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"Fedspeak", the stylized and often nuanced language used by the U.S. Federal Reserve, encodes implicit policy signals and strategic stances. The Federal Open Market Committee strategically employs Fedspeak as a communication tool to shape…

Communication is now a standard tool in the central bank's monetary policy toolkit. Theoretically, communication provides the central bank an opportunity to guide public expectations, and it has been shown empirically that central bank…

This article investigates whether the Federal Reserve Chair strategically controls facial expressions during FOMC press conferences and how these nonverbal cues affect financial markets. I use facial recognition technology on videos of…

This research article analyzes the language used in the official statements released by the Federal Open Market Committee (FOMC) after its scheduled meetings to gain insights into the impact of FOMC official statements on financial markets…

In this study, we analyze documents published by central banks using text mining techniques and propose a method to evaluate the policy tone of central banks. Since the monetary policies of major central banks have a broad impact on…

The Federal Reserve System (the Fed) plays a significant role in affecting monetary policy and financial conditions worldwide. Although it is important to analyse the Fed's communications to extract useful information, it is generally…

Recent developments in monetary policy by the Federal Reserve has created a need for an objective method of communication analysis.Using methods developed for text analysis, we present a novel technique of analysis which creates a semantic…

Forecasting central bank policy decisions remains a persistent challenge for investors, financial institutions, and policymakers due to the wide-reaching impact of monetary actions. In particular, anticipating shifts in the U.S. federal…

Monetary policy pronouncements by Federal Open Market Committee (FOMC) are a major driver of financial market returns. We construct the largest tokenized and annotated dataset of FOMC speeches, meeting minutes, and press conference…

This study examines the relationship between Federal Open Market Committee (FOMC) announcements and financial market network structure through spectral graph theory. Using hypergraph networks constructed from S\&P 100 stocks around FOMC…

This study explores the influence of FOMC sentiment on market expectations, focusing on cognitive differences between experts and non-experts. Using sentiment analysis of FOMC minutes, we integrate these insights into a bounded rationality…

Behavioral finance has become an increasingly important subfield of finance. However the main parts of behavioral finance, prospect theory included, understand financial markets through individual investment behavior. Behavioral finance…

The Federal Funds rate in the United States plays a significant role in both domestic and international financial markets. However, research has predominantly focused on the effects of adjustments to the Federal Funds rate rather than on…

Financial sentiment has become a crucial yet complex concept in finance, increasingly used in market forecasting and investment strategies. Despite its growing importance, there remains a need to define and understand what financial…

The Journal Impact Factor (IF), as a core indicator of academic evaluation, has not been systematically studied in relation to its historical evolution and global macroeconomic environment. This paper employs a period-based regression…

This paper offers a synthesis of the empirical literature on the effects of monetary policy. Using the findings from an extensive collection of meta-analyses, it evaluates the effectiveness of conventional and unconventional monetary policy…

The U.S. Federal Open Market Committee (FOMC) regularly discusses and sets monetary policy, affecting the borrowing and spending decisions of millions of people. In this work, we release Op-Fed, a dataset of 1044 human-annotated sentences…

Financial sentiment analysis plays a crucial role in decoding market trends and guiding strategic trading decisions. Despite the deployment of advanced deep learning techniques and language models to refine sentiment analysis in finance,…

Financial market like the price of stock, share, gold, oil, mutual funds are affected by the news and posts on social media. In this work deep learning based models are proposed to predict the trend of financial market based on NLP analysis…

Natural language processing (NLP) has recently gained relevance within financial institutions by providing highly valuable insights into companies and markets' financial documents. However, the landscape of the financial domain presents…