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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.

168,932 papers · 148 categories

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1234 · Feb 201319922001200920172026
48 results for announcements

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.

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 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.

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.

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.

The purpose of this note is to announce complete answers to the following questions. (1) For an essential simple loop on a 2-bridge sphere in a 2-bridge link complement, when is it null-homotopic in the link complement? (2) For two distinct essential simple loops on a 2-bridge sphere in a 2-bridge link complement, when…

2011-04-18abs ↗pdf ↗

The study reveals distinct patterns in retail investors' holding periods affecting stock returns.

problem Understanding the impact of retail investors' investment horizons on stock returns.
method Using self-reported holding periods from StockTwits, the study categorizes retail investors into long-horizon and short-horizon groups and analyzes their return patterns.
result Long-horizon retail investors exhibit underreaction to earnings announcements, while short-horizon investors show overreaction.

Paper uses machine learning to analyze stock market anomalies, predicting drift direction and portfolio performance.

problem Capturing dynamics of Post-Earnings-Announcement Drift (PEAD) using machine learning.
method Uses Extreme Gradient Boosting (XGBoost) with genetic algorithm optimization to analyze PEAD dynamics.
result Demonstrates how PEAD dynamics are influenced by different factors across sectors and quarters.

In this paper, we prove that each automorphism of the Torelli group of a surface is induced by a diffeomorphism of the surface, provided that the surface is a closed, connected, orientable surface of genus at least 3. This result was previously announced by Benson Farb for genus at least 4 and has recently been announc…

2003-11-14abs ↗pdf ↗

In this paper we announce the following result: ``Every manifold of dimension 3\ge3 admits a complete negatively Ricci curved metric.'' Furthermore we describe some sharper results and sketch proofs.

1992-10-01abs ↗pdf ↗

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 ↗

Proposes a new model to measure trade impact and information content in fluctuating markets.

problem Measuring price impact and information content of trades in a time-varying market setting.
method Non-linear observation-driven model for dynamically estimating market impact and information content.
result Market impact shows intraday patterns with large fluctuations, some of which are exogenous.

Skewness dispersion predicts future stock market returns, especially in months with monetary policy announcements.

problem Predicting future stock market returns using skewness dispersion.
method Cross-sectional analysis of firm-level realized skewness and stock market returns.
result Skewness dispersion is a significant predictor of future stock market returns, robust to various estimation methods.

Study shows SEC crypto classification led to significant market reactions.

problem Impact of SEC classification of crypto assets as securities.
method Event study methodology focusing on explicitly named crypto assets.
result Significant adverse market reactions, with returns plummeting 12% over one week.

We announce the classification of complete, almost embedded surfaces of constant mean curvature, with three ends and genus zero: they are classified by triples of points on the sphere whose distances are the asymptotic necksizes of the three ends.

1999-03-17abs ↗pdf ↗

We announce ultrametric analogues of the results of Kleinbock-Margulis for shrinking target properties of semisimple group actions on symmetric spaces. The main applications are S-arithmetic Diophantine approximation results and logarithm laws for buildings, generalizing the work of Hersonsky-Paulin on trees.

2005-06-26abs ↗pdf ↗

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.

The FCA improved insider trading regulation after 2012, reducing abnormal returns.

problem Regulation of insider trading before and after the UK Financial Services Act 2012.
method Event study methodology using abnormal returns analysis.
result Abnormal returns were reduced after the FCA took over from the FSA.

Study on sequential defaulting in financial networks, analyzing stability and optimal timing.

problem Understanding which banks default and how much they can fulfill in a sequential financial network.
method Sequential model of financial networks, analyzing stability and optimal timing of defaults.
result Stabilization time can heavily depend on the ordering of announcements, and finding the best time for default is NP-hard.