Results 21 to 30 of about 989 (203)
Long memory and FIGARCH models for daily and high frequency commodity prices [PDF]
, 2007 Daily futures returns on six important commodities are found to be well described as FIGARCH fractionally integrated volatility processes, with small departures from the martingale in mean property. The paper also analyzes several years of high frequency
Myers, Robert J. +3 more
core +2 more sources
Analytic Hessian matrices and the computation of FIGARCH estimates [PDF]
Statistical Methods & Applications, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LOMBARDI M., GALLO, GIAMPIERO MARIA
openaire +3 more sources
Modelling High-Frequency Volatility with Three-State FIGARCH Models [PDF]
SSRN Electronic Journal, 2013 Abstract Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH) models have enjoyed considerable popularity over the past decade because of their ability to capture the features of volatility clustering and long-memory persistence.
Shi, Yanlin, Ho, Kin-Yip
openaire +3 more sources
Direct versus iterated multiperiod Value‐at‐Risk forecasts
Journal of Economic Surveys, Volume 37, Issue 3, Page 915-949, July 2023., 2023 Abstract Since the late nineties, the Basel Accords require financial institutions to measure their financial risk by reporting daily predictions of Value at Risk (VaR) based on 10‐day returns. However, a vast part of the related literature deals with VaR predictions based on one‐period returns.
Esther Ruiz, María Rosa Nieto
wiley +1 more source
Volatility and dynamic dependence modeling: Review, applications, and financial risk management
WIREs Computational Statistics, Volume 14, Issue 5, September/October 2022., 2022 Moving 20‐day window dynamic risks of Alphabet Inc. (GOOGL), the Bank of America Corporation (BAC), and the Coca‐Cola Company (KO) during 26 December 2017 to 31 December 2020. Abstract Since the introduction of ARCH models close to 40 years ago, a wide range of models for volatility estimation and prediction have been developed and integrated into ...
Mike K. P. So +3 more
wiley +1 more source
International Review of Finance, Volume 22, Issue 3, Page 540-550, September 2022., 2022 Abstract We examine the forecasting power of a daily newspaper‐based index of uncertainty associated with infectious diseases (EMVID) for real estate investment trusts (REITs) realized market variance of the United States (US) via the heterogeneous autoregressive realized volatility (HAR‐RV) model.
Matteo Bonato +3 more
wiley +1 more source
Integrated ARCH, FIGARCH and AR models: Origins of long memory
, 2015 Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH solution was not established in the literature.
Škarnulis, Andrius +2 more
core +2 more sources
Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning
Discrete Dynamics in Nature and Society, Volume 2022, Issue 1, 2022., 2022 With the gradual integration of global economy and finance, the financial market presents many complex financial phenomena. To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm.
Wangsong Xie, Stefan Cristian Gherghina
wiley +1 more source
Commonality in the LME aluminum and copper volatility processes through a FIGARCH lens [PDF]
Journal of Futures Markets, 2008 AbstractDynamic representation of spot and three‐month aluminum and copper volatilities is considered. Aluminum and copper are the two most important metals traded in the London Metal Exchange. They share common business cycle factors and are traded under identical contract specifications.
Figuerola Ferretti Garrigues, Isabel Catalina +1 more
openaire +4 more sources
[Retracted] Prediction of High‐Frequency Economic Data Based on Stochastic Fluctuation Model
Security and Communication Networks, Volume 2022, Issue 1, 2022., 2022 In order to improve the effect of economic high‐frequency data analysis, this paper combines the stochastic fluctuation model to carry out the forecast analysis of economic high‐frequency data. Moreover, this paper uses the spider web model for data processing and makes a preliminary judgment on the extent to which futures/stock prices lead the spot ...
Xiaoyang Zhang +3 more
wiley +1 more source