Federal Open Market Committee Research Articles

The Impact of Unexpected FOMC Actions on Corporate Earnings Expectations

This paper fills a gap in the literature by examining the impact of unexpected Federal Open Market Committee (FOMC) actions on the markets expectations of U.S. corporate earnings by examining the sell-side analysts' quarterly earnings forecasts from 1989 to 2022. This paper reveals a significant negative correlation between analysts' earnings forecasts and unexpected changes in the target interest rate. This correlation weakened after the Federal Reserves implementation of Forward Guidance as a monetary tool in 2004, which appears to enhance the market's ability to predict target rate adjustments. In addition, this paper shows that with a given amount of unexpected target rate changes, value firms display greater earnings forecast revisions from analysts than growth firms. Debt levels or profitability factors cannot fully explain this phenomenon. The findings of this paper contribute to the knowledge of how FOMC actions exert influence on equity valuations and the transmission mechanisms of monetary policies.

A Horizon‐Based Decomposition of Mutual Fund Value Added Using Transactions

ABSTRACTWe decompose mutual fund value added by the length of funds' holdings using transaction‐level data. We motivate our decomposition with a model featuring horizon‐specific investment ideas, where short‐term ideas are less scalable because the associated trades cannot be spread over time. Fund turnover correlates negatively with the horizon over which value is added and positively with price impact costs. As predicted, holdings of high‐turnover funds add a substantial amount of value in the first two weeks, of which more than 80% is earned on Federal Open Market Committee (FOMC) and earnings announcement days. Holdings of low‐turnover funds add value only over longer horizons.

Tales of Turbulence: BERT-based Multimodal Analysis of FED Communication Dynamics Amidst COVID-19 Through FOMC Minutes

AbstractThis study analyzes Federal Open Market Committee (FOMC) minutes using state-of-the-art Natural Language Processing techniques. We sought to investigate the effect of the global COVID-19 crisis on the FOMC minutes’ pattern and the strength of the Federal Reserve to influence inflation expectations through its primary press releases. To this end, we first quantified minutes leveraging domain-specific pre-trained Bidirectional Encoder Representations from Transformers models (FinBERTs). Then, we applied dynamic time warping to measure temporal sequence proximity over time. In addition, we built multivariable autoregressive integrated moving average models to verify our findings by injecting exogenous variables as indicator functions into the time series. The results suggest that the Federal Reserve has abstained from adjusting its tone and the forward-lookingness settings of its statements for the global pandemic. Therefore, the longstanding association of the FED's tone and forward-lookingness with consumers’ inflation expectations index has weakened during the global health crisis.

Forecasting Consumer Price Index with Federal Open Market Committee Sentiment Index

AbstractThe Federal Open Market Committee (FOMC) is a component of the Federal Reserve System responsible for overseeing open market operations. The FOMC meets roughly eight or more times per year to assess the economy of the United States. After each meeting, the FOMC releases a statement to the press outlining its assessment of the US economy and its monetary policy stance. The sentiment of these statements may have an influence on the US economy and financial markets. Using sentiment and correlational analyses, this research examines how the sentiment of these statements affects the US economy and financial markets by analyzing how FOMC statement sentiment is correlated with the Consumer Price Index (CPI), the National Financial Conditions Index (NFCI), and the Adjusted National Financial Conditions Index (ANFCI). We find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the US City Average CPI value associated with the month before and the month after the statement's release. We also find that there is no evidence to suggest there exists a correlation between an FOMC statement's sentiment and the NFCI value associated with the week before or the week after the statement's release. However, we do find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the ANFCI value associated with the week before and the week after the statement's release. We also found that out of the three models we tested (linear regression, vine copula regression, and Gaussian copula regression), the Gaussian copula regression model performs the best when forecasting the CPI and the ANFCI. Additionally, we find that when forecasting CPI values, the models that include FOMC statement sentiment are more accurate than the models that exclude FOMC statement sentiment.

