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Cited by 465

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Taking Stock: Monetary Policy Transmission to Equity Markets

Open access
Ehrmann, Michael, Fratzscher, Marcel·2004·Journal of Money, Credit, and Banking

Abstract

This paper analyses the effects of US monetary policy on stock markets.We find that, on average, a tightening of 50 basis points reduces returns by about 3%.Moreover, returns react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty.We show that individual stocks react in a highly heterogeneous fashion and relate this heterogeneity to financial constraints and Tobin's q.First, we show that there are strong industry-specific effects of US monetary policy.Second, we find that for the individual stocks comprising the S&P500 those with low cashflows, small size, poor credit ratings, low debt to capital ratios, high price-earnings ratios or high Tobin's q are affected significantly more.The use of propensity score matching allows us to distinguish between firmand industry-specific effects, and confirms that both play an important role.

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Metadata

Authors
Ehrmann, M., & Fratzscher, M.
Venue
Journal of Money, Credit, and Banking
Publisher
Project MUSE
Published
2004
Volume
36
Issue
4
Pages
719-737
ISSN
  • 0022-2879 (ISSN-L)
  • 1538-4616
OpenAlex
W2096527115
Cited by
465
References
47
FWCI
17.41
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Taking Stock: Monetary Policy Transmission to Equity Markets. https://app.cochat.ai/papers/10.1353/mcb.2004.0063
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Ehrmann, M., & Fratzscher, M. (2004). Taking Stock: Monetary Policy Transmission to Equity Markets. Journal of Money, Credit, and Banking. https://doi.org/10.1353/mcb.2004.0063

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.