Search Results (6)

We study a Mean-Risk model, where risk is measured by a Modified CoVaR (Conditional Value at Risk): ${CoVaR}_{\alpha ,\beta }^{\le }\left(X\right|Y)=Va{R}_{\beta }\left(X\right|Y+Va{R}_{\alpha }\left(Y\right)\le 0).$ We prove that in a Gaussian setting, for a sufficiently small $\beta$, such a model has a solution. There exists a portfolio that fulfills the given constraints and for which the risk is minimal. This is shown in relation to the mean–standard deviation portfolio, and numerical examples are provided. Full article

The S&P 500 Index is considered the most popular trading instrument in financial markets. With the rise of cryptocurrencies over the past few years, Bitcoin has grown in popularity and adoption. This study analyzes the daily return distribution of Bitcoin and the S&P 500 Index and assesses their tail probabilities using two financial risk measures. As a methodology, we use Bitcoin and S&P 500 Index daily return data to fit the seven-parameter General Tempered Stable (GTS) distribution using the advanced fast fractional Fourier transform (FRFT) scheme developed by combining the fast fractional Fourier transform algorithm and the 12-point composite Newton–Cotes rule. The findings show that peakedness is the main characteristic of the S&P 500 Index return distribution, whereas heavy-tailedness is the main characteristic of Bitcoin return distribution. The GTS distribution shows that $80.05\%$ of S&P 500 returns are within $-1.06\%$ and $1.23\%$ against only $40.32\%$ of Bitcoin returns. At a risk level ($\alpha$), the severity of the loss ($AVa{R}_{\alpha }\left(X\right)$) on the left side of the distribution is larger than the severity of the profit ($AVa{R}_{1-\alpha }\left(X\right)$) on the right side of the distribution. Compared to the S&P 500 Index, Bitcoin has $39.73\%$ more prevalence to produce high daily returns (more than $1.23\%$ or less than $-1.06\%$). The severity analysis shows that, at $\alpha$ risk level, the average value-at-risk ($AVaR\left(X\right)$) of Bitcoin returns at one significant figure is four times larger than that of the S&P 500 Index returns at the same risk. Full article

Neuropathy is a serious and frequent complication of type 2 diabetes (T2DM). This study was carried out to search for genetic factors associated with the development of diabetic neuropathy by whole exome sequencing. For this study, 24 patients with long-term type 2 diabetes with neuropathy and 24 without underwent detailed neurological assessment and whole exome sequencing. Cardiovascular autonomic function was evaluated by cardiovascular reflex tests. Heart rate variability was measured by the triangle index. Sensory nerve function was estimated by Neurometer and Medoc devices. Neuropathic symptoms were characterized by the neuropathy total symptom score (NTSS). Whole exome sequencing (WES) was performed on a Thermo Ion GeneStudio S5 system determining the coding sequences of approximately 32,000 genes comprising 50 million base pairs. Variants were detected by Ion Reporter software and annotated using ANNOVAR, integrating database information from dbSNP, ClinVar, gnomAD, and OMIM. Integrative genomics viewer (IGV) was used for visualization of the mapped reads. We have identified genetic variants that were significantly associated with increased (22–49-fold) risk of neuropathy (rs2032930 and rs2032931 of recQ-mediated genome instability protein 2 (RMI2) gene), rs604349 of myosin binding protein H like (MYBPHL) gene and with reduced (0.07–0.08-fold) risk (rs917778 of multivesicular body subunit 12B (MVB12B) and rs2234753 of retinoic acid X receptor alpha (RXRA) genes). The rs2032930 showed a significant correlation with current perception thresholds measured at 5 Hz and 250 Hz for n. medianus (p = 0.042 and p = 0.003, respectively) and at 5 Hz for n. peroneus (p = 0.037), as well as the deep breath test (p = 0.022) and the NTSS (p = 0.023). The rs2032931 was associated with current perception thresholds (p = 0.003 and p = 0.037, respectively), deep breath test (p = 0.022), and NTSS (p = 0.023). The rs604349 correlated with values measured at 2000 (p = 0.049), 250 (p = 0.018), and 5 Hz (p = 0.005) for n. medianus, as well as warm perception threshold measured by Medoc device (p = 0.042). The rs2234753 showed correlations with a current perception threshold measured at 2000 Hz for n. medianus (p = 0.020), deep breath test (p = 0.040), and NTSS (p = 0.003). There was a significant relationship between rs91778 and cold perception threshold (p = 0.013). In our study, genetic variants have been identified that may have an impact on the risk of neuropathy developing in type 2 diabetic patients. These results could open up new opportunities for early preventive measures and might provide targets for new drug developments in the future. Full article

