Results 31 to 40 of about 583,999 (299)
Historical Perspectives in Volatility Forecasting Methods with Machine Learning
RisksVolatility forecasting for financial institutions plays a pivotal role across a wide range of domains, such as risk management, option pricing, and market making.
Zhiang Qiu +3 more
doaj +1 more source
Hybrid Forecasting Models Based on the Neural Networks for the Volatility of Bitcoin
Applied Sciences, 2020 In this paper, we study the volatility forecasts in the Bitcoin market, which has become popular in the global market in recent years. Since the volatility forecasts help trading decisions of traders who want a profit, the volatility forecasting is an ...
Monghwan Seo, Geonwoo Kim
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International Journal of Management, Finance and AccountingThis study examines whether realised range volatility improves multivariate volatility forecasting performance in an emerging equity market setting. A comparison between vector heterogeneous autoregressive models constructed with realised volatility ...
Mariam Mohamed Abdelwahab Mohamed Badawi +3 more
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Modelling and Forecasting Noisy Realized Volatility [PDF]
Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even
Michael McAleer +2 more
core +6 more sources
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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Structural and biochemical analysis of a B12 superbinder
FEBS Letters, EarlyView.BtuG proteins are vitamin B12 scavengers in Bacteroides thetaiotaomicron, a dominant human gut bacterium. We present crystal structures of three BtuG homologs bound to cobalamin and its precursor cobinamide, revealing picomolar binding affinities, among the highest known for any natural protein.
Jose M. Martinez Felices +3 more
wiley +1 more source
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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Volatility Forecast in Crises and Expansions [PDF]
Journal of Risk and Financial Management, 2015 We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as ...
openaire +3 more sources
Ethical Foreground and Background in Adult Educator Work
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Adult educators work in a complex ethical environment. The very act of contributing to the learning of another is fraught with moral overtones. In this paper we consider the ethical dimensions of adult educator practice by distinguishing the ethical features of the context or ‘background’ of practice from the ethical capabilities and decision ...
Steven Hodge, Sonal Nakar
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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
doaj +1 more source