Senior Economist at Deutsche Bundesbank. Research on asset pricing, expectations, and macro-financial tail risks.
Stock Price Booms and Expected Capital Gains
with Klaus Adam and Albert Marcet
American Economic Review, 2017, 107( 8):2352-2408
Presentations: Columbia University, University College London, London School of Economics, Yale University, Harvard University, Northwestern University, Stony Brook, IMF, University of Chicago, New York University, London Business School, Banque de France and Chicago Fed Conference on Asset Price Bubbles, 2017 AEA Meetings
Policy Coverage: Bubbles Tomorrow, Yesterday, but Never Today? (John C. Williams), Financial Stability and Monetary Policy: Happy Marriage or Untenable Union? (John C. Williams)
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.
Can a Financial Transaction Tax Prevent Stock Price Booms?
with Klaus Adam, Albert Marcet and Sebastian Merkel
Journal of Monetary Economics, 2015, 76:S90-S109
Presentations: JME Gerzensee Conference 2014, Deutsche Bundesbank, European Central Bank, CSEF-CIM-UCL Conference 2015, Barcelona Summer Forum on Finance and Macroeconomics 2015, Expectations in Dynamic Macroeconomic Models Conference 2015
Policy Coverage: Financial Literacy and Financial Stability (Claudia Buch)
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.
Toothless Tiger With Claws? Financial Stability Communication, Expectations, and Risk-taking
with Norbert Metiu and Valentin Stockerl
Journal of Monetary Economics, 2021, 120:53-69
We study the effects of central bank communication about financial stability on individuals’ expectations and risk-taking. Using a randomized information experiment, we show that communication causally affects individuals’ beliefs and investment behavior, consistent with an expectations channel of financial stability communication. Individuals receiving a warning from the central bank 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.
Does Machine Learning Help us Predict Banking Crises?
with Sophia List and Gregor von Schweinitz
Journal of Financial Stability, 2019, 45:100693
Policy Coverage: Deutsche Bundesbank Financial Stability Review 2017, 2018, 2019, 2021, 2022, German Financial Stability Committee 2018
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.
with Shifrah Aron-Dine, Monika Piazzesi, and Martin Schneider
Slides available. Draft coming soon.
Presentations: European Central Bank, University of Chicago Capstone Conference 22, Joint BoC-ECB-New York Fed Conference on Expectations Surveys 22, Bundesbank Spring Conference 23
Stylized facts on beliefs about green asset returns. Heterogenous agents model calibrated with survey data. Asset pricing implications and counterfactuals.
with Michael Weber
Reject and resubmit, Quarterly Journal of Economics
Presentations: Harvard Business School, University of Oxford, UC Berkeley, Washington University St. Louis, Deutsche Bundesbank, Federal Reserve Bank of San Francisco, ECB-FRBNY Conference on Survey Expectations 2021, ifo Conference on Macroeconomics and Survey Data 2022, UBC Winter Finance Conference 2022, UKY Finance Conference 2022, CEPR Workshop on Household Finance 2022, FIRS 2022, CEBRA 2022, SAFE Asset Pricing Workshop 2022, AFA 2023
We causally test alternative theories of expectation formation and asset pricing. Using a randomized information experiment we show: i) individuals form pro-cyclical beliefs, both about returns and earnings growth and don't respond to information about the aggregate price-earnings ratio; ii) individuals overreact to earnings growth and return news relative to the historical associations in the data; iii) individuals are heterogeneous both at the information acquisition and information processing stage. Their reaction to stock market news depends on their information preference; iv) beliefs and portfolio decisions are causally linked; conditional on their subjective beliefs, individuals' choices are consistent with the standard Merton model of portfolio choice. These results inform and guide the development of novel macro-finance models.
The Global Financial Cycle and Macroeconomic Tail Risks
with Lorenz Emter, Norbert Metiu, Esteban Prieto and Yves Schüler.
SSRN Discussion Paper 2020.
Presentations: European Central Bank, Deutsche Bundesbank, Central Bank of Ireland, Trinity College Dublin, 4th ESCB Research Cluster 3 Workshop, EEA 2020
Media Coverage: Financial Times Article "How to Powell-proof your economy, per the Bundesbank"
Policy Coverage: Deutsche Bundesbank Monthly Report (July 2021)
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.
Social Distancing and the Macrofinancial Consequences of Natural Disasters
with Friederike Fourné and Norbert Metiu
SSRN Discussion Paper, 2021
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.
Dynamics of Subjective Risk Premia
(by Stefan Nagel and Zhengyang Xu)
European Finance Association Meeting, August 2022
60431 Frankfurt am Main, Germany
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