Flight to Quality for Large Financial Institutions

Local correlation analysis is used to investigate flight to quality among large financial institutions before, during, and after the financial crisis of 2008-2009. While standard correlation captures general overall linear association, local correlation analysis more accurately captures changes in the associations in response to changing market conditions. Using raw, market-adjusted, and industry-adjusted stock returns of individual banks, we investigate the performance of troubled banks and the change in investing behavior. Investors react to noisy information from the financial difficulties encountered by banking institutions. This reaction results in flight to quality. While the traditional Pearson correlations capture general overall linear association, local correlation analysis captures changes in the association in response to changing market conditions. Thus, local correlation analysis more accurately measures changes in correlation where it matters most: in the loss tail of the distribution of financial returns; leading to more appropriate diversification, portfolio management, and within-industry implications

Cointegration and Causality in Capital Markets

Purpose The purpose of this paper is to study the efficiency of different oil and gas markets. Most previous studies examined the issue using low frequency date sampled at monthly, weekly, or daily frequencies. In this study, 30-minute intraday data are used to explore efficiency in energy markets. Design/methodology/approach Sophisticated statistical analysis techniques such as Granger-causality regressions, augmented Dickey-Fuller tests, cointegration tests, vector autoregressions are used to explore the transmission of information between oil and gas energy markets. Findings This study provides evidence for efficiency in energy markets. The new information that arrives either to futures markets or spot markets is digested correctly, completely, and in a fast manner, and is propagated to the other market. The evidence indicates high efficiency. Originality/value This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets

Cryptocurrencies: applications and investment opportunities

Purpose This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the purpose of this paper is to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios. Design/methodology/approach The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.Findings The authors provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios. Originality/value This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows to compare optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods

Does an Accounting Internship Impact CPA Exam Performance?

We examined whether an accounting internship influences CPA exam performance. Using 2005–2013 candidate data, we found that an internship is significantly related to CPA exam performance in the Auditing (AUD) section. We speculate that the internship’s observed positive effect for the AUD section and the lack of effect for the other three sections is because the audit section more closely reflects knowledge/skills acquired by interns than the other three exam sections. These results have implications for academics and candidates seeking to improve CPA exam performance. Our study also provides information for those considering incorporating an accounting internship into the curriculum

UNPRME E-Meeting 1

Agenda for Zoom meeting of the Bryant University UNPRME Committee

Applicability of T1-weighted MRI in the assessment of forensic age based on the epiphyseal closure of the humeral head

This work investigates the value of magnetic resonance imaging analysis of proximal epiphyseal fusion in research examining the growth and development of the humerus and its potential utility in establishing forensic age estimation. In this study, 428 proximal humeral epiphyses (patient age, 12-30years) were evaluated with T1-weighted turbo spin echo (T1 TSE) sequences in coronal oblique orientation on shoulder MRI images. A scoring system was created following a combination of the Schmeling and Kellinghaus methods. Spearman's rank correlation analysis revealed a significant positive relationship between age and ossification stage of the proximal humeral epiphysis (all subjects: rho=0.664, p<0.001; males: 0.631, p<0.001; females: rho=0.651, p<0.001). The intra- and inter-observer reliability assessed using Cohen's kappa statistic was =0.898 and =0.828, respectively. The earliest age of epiphysis closure was 17years for females and 18years for males. MRI of the proximal humeral epiphysis can be considered advantageous for forensic age estimation of living individuals in a variety of situations, ranging from monitoring public health to estimating the age of illegal immigrants/asylum seekers, minors engaged in criminal activities, and illegal participants in competitive sports, without the danger of radiation exposure

Forensic age diagnostics by magnetic resonance imaging of the proximal humeral epiphysis

The most commonly used radiological method for age estimation of living individuals is X-ray. Computed tomography is not commonly used due to high radiation exposure, which raises ethical concerns. This problem can be solved with the use of magnetic resonance imaging (MRI), which avoids the use of ionizing radiation. The purpose of the present study was to evaluate the utility of MRI analysis of the proximal humeral epiphyses for forensic age estimations of living individuals. In this study, 395 left proximal humeral epiphyses (patient age 12-30years) were evaluated with fast-spin-echo proton density-weighted image (FSE PD) sequences in a coronal oblique orientation on shoulder MRI images. A five-stage scoring system was used following the method of Dedouit et al. The intra- and interobserver reliabilities assessed using Cohen's kappa statistic were =0.818 and =0.798, respectively. According to this study, stage five first appeared at 20 and 21years of age in males and females, respectively. These results are not directly comparable to any other published study due to the lack of MRI data on proximal humeral head development. These findings may provide valuable information for legally important age thresholds using shoulder MRI. The current study demonstrates that MRI of the proximal humerus can support forensic age estimation. Further research is needed to establish a standardized protocol that can be applied worldwide

Archaeogenetic analysis of Neolithic sheep from Anatolia suggests a complex demographic history since domestication

Yurtman, ozer, Yuncu et al. provide an ancient DNA data set to demonstrate the impact of human activity on the demographic history of domestic sheep. The authors demonstrate that there may have been multiple domestication events with notable changes to the gene pool of European and Anatolian sheep since the Neolithic. Sheep were among the first domesticated animals, but their demographic history is little understood. Here we analyzed nuclear polymorphism and mitochondrial data (mtDNA) from ancient central and west Anatolian sheep dating from Epipaleolithic to late Neolithic, comparatively with modern-day breeds and central Asian Neolithic/Bronze Age sheep (OBI). Analyzing ancient nuclear data, we found that Anatolian Neolithic sheep (ANS) are genetically closest to present-day European breeds relative to Asian breeds, a conclusion supported by mtDNA haplogroup frequencies. In contrast, OBI showed higher genetic affinity to present-day Asian breeds. These results suggest that the east-west genetic structure observed in present-day breeds had already emerged by 6000 BCE, hinting at multiple sheep domestication episodes or early wild introgression in southwest Asia. Furthermore, we found that ANS are genetically distinct from all modern breeds. Our results suggest that European and Anatolian domestic sheep gene pools have been strongly remolded since the Neolithic

Efficiency of Brent Index and Futures Markets

Previous studies on the efficiency of oiI and gas markets have used monthly, weekly, or daily data. With the fast evolving, high-speed transaction globalized financial markets; efficiency of markets is better-explored using intraday day. In this paper, data sampled at 30-minute intervals intraday are used for this purpose. The efficiency and effectiveness of information propagation is examined between spot and derivatives markets of oil and gas commodities. Furthermore, the interpretation of new information and its incorporation into the prices are also examined with high frequency sampled data. The evidence from oil and gas markets is indicative of well-functioning commodity markets with highly efficiency conduction of information