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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.

168,657 papers · 148 categories

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11223243 · Oct 202419922001200920172026
48 results for beta stocks

We present a reactive beta model that includes the leverage effect to allow hedge fund managers to target a near-zero beta for market neutral strategies. For this purpose, we derive a metric of correlation with leverage effect to identify the relation between the market beta and volatility changes. An empirical test ba…

2019-11-03abs ↗pdf ↗

Study finds significant premium for low-beta stocks in firm-level idiosyncratic return distributions.

problem Understanding the role of common idiosyncratic quantile factors in asset pricing.
method Quantile factor analysis to extract common idiosyncratic quantile factors with asymmetric pricing effects.
result Significant premium for innovations to the lower-tail factor: high-beta stocks outperform low-beta stocks by around 7-8% per year.

Study examines time-varying betas and their volatility in bank interest income and expense margins.

problem Understanding the variability of bank betas and their impact on net interest margins.
method Used state-space methods to estimate time-varying betas and conditional volatility.
result Substantial variation in interest income and expense betas, leading to varying net interest margin coefficients.

The study explains how market-makers' hedging affects stock volatility during gamma-squeeze events.

problem Endogenous volatility amplification in option markets during gamma-squeeze events.
method Developed a theoretical framework linking hedging behavior and market turbulence, incorporating beta-normalized volatility.
result Low-beta stocks amplify volatility more during gamma-squeeze events.

Smart beta, also known as strategic beta or factor investing, is the idea of selecting an investment portfolio in a simple rule-based manner that systematically captures market inefficiencies, thereby enhancing risk-adjusted returns above capitalization-weighted benchmarks. We explore the idea of applying a smart strat…

2018-08-07abs ↗pdf ↗

Machine learning improves beta forecasts, enhancing equity valuation and portfolio performance.

problem Improving beta forecasts for better equity valuation and portfolio performance.
method Using machine learning on a large cross-section of US stocks with various firm characteristics.
result Machine learning improves out-of-sample performance of asymmetric beta measures.

Study uses CSIE to estimate portfolio volatility relative to market.

problem Estimating relative volatility risk of stock portfolios.
method Cross-sectional intrinsic entropy (CSIE) model to estimate cross-sectional volatility.
result Discover sets of symbols that outperform market indices in terms of return with similar or lower risk.

New estimator reveals intraday betas mainly driven by correlations.

problem Intraday fluctuations in market betas due to time-varying volatility.
method Proposes a novel subsampled quadrant estimator for high-frequency financial data.
result Intraday variation in betas primarily driven by intraday variation in correlations.

Investment strategy for NYSE stocks minimizes market correlation.

problem Minimizing market correlation for steady returns.
method Combining momentum, fundamentals, and analyst recommendations; feature selection; backtesting various portfolio construction methods.
result Risk parity outperformed other methods, offering higher Sharpe ratio and lower beta.

The study assesses carbon risk in investment portfolios and proposes new management strategies.

problem The impact of carbon risk on stock pricing and portfolio construction.
method Developed a BMG risk factor and estimated time-varying carbon beta using a multi-factor model.
result Carbon risk can be incorporated into portfolio construction to reduce unrewarded financial risks.

In an analysis of the US, the UK, and the German stock market we find a change in the behavior based on the stock's beta values. Before 2006 risky trades were concentrated on stocks in the IT and technology sector. Afterwards risky trading takes place for stocks from the financial sector. We show that an agent-based mo…

2015-04-23abs ↗pdf ↗

We investigate a solution for the problems related to the application of multivariate GARCH models to markets with a large number of stocks by restricting the form of the conditional covariance matrix. The model is a factor model and uses only six free GARCH parameters. One factor can be interpreted as the market compo…

2016-09-22abs ↗pdf ↗

CAPM interpretation is flawed; beta reflects proxy for underlying driver, not causal transmission.

problem Inconsistent interpretation of CAPM regression as contemporaneous causation.
method Formalized CAPM as a structural causal model and analyzed admissible three-node graphs.
result Contemporaneous betas act like proxies rather than mechanisms; genuine market-to-stock channel appears only at a lag.

Study examines tech stocks' reactions to Facebook data leak scandal.

problem Impact of Facebook data leak scandal on U.S. tech stocks.
method Clustering method to identify related companies, CAR to measure impact.
result Overall tech sector showed no adverse impact, but Facebook's performance was negatively affected.

Equity activity is an essential topic for financial market studies. To explore its statistical regularities, we comprehensively examine the trading value, a measure of the equity activity, of the 3314 most-traded stocks in the U.S. equity market and find that (i) the trading values follow a log-normal distribution; (ii…

2009-11-22abs ↗pdf ↗

The study examines stock splits and their effects on companies, managers, and shareholders.

problem Misunderstandings and confounding factors around stock splits and their impacts.
method Selected database analysis of nine recent events, examining market impact, trading volume, and shareholder base.
result Stock splits enhance trading volume, increase shareholder base, and improve market liquidity.

We introduce a model in which a regulator employs mechanism design to embed her human capital beta signal(s) in a firm's capital structure, in order to enhance the value of her post career change indexed executive stock option contract with the firm. We prove that the agency cost of this revolving door behavior increas…

2013-12-27abs ↗pdf ↗

We consider a model of stochastic volatility which combines features of the multiplicative model for large volatilities and of the Heston model for small volatilities. The steady-state distribution in this model is a Beta Prime and is characterized by the power-law behavior at both large and small volatilities. We disc…

2018-07-27abs ↗pdf ↗

Extended study improves covariance matrix estimation for portfolio managers.

problem Limited sample sizes and poor performance of PCA estimator in high-dimensional returns.
method Developed a more general shrinkage framework targeting further information.
result Improves the PCA estimator of beta by shrinking it toward a target.

