Search Results (29)

In this study, we introduce a detailed framework for predicting market conditions and selecting stocks by integrating machine learning techniques with ontological financial analysis. The process starts with ontology-based stock selection, categorizing companies using fundamental financial indicators such as liquidity, profitability, debt ratios, and growth metrics. For instance, firms showcasing favorable debt-to-equity ratios along with robust revenue growth are identified as high-performing entities. This classification facilitates targeted analyses of market dynamics. To predict market states—categorizing them into bull, bear, or neutral phases—the framework utilizes a Non-Stationary Markov Chain (NMC), BERT, to assess sentiment in financial news articles and Long Short-Term Memory (LSTM) networks to identify temporal patterns. Key inputs like the Sentiment Index (SI) and Illiquidity Index (ILLIQ) play essential roles in dynamically influencing regime predictions within the NMC model; these inputs are supplemented by variables including GARCH volatility and VIX to enhance predictive precision further still. Empirical findings demonstrate that our approach achieves an impressive 97.20% accuracy rate for classifying market states, significantly surpassing traditional methods like Naive Bayes, Logistic Regression, KNN, Decision Tree, ANN, Random Forest, and XGBoost. The state-predicted strategy leverages this framework to dynamically adjust portfolio positions based on projected market conditions. It prioritizes growth-oriented assets during bull markets, defensive assets in bear markets, and maintains balanced portfolios in neutral states. Comparative testing showed that this approach achieved an average cumulative return of 13.67%, outperforming the Buy and Hold method’s return of 8.62%. Specifically, for the S&P 500 index, returns were recorded at 6.36% compared with just a 1.08% gain from Buy and Hold strategies alone. These results underscore the robustness of our framework and its potential advantages for improving decision-making within quantitative trading environments as well as asset selection processes. Full article

This study investigates the financial interconnections among Real Estate Investment Trusts (REITs), sukuk (Islamic bonds), and oil in Gulf Cooperation Council (GCC) nations. The study sample comprises S&P GCC Composite Equity Real Estate Investment Trusts (REITs) Shariah, the S&P GCC Bond and Sukuk Index, and the OPEC crude oil basket on a daily basis. The duration of coverage spans from 2014 until the beginning of 2024. The TVP-VAR methodology is utilized to examine the interrelationship among the assets. The results indicate that Real Estate Investment Trusts (REITs) and oil are sources of volatility transmission, whereas sukuk is a recipient of volatility within the network. Examining the net pairwise directional linkages of two assets, namely REITs and oil markets, reveals that they transfer their volatility to the sukuk market. Moreover, a reciprocal relationship exists between REITs and oil regarding volatility spillover. It means that REITs act as transmitters to the oil markets during specific periods, while the influence is reversed at other times. This study implies that portfolio managers and investors can discern the volatility patterns of assets in order to enhance their risk-management techniques. For policymakers, comprehending the interdependence of certain asset classes provides valuable knowledge for formulating regulations that might stabilize the financial system and foster economic growth. From a research and academic perspective, this study enhances understanding of the interconnections between different financial asset classes and pricing dynamics in financial markets. Full article

IT is recognized as the engine of the digital world. The fact that this technology has multiple sub-sectors makes it the driving force of the economy. With these characteristics, the sector is becoming the center of attention of investors. Considering that investors prioritize profitability, it becomes a top priority for managers to make accurate and reliable profitability forecasts. The aim of this study is to estimate the profitability of IT sector firms traded in Borsa Istanbul using machine learning methods. In this study, the financial data of 13 technology firms listed in the Borsa Istanbul Technology index and operating between March 2000 and December 2023 were used. Return on assets (ROA) and return on equity (ROE) were estimated using machine learning methods such as neural networks, multiple linear regression and decision tree regression. The results obtained reveal that the performance of artificial neural networks (ANN) and multiple linear regression (MLR) are particularly effective. Full article

Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents’ medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply–demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a “concentrically decreasing” pattern. The rating ranged from “very reasonable” to “less reasonable”, with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as “less reasonable” occupied 38.73% of the total area. These results indicate that the model accounted for residents’ travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources. Full article