The pre-FOMC announcement drift: short-lived or long-lasting? Evidence from financial and volatility markets

ABSTRACT We examine the effects of Federal Open Market Committee (FOMC) announcements accompanied by press conferences (PC) on both financial and volatility markets. We find a pre-FOMC announcement drift, signifying positive excess returns on equities prior to the FOMC announcement. However, the influence of the FOMC-PC announcements is short-lived, becoming insignificant shortly after the disclosure. This contrasts with findings from Lucca and Moench (2015), who report that the FOMC announcement’s impact is persistent (or long-lasting) in their studied timeframe. Furthermore, we identify a significantly negative return of the VIX both before and after the FOMC announcement. This contrasts with the transient nature of stock returns, suggesting an evolving relationship between stock returns and VIX movements. To exploit the FOMC announcement drift, we construct a profitable trading strategy but note that such coexistence of the profitable trading strategy with the short lived impact by FOMC announcement raises a concern whether FOMC justifies a large price movement around FOMC announcement.

Regional Dissent: Do Local Economic Conditions Influence FOMC Votes?

U.S. monetary-policy decisions are made by the 12 voting members of the Federal Open Market Committee (FOMC). Seven of these members, coming from the Federal Reserve Board of Governors, inherently represent national-level interests. The remaining five members, a rotating group of presidents from the 12 Federal Reserve districts, come instead from sub-national jurisdictions. Does this structure have relevant implications for the monetary policy-making process? In this paper, we first build a panel dataset on economic activity across Fed districts. We then provide evidence that regional economic conditions influence the voting behavior of district presidents. Specifically, a regional unemployment rate that is one percentage point higher than the U.S. level is associated with an approximately nine percentage points higher probability of dissenting in favor of looser policy at the FOMC. This result is statistically significant, robust to different specifications, and indicates that the regional component in the structure of the FOMC could matter for monetary policy.

Financial Markets' Perceptions of the FOMC's Data-Dependent Monetary Policy

Over the past ten years, the Federal Open Market Committee (FOMC) has repeatedly emphasized that future policy is data dependent. In this Economic Commentary, we investigate how financial markets expected future interest rates to change with the release of new data on inflation and labor market conditions. We find that the surprises in economic indicators have a stronger effect on the 2-year Treasury yield than on the expected federal funds rate to be set in the next FOMC meeting. This implies that markets understand that under the data-dependent approach, policy decisions do not heavily rely on the most recent data or short-run fluctuations, but, rather, rely more on the persistent trend of the economy. In addition, we observe that expected future interest rates have become more sensitive to surprises in inflation after 2022, suggesting that the FOMC's determination to reduce inflation has been well-understood by the markets.

Disclosure, Materiality Thresholds, and the Cost of Capital: Evidence from Federal Open Market Committee Announcements

We examine how managers’ disclosure decisions vary in response to monetary policy shocks. Specifically, we examine the extent to which firms issue Forms 8-K, press releases, and management forecasts following unexpected changes to the target federal funds rate. We find consistent evidence that unexpected decreases (increases) in the Federal Open Market Committee target rate lead to larger increases (decreases) in disclosure by firms that are more sensitive to monetary policy shocks. Furthermore, the disclosure response to target rate surprises is concentrated in Form 8-K items that require a materiality-based decision and hold when we examine a sample of M&A-participating firms. Extended tests show that our results are not attributable to changes in the cost of capital leading to increased disclosure because firms are simultaneously raising capital or hyping their stock. Overall, our results are consistent with arguments raised in recent research papers that changes in cost of capital influence firms’ materiality thresholds, which can affect their decision to disclose. This paper was accepted by Suraj Srinivasan, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01896 .

Yield curve momentum

Abstract I analyze time series momentum along the Treasury term structure. Yield curve momentum is primarily due to changes in the level factor of yields. Because yield changes are partly induced by changes in the federal funds rate, yield curve momentum is related to post-FOMC (Federal Open Market Committee) announcement drift. The momentum factor is unspanned by the information in the term structure today and is hence inconsistent with standard term structure, macrofinance, and behavioral models. I argue that the results are consistent with a model with unpriced longer term dependencies.

