Results 181 to 190 of about 48,781 (279)

Intraday Functional PCA Forecasting of Cryptocurrency Returns

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

Quantum tunneling and its absence in deep wells and strong magnetic fields. [PDF]

open access: yesProc Natl Acad Sci U S A
Fefferman CL, Shapiro J, Weinstein MI.
europepmc   +1 more source

Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence From Markov‐Switching Multifractal Models

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu   +3 more
wiley   +1 more source

Evidence of Coulomb liquid phase in few-electron droplets. [PDF]

open access: yesNature
Shaju J   +14 more
europepmc   +1 more source

Evaluating Forecasts at Multiple Horizons: An Extension of the Diebold–Mariano Approach

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecast accuracy tests are fundamental tools for comparing competing predictive models. The widely used Diebold–Mariano (DM) test assesses whether differences in forecast errors are statistically significant. However, its standard form is limited to pairwise comparisons at a single forecast horizon.
Andrew Grant   +2 more
wiley   +1 more source

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

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