Results 41 to 50 of about 23,794,745 (244)
Geometric shrinkage priors for K\"ahlerian signal filters
We construct geometric shrinkage priors for K\"ahlerian signal filters. Based on the characteristics of K\"ahler manifolds, an efficient and robust algorithm for finding superharmonic priors which outperform the Jeffreys prior is introduced. Several ans\"
Choi, Jaehyung, Mullhaupt, Andrew P.
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On the invertibility in periodic ARFIMA models
The present paper, characterizes the invertibility and causality conditions of a periodic ARFIMA (PARFIMA) models. We first, discuss the conditions in the multivariate case, by considering the corresponding p-variate stationary ARFIMA models. Second, we construct the conditions using the univariate case and we deduce a new infinite autoregressive ...
Amimour, Amine, Belaide, Karima
openaire +2 more sources
ABSTRACT One of the critical risks associated with cryptocurrency assets is the so‐called downside risk, or tail risk. Conditional Value‐at‐Risk (CVaR) is a measure of tail risks that is not normally considered in the construction of a cryptocurrency portfolio.
Xinran Huang +3 more
wiley +1 more source
Sesgos en estimación, tamaño y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA Resumen: Castaño et al. (2008) proponen una prueba para investigar la existencia de memoria larga, basada en el parámetro de diferenciación ...
Elkin Castaño Vélez +2 more
doaj +1 more source
Error and Model Misspecification in ARFIMA Process
In developing the long and short memory estimation, it is usually assumed that the innovations in the ARFIMA model are normally distributed. However, circumstances may occur where this assumption is not true. This paper uses Monte Carlo simulation to evaluate the robustness of different estimators of the fractional parameter in stationary and ...
Valderio A. Reisen +2 more
openaire +2 more sources
A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley +1 more source
Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
doaj
We introduce a method for reconstructing macroscopic models of one-dimensional stochastic processes with long-range correlations from sparsely sampled time series by combining fractional calculus and discrete-time Langevin equations.
Johannes A. Kassel, Holger Kantz
doaj +1 more source
Today, the astonishing growth of digital currency has attracted many bold investors. This has caused digital currencies to be gradually introduced as a new asset class with its own criteria. However, the relationship between traditional assets and new assets is not yet deeply understood. This study’s objective is to investigate the dynamic relationship
Farzaneh Shams Tarnabi, Fabio Tramontana
wiley +1 more source
Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility [PDF]
This paper investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex-post variation in asset prices as well as option-implied volatility.
Barunik, Jozef, Zikes, Filip
core +2 more sources