The Federal Reserve’s responses to the post-Covid period of high inflation

In the face of the COVID-19 pandemic in March 2020, the Federal Reserve committed to using its full range of tools to support the U.S. economy. Over the next year and a half, with progress on vaccinations and strong policy support, indicators of economic activity and employment strengthened while inflation moved higher. Faced with a tight labor market and elevated inflation, the Federal Open Market Committee (FOMC) began a process of unwinding the very accommodative stance of monetary policy and moving to a restrictive policy stance to address inflation pressures. Here we review the sequence of actions taken by the Committee between late 2020 and mid-2023 as well as discuss some issues it contemplated along the way; the table provides a chronological list of key events over this period.

When Bankers Go to Hail: Insights into Fed–Bank Interactions from Taxi Data

We introduce taxi ridership between the Federal Reserve (Fed) Bank of New York and large financial institutions headquartered in New York City as a novel proxy for Fed–bank face-to-face interactions. We document a negative relation between past Fed–bank interactions and future stock market returns, particularly on days around the Fed’s public announcements. We also find significantly elevated Fed–bank interactions immediately following the lifting of the Federal Open Market Committee blackout. Our findings suggest that the Fed increases its information gathering via face-to-face interactions when it possesses negative private information about the condition of the economy. This paper was accepted by Agostino Capponi, finance. Funding: This work was supported by the Muma College of Business Center for Analytics and Creativity at the University South Florida, the George Stigler Center for the Study of the Economy and the State, the Lynde and Harry Bradley Foundation, the University of Chicago Booth School of Business, the Liew Fama-Miller Fellowship, and the Fischer Black Fellowship. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.4885 .

Correction: Predicting the reaction of financial markets to Federal Open Market Committee post-meeting statements

Correction: Predicting the reaction of financial markets to Federal Open Market Committee post-meeting statements

The Dynamics of Turn-taking in Meetings of the Federal Open Market Committee

In applied linguistics relatively little empirical research has been devoted to the study of spoken language compared to written genres. This article aims to complement previous research by focusing on domain-specific language use in discussions of monetary policy held by the Federal Open Market Committee in the U.S. We take a corpus-based and discourse-analytic approach and explore the dynamics of turn-taking within this spoken genre based on a recently compiled corpus. In a bottom-up fashion, we explore the corpus with a view to documenting items used to manage the interaction in this formalised and highly specified communicative setting. The concordance and frequency functions of the corpus provide a good way of charting recurrent patterns in the sequential organisation of this discourse genre. Turn-taking is constrained in ways that are characteristic of the meeting genre. Parts of the meeting are dynamically interactive, while other parts are more monologic in nature. Transitions between speakers is regulated through various explicit and less explicit means. Although the chairperson has a particular role in this, the attendees also contribute to the regulation. Turn-regulating mechanisms are often formulaic in nature and turn transitions tend to co-occur with speech acts specific to the interactional setting, such as thanking, addressing a designated speaker, expressing agreement, asking for clarification, ensuring co-participation from others, etc. These functions vary according to their placement in the stretch of discourse that constitutes an agenda item or a meeting.  

Target rate factors in short rate models

This study investigates the risk associated with the uncertainties in the central bank monetary policy targets in the context of short interest rate models. A class of models is proposed which admits two channels of interest rate risk. In a prototypical case, the short duration channel handles the uncertainties in the target rates decided in the forthcoming Federal Open Market Committee meetings. The target rate factors can be calibrated on the market values of the Fed funds futures. The long duration channel has traditional risk factors. The episodes following the Covid-19 outbreak and the 2022 rate hikes are used as examples in an empirical study.

Hawkish or Dovish Fed? Estimating a Time-Varying Reaction Function of the Federal Open Market Committee's Median Participant

This paper estimates a time-varying reaction function of the median participant of the Federal Open Market Committee, using a Taylor rule with time-varying coefficients estimated on one- to three-year ahead median forecasts of the federal funds rate, inflation, and the unemployment rate from the Summary of Economic Projections (SEP). We estimate the model with Bayesian methods, incorporating the effective lower bound on the median federal funds rate projections. The results indicate that the monetary policy rule has become significantly more persistent after the pandemic than in the years prior, and it currently reacts strongly to inflation, at more than twice the responsiveness estimated prior to 2020. Our proposed policy rule produces accurate predictions of the median federal funds rate projections in real time for given SEP forecasts of inflation and the unemployment rate, suggesting that the median participant's reaction function is well-represented by our assumed Taylor rule with time-varying coefficients. Our results show that the median participant's reaction function becomes less persistent and less responsive to inflation yet more responsive to the output gap in anticipation of tighter monetary policy conditions. We also find that labor market activity, inflation, and macroeconomic uncertainty correlate significantly with the evolution of the time-varying coefficients of the rule. Finally, we show that in times of a less persistent policy rule or more responsiveness to inflation, markets perceive nominal bonds as better macroeconomic hedges.

