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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.

168,695 papers · 148 categories

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3977116154 · Jun 202019922001200920172026
48 results for sector constraints

Enhanced indexation with sector constraints using SSD for better portfolio performance.

problem Constructing a portfolio that outperforms a market index while respecting sector investment proportions.
method Subset second-order stochastic dominance (subset SSD) applied to asset subset constraints.
result Subset SSD approach outperforms S&P500 and standard SSD approaches.

Rigidity theorem for spherical sectors in Riemannian manifolds.

problem Rigidity of spherical sectors in Riemannian manifolds under overdetermined conditions.
method Analyzing solutions to the inhomogeneous Helmholtz equation with constant Dirichlet and Neumann boundary conditions.
result Spherical sectors are the only solutions under given conditions.

The dynamic network of relationships among corporations underlies cascading economic failures including the current economic crisis, and can be inferred from correlations in market value fluctuations. We analyze the time dependence of the network of correlations to reveal the changing relationships among the financial,…

2010-11-16abs ↗pdf ↗

We propose a model in which a spliced vector bundle (with an arbitrary number of gauge structures in the splice) possesses a geometry which do not split. The model employs connection 1-forms with values in a space-product of Lie algebras, and therefore interlaces the various gauge structures in a non-trivial manner. Sp…

1997-04-16abs ↗pdf ↗

The study examines biases in Kiva.org's microfinance platform and proposes methods to mitigate them.

problem Identifying and mitigating hidden biases in lender preferences for different sectors on Kiva.org.
method The study uses causal inference and regression models with Bayesian variable selection methods to investigate and quantify biases. Fairness constraints are then incorporated to maintain comparable results.
result The influence of economic factors and loan attributes on lender preferences varies by sector, and models can be adjusted to mitigate biases.

The paper finds a surprising positive correlation between upstreamness and downstreamness in global value chains.

problem The puzzling positive correlation between upstreamness and downstreamness in industries and countries.
method Analysis of a simple model of random Input/Output tables and experiments on empirical data.
result Upstreamness and downstreamness of the same industrial sector/country are positively correlated with a slope close to +1.

The study designs inherently interpretable machine learning models for high-risk sectors.

problem The need for transparent and explainable machine learning models in regulated industries.
method Qualitative template based on feature effects and model architecture constraints for assessing inherent interpretability.
result Demonstrates the design and evaluation of an interpretable ReLU DNN model for predicting credit default.

Framework ranks sectors influenced by Indian Union Budgets.

problem Real-time analysis of budgetary impacts on sector-specific equity performance.
method Fine-tuned embeddings and language models for sector identification and performance ranking.
result 0.997 NDCG score in predicting sector ranks based on post-budget performances.

For a finitely generated discrete group ΓΓ, the ΓΓ-sectors of an orbifold QQ are a disjoint union of orbifolds corresponding to homomorphisms from ΓΓ into a groupoid presenting QQ. Here, we show that the inertia orbifold and kk-multi-sectors are special cases of the ΓΓ-sectors, and that the ΓΓ-sectors are orbif…

2009-02-06abs ↗pdf ↗

Study compares information flow between Chinese and US stock sectors.

problem Analyzing how information flows between sectors in Chinese and US stock markets.
method Daily sector indices, transfer entropy of daily returns, comparing 2000-2017.
result Most active sectors in information exchange differ between China and US, reflecting market dynamics.

Market sectors play a key role in the efficient flow of capital through the modern Global economy. We analyze existing sectorization heuristics, and observe that the most popular - the GICS (which informs the S&P 500), and the NAICS (published by the U.S. Government) - are not entirely quantitatively driven, but rather…

2019-05-31abs ↗pdf ↗

Study uses multidimensional SE-NBD process to analyze default portfolios and identify shock amplification.

problem Analyzing interactions and shock propagation in default portfolios with multiple sectors.
method Applied multidimensional self-exciting negative binomial distribution (SE-NBD) process to 13 sectors.
result Identified upstream and downstream sectors, showing shock amplification in default portfolios.

With the network methods and random matrix theory, we investigate the interaction structure of communities in financial markets. In particular, based on the random matrix decomposition, we clarify that the local interactions between the business sectors (subsectors) are mainly contained in the sector mode. In the secto…

2014-05-31abs ↗pdf ↗

This study analyzes information flow networks in Chinese stock sectors using transfer entropy.

problem Understanding information transmission and market dynamics in Chinese stock sectors.
method Daily closing price data of 28 sectors from 2000 to 2017, transfer entropy, maximum spanning arborescence (MSA).
result The composite sector is an information source, and the non-bank financial sector is an information sink.

