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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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48 results for interest rate announcements

Investigates how 'green' labels affect bond market dynamics.

problem Understanding the impact of 'green' labels on bond market trading activity.
method Used Hawkes processes and a moving average model to analyze high-frequency bond price dynamics.
result Differences in bond market dynamics emerge during periods with interest rate announcements, especially for energy market issuers.

Study finds financial YouTube channel 3PROTV predicts stock market performance and sentiment changes.

problem Determining the informational value of financial YouTube channels.
method Analyzing 3PROTV's content and its impact on stock market performance and sentiment.
result 3PROTV's content, particularly negative sentiment, predicts stock market performance and sentiment changes.

We study the role of co-jumps in the interest rate futures markets. To disentangle continuous part of quadratic covariation from co-jumps, we localize the co-jumps precisely through wavelet coefficients and identify statistically significant ones. Using high frequency data about U.S. and European yield curves we quanti…

2019-05-04abs ↗pdf ↗

Investor emotions predict earnings announcements, but excitement lowers returns.

problem The impact of investor emotions on earnings announcements and their returns.
method Social media data analysis over a decade to test the relationship between investor emotions and earnings announcements.
result Excitement about earnings announcements is associated with lower announcement returns.

This study examines how earnings announcements affect option volatility and pricing.

problem The impact of earnings announcements on option volatility and pricing.
method Analysis of extremely short-term options data to study bimodality and concavity in IV curves.
result Investors pay a premium to hedge against extreme volatility during earnings announcements in the presence of concave IV smiles.

The study classifies policy announcements' impact on stock market volatility.

problem Evaluating the impact of Central Bank announcements on stock market volatility.
method Proposed a model-based classification method using Markov Switching dynamics and Multiplicative Error Model.
result Successful classification of 144 European Central Bank announcements on stock market volatility.

Predicts stock price changes based on clinical trial announcements.

problem Forecasting the impact of clinical trial results on pharma stock prices.
method BERT for sentiment analysis, Temporal Fusion Transformer for forecasting, graph convolution network for event relationships, gradient boosting for price change prediction.
result Identifies two crucial factors: drug portfolio size and network effect of related events.

Media tone around earnings announcements predicts stock returns.

problem Determining if media tone around earnings announcements provides useful information for stock prices.
method Conducted an event study on media tone around earnings announcements for nonfinancial S&P 500 firms.
result Media tone around earnings announcements predicts abnormal stock returns.

This article is an exposition of a body of existing results, together with an announcement of recent results. We discuss a theory of polytopes associated to bipartite graphs and trinities, developed by Kálmán, Postnikov and others. This theory exhibits a variety of interesting duality and triality relations, and extend…

2017-02-13abs ↗pdf ↗

The above title is the same, but with "semisimple" instead of "simple," as that of a notice by N. Kowalsky. There, she announced many theorems on the subject of actions of simple Lie groups preserving a Lorentz structure. Unfortunately, she published proofs for essentially only half of the announced results before her …

2006-01-09abs ↗pdf ↗

This study analyzes how the Indian stock market reacts to budget announcements using fractal methods.

problem Understanding the impact of Union Budget announcements on the Indian stock market.
method Utilizes fractal interpolation function and fractal dimensional analysis to study the NIFTY50 index over -15 to +15 days post-budget day.
result The budget announcements significantly affect the Indian stock market, as evidenced by average abnormal return and cumulative abnormal return.

We study an option pricing framework that accounts for the price impact of an earnings announcement (EA), and analyze the behavior of the implied volatility surface prior to the event. On the announcement date, we incorporate a random jump to the stock price to represent the shock due to earnings. We consider different…

2014-12-29abs ↗pdf ↗

This thesis identifies share buybacks and predicts their impact on stock performance.

problem Recognizing and predicting the impact of share buybacks on stock performance.
method NLP approaches for automated detection of share buybacks, machine learning models for prediction.
result Most companies underperform after a share buyback, but some significantly outperform.

