This paper puts forward a manual for how to set up and solve a continuous time model that allows to analyze endogenous (1) level and risk dynamics. The latter includes (2) tail risk and crisis probability as well as (3) the Volatility Paradox. Concepts such as (4) illiquidity and liquidity mismatch, (5) endogenous leverage, (6) the Paradox of Prudence, (7) undercapitalized sectors (8) time-varying risk premia, and (9) the external funding premium are part of the analysis. Financial frictions also give rise to an endogenous (10) value of money.
This paper reviews some of the most prominent asset price bubbles from the past 400 years and documents how central banks (or other institutions) reacted to those bubbles. The historical evidence suggests that the emergence of bubbles is often preceded or accompanied by an expansionary monetary policy, lending booms, capital inflows, and financial innovation or deregulation. We find that the severity of the economic crisis following the bursting of a bubble is less linked to the type of asset than to the financing of the bubble – crises are most severe when they are accompanied by a lending boom, high leverage of market players, and when financial institutions themselves are participating in the buying frenzy. Past experience also suggests that a purely passive “cleaning up the mess” stance towards inflating bubbles in many cases is costly. At the same time, while interest-rate leaning policies and macroprudential tools can and sometimes have helped to deflate bubbles and mitigate the associated economic crises, the correct implementation of such proactive policy approaches remains fraught with difficulties.
This chapter surveys the literature on bubbles, financial crises, and systemic risk. The first part of the chapter provides a brief historical account of bubbles and financial crisis. The second part of the chapter gives a structured overview of the literature on financial bubbles. The third part of the chapter discusses the literatures on financial crises and systemic risk, with particular emphasis on amplification and propagation mechanisms during financial crises, and the measurement of systemic risk. Finally, we point toward some questions for future research.
This article surveys the macroeconomic implications of financial frictions. Financial frictions lead to persistence and when combined with illiquidity to non-linear amplification eects. Risk is endogenous and liquidity spirals cause financial instability. Increasing margins further restrict leverage and exacerbate the downturn. A demand for liquid assets and a role for money emerges. The market outcome is generically not even constrained ecient and the issuance of government debt can lead to a Pareto improvement. While financial institutions can mitigate frictions, they introduce additional fragility and through their erratic money creation harm price stability.
In many situations, timing is crucial—individuals face a trade-off between gains from waiting versus the risk of being preempted. To examine this, we offer a model of clock games, which we then test experimentally. Each player's clock starts upon receiving a signal about a payoff-relevant state variable. Since the timing of the signals is random, clocks are de-synchronized. A player must decide how long, if at all, to delay his move after receiving the signal. We show that (i) delay decreases as clocks become more synchronized, and (ii) when moves are observable, players “herd” immediately after any player makes a move. Our experimental results are broadly consistent with these two key predictions of the theory.
A reduction in inflation can fuel run-ups in housing prices if people suffer from money illusion. For example, investors who decide whether to rent or buy a house by simply comparing monthly rent and mortgage payments do not take into account the fact that inflation lowers future real mortgage costs. We decompose the price-rent ratio into a rational component-meant to capture the "proxy effect" and risk premia–and an implied mispricing. We find that inflation and nominal interest rates explain a large share of the time series variation of the mispricing, and that the tilt effect is very unlikely to rationalize this finding.
This paper documents that hedge funds did not exert a correcting force on stock prices during the technology bubble. Instead, they were heavily invested in technology stocks. This does not seem to be the result of unawareness of the bubble: Hedge funds captured the upturn, but, by reducing their positions in stocks that were about to decline, avoided much of the downturn. Our findings question the efficient markets notion that rational speculators always stabilize prices. They are consistent with models in which rational investors may prefer to ride bubbles because of predictable investor sentiment and limits to arbitrage.
We present a model in which an asset bubble can persist despite the presence of rational arbitrageurs. The resilience of the bubble stems from the inability of arbitrageurs to temporarily coordinate their selling strategies. This synchronization problem together with the individual incentive to time the market results in the persistence of bubbles over a substantial period. Since the derived trading equilibrium is unique, our model rationalizes the existence of bubbles in a strong sense. The model also provides a natural setting in which news events, by enabling synchronization, can have a disproportionate impact relative to their intrinsic informational content.
We argue that arbitrage is limited if rational traders face uncertainty about when their peers will exploit a common arbitrage opportunity. This synchronization risk—which is distinct from noise trader risk and fundamental risk—arises in our model because arbitrageurs become sequentially aware of mispricing and they incur holding costs. We show that rational arbitrageurs “time the market” rather than correct mispricing right away. This leads to delayed arbitrage. The analysis suggests that behavioral influences on prices are resistant to arbitrage in the short and intermediate run.