Results 111 to 120 of about 237,695 (301)
Forecasting Value-at-Risk Using the Markov-Switching ARCH Model [PDF]
This paper analyzes the application of the Markov-switching ARCH model (Hamilton and Susmel, 1994) in improving value-at-risk (VaR) forecast. By considering a mixture of normal distributions with varying variances over different time and regimes, we find
Wei-Ting Tang, Yin-Feng Gau
core
Advanced Science, EarlyView.Glaucoma, a major cause of blindness, involves retinal ganglion cell (RGC) degeneration. This study shows growth hormone‐releasing hormone receptor (GHRHR) deficiency preserves RGC survival and restores vision, unlike activation which only aids survival.
Yan Tong +24 more
wiley +1 more source
BarekengThis study aims to estimate Conditional Value at Risk (CVaR) for insurance company stock portfolios using a machine learning approach to improve the accuracy of financial risk measurement under extreme market conditions.
Purwanto Purwanto, Agna Olivia
doaj +1 more source
Trading risk control model of electricity retailers in multi‐level power market of China
Energy Science & Engineering, 2019 The decision‐making and risk assessment of electricity purchase and sales is the key to adapt to the electricity market for independent electricity retailers in China.
Xiaobao Yu, Yixin Sun
doaj +1 more source
Time-varying conditional Johnson SU density in value-at-risk (VaR) methodology
Stylized facts on financial time series data are the volatility of returns that follow non-normal conditions such as leverage effects and heavier tails leading returns to have heavier magnitudes of extreme losses.
Cayton, Peter Julian A., Mapa, Dennis S.
core
Value at Risk: A Comparative Analysis [PDF]
study develops a comparative analysis concerning Value at Risk measure for a portfolio consisting of three stocks traded at Bucharest Stock Exchange. The analysis set out from 1-day, 1% VaR and has been extended in two directions: the volatility models ...
Filip Iorgulescu
core
Advanced Science, EarlyView.Slow‐transit constipation (STC) is a disabling motility disorder with unclear smooth‐muscle mechanisms. Spatial proteomic analysis of STC patient colon reveals both the central pathogenic role of smooth muscle cells (SMCs) in STC and novel regulators of intestinal motility, BIN1 and ALDH1B1.
Jianbo Liu +10 more
wiley +1 more source
Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures [PDF]
It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institutions (ADIs) to communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more ...
Michael McAleer +4 more
core +4 more sources
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
Advanced Science, EarlyView.In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
Advanced Science, EarlyView.Under colitis, Gsdmd mediates the release of IL‐33 from the epithelium of pregnant mice. IL‐33 can cross the placenta and enhance the proliferative capacity of neural stem cells, ultimately resulting in behavioral deficits in the offspring. Excessive pyroptosis in the colonic epithelium also triggers the translocation of LPS, which in turn increases ...
Huiyang Jia +4 more
wiley +1 more source