non-fundamental price fluctuations (noise trading risk), which reduces information-based trading and the informativeness of asset prices. Uncertainty can spike quite dramatically as conditions deteriorate due to amplification mechanisms that arise from the dispersed nature of information, and the presence of information externalities in a dynamic environment.I show that heightened uncertainty leads to increased risk premia, Sharpe ratios, and stock price volatility even when attitude towards risk and the unconditional volatility of fundamentals remain constant. I also trace the implications for real investment decisions when firms learn about productivity from the observation of stock prices: uncertainty affects welfare by reducing the accuracy of investment and also reduces its level as a precautionary response of firms. The mechanism outlined suggests that the success of public liquidity provision in stabilizing markets depends crucially on the distribution of liquidity across agents.

We study the joint determination of fund managers ’ contracts and equilibrium asset prices. Because of agency frictions, investors make managers ’ fees more sensitive to performance and benchmark performance against a market index. This makes managers unwilling to deviate from the index and exacerbates price distortions. Because trading against overvaluation ex-poses managers to greater risk of deviating from the index than trading against undervaluation, agency frictions bias the aggregate market upwards. They can also generate a negative rela-tionship between risk and return because they raise the volatility of overvalued assets. Socially optimal contracts provide steeper performance incentives and cause larger pricing distortions than privately optimal contracts.

I develop a dynamic equilibrium model that incorporates incorrect beliefs about crash risk and use it to explain the available empirical evidence on financial booms and busts. In the model, if a long period of time goes by without a crash, some investors ’ perceived crash risk falls below the true crash risk, inducing them to take on excessive leverage. Following a drop in fundamentals, these investors de-lever substantially, both because of their high pre-crash leverage and because they now believe future crashes to be more likely. Together, these two channels generate a crash in the risky asset price that is much larger than the drop in fundamentals. The lower perceived crash risk after years with no crashes also means that the average excess return on the risky asset is low at precisely the moment when any crash that occurs would be especially large in size; moreover, it means that, in the event of a crash, some investors may default and banks may sustain large unexpected losses. Finally, the model shows how pre-crash warning signs can generate financial fragility. By reducing investors ’ optimism, warning signs also increase investors ’ uncertainty about their beliefs and thereby make them more likely to overreact to future bad news. ∗I am indebted to Nicholas Barberis and Jonathan Ingersoll for guidance and encouragement. I also thank George

We introduce banks, modeled as in Diamond and Rajan (JoF 2000 or JPE 2001), into a standard DSGE model and use this framework to study the role of banks in the transmission of shocks, the e¤ects of monetary policy when banks are exposed to runs, and the interplay between monetary policy and Basel-like capital ratios. In equilibrium, bank leverage depends positively on the uncertainty of projects and on the bank’s "relationship lender " skills, and negatively on short term interest rates. A monetary restriction reduces leverage, while a productivity or asset price boom increases it. Procyclical capital ratios are destabilising; monetary policy can only partly o¤set this e¤ect. The best policy combination includes mildly anticyclical capital ratios and a response of monetary policy to asset prices or leverage.

We show that a simple dynamic portfolio choice model can generate \risk panics" characterized by a rational self-ful lling surge in both risk and the volatility of risk. During a panic, a macro variable suddenly becomes the focal point for such a self-ful lling shift in beliefs about risk. This \sunspot-like " role comes on top of its usual role as a macro fundamental. When the variable is weak at the time of the panic (e.g. the net worth of leveraged institutions is low), it generates a large increase in perceived risk. Our model can account for the two stages of the recent crisis. A risk panic parallels the Fall 2008 events, characterized by a sharp increase in risk and volatility of risk, a large drop in asset prices, liquidity and leverage. At the same time the model accounts for the more muted behavior of these variables The recent nancial crisis came in the form of a one-two punch: it started in mid-2007 but a full scale nancial panic did not hit until the Fall of 2008. While the rst year saw a drop in equity prices, an increase in risk and a reduction in liquidity,