Yu, W., Yudong, W., Dengshi, H., Forecasting crude oil market volatility : Further evidence using GARCH-class models, Energy Economics, 32, 1477-1484, 2010.
Yoon, S. M., Kang, S. H., Asymmetric and long memory volatility process in the Chinese stock markets : A FIAPARCH skewed Student-t VaR approach, Journal of Money and Finance, 11(1), 105-130, 2012.
Yilmaz, K., Return and volatility spillovers among the East Asian equity markets, Journal of Asian Economics, 21, 304-313, 2010.
Yen-Hsien, L., Global and regional range-based volatility spillover effects, Emerging Markets Review, 14, 1-10, 2013.
Xiangyi, Z., Weijin, Z., Jie, Z., Volatility spillovers between the Chinese and world equity markets, Pacific-Basin Finance Journal, 20, 247-270, 2012.
Wu, P. T., Shieh, S. J., Value-at-risk analysis for long-term interest rate futures : Fat-tail and long memory in return innovations, Journal of Empirical Finance, 14, 248-259, 2007.
Wu, C. C., Chung, H., Chang, Y. H., The economic value of co-movement between oil price and exchange rate using coupla-based GARCH models, Energy Economics, 34, 270-282, 2012.
Weigel, D. D., Gemmill, G., What drives credit risk in emerging markets? The role of country fundamentals and market co-movement, Journal of International Money and Finance, 25, 476-502, 2006.
Weber, E., Zhang, Y., Common influences, spillover and integration in Chinese stock markets, Journal of Empirical Finance, 19, 382-394, 2012.
Wang, Y. D., Wu, C. F., Wei, Y., Can GARCH-class models capture long memory in WTI crude oil markets?, Economic Modelling, 28, 921-927, 2011.
Wang, Y. D., Wu, C. F., Forecasting energy market volatility using GARCH models : Can multivariate models beat univariate models?, Energy Economics, 34, 2167-2181, 2012.
Wang, K. M., Binh, T., Thi, N., Testing for contagion under asymmetric dynamics : Evidence from the stock markets between US and Taiwan, Physica A, 376, 422-432, 2007.
Wang, J., Yang, M., Asymmetric volatility in the foreign exchange markets, International Finance Markets, Institutions and Money, 19, 597-615, 2009.
Walid, C., Chaker, A., Masood, O., Fry, J., Stock market volatility and exchange rates in emerging countries : A Markov-state switching approach, Emerging Markets Review, 12, 272-292, 2011.
Verma, R., Ozuna, T., Are emerging equity markets responsive to cross-country macroeconomic movements? Evidence from Latin America, Journal of International Financial Markets, Institutions and Money, 15, 73-87, 2005.
Tse, Y. K., The conditional heteroscedasticity of the yen-dollar exchange rate, Journal of Applied Econometrics, 13, 49-55, 1998.
Tonn, T., Marc, O. R., Explaining asymmetric volatility around the world, Journal of Empirical Finance, 17, 938-956, 2010.
Timotheos, A., Alexandros, B., Stavros, D., The use of GARCH models in VaR estimation, Statistical Methodology, 1, 105-128, 2004.
Timotheos, A., Alexandros, B., Stavros, D., The use of GARCH model in VaR estimation, Statistical Methodology, 1, 105-128, 2004.
Thierry, A., An analysis of the flexibility of asymmetric power GARCH models, Computational Statistics and Data Analysis, 51, 1293-1311, 2006.
Tao, J. J., Green, C., Asymmetries, causality and correlation between FTSE100 spot and futures : A DCC-TGARCH-M analysis, International Review of Financial Analysis, 24, 26-37, 2012.
Tang, T. L., Shieh, S. J., Long memory in stock index futures markets : A value-at-risk approach, Physica A, 366, 437-448, 2006.
Tamakoshi, G., Hamori, S., Co-movements among major European exchange rates : A multivariate time-varying asymmetric approach, International Review of Economics and Finance, 31, 105-113, 2014.
Talpsepp, T., Rieger, M. O., Explaining asymmetric volatility around the world, Journal of Empirical Finance, 17, 938-956, 2010.