Resurrecting the market factor: A case of data mining across international markets

In this paper, using the stepwise model selection method proposed by Harvey and Liu (2021), we study whether anomalies can explain the cross-sectional individual stock returns in 38 countries for the period between 1992 and 2018. Among the 95 anomalies examined, we document the following results: (1) the market factor is the single most dominant factor in explaining the cross-sectional equity returns both on individual and portfolio levels; (2) local, regional and global market factors are equally useful; (3) the dominant role of the market factor, regardless whether it is the local, regional, or global version, is concentrated in Federal Open Market Committee (FOMC) months. Collectively, the results support a strong role of the market factor in the integrated international equity markets.

Aspect-based Sentiment Analysis in Document - FOMC Meeting Minutes on Economic Projection

The Federal Open Market Committee (FOMC) within the Federal Reserve System is responsible for managing inflation, maximizing employment, and stabilizing interest rates. Meeting minutes play an important role for market movements because they provide the bird’s eye view of how this economic complexity is constantly re-weighed. Therefore, there has been growing interest in analyzing and extracting sentiments on various aspects from large financial texts for economic projection. However, Aspect-based Sentiment Analysis (ABSA) is not widely used on financial data due to the lack of large labeled dataset. In this paper, I propose a model to train ABSA on financial documents under weak supervision and analyze its predictive power on various macroeconomic indicators.

Predicting the reaction of financial markets to Federal Open Market Committee post-meeting statements

AbstractThis article examines the impact of Federal Open Market Committee (FOMC) statements on stock and foreign exchange markets with the use of text-mining and predictive models. We take into account a long period since March 2001 until June 2023. Unlike in most previous studies, both linear and non-linear methods were applied. We also take into account additional explanatory variables that control for the current corporate managers’ and retail customers’ assessment of the economic situation. The proposed methodology is based on calculating the FOMC statements’ tone (called sentiment) and incorporate it as a potential predictor in the modeling process. For the purpose of sentiment calculation, we utilized the FinBERT pre-trained NLP model. Fourteen event windows around the event are considered. We proved that the information content of FOMC statements is an important predictor of the financial markets’ reaction directly after the event. In the case of models explaining the reaction of financial markets in the first minute after the announcement of the FOMC statement, the sentiment score was the first or the second most important feature, after the market surprise component. We also showed that applying non-linear models resulted in better prediction of market reaction due to identified non-linearities in the relationship between the two most important predictors (surprise component and sentiment score) and returns just after the event. Last but not least, the predictive accuracy during the COVID pandemic was indeed lower than in the previous year.

Global Inflation Uncertainty and its Economic Effects

Policymakers, including Federal Open Market Committee (FOMC) participants, have been stressing the elevated level of uncertainty, especially related to inflation, and the challenge this poses for monetary policy. As seen in Figure 1, with few exceptions, FOMC participants see the level of uncertainty around their forecasts for core PCE inflation as high, compared to the average over the past 20 years.

A Comparative Textual Study of FOMC Transcripts Through Inflation Peaks

This paper examines how natural language processing algorithms, utilizing textual analysis, can aid in comprehending the decision-making process of the Federal Open Market Committee (FOMC) and the factors influencing its monetary policy decisions in periods of high inflation, specifically, Feb 1979–Dec 1986 and Feb 2018–Feb 2023. The analysis uncovers common themes such as the economy and growth, along with remarkable differences in the language used. Volcker's focus was on combating high inflation through interest rates, economic growth, and money supply, whereas Powell's focus centered on discussing inflation more than relevant policy responses such as interest rates or asset purchases. These findings suggest that unlike Powell, Volcker took high inflation as a given and concentrated on policy actions to fight inflation, which he successfully managed.