| 1. |
- Fresard, Laure, et al.
(författare)
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Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
- 2019
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Ingår i: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
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Tidskriftsartikel (refereegranskat)abstract
- It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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| 2. |
- Mishra, Nandita, et al.
(författare)
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Predicting Financial Distress in the Indian Banking Sector: A Comparative Study Between the Logistic Regression, LDA and ANN Models
- 2021
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Ingår i: Global Business Review. - : SAGE PUBLICATIONS LTD. - 0972-1509 .- 0973-0664.
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Tidskriftsartikel (refereegranskat)abstract
- Financial distress is a socially and economically significant issue that affects almost every firm across the world. Predicting financial distress in the banking industry can substantially aid in the reduction of losses and can help avoid misallocation of banks financial resources. Models for financial distress prediction of banks are being increasingly employed as important tools to identify early warning signals for the whole banking system. This study attempts to forecast the financial distress of commercial banks by developing a bankruptcy prediction model for banks. The sample size for the study is 75 Indian banks. Logistic, linear discriminant analysis (LDA) and artificial neural network (ANN) models have been applied on the last 5 years (2015-2019) data of these banks. Data analysis results reveal the logistic and LDA models exhibiting similar prediction accuracy. The results of the ANN prediction model exhibit better prediction accuracy. It is expected that the results of this study will be useful for managers, depositors, regulatory bodies and shareholders to better manage their interests in the banking sector of the country.
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| 3. |
- Mishra, Nandita, et al.
(författare)
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Rising Eminence of Sustainability Reporting : Evidence from India
- 2021
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Ingår i: The Importance of New Technologies and Entrepreneurship in Business Development. - Cham : Springer. - 9783030692216 - 9783030692209 ; , s. 246-260
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Bokkapitel (refereegranskat)abstract
- This paper is an attempt to examine the sustainability reporting practices of the top 40 public & private Indian companies (as per the ET-500 list). Using NVivo software, each company’s overall disclosure index is calculated on seven identified parameters. The study is conducted by applying content analysis on the past two-year’s annual reports of all the companies. To identify substantial variation in public and private company’s disclosure norms, the Mann-Whitney U test was applied for statistical analysis. Results indicate a significant difference in disclosure of environmental, human rights, social performance, society, product responsibility, and six capitals. Public sector companies are found to be more inclined in societal disclosures while the private sector companies are more inclined towards social responsibility. Environmental disclosures exhibit higher values for public companies and social performance indicators display higher values for private sector companies.
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| 4. |
- Yadav, Miklesh, et al.
(författare)
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Dynamic connectedness of green bond with financial markets of European countries under OECD economies
- 2023
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Ingår i: Economic Change and Restructuring. - : Springer. - 1573-9414 .- 1574-0277. ; 56, s. 609-631
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Tidskriftsartikel (refereegranskat)abstract
- This paper examines the dynamic connectedness between green bonds and OECD financial markets of European countries. The study is conducted on daily price of green bonds and selected European stock markets from January 27, 2015, to August 4, 2021. Top ten European countries namely Luxembourg, Switzerland, Norway, Denmark, Germany, Netherlands, Iceland, Austria, Sweden, and Belgium are included within the OECD economies. The study uses Diebold and Yilmaz and Barunik & Krehlic tests to examine the connectedness between the economies and green bonds in short, medium, and long term. Result exhibits volatility across all frequency cycles. Brussel Stock Exchange and Euronext Amsterdam are identified as high-risk markets in the OECD European market. Evidence emerging from this study advocate the inclusion of green bonds in these financial markets for shorter time periods only. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, suggesting incorporation of green bonds in investor portfolio for efficient diversification of risk.
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| 5. |
- Yadav, Miklesh Prasad, et al.
(författare)
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Uncovering time and frequency co-movement among green bonds, energy commodities and stock market
- 2023
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Ingår i: Studies in Economics and Finance. - USA : Emerald Group Publishing Limited. - 1086-7376 .- 1086-7376.
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Tidskriftsartikel (refereegranskat)abstract
- Purpose – This paper aims to examine the comovement among green bonds, energy commodities and stockmarket to determine the advantages of adding green bonds to a diversified portfolio.Design/methodology/approach – Generic 1 Natural Gas and Energy Select SPDR Fund are used asproxies to measure energy commodities, bonds index of S&P Dow Jones and Bloomberg Barclays MSCI areused to represent green bonds and the New York Stock Exchange is considered to measure the stock market.Granger causality test, wavelet analysis and network analysis are applied to daily price for the select marketsfrom August 26, 2014, to March 30, 2021.Findings – Results from the Granger causality test indicate no causality between any pair of variables,while cross wavelet transform and wavelet coherence analysis confirm strong coherence at a high scaleduring the pandemic, validating comovement among the three asset classes. In addition, network analysisfurther corroborates this connectedness, implying a strong association of the stock market with the energycommodity market.Originality/value – This study offers new evidence of the temporal association among the US stockmarket, energy commodities and green bonds during the COVID-19 crisis. It presents a novel approach thatmeasures and evaluates comovement among the constituent series, simultaneously using both wavelet andnetwork analysis
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