Takamitsu, K., Dynamic characteristics of the daily yen-dollar exchange rate, Research in International Business and Finance, 30, 72-82, 2014.
Syriopoulos, T., Roumpis, E., Dynamic correlations and volatility effects in the Balkan equity markets, Internationaal Finance Markets, Institutions and Money, 19, 565-587, 2009.
Syllignakis, M. N., Kouretas, G. P., Dynamic correlation analysis of financial contagion : Evidence from the central and eastern European markets, International Review of Economics and Finance, 20, 717-732, 2011.
Susmel, R., Eagle, R. F., Hourly volatility spillovers between international equity markets, Journal of International Money and Finance, 13, 3-25, 1994.
Su, J. B., Lee, M. C., Chiu, C. L., Why does skewness and the fat-tail effect infulence value-at-risk estimates? Evidence from alternative capital markets, International Review of Economics and Finance, 31, 59-85, 2014.
Steven, J. C., Iqbal, M., Babatunde, O., Volatility persistence in metal returns : A FIGARCH approach, Journal of Economics and Business, 64, 287-305, 2012.
Solnik, B. C., Bouecrelle, K., Le Fur, Y., International market correlation and volatility, Financial Analysts Journal, 52, 17-34, 1996.
So, M. K. P., Yu, P. L. H., Empirical analysis of GARCH models in value at risk estimation, International Finance Markets, Institutions and Money, 16, 180-197, 2006.
Shim, J. Y., Hwang, C. H., Forecasting volatility via conditional autoregressive value at risk model based on support vector quantile regression, Journal of the Korean Data Information Science Society, 22(3), 589-596, 2011.
Shao, X. D., Lian, Y. J., Yin, L. Q., Forecasting value-at-risk using high frequency data : The realized range model, Global Finance Journal, 20, 128-136, 2009.
Samitas, A., Tsakalos, I., How can a small country affect the European economy? The Greek contagion phenomenon, International Finance Markets, Institutions and Money, 25, 18-32, 2013.
Salisu, A. A., Mobolaji, H., Modeling returns and volatility transmission between oil price and US-Nigeria exchange rate, Energy Economics, 39, 169-176, 2013.
Saleem, K., International linkage of the Russian market and the Russian financial crisis : A multivariate GARCH analysis, Research in International Business and Finance, 23, 243-256, 2009.
Sadorsky, P., Modelling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat, Energy Economics, 43, 72-81, 2014.
Robert, D., Hakan, S., Joseph, M., Hsi, L., Long memory in the volatility of an emerging equity market : The case of Turkey, International Finance Markets, Institutions and Money, 18, 305-312, 2008.
Raganathan, V., Faff, R. W., Brooks, R. D., Correlations, business cycle and integration, Journal of International Financial Markets, Institutions and Money, 9, 75-95, 1999.
Phylaktis, K., Ravazzolo, F., Stock price and exchange rate dynamics, Journal of International Money and Finance, 2004, 1031-1053, 2005.
Pesaran, B., Pesaran, M. H., Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash, Economic modelling, 1398-1416, 2010.
Paolella, M. S., Using flexible GARCH models with asymmetric distributions, Working paper, Institute of Statistics and Econometrics Christian Albrechts University at Kiel, 1997.
Ornberg, J. K., Nikkinen, J., Aijo, J., Stock market correlations during the financial crisis of 2008-2009 : Evidence from 50 equity markets, International Review of Financial Analysis, 28, 70-78, 2013.
Orhan, M., Koksal, B., A comparison of GARCH models for VaR estimation, Expert Systems with Applications 39, 3582-3592, 2012.
Oh, G. J., Kim, S. H., Value-at-risk estimation of the KOSPI returns by employing long memory volatility models, The Korean Journal of Applied Statistics, 26(1), 163-185, 2013.
Oh, G. J., Kim, S. H., Eom, C. J., Long-term memory and volatility clustering in high-frequency price changes, Physica A, 387, 1247-1254, 2008.
Nikolay, Y. N., Geirgi, N. B., Robert, Z., Heavy-tailed mixture GARCH volatility modeling and value-at-risk estimation, Expert Systems with Applications, 40, 2233-2243, 2013.
