Results 51 to 60 of about 10,989,864 (91)

Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods. [PDF]

SN Bus Econ, 2022
Sahiner M.
europepmc   +1 more source

Dual long memory of inflation and test of the relationship between inflation and inflation uncertainty

long memory, inflation rate, inflation uncertainty, ARFIMA-FIGARCH, C22, E31, 长记忆性, 通货膨胀率, 通货膨胀不确定性, ARFIMA-FIGARCH,
Tingguo Zheng, Jinquan Liu, Jianli Sui
core   +1 more source

Estimating Value-at-Risk for the Turkish Stock Index Futures in the Presence of Long Memory Volatility [PDF]

This paper examines the long memory properties for closing prices of the Turkish stock index futures market using the FIGARCH(1,d,1) model with three different distributions : Normal, Student-t, and skewed Student-t.
Adnan Kasman
core  

Stock Market Volatility and Return Analysis: A Systematic Literature Review. [PDF]

Entropy (Basel), 2020
Bhowmik R, Wang S.
europepmc   +1 more source

Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach [PDF]

Previous models of monthly CPI inflation time series have focused on possible regime shifts, non-linearities and the feature of long memory. This paper proposes a new time series model, named Adaptive ARFIMA; which appears well suited to describe ...
Richard T. Baille, Claudio Morana
core  

Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models [PDF]

, 2004
We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory ...
Kaizoji, Taisei, Lux, Thomas
core  

Long memory mean and volatility models of platinum and palladium price return series under heavy tailed distributions. [PDF]

Springerplus, 2016
Ranganai E, Kubheka SB.
europepmc   +1 more source

Fractional Integration and Business Cycles Features [PDF]

We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well ...
Luis A. Gil-Alana, Bertrand Candelon
core  

Forecasting UNTR Weekly Stock Price using ARFIMA

Predicting stock prices plays a pivotal role in the decision-making processes of organizations and individual investors. This research focuses on the predicting weekly closing stock prices, specifically for UNTR, using the ARFIMA method.
Gabriella Maria Singgih, Dadang Amir Hamzah   +1 more
core   +1 more source

High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions. [PDF]

PLoS One
Kuang W.
europepmc   +1 more source