Considered an important macroeconomic indicator, the Purchasing Managers' Index (PMI) on Manufacturing generally assumes that PMI announcements will produce an impact on stock markets. International experience suggests that stock markets react to negative PMI news. In this research, we empirically investigate the stock…

2018-06-12abs ↗pdf ↗

Study predicts stock price direction on earnings announcement days using multi-modal deep learning.

problem Predicting stock price movements during earnings announcements is challenging due to market noise and discontinuities.
method Constructed a multi-modal feature space combining fundamental metrics, technical indicators, and sentiment scores from financial news articles. Evaluated LSTM and Transformer models against a baseline.
result Transformer model outperforms LSTM in identifying volatile movements, achieving higher macro F1-score.

Study examines how COVID-19 affected India's exchange rates and stock market.

problem Impact of COVID-19 on India's financial markets during and after lockdown.
method Secondary data analysis using VAR models across different phases of lockdown and unlock.
result Increase in confirmed cases does not significantly affect exchange rate and stock market.

New framework predicts earnings announcements using press release content, surpassing earnings surprises.

problem Predicting stock returns based on earnings press releases.
method Compared traditional and BERT-based embeddings of press releases, finding content as informative as earnings surprises.
result FinBERT yields highest predictive power for earnings announcement returns.

Regulatory compliance is an organization's adherence to laws, regulations, guidelines and specifications relevant to its business. Compliance officers responsible for maintaining adherence constantly struggle to keep up with the large amount of changes in regulatory requirements. Keeping up with the changes entail two …

2019-08-20abs ↗pdf ↗

Configuration spaces of distinct labeled points on the plane are of practical relevance in designing safe control schemes for Automated Guided Vehicles (robots) in industrial settings. In this announcement, we consider the problem of the construction and classification of configuration spaces for graphs. Topological da…

1999-05-05abs ↗pdf ↗

This study shows how monetary uncertainty affects stock market reactions to macroeconomic news.

problem Understanding stock market reactions to macroeconomic news under varying levels of monetary uncertainty.
method Decomposes stock market response into cash flow and risk-free rate channels, analyzing time-varying effects.
result High monetary uncertainty weakens the positive stock market response to macroeconomic news.

NAPLES resolves lead-lag analysis challenges in non-synchronous high-frequency data.

problem Challenges in analyzing lead-lag effects due to non-synchronous observations and high-frequency data.
method NAPLES (Negative And Positive lead-lag EStimator) resolves these challenges.
result NAPLES has a strong correlation with actual lead-lag effects, including those triggered by macroeconomic announcements.

We consider the problem of identifying current coupons for Agency backed To-be-Announced (TBA) Mortgage Backed Securities. In a doubly stochastic factor based model which allows for prepayment intensities to depend upon current and origination mortgage rates, as well as underlying investment factors, we identify the cu…

2015-10-07abs ↗pdf ↗

This paper quantifies the impact of Dow Jones Sustainability Index listing on stock returns.

problem Measuring the impact of listing on the Dow Jones Sustainability Index.
method A matching portfolio approach to analyze pre- and post-listing returns.
result Cumulative abnormal returns are significantly positive in the weeks leading to the official announcement.

This is the first in a series of four papers (with research announcement posted on this arXiv) that together develop a decomposition theory for subgroups of Out(F_n). In this paper we develop further the theory of geometric EG strata of relative train track maps originally introduced in the work of Bestvina, Feighn, an…

2013-02-10abs ↗pdf ↗

The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space - time and maturity. Geostatistical models and machine le…

2007-09-27abs ↗pdf ↗

Study proposes optimal risk-aware interest rates for crypto lending protocols.

problem Determining optimal interest rates for decentralized lending protocols to maximize profit and minimize risk.
method Agent-based model, Riccati-type ODEs for linear behaviors, Monte-Carlo estimator and deep learning for nonlinear behaviors.
result Calibrated model shows superior risk-adjusted performance compared to industry-standard interest rate models.

The paper identifies key macroeconomic events affecting exchange rate volatility.

problem Understanding which macroeconomic events impact exchange rate volatility.
method Data-driven approach to select relevant macroeconomic events using sparsity-based methods.
result The identified macroeconomic events significantly impact exchange rate volatility.