Johannes Beutel

This paper studies green investing using data from a representative survey of German households that inform a quantitative asset pricing model. We document substantial heterogeneity in nonpecuniary benefits and hedging across the wealth distribution, as well as sizeable unmet demand for green deposit accounts.  Model counterfactuals show that optimism about green equity returns, rather than tastes, is currently responsible for the greenium. Introducing green deposits at a spread would not crowd out green equity but increase overall green investment. Feeding results from an RCT into the model, we show green equity could increase with better information about green finance.

We show  that selective recall of events spanning six decades shapes beliefs about rare downside outcomes in a representative survey. Recalled memories exhibit both recency and primacy: events close to the time of recall and early-life experiences  are disproportionately likely to come to mind. The impact of memories on tail beliefs is governed by similarity and interference: memory negativity is strongly associated with perceived stock market crash risk, even controlling for objective lifetime experiences. Rather than simply shifting subjective return distributions, selective recall changes their perceived shape by disproportionately affecting downside risk. Belief updating is consistent with a memory-based model in which similarity, representativeness, and interference determine how new information is interpreted. Households adjust their portfolio allocations only in response to higher perceived tail risks, and perceived safe-haven assets depend on the type of tail event. 

Biases in investor expectations can affect welfare by driving asset prices away from fundamentals, giving rise to boom-bust cycles. We study the optimal design of public signals in asset markets where heterogeneous investors differ in their  belief formation. In our model, a social planner chooses how to disclose the realization of a private signal to maximize social surplus. Full disclosure is optimal only when investors' belief formation is sufficiently homogeneous and close to rational. Otherwise, no disclosure is optimal, as communication can amplify disagreement and reduce risk-sharing.  Moreover, disclosure  can cause over- or under-production of risky assets when investors overreact to signals. With short-sale constraints, partial disclosure can be optimal. Communication is more effective in the early phase of an asset price boom, before behavioral investors’ priors have become too entrenched. 

Limits of arbitrage can explain why hedge funds and other investors do not take large counter-cyclical positions in the aggregate equity market, but they leave open the question of who buys when markets crash and who sells during booms. We address this long-standing puzzle using transaction-level data on the universe of  trades across major European equity and interest rate cash and derivatives markets. We classify investors into sectors and quantify, at horizons from 15 minutes to one month, which sectors absorb the net flows of the most pro-cyclical investors (asset managers). We find  dealer banks are the dominant liquidity providers across markets. At daily frequency, they absorb nearly the entire net flow of asset managers, while principal trading firms and hedge funds absorb only about 10% and 5%, respectively. Long-term investors trade pro-cyclically, amplifying rather than offsetting flows. Our results provide direct evidence for the conjecture in the intermediary asset pricing literature that dealer banks are key liquidity providers across different asset classes.

We causally test alternative theories of expectation formation.  Using a randomized information experiment we show overreaction is a key feature of individuals' return expectations, and individuals' response to the price-earnings ratio is opposite to the academic consensus.  Our evidence is inconsistent with standard models of expectation formation but subjective mental models that deviate from objective benchmarks can jointly explain the updating behavior in the experiment,  the link between individuals' prior perceptions and expectations, and the heterogeneity of updating. Conditional on their beliefs, individuals' sensitivity of equity shares in a hypothetical portfolio choice experiment is consistent with the standard Merton model.

We study the link between the global financial cycle and macroeconomic tail risks using quantile

vector autoregressions. Contractionary shocks to financial conditions and monetary policy in the

United States cause elevated downside risks to growth around the world. By tightening financial

conditions globally, these shocks affect the left tail of the conditional output growth distribution

more strongly than the center of the distribution. This effect is particularly pronounced for countries 

with less flexible exchange rate arrangements, higher foreign currency exposures, and higher

levels of private sector leverage, suggesting that exchange rate policies and macroprudential

policies can mitigate downside risks to growth.

Central bank communication about financial stability causally affects individuals’ beliefs and risk-taking behavior, consistent with an expectations channel of financial stability communication. Individuals receiving a warning from the central bank in a randomized information experiment expect a higher probability of a financial crisis and reduce their demand for risky assets. This reduction is driven by downward revisions in individuals’ expected Sharpe ratios due to lower expected returns and higher perceived downside risks. In addition, these individuals deposit a smaller fraction of their savings at riskier banks.

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

Investors’ subjective capital gains expectations are a key element explaining stock price fluctuations.  Survey measures of these expectations display excessive optimism (pessimism) at market peaks (troughs). We formally reject the hypothesis that this is compatible with rational expectations. We incorporate subjective price beliefs with such properties into a standard asset-pricing model with rational agents (internal rationality). The model gives rise to boom-bust cycles that temporarily delink stock prices from fundamentals. It quantitatively replicates many asset-pricing moments, including the observed strong positive correlation between the price dividend ratio and survey return expectations, which cannot be matched by rational expectations. 

We present a stock market model that quantitatively replicates the joint behavior of stock prices, trading volume and investor expectations. Stock prices in the model occasionally display belief-driven boom and bust cycles that delink asset prices from fundamentals and redistribute considerable amounts of wealth from less to more experienced investors. Although gains from trade arise only from subjective belief differences, introducing financial transactions taxes (FTTs) remains undesirable. While FTTs reduce the size and length of boom-bust cycles, they increase the likelihood of such cycles, thereby overall return volatility and wealth redistribution. Contingent FTTs, which are levied only above a certain price threshold, give rise to problems of equilibrium multiplicity and non-existence.

We use the Covid-19 pandemic as a natural experiment to estimate the effects of a global disaster shock on economic activity, international trade, and financial markets. To identify the shock, we exploit cross-country variation in the timing and intensity of pandemic-induced social distancing at daily frequency. An unexpected reduction in human mobility relative to pre-pandemic levels leads to significant declines in high-frequency measures of global economic activity, such as daily nitrogen dioxide concentrations and daily maritime trade carried by large cargo ships. Global stock markets decline, and sovereign credit spreads persistently widen after the pandemic disaster shock.