Statistical inference for the APGARCH and threshold APGARCH models
, 2012 published_or_final_version ; Statistics and Actuarial Science ; Master ; Master of ...
Chen, Qiming, 陈启明
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بررسی تأثیر تکانه¬های نرخ ارز غیررسمی ایران بر نا اطمینانی اسمی آن: رهیافت حافظه بلند بودن نرخ ارز غیر رسمی [PDF]
Quarterly Journal of Applied Theories of Economics, 2013 در این مطالعه، با استفاده از داده‌های ماهیانه نرخ ارز غیررسمی طی دوره زمانی 1359- 1388، به بررسی حافظه بلند بودن نرخ ارز غیررسمی ایران و تأثیر تکانه های نرخ ارز بر نا اطمینانی اسمی آن پرداخته شده است.
علیرضا عرفانی +1 more
doaj +1 more source
Fractal market hypothesis test of the banks' stock returns in Turkey [PDF]
, 2022 Bankalarda volatilite yapısının modellenmesiyle, bankaların yanında ekonominin genelini ilgilendiren risk ve belirsizliklerin karakteristik yapısı ortaya konulmaktadır.
Atukalp, M. Esra +3 more
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SDÜ Vizyoner Dergisi, 2019 Bu çalışmanın amacı Engel ve Ng (1993) nin işaret ve boyut yanlılığı testleri ile belirlenen asimetrik etkileri dikkate alarak döviz kurlarında yaşanan oynaklığın modellenmesidir.
Hakan Demirgil +2 more
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Discrete Dynamics in Nature and Society, Volume 2019, Issue 1, 2019., 2019 This article aims to investigate the Value at Risk of basis for stock index futures hedging in China. Since the RS‐GARCH model can effectively describe the state transition of variance in VaR and the two‐state Markov process can significantly reduce the dimension, this paper constructs the parameter and semiparametric RS‐GARCH models based on two‐state
Liang Wang +4 more
wiley +1 more source
Low‐Frequency Volatility in China’s Gold Futures Market and Its Macroeconomic Determinants
Mathematical Problems in Engineering, Volume 2015, Issue 1, 2015., 2015 We extract low‐ and high‐frequency volatility from China’s Shanghai gold futures market using an asymmetric Spline‐GARCH (ASP‐GARCH) model. We then regress monthly low‐frequency volatility on selected monthly macroeconomic indicators to study the impact of macroeconomy on gold futures market and to test for excess volatility.
Song Liu +4 more
wiley +1 more source
Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models [PDF]
, 2012 Recently, Donaldson and Kamstra (1997) proposed a class of NN-GARCH models which are extended to a class of NN-GARCH family by Bildirici and Ersin (2009).
Bildirici, Melike, Ersin, Özgür
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Forecasting oil prices: Smooth transition and neural network augmented GARCH family models [PDF]
, 2013 The study focuses on a new class of nonlinear volatility models based on neural networks and STAR type nonlinearity. Accordingly, LSTAR-LST-GARCH family and LSTAR-LST-GARCH-NN family of models will be evaluated to analyze petrol prices with economic ...
Bildirici, Melike Elif +3 more
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On Valuing Participating Life Insurance Contracts with Conditional Heteroscedasticity
, 2007 APGARCH model, Conditional Esscher transforms, Conditional heteroscedasticity, Default option, Leverage effect, Memoryness, Participating life insurance policies,
Lau, JW +7 more
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Modeling Stock Return Data using Asymmetric Volatility Models : A Performance Comparison based on the Akaike Information Criterion and Schwarz Criterion [PDF]
, 2019 The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model has been widely used in time series forecasting especially with asymmetric volatility data. As the generalization of autoregressive conditional heteroskedasticity model, GARCH is
E Setiawan +5 more
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