Narayan, S., Sriananthakumar, S., Islam, S. Z., Stock market integration of emerging Asian economies : Patterns and causes, Economic Modelling, 39, 19-31, 2014.
Najand, M., Yung, K., A GARCH examination of the relationship between volume and price variability in futures markets, Journal of Futures Markets, 11, 613-621, 1991.
Morelli, D., The relationship between conditional stock market volatility and conditional macroeconomic volatility : Empirical evidence based on UK data, International Review of Financial Analysis, 11(1), 101-110, 2002.
Mollick, A. V., Assefa, T. A., U.S. stock returns and oil prices : The tale from daily data and the 2008-2009 financial crisis, Energy Economics, 36, 1-18, 2013.
Miyakoshi, T., Spillover of stock return volatility to Asian equity markets from Japan and the U.S. Journal of International Financial Markets, Institutions and Money, 13, 383-399, 2003.
Mittnik, S., Paolella, S. M., Comditional density and value-at-risk prediction of Asian currency exchange rates, Journal of Forecasting, 19, 313-333, 2000.
Michel, B., Volatility expectations and asymmetrics effects of direct interventions in the FX market, J. Japanese International Economics, 17, 55-80, 2003.
McKinnon, T., Ronald, I., Gunther, S., Synchronized business cycles in East Asia : Fluctuations in the Yen/Dollar exchange rate and China’s stabilizing role, The World Economy, 26(8), 1067-1088, 2008.
Marshall, A., Maulana, T., Tang, L., The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model, International Review of Financial Analysis, 18, 250-259, 2009.
Markus, H., Jochen, K., Marc, S. P., Time-varying mixture GARCH models and asymmetric volatility, North American Journal of Economics and Finance, 26, 602-623, 2013.
Majdoub, J., Mansour, W., Islamic equity market integration and volatility spillover between emerging and US stock markets, North American Journal of economics and Finance, 29, 452-470, 2014.
Mabrouk, S., Saadi, S., Parametric value-at-risk analysis : Evidence from stock indices, The Quarterly Review of Economics and Finance 52, 305-321, 2012.
Lyocsa, S., Vyrist, T., Baumohl, E., Stock market networks : The dynamic conditional correlation approach, Physica A, 391, 4147-4158, 2012.
Lopez, J. A., Methods for evaluating value-at-risk estimates, Federal Reserve Bank of New York Research Paper, 9802, 1998.
Longin, F., Solnik, B., Is correlation in international equity returns, constant : 1960-1990?, Journal of International Money and finance, 14, 3-26, 1995.
Liu, H. C., Hung, J. C., Forecasting S&P 100 stock index volatility : The role of volatility asymmetry and distributional assumption in GARCH models, Expert Systems with Applications, 37, 4928-4934, 2010.
Liu, H. C., Chiang, S. M., Cheng, Y. P., Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures, International Review of Economics and Finance, 22, 78-91, 2012.
Lin, X., Fei, F., Long memory revisit in Chinese stock markets : Based on GARCH-class models and multiscale analysis, Economic Modelling, 31, 265-275, 2013.
Lin, K. P., Menkveld, A. J., Yang, Z., Chinese and world equity markets : A review of the volatilities and correlations in the first fifteen years, China Economic Review, 20, 29-45, 2009.
Lin, B., Jr Wesseh, P. K., Appiah, M. O., Oil price fluctuation, volatility spillover and the Ghanaian equity market : Implication for portfolio management and hedging effectiveness, Energy Economics, 42, 172-182, 2014.
Lim, C. M., Sek, S. K., Comparing the performances of GARCH-type models in capturing the stock market volatility in Malaysia, Procedia Economics and Finance, 5, 478-487, 2013.
Lee, Y. H., Pai, T. Y., REIT volatility prediction for skew-GED distribution of the GARCH model, Expert Systems with Applications, 37, 4737-4741, 2010.
Lee, S. Y., Noh, J. S., Value at risk forecaasting based on quantile regression for GARCH models, The Korean Journal of Applied Statistics, 23(4), 669-681, 2010.
Lee, J., The comovement between output and prices : Evidence from a dynamic conditional correlation GARCH model, Economics Letters, 91, 110-116, 2006.