The paper analyzes Indian stock sectors using multifractal analysis for long and short-term investment.

problem Investment risk and stability in Indian stock sectors.
method Sector-wise multifractal analysis of Bombay Stock Exchange, India, over short and long time scales.
result Long-term investment in stable sectors is more profitable, while sectors with large fluctuations may lead to downturns.

The study finds significant financial sector volatility and tail risk spillovers to real economy sectors.

problem Volatility and tail risk spillovers from financial to real economy sectors.
method New measure of tail risk spillover, empirical analysis of U.S. economy 2001-2011.
result Significant volatility and tail risk spillovers from financial to real economy sectors, especially during crises.

Proposes a two-stage sector rotation method using machine learning and deep learning.

problem Identifying sectors with high investment attractiveness based on market conditions.
method Two-stage methodology: 1) Predict ETF prices using market indicators and feature selection, 2) Rank sectors based on predicted returns and select top sectors.
result The proposed methodology outperforms equally weighted portfolios and Echo State Networks show outstanding performance.

Factor analysis is a statistical technique employed to evaluate how observed variables correlate through common factors and unique variables. While it is often used to analyze price movement in the unstable stock market, it does not always yield easily interpretable results. In this study, we develop improved factor mo…

2014-08-11abs ↗pdf ↗

Quantum model outperforms classical in training but underperforms in real-world metrics.

problem Mismatch between proxy reward signals and true investment objectives in financial domains.
method Hybrid quantum-classical reinforcement learning framework with automated feature engineering.
result Quantum models achieve higher training rewards but underperform in real-world metrics.

A classification of companies into sectors of the economy is important for macroeconomic analysis and for investments into the sector-specific financial indices and exchange traded funds (ETFs). Major industrial classification systems and financial indices have historically been based on expert opinion and developed ma…

2015-03-20abs ↗pdf ↗

Temporal coarse-graining of multi-sector default count data generates effective correlation matrices and rank copulas.

problem Explaining the difference in default dependence between monthly and annual aggregation.
method Dynamic low-rank state-space model with AR(1) latent credit-state factors.
result Effective correlation matrices and rank copulas are generated from monthly default count data.

New techniques identify shifts in financial market sectors.

problem Identifying shifts in financial market structure and composition.
method Developed new mathematical techniques to identify nonlinear shifts in market sectors.
result Identified meaningful sector-to-sector mappings and optimal portfolio styles.

Bangladesh's banking sector improved through financial reforms, but challenges remain.

problem Weak asset quality, inadequate provisioning, and negative capitalization of state-owned banks.
method Two phases of reforms: private ownership promotion and gradual deregulation.
result Significant improvements in asset quality and capitalization, but challenges persist.

The purpose of this study is to estimate the production function and examine the structure of production in the mining sector of Iran. Several studies have already been conducted in estimating production functions of various economic sectors; however, less attention has been paid to mining sectors. After examining the …

2015-09-12abs ↗pdf ↗

We consider the isoperimetric problem in planar sectors with density rpr^{p}, and with density a>1a>1 inside the unit disk and 11 outside. We characterize solutions as a function of sector angle. We also solve the isoperimetric problem in Rn\mathbb{R}^{n} with density rp,  p<0r^{p},\; p<0.

2010-12-02abs ↗pdf ↗

In this paper, we perform a comparative segmentation and clustering analysis of the time series for the ten Dow Jones US economic sector indices between 14 February 2000 and 31 August 2008. From the temporal distributions of clustered segments, we find that the US economy took one and a half years to recover from the m…

2009-11-25abs ↗pdf ↗

This paper studies business cycle patterns in UK sectoral output. It analyzes the distinction between white noise processes and their non-white noise counterparts in the frequency domain and further examines the associated features and patterns for the process where white noise conditions are violated. The characterist…

2010-01-26abs ↗pdf ↗

This study optimizes stock portfolios for Indian sectors using historical data.

problem Challenges in optimizing stock portfolios due to volatility and future value estimation.
method Used Sharpe, Sortino, and Calmar ratios to design mean-variance optimized portfolios.
result Identified the ratio that maximizes cumulative returns for most sectors.

We analyze the sectoral dynamics of startup venture financing. Based on a dataset of 52000 start-ups and 110000 funding rounds in the United States from 2000 to 2017, and by applying both Principal Component Analysis (PCA) and Tensor Component Analysis (TCA) in sector space, we visualize and measure the evolution of th…

2019-06-05abs ↗pdf ↗

The paper models financial markets and real economy interactions using a large agent framework.

problem Understanding capital allocation and accumulation in financial markets and real economy interactions.
method Developed a field-formalism model to analyze interactions between financial markets and real economy with a large number of heterogeneous agents.
result The number of firms in each sector depends on the aggregate financial capital invested and expected long-term returns.