Forecasting Corn Futures Volatility in the Presence of Long Memory, Seasonality and Structural Change [PDF]
Price volatility in the corn market has changed considerably globalization and stronger linkages to the energy complex. Using data from January 1989 through December 2009, we estimate and forecast the volatility in the corn market using futures daily ...
Garcia, Philip, Wang, Xiaoyang
core +1 more source
The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey [PDF]
The purpose of this study is to test predictive performance of Asymmetric Normal Mixture GARCH (NMAGARCH) and other GARCH models based on Kupiec and Christoffersen tests for Turkish equity market.
Alper Özün, Atilla Çifter
core +3 more sources
Gestão & Produção, 2012 O presente estudo propõe uma análise comparativa de dez modelos de volatilidade para o cálculo do Value-at-Risk (VaR) para carteira teórica do Ibovespa, considerando a presença de memória longa na série temporal dos seus retornos diários.
Luiz Eduardo Gaio +1 more
doaj +1 more source
Long Memory and FIGARCH Models for Daily and High Frequency Commodity Prices [PDF]
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
Jeongseok Song +3 more
core
Economies, 2019 The impact that oil market shocks have on stock markets of oil-related economies has several implications for both domestic and foreign investors. Thus, we investigate the role of the oil market in deriving the dynamic linkage between stock markets of ...
Manel Youssef, Khaled Mokni
doaj +1 more source
New practice for investors in Chinese stock market: From perspective of fractionally integrated realized GARCH model. [PDF]
Heliyon, 2023 Xiao M, Tao Z, Gu Z, Li Z, Chen X.
europepmc +1 more source
Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models [PDF]
This paper investigates whether structural breaks and long memory are relevant features in modeling and forecasting the conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural breaks ...
Amine Lahiani +2 more
core
Application of FIGARCH and EWMA Models on Stock Indices PX and BUX [PDF]
Acta Oeconomica Pragensia, 2011 Volatility of the financial time series belongs to the crucial estimated parameters in finance (e.g. in risk management, derivative pricing). It is well known, that volatility varies in time, so that new approaches of volatility modeling have appeared.
openaire +1 more source
Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets
International Journal of Financial Studies, 2016 In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory, fat tails and
Samet Günay
doaj +1 more source
VOLATILITY AND VAR FORECASTING FOR THE IBEX-35 STOCK-RETURN INDEX USING FIGARCH-TYPE PROCESSES AND DIFFERENT EVALUATION CRITERIA [PDF]
In this paper I analyze the relative performance of Gaussian and Student-t GARCH and FIGARCH type models for volatility and Value-at-Risk forecasting of daily stock-returns using data from the Spanish equity index IBEX-35.
Trino-Manuel Ñíguez
core