Lean, H. H., Teng, K. T., Integration of world leaders and emerging powers into the Malaysian stock market : A DCC-MGARCH approach, Economic Modelling, 32, 333-342, 2013.
Lambert, P., Laurent, S., Modeling financial time series using GARCH-type models and a skewed Student density, Mimeo, Universite de Liege, 2001.
Lahrech, A., Sylwester, K., U.S. and Latin American stock market linkages, Journal of International Money and Finance, 30, 1341-1357, 2011.
Lahrech, A., Sylwester, K., The impact of NAFTA on North American stock market linkages, North American Journal of Economics and Finance, 25, 94-108, 2013.
Kupiec, P., Techniques for verifying the accuracy of risk measurement models, Journal of Derivative, 2, 73-84, 1995.
Kumar, D., Maheswaran, S., Modeling asymmetry and persistence under the impact of sudden changes in the volatility of the Indian stock market, IIMB Management Review, 24, 123-136, 2012.
Kroner, K. F., Sultan, J., Time-varying distributions and dynamic hedging with foreign currency futures, Journal of Financial and Quantitative Analysis, 12, 535-551, 1993.
Kroner, K. F., Ng, V. K., Modeling asymmetric comovements of asset returns, Review of Financial Studies, 11, 817–844, 1998.
Koutmes, G., Booth, G. G., Asymmetric volatility transmission in international stock markets, Journal of International Money and Finance, 14, 747-762, 1995.
Koutmes, G., Asymmetric volatility and risk return tradeoff in foreign stock markets, Journal of Multinational Financial Management, 2, 27-43, 1992.
Korkmaz, T., Cevik, E, I., Atukeren, E., Return and volatility spillovers among CIVETS stock markets, Emerging Markets Review, 13, 230-252, 2012.
Kizys, R., Pierdziocj, C., Changes in the international comovement of stock returns and asymmetric macroeconomic shocks, Journal of International Financial Markets, Institutions and Money, 19, 289-305, 2009.
Kizys, R., Pierdziocj, C., Business-cycle fluctuation and international equity correlations, Global Finance Journal, 17, 252-270, 2006.
Kim, B. H., Kim, S. W., Transmission of the global financial crisis to Korea, Journal of Policy Modelling, 35, 339-353, 2013.
Kenourgios, D., Samitas, A., Paltalidis, D., Financial crises and stock market contagion in a multivariate time-varying asymmetric framework, International Finance Markets, Institutions and Money, 21, 92-106, 2011.
Kenourgios, D., Asteriou, D., Samitas, A., Testing for asymmetric financial contagion : New evidence from the Asian crisis, The Journal of Economic Asymmetries, 10, 129-137, 2013.
Kang, S. H., Yoon, S. M., Value-at-risk analysis for Asian emerging markets : Asymmetry and fat-tails in returns innovation, The Korean Economic Review, 25, 387-408, 2009.
Kang, S. H., Yoon, S. M., Asymmetry and long memory features in volatility : Evidence from Korean stock market, The Korean Economic Review, 24, 383-408, 2008.
Kang, S. H., Volatility spillover between the KOSPI 200 spot and futures markets using the VECM-DCC-GARCH model, Korean Journal of Futures and Options, 19(3), 233-249, 2011.
Kang, S. H., Long memory value-at-risk for long and short trading positions in the Korean bond index, Journal of Money and Finance, 10(4), 203-222, 2011.
Kang, S. H., Kim, H. B., Yoon, S. M., Volitility spillover effect between Chinese and Korean stock markets, Journal of Money and Finance, 10(1), 161-177, 2011.
Jullavut, K., Yiuman, T., Modeling the fat tails in Asian stock markets, International Review of Economics and Finance, 20, 430-440, 2011.
Jones, P. M., Olson, E., The time-varying correlation between uncertainty, output, and inflation : Evidence from a DCC-GARCH model, Economics Letter, 118, 33-37, 2013.
Jammazi, R., Oil shock transmission to stock market returns : Wavelet-multivariate Markov swiching GARCH approach, Energy, 37, 430-454, 2012.
Hwang, S. Y., Park, J., VaR(Value at risk) for Korean financial time series, Journal of Korean Data and Information Science Society, 16(2), 283-288, 2005.
