Modeling dynamic volatility under uncertain environment with fuzziness and randomness

The problem related to predicting dynamic volatility in financial market plays a crucial role in many contexts. We build a new generalized Barndorff-Nielsen and Shephard (BN-S) model suitable for uncertain environment with fuzziness and randomness. This new model considers the delay phenomenon between price fluctuation and volatility changes, solves the problem of the lack of long-range dependence of classic models. Through the experiment of Dow Jones futures price, we find that compared with the classical model, this method effectively combines the uncertain environmental characteristics, which makes the prediction of dynamic volatility has more ideal performance

Stochastic volatility modeling of high-frequency CSI 300 index and dynamic jump prediction driven by machine learning

This paper models stochastic process of price time series of CSI 300 index in Chinese financial market, analyzes volatility characteristics of intraday high-frequency price data. In the new generalized Barndorff-Nielsen and Shephard model, the lag caused by asynchrony of market information is considered, and the problem of lack of long-term dependence is solved. To speed up the valuation process, several machine learning and deep learning algorithms are used to estimate parameter and evaluate forecast results. Tracking historical jumps of different magnitudes offers promising avenues for simulating dynamic price processes and predicting future jumps. Numerical results show that the deterministic component of stochastic volatility processes would always be captured over short and longer-term windows. Research finding could be suitable for influence investors and regulators interested in predicting market dynamics based on realized volatility

Sustainable Transport Infrastructure and Economic Returns: A Bibliometric and Visualization Analysis

Sustainable transport infrastructure can determine the effect of countries&rsquo transport-driven economic returns. Considering the economic, environmental, and social relevance and growing issues of CO 2 in the countries concerned, this study aims to examine sustainable transport infrastructure related to economic return through a bibliometric and visualization analysis from 2000 to 2019. First, to measure the status of sustainable transport infrastructure literature, we determine the number of publications produced per year. Second, we determine the most frequently cited articles and prominent journals on sustainable transport infrastructure. Third, we examine the co-occurrence of the author&rsquo s keywords below the abstract. Fifth, we describe the bibliometric details in clusters and analyze the network link between reference, sources, and authors&rsquo co-citations, and discuss the characteristics and structures of clusters. Sixth, we discuss the bibliographic relationship between authors, and finally, determine the country and the institutional network of co-authors. The obtained results identify that the most influential articles, journals, and authors that make a significant contribution to sustainable transport infrastructure studies and present the research sub-areas or themes related to sustainable transport infrastructure. Overall, the study found the paradigms of today, key research areas, and the link between the fields of sustainable transport infrastructure studies. In the meantime, this study also reveals the improvements in the main topics and sub-sections over the last 20 years and shows the changes in future areas of research. The study concluded that the findings could provide researchers with some insights and help to advance studies on sustainable transport systems. Document type: Articl

LncRNA MALAT1: A potential therapeutic target in DSSinduced ulcerative colitis progression in vitro

Purpose: Ulcerative colitis is a severe disease affecting human health worldwide. Studies have shown that lncRNA MALAT1 has a significant correlation with breast, pancreatic, colon and liver cancers, but its effects on colitis is yet to be discovered. In this study, the potential role of lncRNA MALAT1 and the underlying molecular mechanism in DSS-induced colitis were investigated in vitro.Methods: Colorectal mucosal cell line FHC was induced with dextran sulphate sodium (DSS) to form an in vitro colitis model. Transfection procedure was employed to up- or down-regulate the expressions of lncRNA MALAT1 or miR-30c-5p in FHC cells. Cell viabilities were detected by CCK-8 assay. RT-qPCR was applied for evaluating gene expressions in normal FHC and DSS-induced FHC cell lines, while protein expression levels of target genes were examined by Western blot analysis. Starbase was used to predict the molecular interaction between MALAT1 and miR-30c-5p, while luciferase reporter assay was utilized to verify the binding sites between the two genes.Results: Expression of MALAT1 in the DSS-induced FHC cells was high with low cell viabilities, compared to the normal FHC cells. In the DSS-induced colitis-like FHC cells, overexpression of MALAT1 inhibited cell viabilities, while its downregulation promoted it. MiR-30c-5p directly targets MALAT1 and inhibited its expression in DSS-treated FHC cells. Upregulation of miR-30c-5p increased cell viabilities. Bcl-xL expression was inhibited by the up-regulation of MALAT1, while that of Bax was enhanced and the mimics of miR-30c-5p reversed these observations, suggesting that the enhancement of apoptosis promoted by oe-MALAT1 could be inhibited by miR-30c-5p. The interaction between MALAT1 and miR-30c-5p regulated NF-κB/TGF-β/Wnt-β-catenin signaling pathway.Conclusion: Overexpression of MALAT1 led to inhibition of cell viability, while apoptosis and inflammation were promoted by targeting miR-30c-5p via NF-κB/TGF-β/Wnt-β-catenin signaling pathway. These findings suggest MALAT1 as a therapeutic target for treating colitis. Keywords: Colitis, MALAT1, miR-30c-5p, NF-κB/TGF-β/Wnt-β-catenin&nbsp

Nouveauté or Cliché? Assessment on island ecological vulnerability to Tourism: Application to Zhoushan, China

