Results 31 to 40 of about 4,901 (213)

PERAMALAN NILAI EKSPOR MIGAS DENGAN MENERAPKAN MODEL AUTOREGREGRESSIVE FRACTIONALLY INTEGRATED MOVING AVERAGE (ARFIMA)

open access: yesJurnal Lebesgue
Indonesia, a nation in Southeast Asia, has a wealth of natural resources that could serve as the basis for future economic growth. Increased exports of natural resources are crucial for market expansion, job creation, foreign exchange gains, and economic
Putri Hazizah Rahwani   +2 more
doaj   +1 more source

Mathematical Models for Dynamics of Molecular Processes in Living Biological Cells. A Single Particle Tracking Approach

open access: yesAnnales Mathematicae Silesianae, 2018
In this survey paper we present a systematic methodology of how to identify origins of fractional dynamics. We consider three models leading to it, namely fractional Brownian motion (FBM), fractional Lévy stable motion (FLSM) and autoregressive ...
Weron Aleksander
doaj   +1 more source

Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility [PDF]

open access: yes, 2013
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

Comparing the bias and misspecification in ARFIMA models [PDF]

open access: yesJournal of Time Series Analysis, 1997
We investigate the bias in both the short‐term and long‐term parameters for a range of autoregressive fractional integrated moving‐average (ARFIMA) models using both semi‐parametric and maximum likelihood (ML) estimation methods. The results suggest that, provided the correct model is estimated, the ML method outperforms the semi‐parametric methods in ...
Smith, Jeremy   +2 more
openaire   +2 more sources

On the invertibility in periodic ARFIMA models

open access: yes, 2020
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

Wavelet based long memory model for modelling wheat price in India

open access: yesThe Indian Journal of Agricultural Sciences, 2021
Agricultural time-series data concerning production, prices, export and import of several agricultural commodities is published by Indian government along with other private agricultural sectors every year.
RANJIT KUMAR PAUL   +2 more
doaj   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann   +2 more
wiley   +1 more source

Forecasting price of Indian mustard (Brassica juncea) using long memory time series model incorporating exogenous variable

open access: yesThe Indian Journal of Agricultural Sciences, 2022
The objective of present study was to investigate the efficiency of Autoregressive fractionally integrated moving average model with exogenous input (ARFIMAX) in forecasting price of Indian mustard [Brassica juncea (L.) Czern. & Coss].
RANJIT KUMAR PAUL   +4 more
doaj   +1 more source

Error and Model Misspecification in ARFIMA Process

open access: yesBrazilian Review of Econometrics, 2001
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

Using Deep Learning Conditional Value‐at‐Risk Based Utility Function in Cryptocurrency Portfolio Optimisation

open access: yesInternational Journal of Finance &Economics, EarlyView.
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

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