Given the effect of urbanization on land use and the allocation and implementation of urban green spaces, this paper attempts to analyze the distribution and accessibility of public parks in India’s Bengaluru city (previously known as Bangalore). Availability, accessibility, and utilization—the key measures of Urban Green Spaces (UGS)—are mostly used in health research and policy and are important components of Planetary Health Equity in the context of studying UGSs and health. A geo-spatial method was used for mapping the park’s distribution and measuring its accessibility, using road network data. To understand equitable access to the parks, four socio-economic parameters—population density, the percentage of the population below 6 years of age, the proxy wealth index, and scheduled caste population—were correlated with the parks’ accessibility. This spatial distribution revealed that 19 of 198 wards did not have a single park and that 36 wards only had one park. About 25–29% of wards did not have accessibility to neighborhood-level and community-level parks within a 400–800 m distance. These parks must be accessible within a walking distance of 400–800 m but were found to most likely be inaccessible on the periphery of the city where the population density is low and the children population is high, in comparison to the central part of the city. Similarly, parks were found to be inaccessible in the eastern part of the city where the scheduled caste population is high and also found to be inaccessible for the low-income neighborhoods residing in the western part and southern periphery of the city, indicating the uneven distribution of and inequitable access to public parks. Our study proposes a reshaping of both neighborhood parks and community parks in an attempt to look beyond biodiversity, through the planetary health equity approach, by noting that, while biodiversity indirectly has a positive effect on health, public parks should not only be considered as advancing environmental sustainability and climate resilience, but also as improving the health and wellbeing of the population. Affirmative action in terms of the availability of public parks with adequate area requirements and essential services at a neighborhood scale is required to redress the inequity of access; in addition, the accessibility of parks must be considered important during urban planning. Full article

Urban street greening, a key component of urban green spaces, significantly impacts residents’ physical and mental well-being, contributing substantially to the overall quality and welfare of urban environments. This paper presents a novel framework that integrates street greenery with accessibility, enabling a detailed evaluation of the daily street-level greenery visible to residents. This pioneering approach introduces a new measurement methodology to quantify the quality of urban street greening, providing robust empirical evidence to support its enhancement. This study delves into Nanjing’s five districts, employing advanced image semantic segmentation based on machine learning techniques to segment and extract green vegetation from Baidu Street View (BSV) images. Leveraging spatial syntax, it analyzes street network data sourced from OpenStreetMap (OSM) to quantify the accessibility values of individual streets. Subsequent overlay analyses uncover areas characterized by high accessibility but inadequate street greening, underscoring the pressing need for street greening enhancements in highly accessible zones, thereby providing valuable decision-making support for urban planners. Key findings revealed that (1) the green view index (GVI) of sampled points within the study area ranged from 15.79% to 38.17%, with notably better street greening conditions observed in the Xuanwu District; (2) the Yuhua District exhibited comparatively lower pedestrian and commuting accessibility than the Xuanwu District; and (3) approximately 139.62 km of roads in the study area demonstrated good accessibility but lacked sufficient greenery visibility, necessitating immediate improvements in their green landscapes. This research utilizes the potential of novel data and methodologies, along with their practical applications in planning and design practices. Notably, this study integrates street greenery visibility with accessibility to explore, from a human-centered perspective, the tangible benefits of green landscapes. These insights highlight the opportunity for local governments to advance urban planning and design by implementing more human-centered green space policies, ultimately promoting societal equity. Full article

The connotation and measurement standard of “fairness” in parkland planning is closely related to the level of urban development and residents’ needs, with solid realism and dynamics, and it is still a complex problem to control accurately in planning. Therefore, to conduct a more comprehensive study, taking the main urban area of Harbin as an example, this paper combined urban development background and practical problems at different stages and, based on POI and AOI data, divided the connotation of “equity” in park green space planning into two levels: “spatial equity” and “social equity”. Based on these two levels of fairness, the research framework of urban park green space layout is constructed. Kernel density estimation and GIS-based network analysis were used to study the spatial layout and accessibility of urban parkland. The ability to match supply and demand for parkland in the study area as a whole was analyzed using a gridded two-step moving search method, as well as the degree of equity in the enjoyment of urban parkland by vulnerable groups including the elderly and children using the Lorenz curve with the Gini coefficient, the share index, and the entropy of the locality. The results show that: (1) the parkland is concentrated in the seven main urban areas of the two–two junctions, and the cohesion distribution trend is outside the distribution. (2) Motorized vehicles have the best 15-min accessibility for travel, but it still does not cover all the parkland. (3) Supply and demand within the region are unsatisfactory, with the area with the strongest supply and demand capacity for parkland accounting for only 3.19% of the total area. (4) The Gini coefficient of parkland enjoyed by the residents of Harbin city center is 0.407, with a massive gap in the overall distribution. In addition, the share index of vulnerable groups of the elderly and children all have share indices below 1, and the results of the analysis of locational entropy indicate that the level of street park green space resources enjoyed by these two groups belongs to the low socio-spatial equity pattern, which is not balanced. This study investigates the spatial layout of urban parkland from two equity levels, which can provide new ideas for the equity study of urban green space planning. Full article

