Monetary Policy through Exchange Rate Pegs: The Removal of the Swiss Franc‐Euro Floor and Stock Price Reactions
Gregor von Schweinitz, Lena Tonzer, Manuel Buchholz
International Review of Finance,
No. 4,
2021
Abstract
The Swiss National Bank abolished the exchange rate floor versus the Euro in January 2015. Using a synthetic matching framework, we analyze the impact of this unexpected (and therefore exogenous) policy change on the stock market. The results reveal a significant level shift (decline) in asset prices following the discontinuation of the minimum exchange rate. As a novel finding in the literature, we document that the exchange‐rate elasticity of Swiss asset prices is around −0.75. Differentiating between sectors of the Swiss economy, we find that the industrial, financial and consumer goods sectors are most strongly affected by the abolition of the minimum exchange rate.
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Measuring Market Expectations
Christiane Baumeister
NBER WORKING PAPER SERIES,
2021
Abstract
Asset prices are a valuable source of information about financial market participants' expectations about key macroeconomic variables. However, the presence of time-varying risk premia requires an adjustment of market prices to obtain the market's rational assessment of future price and policy developments. This paper reviews empirical approaches for recovering market-based expectations. It starts by laying out the two canonical modeling frameworks that form the backbone for estimating risk premia and highlights the proliferation of risk pricing factors that result in a wide range of different asset-price-based expectation measures. It then describes a key methodological innovation to evaluate the empirical plausibility of risk premium estimates and to identify the most accurate market-based expectation measure. The usefulness of this general approach is illustrated for price expectations in the global oil market. Then, the paper provides an overview of the body of empirical evidence for monetary policy and inflation expectations with a special emphasis on market-specific characteristics that complicate the quest for the best possible market-based expectation measure. Finally, it discusses a number of economic applications where market expectations play a key role for evaluating economic models, guiding policy analysis, and deriving shock measures.
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What Drives the Commodity-Sovereign Risk Dependence in Emerging Market Economies?
Hannes Böhm, Stefan Eichler, Stefan Gießler
Journal of International Money and Finance,
March
2021
Abstract
Using daily data for 34 emerging markets in the period 1994–2016, we find robust evidence that higher export commodity prices are associated with lower sovereign default risk, as measured by lower EMBI spreads. The economic effect is especially pronounced for heavy commodity exporters. Examining the drivers, we find that, first, commodity dependence is higher for countries that export large volumes of commodities, whereas other portfolio characteristics like volatility or concentration are less important. Second, commodity-sovereign risk dependence increases in times of recessions and expansionary U.S. monetary policy. Third, the importance of raw material prices for sovereign financing can likely be mitigated if a country improves institutions and tax systems, attracts FDI inflows, invests in manufacturing, machinery and infrastructure, builds up reserve assets and opens capital and trade accounts. Fourth, the country’s government indebtedness or amount of received development assistance appear to be only of secondary importance for commodity dependence.
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East Germany
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Dynamic Equity Slope
Matthijs Breugem, Stefano Colonnello, Roberto Marfè, Francesca Zucchi
Working Papers University of Venice "Ca' Foscari",
No. 21,
2020
Abstract
The term structure of equity and its cyclicality are key to understand the risks drivingequilibrium asset prices. We propose a general equilibrium model that jointly explainsfour important features of the term structure of equity: (i) a negative unconditionalterm premium, (ii) countercyclical term premia, (iii) procyclical equity yields, and (iv)premia to value and growth claims respectively increasing and decreasing with thehorizon. The economic mechanism hinges on the interaction between heteroskedasticlong-run growth — which helps price long-term cash flows and leads to countercyclicalrisk premia — and homoskedastic short-term shocks in the presence of limited marketparticipation — which produce sizeable risk premia to short-term cash flows. The slopedynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
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.
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