Bond yield modelling and its application in the European Union

Forecasting crises has always been an interesting and important topic for econometricians or statisticians. Literature suggests that government bond yields can be a valid leading indicator for this purpose. This thesis uses government bond yields and applies various models to forecast the crisis which happened recently. Chapter 2 investigates a model utilising the term structure of interest rates to predict output growth and recession in the UK. In contrast to previous literature, information retrieved from the whole yield curve is used rather than just the yield spread. Using di�erent methods, our models are found to outperform the yield spread models both in in-sample and out-of-sample forecasting. Notably, the B-spline fitting model is able to forecast the 2009-2010 recession. Moreover, the model with lag of growth shows great forecasting ability in out-of-sample output growth forecasting. In most cases, models based on B-spline perform better than the ones based on the Diebold-Li framework. Chapter 3 examines the existence of time series non-linearities in the real output growth / recession-term spread relationship. Vector Autoregression (VAR), Threshold VAR (TVAR), Structural break VAR (SBVAR), Structural break threshold VAR (SBTVAR) are applied in the analysis. The in-sample results indicate there are non-linear components in this relationship. And this non-linearity tends to be caused by structural breaks. The best in-sample model also shows its robustness on arrival of new information in the out-of-sample tests. Evidence shows the model with only structural break non-linearity outperforms linear models in 1-quarter, 3-quarter and 4-quarter ahead forecasting. The European sovereign debt crisis has become a very popular topic since late 2009. In Chapter 4, the sovereign debt crisis is investigated by calculating the probabilities of the potential future crisis of 11 countries in the European Union. We use sovereign 2 3 spreads of the European countries against Germany as targets and apply the GARCH based vine copula simulation technique. The methodology solves the di�culties of calculating the probabilities of rarely happening events and takes sovereign debt movement dependence, especially tail dependence, into consideration. Results indicate that Italy and Spain are the most likely next victims of the sovereign debt crisis, followed by Ireland, France and Belgium. The UK, Sweden and Denmark, which are outside EMU, are the most financially stable countries in the sample

A comparative and conceptual intellectual study of environmental topic in economic and finance

We aim to provide a comprehensive overview of the past, present, and future development of environmental related topics in Economics and Finance. In this regard, Environmental Finance (EF)- and Environmental, Social, and Governance (ESG)-related literature is collected and analysed. The paper draws chronical pictures of the topic development in these two recently developed fields by applying bibliometric methods. Then, we provide a novel systemic comparison on their main differences. Reviewing the top journal publications, we identify literature gaps for a future research agenda. In particular, on the one hand, for EF, we suggest exploring various financial innovations to generate environmental benefits research, and thus building up efficient regulatory framework for addressing major regional and/or global environmental issues. On the other hand, for ESG, we respectively provide potential research directions to conduct the cost-benefit study on the real impact of ESG disclosure and to evaluate how ESG investment strategy efficiently deliver sustainable development

How liquid are banks : some evidence from the United Kingdom

This paper uses quantitative balance sheet liquidity analysis, based upon modified versions of the BCBS 1 and Moody’s 2 models, to provide indicators which would alarm the UK banks’ short and long-term liquidity positions respectively. These information will also underpin other research related liquidity risk to banks’ lending and performance. Our framework accurately reflect UK banks’ liquidity positions under both normal and stress scenarios based on the consistent accounting information under IFRS. It has significant contribution on Basel III liquidity ratios calculation. The study also presents fundamental financial information to facilitate analysis of banks’ business models and funding strategies. Using data for the period 2005-2010, we provide evidence that there have been variable liquidity strains across the UK banks in our sample. The estimated results show that Barclays Bank was the only bank to maintain a healthy short-term liquidity position throughout the sample period; while HSBC remained liquid in the short term, in both normal and stress conditions, except in 2008 and 2010. RBS, meanwhile, maintained healthy long-term liquidity positions from 2008 after receiving government injections of capital. And Santander UK was also able to post healthy long-term liquidity positions, except in 2009. However, the other four banks, the Bank of Scotland, Lloyds TSB, Natwest, and Standard Chartered, proved illiquid, on both a short-term and long-term basis, throughout the six-year period, with Natwest being by far the worst performer

Characterization of a novel N-acetylneuraminic acid lyase favoring industrial N-acetylneuraminic acid synthesis process

N-Acetylneuraminic acid lyase (NAL, E.C. number 4.1.3.3) is a Class I aldolase that catalyzes the reversible aldol cleavage of N-acetylneuraminic acid (Neu5Ac) from pyruvate and N-acetyl-D-mannosamine (ManNAc). Due to the equilibrium favoring Neu5Ac cleavage, the enzyme catalyzes the rate-limiting step of two biocatalytic reactions producing Neu5Ac in industry. We report the biochemical characterization of a novel NAL from a “GRAS” (General recognized as safe) strain C. glutamicum ATCC 13032 (CgNal). Compared to all previously reported NALs, CgNal exhibited the lowest kcat/Km value for Neu5Ac and highest kcat/Km values for ManNAc and pyruvate, which makes CgNal favor Neu5Ac synthesis the most. The recombinant CgNal reached the highest expression level (480 mg/L culture), and the highest reported yield of Neu5Ac was achieved (194 g/L, 0.63 M). All these unique properties make CgNal a promising biocatalyst for industrial Neu5Ac biosynthesis. Additionally, although showing the best Neu5Ac synthesis activity among the NAL family, CgNal is more related to dihydrodipicolinate synthase (DHDPS) by phylogenetic analysis. The activities of CgNal towards both NAL's and DHDPS' substrates are fairly high, which indicates CgNal a bi-functional enzyme. The sequence analysis suggests that CgNal might have adopted a unique set of residues for substrates recognition