The search for less expensive and viable products is always one of the challenges for research development. Commonly, the synthesis of coordination compounds involves expensive ligands, through expensive and low-yield routes, in addition to generating toxic and unusable residues. In this work, the organic ligand used is derived from the resin of a reforestation tree, Pinus elliottii var. elliottii. The synthesis method used Pinus resin and an aqueous solution of vanadium(III) chloride at a temperature of 80 °C. The procedure does not involve organic solvents and does not generate toxic residues, thus imparting the complex formation reaction a green chemistry character. The synthesis resulted in an unprecedented oxovanadium(IV)-bis(abietate) complex, which was characterized by mass spectrometry (MS), chemical analysis (CHN), vibrational (FTIR) and electronic spectra (VISIBLE), X-ray diffraction (XRD), and thermal analysis (TG/DTA). Colorimetric studies were performed according to the CIELAB color space. The structural formula found, consisted of a complex containing two abietate ligands, [VO(C₂₀H₂₉O₂)₂]. The VO(IV)-bis(abietate) complex was applied against microorganisms and showed promising results in antibacterial and antifungal activity. The best result of inhibitory action was against the strains of Gram-positive bacteria S. aureus and L. monocytogenes, with minimum inhibitory concentration (MIC) values of 62.5 and 125 μmol L⁻¹, respectively. For Gram-negative strains the results were 500 μmol L⁻¹ for E. coli; and 1000 μmol L⁻¹ for Salmonella enterica Typhimurium. Antifungal activity was performed against Candida albicans, where the MIC was 15.62 μmol L⁻¹, and for C. tropicalis it was 62.5 μmol L⁻¹. According to the MFC analysis, the complex presented, in addition to the fungistatic action, a fungicidal action, as there was no growth of fungi on the plates tested. The results found for the tests demonstrate that the VO(IV)-bis(abietate) complex has great potential as an antimicrobial and mainly antifungal agent. In this way, the pigmented ink with antimicrobial activity could be used in environments with a potential risk of contamination, preventing the spread of microorganisms harmful to health. Full article

In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate Value-at-Risk (VaR) by means of the proposed distribution. We compare the distribution with a few other models to show its versatility in modelling data with heavy tails. VaR estimation with the Burr X Pareto distribution is presented using time series data, and the new model could be considered as an alternative VaR model against the generalized Pareto model for financial institutions. Full article

A spectrum of upper bounds (Q_α(X ; p) _αε[0,∞] on the (largest) (1-p)-quantile Q(X;p) of an arbitrary random variable X is introduced and shown to be stable and monotonic in α, p, and X , with Q₀(X ;p) = Q(X;p). If p is small enough and the distribution of X is regular enough, then Q_α(X ; p) is rather close to Q(X ; p). Moreover, these quantile bounds are coherent measures of risk. Furthermore, Q_α(X ; p) is the optimal value in a certain minimization problem, the minimizers in which are described in detail. This allows of a comparatively easy incorporation of these bounds into more specialized optimization problems. In finance, Q₀(X;p) and Q₁(X ; p) are known as the value at risk (VaR) and the conditional value at risk (CVaR). The bounds Q_α(X ; p) can also be used as measures of economic inequality. The spectrum parameter α plays the role of an index of sensitivity to risk. The problems of the effective computation of the bounds are considered. Various other related results are obtained. Full article