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Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures
Liu, Hung-Chun; Chiang, Shu-mei; Cheng, Nick Ying-pin - In: International review of economics & finance : IREF 22 (2012) 1, pp. 78-91
Persistent link: https://www.econbiz.de/10009618705
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Selection criteria in regime switching conditional volatility models
Chuffart, Thomas - In: Econometrics : open access journal 3 (2015) 2, pp. 289-316
Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and …
Persistent link: https://www.econbiz.de/10011297653
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Generalized fractional processes with long memory and time dependent volatility revisited
Peiris, M. Shelton; Asai, Manabu - In: Econometrics : open access journal 4 (2016) 3, pp. 1-21
follow GARCH and stochastic volatility (SV). Under certain regularity conditions, we give asymptotic results for the … approximate maximum likelihood estimator for the GARMA-GARCH model. We discuss a Monte Carlo likelihood method for the GARMA …
Persistent link: https://www.econbiz.de/10011568296
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Modeling autoregressive processes with moving-quantiles-implied nonlinearity
Ishida, Isao; Kvedaras, Virmantas - In: Econometrics : open access journal 3 (2015) 1, pp. 2-54
We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor's 500...
Persistent link: https://www.econbiz.de/10010478989
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Testing for a set of linear restrictions in VARMA models using autoregressive metric : an application to Granger causality test
Di Iorio, Francesca; Triacca, Umberto - In: Econometrics : open access journal 2 (2014) 4, pp. 203-216
In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...
Persistent link: https://www.econbiz.de/10010479050
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COVID-19 pandemic and Romanian stock market volatility : a GARCH approach
Gherghina, Ștefan Cristian; Armeanu, Daniel Ștefan; … - In: Journal of risk and financial management : JRFM 14 (2021) 8, pp. 1-29
GARCH approach. In the survey, the GARCH model (1,1) was applied to explore the volatility of the BET and BSE traded shares …
Persistent link: https://www.econbiz.de/10012626337
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Bitcoin network mechanics : forecasting the btc closing price using vector auto-regression models based on endogenous and exogenous feature variables
Ibrahim, Ahmed; Kashef, Rasha; Li, Menglu; Valencia, Esteban - In: Journal of risk and financial management : JRFM 13 (2020) 9/189, pp. 1-21
different factors influence it. In this paper, the BTC market mechanics are broken down using vector autoregression (VAR) and … Bayesian vector autoregression (BVAR) prediction models. The models proved to be very useful in simulating past BTC prices … some state-of-the-art forecasting models over two time periods. Experimental results show that the vector-autoregression …
Persistent link: https://www.econbiz.de/10012386874
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Managing financial risk in Chinese stock markets : option pricing and modeling under a multivariate threshold autoregression
Li, Johnny Siu-Hang; Ng, Andrew C.Y.; Chan, Wai-Sum - In: International review of economics & finance : IREF 40 (2015), pp. 217-230
Persistent link: https://www.econbiz.de/10011573584
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Likelihood inference for generalized integer autoregressive time series models
Joe, Harry - In: Econometrics : open access journal 7 (2019) 4/43, pp. 1-13
For modeling count time series data, one class of models is generalized integer autoregressive of order p based on thinning operators. It is shown how numerical maximum likelihood estimation is possible by inverting the probability generating function of the conditional distribution of an...
Persistent link: https://www.econbiz.de/10012160754
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On the power and size properties of cointegration tests in the light of high-frequency stylized facts
Krauss, Christopher; Herrmann, Klaus - In: Journal of risk and financial management : JRFM 10 (2017) 1, pp. 1-24
facts. AR(1)-GARCH(1,1) and MR(3)-STAR(1)-GARCH(1,1) processes contaminated with reversible and non-reversible jumps are …
Persistent link: https://www.econbiz.de/10011619116