Proposes logistic-beta process for modeling dependent probabilities with beta marginals.

problem Limited work on flexible and computationally convenient stochastic process extensions for dependent random probabilities.
method Introduces logistic-beta process with logistic transformation and beta marginals, capable of modeling dependence in discrete and continuous domains.
result Logistic-beta processes enable effective posterior inference and design of computationally tractable dependent Bayesian nonparametric models.

Study finds companies react negatively to material cybersecurity incident disclosures.

problem Understanding market reactions to cybersecurity incidents.
method Examined daily stock price movements of companies disclosing material cybersecurity incidents.
result Companies tend to experience negative price reactions after disclosing material cybersecurity incidents.

Study analyzes stock performance before, during, and after the pandemic.

problem Impact of the pandemic on stock performance and risk.
method Daily data of most traded companies in Colombia from 2015 to 2023, using minimum variance approach.
result Portfolio returns and risks varied significantly during the pandemic.

Study finds 'Dragon Kings' in stock market volatility during major economic crises.

problem Identifying significant deviations from normal market volatility.
method Analyzed S&P500 index volatility, categorized as Black Swans, Dragon Kings, or Negative Dragon Kings, using modified Generalized Beta and Generalized Beta Prime distributions.
result Observed 'potential' Dragon Kings that eventually turn into Negative Dragon Kings, with more pronounced phenomenon as time averaging increases.

A beta-negative binomial (BNB) process is proposed, leading to a beta-gamma-Poisson process, which may be viewed as a "multi-scoop" generalization of the beta-Bernoulli process. The BNB process is augmented into a beta-gamma-gamma-Poisson hierarchical structure, and applied as a nonparametric Bayesian prior for an infi…

2011-12-15abs ↗pdf ↗

The beta-Bernoulli process provides a Bayesian nonparametric prior for models involving collections of binary-valued features. A draw from the beta process yields an infinite collection of probabilities in the unit interval, and a draw from the Bernoulli process turns these into binary-valued features. Recent work has …

2011-06-03abs ↗pdf ↗

This paper introduces a new market-based carbon risk measure for portfolio optimization.

problem The challenge of measuring and managing carbon risk in investment portfolios.
method Develops a market-based carbon risk measure and applies it to minimum variance portfolio construction.
result Market-based carbon risk measures can complement fundamental-based approaches in portfolio optimization.

In this paper, the geometric meaning of (alpha,beta)-norms is made clear. On this basis, we introduce a new class of Finsler metrics called general (alpha,beta)-metrics, which are defined by a Riemannian metric and an 1-form. These metrics not only generalize original (alpha,beta)-metrics naturally, but also include so…

2012-09-05abs ↗pdf ↗

Beta-SOD detects and corrects noisy object re-identification using cosine similarity and Beta mixtures.

problem Noisy object re-identification in image datasets.
method Reframed Re-ID as a similarity task, using Siamese networks and Beta mixture models.
result Superior performance in noisy conditions compared to state-of-the-art methods.

This is a short description of graphic lambda calculus, with special emphasis on a duality suggested by the two different appearances of knot diagrams, in lambda calculus and emergent algebra sectors of the graphic lambda calculus respectively. This duality leads to the introduction of the dual of the graphic beta move…

2013-02-04abs ↗pdf ↗

Bayesian Beta regression for proportions in high dimensions with theoretical guarantees.

problem Modeling bounded continuous responses in high-dimensional settings with theoretical guarantees.
method Proposes a Bayesian approach using a tempered posterior with Horseshoe prior for shrinkage and variable selection.
result Demonstrates improved estimation accuracy and model interpretability in high-dimensional scenarios.

We describe the underlying probabilistic interpretation of alpha and beta divergences. We first show that beta divergences are inherently tied to Tweedie distributions, a particular type of exponential family, known as exponential dispersion models. Starting from the variance function of a Tweedie model, we outline how…

2012-09-19abs ↗pdf ↗

Study explores geometric structure and prior for beta-logistic distribution.

problem Understanding the geometric structure and prior distributions of the beta-logistic distribution.
method Exploring dual geometric structure and uncovering α\alpha-parallel prior.
result The beta-logistic distribution admits an α\alpha-parallel prior for any real number α\alpha.

Unified framework for scale-invariant representation learning using MAPCA.

problem Learning invariant representations in data.
method Metric-Aware Principal Component Analysis (MAPCA) based on generalized eigenproblem.
result MAPCA provides a unified geometric language for various self-supervised learning objectives.

This paper generalizes beta divergence beyond its classical form associated with power variance functions of Tweedie models. Generalized form is represented by a compact definite integral as a function of variance function of the exponential dispersion model. This compact integral form simplifies derivations of many pr…

2013-06-14abs ↗pdf ↗

We derive and approximate the conjugate prior of Dirichlet and beta distributions.

problem Intractability of conjugate prior for Dirichlet and beta distributions.
method Derive conjugate prior, define closed-form approximation, and provide algorithm.
result Closed-form approximation enables fully tractable Bayesian treatment.