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…
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48 results for “sector structure”
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.
Model shows how sector structure and volatility clustering emerge in financial markets.
problem Understanding the microscopic generation mechanism of sector structure and volatility clustering in complex financial systems.
method Introduced a novel interaction mechanism, multi-level herding, in an agent-based model.
result Multi-level herding is the microscopic mechanism producing sector structure and volatility clustering.
Machine learning identifies 'canonical sectors' in US stocks.
problem Classifying companies into sectors for economic analysis and investments.
method Unsupervised machine learning of historical stock price returns.
result Emergent canonical sectors identified and their weights over time.
Study validates capital structure theories in Indian public sector banks.
problem Understanding the impact of capital structure on financial performance in Indian banks.
method Developed theoretical framework from capital structure theories, tested hypotheses using statistical techniques.
result Established relation between debt component and financial performance variables.
New method detects financial clustering influenced by sector and geography.
problem Detecting overlapping clusters in financial networks with multiple factors.
method Robust regression to remove sector and geography influences.
result Geography became more important for clustering after the 2008 financial crisis.
This paper explores differential and sector forms in tangent categories, finding rich structures and connections.
problem Understanding differential and sector forms in tangent categories.
method Investigates differential and sector forms in tangent categories, developing new equational presentations and structures.
result Sector forms in tangent categories form a symmetric cosimplicial object, with a subcomplex isomorphic to the de Rham complex of differential forms.
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.
Dynamic structure of stock communities: A comparative study between stock returns and turnover ratesq-fin.ST
Study community structures in Chinese stock markets using returns and turnover rates.
problem Detecting community structure in stock markets for financial dynamics and risk estimation.
method Used PMFG and infomap methods on a distance matrix to analyze community structures in both price returns and turnover rates.
result Community structures for turnover rates are more complex and sector effects are weaker compared to returns.
Estimates production function of Iran's mining sector, finding capital and labor intensive.
problem Estimating production function of Iran's mining sector.
method Used co-integration method and time-series data for 1976-2006, augmented Dickey-Fuller and Phillips-Perron tests for stationarity.
result Elasticity of production with respect to capital and labor are 0.44 and 0.41, respectively; technological progress positively affects output.
Temporal Coarse-Graining of Multi-Sector Default Count Data Generates Posterior-Implied Copulasq-fin.RM
This paper models default data to capture dynamic dependence across sectors.
problem Static models fail to explain monthly default dependence.
method Dynamic low-rank state-space model for monthly multi-sector default-count data.
result Effective correlation matrices and copulas are induced from monthly data.
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.
Temporal Coarse-Graining of Multi-Sector Default Count Data Generates Posterior-Implied Copulasq-fin.RM
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.
A new sector classification method outperforms existing ones in risk-adjusted returns.
problem Subjective sector classification heuristics like GICS and NAICS are not optimal.
method Learned sector classification using hierarchical clustering and reIndexer evaluation tool.
result 17-sector learned sector universe outperforms GICS and NAICS in backtests.
The study finds variations in ownership structure and efficiency across sectors in Malaysia.
problem Investigate variations in ownership structure and firm efficiency across sectors in Malaysia.
method Frequency distributions of ownership structure, DEA under CRS and VRS, stratified random sampling.
result There are variations in firm ownership structure and efficiency across sectors in Malaysia.
Study global geometry of dynamical systems with entire vector fields.
problem Understanding the global structure of equilibria and their basins.
method Step-by-step analysis of basins of centers, nodes, and foci; introduction of global elliptic sectors.
result Characterization of heteroclinic regions connecting equilibria.
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 Indian IT sector is strongly linked to global markets, while CG sector reflects domestic growth.
problem Analyzing the structural characteristics of Indian IT and CG sectors.
method Time series analysis and forecasting using R programming.
result The IT sector is strongly associated with global markets (DJIA and USD/INR), while CG sector is linked to domestic growth (NIFTY).
The study analyzes co-movements in Indian stock market sectors using network techniques.
problem Understanding co-movements among Indian stock sectors.
method Mesoscopic network analysis, recurrence analysis, partial correlations, multidimensional scaling, minimum spanning tree.
result Minimum spanning tree effectively separates technologically related sectors.
Study examines insurance sector linkages and systemic risk using dynamic spanning trees.
problem Interlinkages and systemic risk in the European insurance sector.
method Analysis of linkage dynamics and systemic risk using correlation networks, copulas, and minimum spanning trees.
result Minimum spanning trees describe linkage dynamics in the European insurance sector.
The study identifies persistent motifs in stock correlations for sector-neutral portfolio diversification.
problem Forecasting and diversification of sector-neutral portfolios using long-term correlations.
method Analysis of Triangulated Maximally Filtered Graphs (TMFG) generated from rolling windows of stock price log-returns, identifying persistent motifs.
result Persistent motifs in stock correlations can be used to forecast and diversify sector-neutral portfolios, reducing volatility.
Identifies key industrial sectors in S&P 500 states.
problem Understanding changing market conditions in financial markets.
method Clustering algorithm, XAI relevance scores, Bayesian change point analysis.
result Dominant sectors (energy and IT) determine market states.
The aim of this paper is to present a further contribution to the analysis of absolute convergence (and), associated with the neoclassical theory, and conditional, associated with endogenous growth theory, of the sectoral productivity at regional level. Presenting some empirical evidence of absolute convergence of prod…
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…
Study identifies key ESG variables for assessing financial risk.
problem Assessing financial risk from ESG data with many variables.
method Proposed framework for hierarchical ESG data, selecting relevant variables.
result Selected ESG variables are more relevant to financial risk than aggregated scores.
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…
The paper analyzes cryptocurrency and equity markets using advanced statistical methods.
problem Comparing dynamics and strategies between cryptocurrency and equity markets.
method Random matrix theory, PCA, spectral dynamics, structural break analysis, portfolio simulation.
result Cryptocurrency and equity markets exhibit distinct evolutionary dynamics and time-varying sector behaviors.
We study compactifications of type II theories on SU(2) x SU(2) structure manifolds to six, five and four spacetime dimensions. We use the framework of generalized geometry to describe the NS-NS sector of such compactifications and derive the structure of their moduli spaces. We show that in contrast to SU(3) x SU(3) s…
Model predicts Mozambique bank failures, aiding risk management.
problem Lack of bankruptcy prediction model in Mozambique banking sector.
method Linear Discriminant Analysis method, using financial indicators.
result Model accurately predicted 84% of bank failures 1 year before Central Bank intervention.
A motif-based framework identifies local spillover structures in financial markets.
problem Aggregate risk spillovers obscure local interaction patterns in systemic risk.
method Develops a motif-based framework using multiscale backbones and colored motifs.
result Motif-based portfolios outperform traditional benchmarks on risk-adjusted returns.
For a finitely generated discrete group , the -sectors of an orbifold are a disjoint union of orbifolds corresponding to homomorphisms from into a groupoid presenting . Here, we show that the inertia orbifold and -multi-sectors are special cases of the -sectors, and that the -sectors are orbif…
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.
We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the indu…
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.
Sector identification in a set of stock return time series traded at the London Stock Exchangecond-mat.dis-nn
We compare some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a portfolio of s…
Study of separatrix configurations in holomorphic flows with real time.
problem Characterize separatrices in holomorphic flows with real-valued time.
method Establish continuity of transit times, classify path components, prove blow-up scenarios.
result Separatrices of different types of equilibria exhibit blow-up in finite time.
The Indian auto sector's stock index is decomposed into trend, seasonal, and random components.
problem Understanding the components of stock market data for better prediction.
method Structural analysis of time series data using Trend, Seasonal, and Random components.
result Decomposition results and forecasting techniques are accurate even with a dominant random component.
Paper forecasts Indian healthcare sector stock prices using time series analysis.
problem Accurate prediction of Indian healthcare sector stock prices.
method Time series decomposition and six forecasting methods.
result Forecasting methods demonstrate effectiveness in predicting healthcare sector index.
Sector-wise analysis of Indian stock market: Long and short-term risk and stability analysisq-fin.ST
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.
To investigate the universal structure of interactions in financial dynamics, we analyze the cross-correlation matrix C of price returns of the Chinese stock market, in comparison with those of the American and Indian stock markets. As an important emerging market, the Chinese market exhibits much stronger correlations…
In this paper we consider a multivariate model-based approach to measure the dynamic evolution of tail risk interdependence among US banks, financial services and insurance sectors. To deeply investigate the risk contribution of insurers we consider separately life and non-life companies. To achieve this goal we apply …
Analyzes global economic sectors' interdependence using Google matrix analysis.
problem Understanding interdependencies and interactions among world economies and sectors.
method Reduced Google matrix algorithm applied to OECD-WTO network data.
result Shows sensitivity of sectors to petroleum activity and interdependencies among countries.
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…
Study develops sector rotation models using factor and fundamental analysis.
problem Understanding and predicting sector shifts in financial markets.
method Systematic sector classification, factor analysis, and fundamental metrics evaluation.
result Developed predictive models with notable predictive capabilities.
Study reveals risk transmission channels among Chinese sectors.
problem Understanding risk transmission within Chinese economic sectors.
method Volatility spillovers analysis using VAR model and rolling window approach.
result 17 sectors are risk transmitters and 11 are risk takers.
Analyzes how venture investment strategies have evolved over time in different sectors.
problem Understanding changes in venture investment strategies across sectors over time.
method Applied PCA and TCA to analyze a dataset of 52,000 startups and 110,000 funding rounds.
result There has been a shift in venture investment towards lower-tech sectors and a rise in accelerator investments.