50 research outputs found
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
2,4-Diiodo-3-nitroÂanisole
In the title compound (systematic name: 1,3-diiodo-4-methÂoxy-2-nitroÂbenzene), C7H5I2NO3, the dihedral angle between the benzene ring and the nitro group is 88.0 (3)°, and the methyl group lies almost in the same plane as the ring [deviation = 0.034 (6) Å]. In the crystal, aromatic π–π stacking occurs between inversion-related rings [centroid–centroid separation = 3.865 (3) Å and slippage = 0.642 Å]. A possible weak C—I⋯π interÂaction occurs [I⋯π = 3.701 (2) Å and C—I⋯π = 130.18 (13)°], but there are no significant interÂmolecular I⋯I contacts
3,15-DimethÂoxy-10-methylÂtricycloÂ[9.4.0.02,7]pentaÂdeca-1(11),2(7),3,5,9,12,14-heptaen-8-one
The title molÂecule, C18H16O3, contains three fused rings, of which the seven-membered cycloÂhept-2-enone ring has a screw-boat conformation. The two methÂoxyÂphenyl rings make a dihedral angle of 50.4 (2)°. In the crystal, molÂecules are linked by interÂmolecular C—H⋯O hydrogen bonds, leading to a three-dimensional supraÂmolecular architecture
Research on Three-phase Optimal Power Flow for Distribution Networks Based on Constant Hessian Matrix
Influential factors on urine EV DNA methylation detection and its diagnostic potential in prostate cancer
The value of Extracellular vesicles (EVs) diagnostic markers is widely recognized. However, current research on EV DNA remains limited. This study investigates the biological properties, preprocessing factors, and diagnostic potential of EV DNA. We found that DNA positive vesicles account for 23.3% ± 6.7% of the urine total EV, with a large amount of DNA attached to the outside. EV DNA fragments are large, there is no significant effect on uEV DNA when store urine less than 6 h at 4°C. In addition, the influence of different EV extraction methods on methylation detection is also minor. More importantly, RASSF1A methylation in urine total EV DNA can distinguish between PCa and BPH, with an AUC of 0.874. Our results suggest the potential of urine EV DNA as a novel marker for PCa diagnosis. This provides a new idea for the study of urinary tumor markers
Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis
Testing and comparing two self-care-related instruments among older Chinese adults
Objectives The study aimed to test and compare the reliability and validity, including sensitivity and specificity of the two self-care-related instruments, the Self-care Ability Scale for the Elderly (SASE), and the Appraisal of Self-care Agency Scale-Revised (ASAS-R), among older adults in the Chinese context. Methods A cross-sectional design was used to conduct this study. The sample consisted of 1152 older adults. Data were collected by a questionnaire including the Chinese version of SASE (SASE-CHI), the Chinese version of ASAS-R (ASAS-R-CHI) and the Exercise of Self-Care Agency scale (ESCA). Homogeneity and stability, content, construct and concurrent validity, and sensitivity and specificity were assessed. Results The Cronbach's alpha (α) of SASE-CHI was 0.89, the item-to-total correlations ranged from r = 0.15 to r = 0.81, and the test-retest correlation coefficient (intra-class correlation coefficient, ICC) was 0.99 (95% CI, 0.99±1.00; P<0.001). The Cronbach's α of ASAS-R-CHI was 0.78, the item-to-total correlations ranged from r = 0.20 to r = 0.65, and the test-retest ICC was 0.95 (95% CI, 0.92±0.96; P<0.001). The content validity index (CVI) of SASE-CHI and ASAS-R-CHI was 0.96 and 0.97, respectively. The findings of exploratory and confirmatory factor analyses (EFA and CFA) confirmed a good construct validity of SASE-CHI and ASAS-R-CHI. The Pearson's rank correlation coefficients, as a measure of concurrent validity, between total score of SASE-CHI and ESCA and ASAS-R-CHI and ESCA were assessed to 0.65 (P<0.001) and 0.62 (P<0.001), respectively. Regarding ESCA as the criterion, the area under the receiver operator characteristic (ROC) curve for the cut-point of SASE-CHI and ASAS-R-CHI were 0.93 (95% CI, 0.91±0.94) and 0.83 (95% CI, 0.80±0.86), respectively. Conclusion There is no significant difference between the two instruments. Each has its own characteristics, but SASE-CHI is more suitable for older adults. The key point is that the users can choose the most appropriate scale according to the specific situation.publishedVersionNivå
Most Lithium-rich Low-mass Evolved Stars Revealed as Red Clump stars by Asteroseismology and Spectroscopy
Lithium has confused scientists for decades at almost each scale of the
universe. Lithium-rich giants are peculiar stars with lithium abundances over
model prediction. A large fraction of lithium-rich low-mass evolved stars are
traditionally supposed to be red giant branch (RGB) stars. Recent studies,
however, report that red clump (RC) stars are more frequent than RGB. Here, we
present a uniquely large systematic study combining the direct asteroseismic
analysis with the spectroscopy on the lithium-rich stars. The majority of
lithium-rich stars are confirmed to be RCs, whereas RGBs are minor. We reveal
that the distribution of lithium-rich RGBs steeply decline with the increasing
lithium abundance, showing an upper limit around 2.6 dex, whereas the Li
abundances of RCs extend to much higher values. We also find that the
distributions of mass and nitrogen abundance are notably different between RC
and RGB stars. These findings indicate that there is still unknown process that
significantly affects surface chemical composition in low-mass stellar
evolution.Comment: 27 pages, 10 figures, 3 table