Scholars have sought to integrate sustainable principles, attitudes, and methodologies into urban development, drawing insights from the natural and social sciences as well as historical contexts. However, current sustainable urban planning (SUP) research has a broad scope, unclear boundaries, and an absence of systematic literature reviews. To fill this research gap, this review presents a visual analysis of 38,344 publications on SUP indexed in the Web of Science (WoS) from 1964 to 2023, with the aim of detailing the trajectory of SUP research. Utilizing data retrieval and scientific metrology techniques, we: (1) Identified distinct phases in SUP research: budding (pre-1990s), exploration (1990s), foundation (2000s), and maturation (2010–present). (2) Discovered that publications predominantly focused on urban research, landscape architecture, and ecological studies, with publishing trends favoring developed, highly urbanized, and coastal nations. (3) Employed visualized dual map overlays, co-citation clustering networks, and keyword statistical charts to construct a knowledge framework of the interdisciplinary progression and thematic shifts in SUP. Key knowledge clustering included ‘community planning’, ‘urban expansion’, ‘ecosystem services’, and ‘nature-based solutions’. (4) Described the progression of SUP, green innovation is the most promising direction for future research. (5) Defined its scope and elements and advocated for three foundational principles: equity and justice, value articulations, and practical needs, offering a path to actualize SUP efforts. Full article

Equity is one of the fundamental principles in the planning of public service facilities. In recent years, many cities have started to promote the construction of 15 min community living circles with the aim of providing residents with more equitable access to basic public services. Based on this background, this study explores an equity-oriented spatial quantitative analysis method to assist in the planning of public service facility layouts. The node centrality measurement index, such as betweenness from spatial syntax and social network analysis is introduced into the analysis method in order to consider the potential activity paths and flows of people at the community scale. Selecting the central city of Shanghai as a case study, the research presents results regarding spatial equity based on the relationship between public service demand and public service facilities supply. Building on this foundation, various approaches to enhancing equity are discussed: (1) optimizing the layout of public service facilities; (2) optimizing residential spatial patterns; and (3) optimizing pedestrian transportation networks. Full article

As part of urban green space and emergency shelters, refuge green spaces (RGS) contribute significantly to the resilience of cities to natural disasters. In contrast, few studies have been conducted to assess the equity of RGS in relation to their planning layout. The presented research aims to quantitatively evaluate the equity of RGS within Chengdu’s Third Ring Road, and to propose corresponding optimization measures in conjunction with future green space planning. The rapid evacuation capacity of the RGS was evaluated by calculating the equity of the RGS in walking modes of 5, 10 and 15 min using an improved three-step floating catchment area method (3SFCA). Based on the results, RGS had an average equity in the study area. The total number of RGS within the Third Ring Road of Chengdu was insufficient, with an uneven spatial distribution and a structure to be optimized. The rapid evacuation capacity of RGS in 5 and 10 min needs to be further improved. The short-term resettlement capacity of RGS after 15 min was relatively good. Using Moran’s I index, the RGS equity and house price results were analyzed and no significant aggregation and polarization were observed. Following the evaluation, recommendations are made for optimizing and adding future RGS in accordance with Chengdu Green Space System Planning. The equity of RGS has been significantly improved after optimization, which can meet the needs of over 90% of residents for 15 min. This study provided feasible suggestions for the layout and structural optimization of the future RGS within the Third Ring Road of Chengdu, which aimed to create a RGS network with complex functions, to meet the multiple needs of citizens. Full article

Accessibility to public hospital services is crucial for healthcare provision, particularly in regions characterized by high tourist presence, such as the Mediterranean islands. This study aims to assess the accessibility of public hospital services in Mallorca, considering access time, the geographic distribution of the resident population, and tourist accommodations. A GIS-based analysis using optimal routing algorithms and the Gini index was conducted to examine the equity in the distribution of regional and reference hospitals across four Health Sectors: Ponent, Migjorn, Tramuntana, and Llevant. The findings reveal that accessibility to regional hospitals is generally favorable, with average access times of 18, 16, 15, and 26 min, respectively, without surpassing 60 min. Accessibility to referral hospitals is comparatively lower, with 31,499 individuals located more than 1 h away. Moreover, 56% of the population is within 10 min from the referral hospital, and only 1.6% require more than 50 min to reach the hospital. Accessibility differs among Health Sectors, with Llevant experiencing the most significant impact. The hospital distribution in Mallorca is deemed to be adequate to serve residents, tourists, and the road network. Although limited in comparisons to other studies conducted in Spain, accessibility in Mallorca is fairly similar to Andalusia, Extremadura, and Catalonia. The study underscores the necessity for health infrastructure planning in order to account for the distribution of resident and tourist populations to ensure efficient and equitable services, particularly in Mediterranean island environments with a substantial tourist presence. Full article