Plasma Exosomal Long Non-Coding RNAs Serve as Biomarkers for Early Detection of Colorectal Cancer

Background/Aims: Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths worldwide. Thus, methods for early diagnosis of CRC are urgently needed. We aimed to identify potential long non-coding RNAs (lncRNAs) in circulatory exosomes that may serve as biomarkers for the detection of early-stage CRC. Methods: Exosomes from the plasma of CRC patients (n = 50) and healthy individuals (n = 50) were isolated by ultracentrifugation, followed by extraction of total exosomal RNAs using TRIzol reagent. Microarray analysis was used for exosomal lncRNA profiling in the two groups, and real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to determine the expression level of lncRNAs in all patients and healthy subjects. Results: The expression of six lncRNAs (LNCV6_116109, LNCV6_98390, LNCV6_38772, LNCV_108266, LNCV6_84003, and LNCV6_98602) was found to be significantly up-regulated in CRC patients compared with that in healthy individuals by qRT-PCR. The receiver operating characteristic curve was used to verify their diagnostic accuracy. The values of the area under the curve for these lncRNAs were 0.770 (LNCV6_116109), 0.7500 (LNCV6_98390), 0.6500 (LNCV6_38772), 0.6900 (LNCV_108266), 0.7500 (LNCV6_84003), and 0.7200 (LNCV6_98602). Conclusion: Our study suggested that the expression of these six exosomal lncRNAs (LNCV6_116109, LNCV6_98390, LNCV6_38772, LNCV_108266, LNCV6_84003, and LNCV6_98602) was significantly up-regulated in the plasma of CRC patients, and that they may serve as potential non-invasive biomarkers for early diagnosis of CRC

Validating automated eye disease screening AI algorithm in community and in-hospital scenarios

Purpose:To assess the accuracy and robustness of the AI algorithm for detecting referable diabetic retinopathy (RDR), referable macular diseases (RMD), and glaucoma suspect (GCS) from fundus images in community and in-hospital screening scenarios.MethodsWe collected two color fundus image datasets, namely, PUMCH (556 images, 166 subjects, and four camera models) and NSDE (534 images, 134 subjects, and two camera models). The AI algorithm generates the screening report after taking fundus images. The images were labeled as RDR, RMD, GCS, or none of the three by 3 licensed ophthalmologists. The resulting labels were treated as “ground truth” and then were used to compare against the AI screening reports to validate the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the AI algorithm.ResultsOn the PUMCH dataset, regarding the prediction of RDR, the AI algorithm achieved overall results of 0.950 ± 0.058, 0.963 ± 0.024, and 0.954 ± 0.049 on sensitivity, specificity, and AUC, respectively. For RMD, the overall results are 0.919 ± 0.073, 0.929 ± 0.039, and 0.974 ± 0.009. For GCS, the overall results are 0.950 ± 0.059, 0.946 ± 0.016, and 0.976 ± 0.025.ConclusionThe AI algorithm can work robustly with various fundus camera models and achieve high accuracies for detecting RDR, RMD, and GCS

Knowledge, attitudes, and practices of adolescent depression among parents of children diagnosed with depression in Ningbo City, eastern China

ObjectiveTo investigate parental knowledge, attitudes, and practices (KAP) toward adolescent depression.MethodsA cross-sectional survey was conducted between October 2022 and October 2023 at The First Affiliated Hospital of Ningbo University among parents of adolescents diagnosed with depression. A self-administered questionnaire was used to collect the parents’ demographic characteristics and KAP toward adolescent depression.ResultsA total of 522 questionnaires were collected from parents of depressed adolescents. Among the participants, 383 (73.37%) were female. In addition, 426 participants (81.61%) had children aged 14–18. The mean knowledge, attitude, and practice scores were 9.09 ± 2.37 (possible range: 0–12), 37.04 ± 4.11 (possible range: 11–55), and 31.53 ± 3.84 (possible range: 8–40), respectively. There were significant positive correlations between knowledge and attitude (r = 0.225, p < 0.001), knowledge and practice (r = 0.240, p < 0.001), and attitude and practice (r = 0.381, p < 0.001). The path analysis showed significant direct effects of knowledge on attitude (β = 0.422, p < 0.001) and practice (β = 0.283, p < 0.001). There was an indirect effect of knowledge on practice through attitude (β = 0.131, p = 0.004). Attitude directly impacted practice (β = 0.311, p < 0.001).ConclusionParents of adolescents diagnosed with depression exhibited moderate KAP regarding adolescent depression. The study underscored the importance of targeted interventions to improve parental KAP in supporting adolescents with depression. Moreover, future research should explore additional factors influencing parental attitudes and behaviors toward adolescent depression to develop more effective interventions