Results 41 to 50 of about 583,999 (299)

Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms

Future Business Journal, 2023
The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN ...
Farman Ullah Khan, Faridoon Khan, Parvez Ahmed Shaikh   +2 more
doaj   +1 more source

Comprehensive Characterization of 98 Chinese Cases of Genetic Creutzfeldt‐Jakob Disease With T188K Mutation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To characterize the demographic, clinical, and laboratory features of the Chinese patients of genetic Creutzfeldt‐Jakob disease with T188K variant (T188K‐gCJD), the most common subtype of genetic prion diseases (gPrDs) in China. Methods In this nationwide retrospective study, data from 98 genetically confirmed T188K‐gCJD patients ...
Chun‐Jie Li, Dong‐Lin Liang, Li‐Ping Gao, Wei‐Wei Zhang, Wei Zhou, A. Ruhan, Bing Xu, Run‐Dong Cao, Kang Xiao, Cao Chen, Qi Shi, Xiao‐Ping Dong   +11 more
wiley   +1 more source

Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets

Indonesian Capital Market Review, 2014
Volatility forecasting is an imperative research field in financial markets and crucial component in most financial decisions. Nevertheless, which model should be used to assess volatility remains a complex issue as different volatility models result in ...
Erie Febrian, Aldrin Herwany
doaj   +1 more source

Adding dummy variables: A simple approach for improved volatility forecasting in electricity market

Journal of Management Science and Engineering, 2023
This study used dummy variables to measure the influence of day-of-the-week effects and structural breaks on volatility. Considering day-of-the-week effects, structural breaks, or both, we propose three classes of HAR models to forecast electricity ...
Xu Gong, Boqiang Lin
doaj   +1 more source

Validation of a Cellular Imaging‐Based Method as a Potential Biomarker for SPG4 Hereditary Spastic Paraplegia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Hereditary Spastic Paraplegia (HSP) comprises a group of rare genetic diseases characterized by length‐dependent axonal degeneration of the corticospinal tracts and dorsal columns, whose main clinical feature is spastic gait. Pathogenic variants in the SPG4 gene cause Spastic Paraplegia Type 4 (SPG4‐HSP), the most common form of HSP.
Gaia Fattorini, Valerio Licursi, Gianmarco Dalla Zanna, Flavio Dal Canto, Melissa Barghigiani, Nunzio Setola, Salvatore Rossi, Antonio Funcis, Filippo M. Santorelli, Gabriella Silvestri, Carlo Casali, Francesca Sardina, Cinzia Rinaldo   +12 more
wiley   +1 more source

Forecasting Bitcoin Volatility Spikes From Whale Transactions and CryptoQuant Data Using Synthesizer Transformer Models

IEEE Access
The cryptocurrency market is highly volatile compared to traditional financial markets. Hence, forecasting its volatility is crucial for risk management. In this paper, we investigate CryptoQuant data (e.g.
Dorien Herremans, Kah Wee Low
doaj   +1 more source

Volatility Forecasting for High-Frequency Financial Data Based on Web Search Index and Deep Learning Model

Mathematics, 2021
The existing index system for volatility forecasting only focuses on asset return series or historical volatility, and the prediction model cannot effectively describe the highly complex and nonlinear characteristics of the stock market.
Bolin Lei, Boyu Zhang, Yuping Song
doaj   +1 more source

Diffuse MRI Edema Predicts Relapse in Cerebral Amyloid Angiopathy–Related Inflammation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To identify MRI predictors of relapse and quantify relapse and mortality risk in cerebral amyloid angiopathy–related inflammation (CAA‐RI). A secondary objective was to assess the association between mycophenolate mofetil use and relapse risk. Methods We performed a retrospective cohort study of 36 patients with CAA‐RI treated at the
G. Abbas Kharal, Gowtham Yerneni, Kim J. Griffin, Nicolas Thompson, Ken Uchino, Irene Katzan, Dolora Wisco, Abeer Farrag, Jayashree Sundarajan, Andrew Russman, M. Shazam Hussain   +10 more
wiley   +1 more source

Innovative Study on Volatility Prediction Model for New Energy Stock Indices

IEEE Access
Stock market volatility is a pivotal research area in finance, and accurately forecasting stock market volatility has long been a challenge for both academia and practice.
Yanguo Li, Chao Long
doaj   +1 more source

Evaluating volatility and interval forecasts

Journal of Forecasting, 1999
A widely used approach to evaluating volatility forecasts uses a regression framework which measures the bias and variance of the forecast. We show that the associated test for bias is inappropriate before introducing a more suitable procedure which is based on the test for bias in a conditional mean forecast.
openaire   +3 more sources