In comparison with coastal zones, islands are even more vulnerable to anthropogenic disturbance, especially to tourism and tourism-induced activities. Despite a great number of studies on either island tourism or island vulnerability reviewed in this paper, knowledge and practice of the impact from tourism upon island ecological vulnerability (IEV) still needs to be expanded. In this contribution, the IEV of four administrative regions in Zhoushan, China is assessed between 2012 and 2017 based on an “exposure (E)-sensitivity (S)-adaptive capacity (A)” framework and by means of coupling coordination degree modeling (CCDM) for determination of the overall development level of E-S-A subsystems in each region. The assessment results show that: (1) An index system consisting of 1 objective, 3 sub-objectives, 7 elements, and 20 indicators can be established and tested to reflect the IEV to tourism; (2) As the most attractive tourist destinations, Shengsi and Putuo inevitably have the highest IEV values; (3) Dinghai's moderate low level of IEV comes as a surprise, due to its direct connectivity to its neighboring coastal city of Ningbo; (4) The more balanced the coupling coordination degree (CCD) values among E-S-A subsystems are, the higher the IEV values in the four tourist destinations of Zhoushan. In conclusion, tourism can be a double-edged sword for islands, the overall benefits of which outweigh the negative impacts upon island ecological conditions

Selecting a better valuation model to measure bubble level of stocks price: empirical study from internet-based finance stocks in A-share market

As a star of emerging industries in China, internet-based finance has been developing rapidly. This paper, considers selecting a more suitable valuation model to measure the intrinsic value and price bubble of Internet-based Finance stocks. By comparing the relative valuation accuracy of the Kim et al. model with the Frankel-Lee model and the F-O model applied in the prior studies, this study finds that the Kim et al. model highlights the industry-specific features and outperforms other models in interpreting stocks price variation. Especially, under the circumstance of soaring and slumping stocks price variation (e.g. 2015), it is essential to study the price bubbles of internetbased finance stocks at different points of Shanghai Stock Exchange Composite Index. Surprisingly, our empirical results suggest that the internet-based finance stocks have negative bubbles at the whole average level, and about half of them are undervalued. Moreover, there are positive correlations between the bubble level and three key factors including the trading volume, the price to book ratio and whether to do cross-industry business on internet-based finance. These findings imply that the Kim et al. model contributes to improving valuation accuracy of internet-based finance stocks and explainability of the price bubbles in A-share market

City branding in China's Northeastern region

The past decade has seen a surge in the use of city branding, which is used to attract specific target groups of investors, high-tech green firms and talented workforce and reflects a desired shift from old, polluting manufacturing industries to new, clean service industries. Previous studies in the Chinese mega-city regions Pearl River Delta, Yangtze River Delta a

Contrasting fate of western Third Pole's water resources under 21st century climate change

Seasonal melting of glaciers and snow from the western Third Pole (TP) plays important role in sustaining water supplies downstream. However, the future water availability of the region, and even today’s runoff regime, are both hotly debated and inadequately quantified. Here, we characterize the contemporary flow regimes and systematically assess the future evolution of total water availability, seasonal shifts, and dry and wet discharge extremes in four most meltwater-dominated basins in the western TP, by using a process-based, well-established glacier-hydrology model, well-constrained historical reference climate data, and the ensemble of 22 global climate models with an advanced statistical downscaling and bias correction technique. We show that these basins face sharply diverging water futures under 21st century climate change. In RCP scenarios 4.5 and 8.5, increased precipitation and glacier runoff in the Upper Indus and Yarkant basins more than compensate for decreased winter snow accumulation, boosting annual and summer water availability through the end of the century. In contrast, the Amu and Syr Darya basins will become more reliant on rainfall runoff as glacier ice and seasonal snow decline. Syr Darya summer river-flows, already low, will fall by 16–30% by end-of-century, and striking increases in peak flood discharge (by >60%), drought duration (by >1 month) and drought intensity (by factor 4.6) will compound the considerable water-sharing challenges on this major transboundary river

Immunogenomic Landscape in Breast Cancer Reveals Immunotherapeutically Relevant Gene Signatures

Breast cancer is characterized by some types of heterogeneity, high aggressive behaviour, and low immunotherapeutic efficiency. Detailed immune stratification is a prerequisite for interpreting resistance to treatment and escape from immune control. Hence, the immune landscape of breast cancer needs further understanding. We systematically clustered breast cancer into six immune subtypes based on the mRNA expression patterns of immune signatures and comprehensively depicted their characteristics. The immunotherapeutic benefit score (ITBscore) was validated to be a superior predictor of the response to immunotherapy in cohorts from various datasets. Six distinct immune subtypes related to divergences in biological functions, signatures of immune or stromal cells, extent of the adaptive immune response, genomic events, and clinical prognostication were identified. These six subtypes were characterized as immunologically quiet, chemokine dominant, lymphocyte depleted, wounding dominant, innate immune dominant, and IFN-γ dominant and exhibited features of the tumor microenvironment (TME). The high ITBscore subgroup, characterized by a high proportion of M1 macrophages:M2 macrophages, an activated inflammatory response, and increased mutational burden (such as mutations in TP53, CDH1 and CENPE), indicated better immunotherapeutic benefits. A low proportion of tumor-infiltrating lymphocytes (TILs) and an inadequate response to immune treatment were associated with the low ITBscore subgroup, which was also associated with poor survival. Analyses of four cohorts treated with immune checkpoint inhibitors (ICIs) suggested that patients with a high ITBscore received significant therapeutic advantages and clinical benefits. Our work may facilitate the understanding of immune phenotypes in shaping different TME landscapes and guide precision immuno-oncology and immunotherapy strategies