With the accelerated pace of financial globalization and the gradual increase in linkages among financial markets, correctly identifying and describing the risk spillover and network diffusion in the financial system is extremely important for the prevention and management of systemic risk. Based on this, this paper takes the equity markets of 17 countries around the world from 2007 to 2022 as the research object, measures the volatility spillover effect of global financial markets using R-Vine Copula and the DY spillover index, constructs the volatility spillover network of global financial markets, discovers the spillover and diffusion pattern of global financial market risks, and provides relevant suggestions for systemic risk management. It is found that (1) there are certain aggregation characteristics in the network diffusion of global financial market volatility spillover; (2) developed European countries such as the Netherlands, France, the UK, and Germany are at the center of the network and have a strong influence; (3) Asian countries such as China, Japan, and India are at the periphery of the network; and (4) shocks from crisis events enhance the global financial market volatility spillover effect. Based on the above findings, effective prevention of global financial market risk volatility spillover and network diffusion and reduction in systemic risk need to be carried out in two ways. First, by focusing on the financial markets of key countries in the network, such as the Netherlands, the UK, France, and Germany. The second approach is to mitigate the uneven development in global financial markets and reduce the high correlation among them. Full article

Both transport development and poverty alleviation are vital for sustainable development. However, due to the lack of long-term, comparable, county-level transport accessibility and poverty incidence data, the spatiotemporal patterns of these factors have rarely been accurately revealed in the poverty-stricken regions of China, causing the impacts of transport accessibility on poverty alleviation to be difficult to quantify. Taking Guizhou Province in China as the study area, this study revealed the spatiotemporal patterns of transport accessibility and poverty alleviation in 88 counties from 2000 to 2018 based on multisource data, including nighttime light data, LandScan population data, and transport network data. It was found that the transport accessibility decreased from 4.9 h to 3.3 h, and the poverty index decreased from 0.75 to 0.29 on average. All these factors exhibited a “core–periphery” spatial pattern. Furthermore, the panel data regression analysis suggested that transport accessibility has played a dominant role in poverty alleviation, with an elasticity coefficient of 0.839. In the future, policies concerned to integrate transport development with rural industries such as agriculture, e-commence, and tourism are recommended for poverty alleviation and rural revitalization, which are especially significant for promoting sustainable development, securing a win–win of economic growth and social equity. Full article

Travel equity has always been an important but difficult topic in urban traffic research, especially for different groups. Firstly, based on bus operation, this paper constructs the ride change network using the ArcGIS platform. Secondly, through network analysis and based on the transfer network, the time measurement model of bus stops and the time accessibility measurement model of the traffic zones are used to measure and analyze bus stops and traffic zones, respectively. Finally, combined with the global and local spatial autocorrelation model, the travel space allocation equilibrium of pilgrimage is quantified. This case study shows that the time accessibility index reflects the fairness of pilgrimage resource allocation well. According to the overall and local Moran’s I index, the spatial distribution of the configuration equilibrium of the traffic zone is obtained. This paper offers two contributions to the literature: an assessment of the travel fairness of pilgrimage and conclusions that fill the research gaps on the travel equity of vulnerable groups. In this paper, the spatial fairness of pilgrimage behavior is studied, which reflects the fairness and balance of the public transportation system for pilgrimage, as well as the travel fairness of pilgrimage in various regions. The presented knowledge can promote the fairness of residential travel and achieve social equity. Full article

In this paper, we propose a multi-criteria decision making (MCDM) model by integrating the entropy–DEMATEL with TOPSIS model to analyze the causal relationship of financial ratios towards the financial performance of the companies. The proposed model is illustrated using the financial data of the companies of Dow Jones Industrial Average (DJIA). The financial network analysis using entropy–DEMATEL shows that the financial ratios such as debt to equity ratio (DER) and return on equity (ROE) are classified into the cause criteria group, whereas current ratio (CR), earnings per share (EPS), return on asset (ROA) and debt to assets ratio (DAR) are categorized into the effect criteria group. The top three most influential financial ratios are ROE, CR and DER. The significance of this paper is to determine the causal relationship of financial network towards the financial performance of the companies with the proposed entropy–DEMATEL–TOPSIS model. The ranking identification of the companies in this study is beneficial to the investors to select the companies with good performance in portfolio investment. The proposed model has been applied and validated in the portfolio investment using a mean-variance model based on the selection of companies with good performance. The results show that the proposed model is able to generate higher mean return than the benchmark DJIA index at minimum risk. However, short sale is not allowed for the applicability of the proposed model in portfolio investment. Full article