Hung, J. C., Lee, M. C., Liu, H. C., Estimation of value-at-risk for energy commodities via fat-tailed GARCH models, Energy Economics, 30, 1173-1191, 2008.
Hull, J., White, D., Value at risk when daily changes in market variables are not nomally distributed, Journal of Derivatives, 5(1), 9-19, 1998.
Hull, J., White, D., Incorporating volatility updating into the historical simulation method for VaR, The Journal of Risk, 1, 5-19, 1998.
Huang, Y. C., Lin, B. J., Value-at-risk analysis for Taiwan stock index futures : Fat tail and conditional asymmetries in return innovations, Review of Quantitative Finance and Accounting, 22, 79-95, 2004.
Hou, Y., Li, S., Hedging performance of Chinese stock index futures : An empirical analysis using wavelet analysis and flexible bivariate GARCH approahes, Pacific-Basin Finance Journal, 24, 109-131, 2013.
Hess, M. K., Dynamic and asymmetric impacts of macroeconomic fundamentals on an integrated stock market, Journal of International Financial Markets, Institutions and Money, 14, 455-471, 2004.
Hendricks, D., Evaluation of value-at-risk models using historical data, Federal Reserve Bank of New Economic Policy Review, April, 1996.
Hansen, B. E., Autoregressive conditional density estimaton, International Economic Review, 35, 705-730, 1994.
Han, Y. W., Long memory volatility dependency, temporal aggregation and the Korean currency crisis : The role of a high frequency Korean won(KRW)-US dollar($) exchange rate, Japan and the world Economy, 17, 97-109, 2005.
Gupta, R., Donleavy, G. D., Benefits of diversifying investments into emerging markets with time-varying correlations : An Australian perspective, Journal of Multinational Financial Management, 19, 160-177, 2009.
Guesmi, K., Nguyen, D. K., How strong is the global integration of emerging market regions? An empirical assessment, Economic Modelling, 28, 2517-2527, 2011.
Guesmi, K., Fattoum, S., Return and volatility transmission between oil prices and oil-exporting and oil-importing countries, Economics Modelling, 38, 305-310, 2014.
Grubel, H., International diversified portfolio : Welfare gains and capital flows, American Economic Review, 58, 1299-1314, 1968.
Granger, C. W. J., Huang, B. N., Yang, C. W., A bivariate causality between stock prices and exchange rates : Evidence from recent Asian flu, The Quarterly Review of Economics and Finance, 40, 337-354, 2000.
Glosten L., Jagannathan, R., Runkel, D., On the relation between the expected value and the volatility of the nominal excess return on stocks, Journal of Finance, 48, 1779-1801, 1993.
Gjika, D., Horvath, R., Stock market comovements in central Europe : Evidence from the asymmetric DCC model, Economic Modelling, 33, 55-64, 2013.
Giot, P., Laurent, S., Value-at-risk for long and short trading positions, Journal of applied econometrics, 18, 641-664, 2003.
Giot, P., Laurent, S., Modelling daily value-at-risk using realized volatility and ARCH type models, Journal of Empirical Finance, 11, 379-398, 2004.
Giot, P., Laurent, S., Market risk in commodity markets : A VaR approach, Energy Economics, 25, 435-457, 2003.
Gian, P. A., Massimiliano, C., Fast clustering of GARCH processes via Gaussian mixture models, Mathematics and Computers in Simulation, 94, 205-222, 2013.
Ghose, D., Kroner, K. F., The relationship between GARCH and symmetric stable processes : Finding the source of fat tails in financial data, Journal of Empirical Finance, 2, 225-251, 1995.
Gardebroek, C., Hernandez, M. A., Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets, Energy Economics, 40, 119-129, 2013.
Fratzher, M., Financial market integration in Europe : On the effects of EMU on stock markets, International Journal of Finance and Economics, 7, 165-193, 2002.
Filis, G., Degiannakis, S., Floros, C., Dynamic correlation between stock market and oil prices : The case of oil-importing and oil-exporting countries, International Review of Financial Analysis, 20, 152-164, 2011.
