Volatility Modeling and Spillover: The Turkish and Russian Stock Markets
Istanbul Business ResearchThis study investigates the internal and external (spillover) characteristics of the volatility of the Turkish and Russian stock market indices. To this end, generalized autoregressive conditional heteroskedasticity models that are classified as short ...
Ahmet Galip Gençyürek
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Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models [PDF]
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
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Estimation and Prediction of Commodity Returns Using Long Memory Volatility Models
RisksModelling the volatility of commodity prices and creating more reliable models for estimating and forecasting commodity price returns are crucial.
Kisswell Basira +4 more
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Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach [PDF]
This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the conditional variance process.
Claudio Morana, Richard T. Baillie
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Dynamic linkages and determinants of sovereign CDS and exchange rates: evidence from G7 and BRICS
Humanities & Social Sciences CommunicationsIn the wake of the COVID-19 pandemic, global public debt has escalated, further intensified by ongoing geopolitical tensions. This paper explores the dynamic relationship between sovereign credit risk and exchange rate fluctuations through the innovative
Min Su +3 more
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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
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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
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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
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
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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
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