Results 31 to 40 of about 5,992 (265)
Volatility Forecasting: Downside Risk, Jumps and Leverage Effect
Econometrics, 2016 We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the ...
Francesco Audrino, Yujia Hu
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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 +2 more
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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
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A general equilibrium approach to pricing volatility risk.
PLoS ONE, 2019 This paper provides a general equilibrium approach to pricing volatility. Existing models (e.g., ARCH/GARCH, stochastic volatility) take a statistical approach to estimating volatility, volatility indices (e.g., CBOE VIX) use a weighted combination of ...
Jianlei Han +4 more
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Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
Molecular Oncology, EarlyView.The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
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PERAMALAN VOLATILITAS SAHAM MENGGUNAKAN MODEL EXPONENTIAL GARCH DAN THRESHOLD GARCH
E-Jurnal Matematika, 2019 In financial data there is asymmetric volatility, which denotes the different movements on conditional volatility of increase and decrease financial asset returns.
SITI RAHAYU NINGSIH +2 more
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FEBS Open Bio, EarlyView.CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 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
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, 2017 In Sects. 2.3 and 4.2, the common volatility modelling oversights that exist in literature were highlighted. In this Chapter, we discuss the potential impact of these oversights on volatility forecasting and provide a methodology for testing the impact of these oversights on the forecasting accuracy of volatility models.
Mostafa, F, Dillon, T, Chang, E
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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 +11 more
wiley +1 more source