Fernandez, C., Steel, M., On bayesian modelling of fat tails and skewness, Journal of the American Statistical Association, 93, 359-371, 1998.
Fan, Y., Zhang, Y. J., Tsai, H. T., Wei, Y. M., Estimating ‘Value at risk’ of crude oil price and its spillover effect using the GED-GARCH approach, Energy Economics, 30, 3156-3171, 2008.
Erhan, D., Value-at-risk(VaR) analysis and long memory : Evidence from FIAPARCH in Istanbul stock exchange(ISE), Ataturk University Journal of Economics and Administrative Science, 24, 217-228, 2010.
Engle, R. F., Manganelli, S., CAViaR conditional autoregressive value at risk by regression quantiles, Journal of Business and Economic Statistics, 22, 367-381, 2004.
Engle, R. F., Bollerslev, T., Modeling the persistence of conditional variance, Econometric Review, 5, 1-50, 81-87, 1986.
Engle, R. F., Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50, 987-1007, 1982.
Efimova, O., Serletis, A., Energy markets volatility modelling using GARCH, Energy Economics, 43, 264-273, 2014.
Ebrahim, S. K., Volatility transmission between foreign exchange and monetary market, Bank of Canada Working Paper, Aug, 18-20, 2000.
Dumas, B., Harvey, C. R., Ruiz, P., Are correlations of stock returns justified by subsequent changes in national outputs?, Journal of International Money and Finance, 22, 777-811, 2003.
Duan, J. C., Jacobs, K., A simple long memory equilibrium interest rate model, Economics Letters, 53, 317-321, 1996.
Doong, S. C., Tang, S. Y., Chiang, T. C., Responses asymmetries in Asian stock markets, Review of Pacific Basin Financial Markets and Policies, 8(4), 637-657, 2005.
Ding, Z., Granger, C. W. J., Modeling volatility persistence of speculative returns : A new approach, Journal of Econometrics, 73, 185-215, 1996.
Ding, Z., Granger, C. W. J., Engle, R. F., A long memory property of stock market returns and a new model, Journal of Empirical Finance, 1, 83-106, 1993.
Dimitrios, D., Kenourgios, D., Simos, T., Global financial crisis and emerging stock market contagion : A multivariate FIAPARCH-DCC approach, International Review of Financial Analysis, 30, 46-56, 2013.
Dimitrios, D., Kenourgios, D., Financial crises and dynamic linkages among international currencies, International Finance Markets, Institutions and Money, 26, 319-332, 2013.
Diamandis, P. F., Drakos, A. A., Kouretas, G. P., Zarangas, L., Value-at-risk for long and short trading positions : Evidence from developed and emerging equity markets, International Review of Financial Analysis, 20, 165-176, 2011.
Degiannakis, S., Volatility forecasting : Evidence from a fractional integrated asymmetric power ARCH skewed-t model, Applied Financial Economics, 14, 1333-1342, 2004.
Degiannakis, S., Floros, C., Dent, P., Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility : International evidence, International Review of Financial Analysis, 27, 21-33, 2013.
David, G. M., Dimos, K., Are RiskMetrics forecasts good enough? Evidence from 31 stock markets, International Review of Financial Analysis, 18, 117-124, 2009.
David, A., Lennart, F. H., GARCH models for daily stock returns : Impact of estimation frequency on value-at-risk and expected shortfall forecasts, Economics Letter, 123, 187-190, 2014.
Danielsson, J., Morimoto, Y., Forecasting extreme financial risk : A critical analysis of practical methods for the Japanese market, Monetary and Economic Studies, 18, 25-48, 2000.
Cumhur, E., Arslan, C. K., Meziyet, S. E., Effects of macroeconomic variables on Istanbul stock exchange, Applied Financial Economics, 15, 987-994, 2005.
Corsi, F. A., Simple approximate long-memory model of realized volatility, Journal of Financial Econometrica, 50, 174-196, 2009.
Conrad, C., Loch, K., Rittler, D., On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets, Journal of Empirical Finance, 725, 1-34, 2014.
Conrad, C., Karanasos, M., Zeng, N., Multivariate fractionally integrated APARCH modeling of stock market volatility : A multi-country study, