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.
Study uses Hawkes processes to analyze stock market contagion in China.
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…
Model predicts S&P 500 IT sector index prices with high accuracy.
Proposes a two-stage sector rotation method using machine learning and deep learning.
Generative AI models enhance sector-based investment portfolios, but performance varies by market conditions.
In this article we review several techniques to extract information from stock market data. We discuss recurrence analysis of time series, decomposition of aggregate correlation matrices to study co-movements in financial data, stock level partial correlations with market indices, multidimensional scaling and minimum s…
The objective of this paper is to fill a gap in the literature on internationalization, in relation to the absence of objective and measurable performance indicators on the process of how firms sequentially enter external markets. To that end, this research develops a quantitative tool that can be used as a performance…
Using a time-varying approach, this paper examines the dynamics of volatility in the REIT sector. The results highlight the attractiveness and suitability of using GARCH based approaches in the modeling of daily REIT volatility. The paper examines the influencing factors on REIT volatility, documenting the return and v…
TDA detects stock market crashes across continents.
Study compares information flow between Chinese and US stock sectors.
Model predicts Mozambique bank failures, aiding risk management.
Network theory assesses systemic risk in the insurance sector.
Paper uses LLMs for sector allocation, showing better returns.
Study develops sector rotation models using factor and fundamental analysis.
Enhanced indexation with sector constraints using SSD for better portfolio performance.
LSTM model predicts stock prices with high accuracy in stable sectors but struggles with volatile ones.
In the present work we analyse the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis we assume that the stock quotations of insurance companies reflect market sentiments which constitute a very important systemic risk factor. Interlinkages between insur…
This study analyses, through cross-section estimation methods, the influence of spatial effects and human capital in the conditional productivity convergence (product per worker) in the economic sectors of NUTs III of mainland Portugal between 1995 and 2002. To analyse the data, Moran's I statistics is considered, and …
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 …
This paper optimizes portfolios of thematic sector stocks using LSTM models.
The study visualizes Spanish fish and meat processing companies using financial, environmental, and social ratios.
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
We investigate a multi-factor extension of the asymptotic single risk factor (ASRF) model that underlies the capital charges of the "Basel II Accord". In this extended model, it is still possible to derive closed-form solutions for the risk contributions to Value-at-Risk and Expected Shortfall. As an application of the…
We study the various sectors of the Bombay Stock Exchange(BSE) for a period of 8 years from April 2006 - March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows signif…
The paper uses LSTM to predict stock prices and analyzes sector profitability.
A flexible calendar rebalancing approach for Indian stock portfolios.
This paper surveys the evolution of industrial concentration of the Brazilian automotive market as well as its positioning in the worldmarket. Data available by OICA (International Organization of Motor Vehicle Manufacturers) were used to better understand the characteristics of the Brazilian market on the world stage.…
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…
We study the various sectors of the Bombay Stock Exchange (BSE) for a period of eight years from January 2006 to March 2014. Using the data of the daily returns of a period of eight years we investigate the financial cross correlation co-efficients among the sectors of BSE and Price by Earning (PE) ratio of BSE Sensex.…
The paper analyzes how news sentiment of companies can affect market movements.
The study distills news sources to analyze stock reactions, finding sentiment has asymmetric and sector-specific effects.
Study compares ANN and GARCH models for volatility prediction across sectors.
The purpose of this study is to measure the Total Factor Productivity (TFP) growth and determine the share of each of the economic growth sources in the mining sector of Iran. The time period of this study is 1355-1385 of the Solar Hijri calendar (roughly overlaying with the time period of 1976-2006 of the Gregorian ca…
The sectoral synchronization observed for the Japanese business cycle in the Indices of Industrial Production data is an example of synchronization. The stability of this synchronization under a shock, e.g., fluctuation of supply or demand, is a matter of interest in physics and economics. We consider an economic syste…
The professional services sector is at a turning point, with some industries showing growth opportunities.
Researchers infer firm-level supply chain networks from sector-level data to assess systemic risk.
Expert system predicts credit card charge-offs using macroeconomic indicators.
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correl…
Study clusters Kenyan medical insurance companies based on financial performance and reporting consistency.
Study shows how China's stock market reflects economic demand changes during COVID-19.
This study examines representation bias in open-source Qwen models for investment decisions.
Develops a climate risk model for asset managers.
The paper uses LSTM to predict stock prices and optimize portfolio weights.
Measures collectivity in financial covariances and correlations to reveal trends and precursors.
This paper forecasts renewable energy prospects in South America through cross-border interconnection.
This work is an answer to the EIOPA 2017 report. It follows from the latter that in order to assess the potential systemic risk we should take into account the build-up of risk and in particular the risk that arises in time, as well as the interlinkages in the financial sector and the whole economy. Our main tools used…
The consideration of spatial effects at a regional level is becoming increasingly frequent and the work of Anselin (1988), among others, has contributed to this. This study analyses, through cross-section estimation methods, the influence of spatial effects in productivity (product per worker) in the NUTs III economic …
A3T-GCN model forecasts FTSE100 stock prices using technical indicators and financial ratios.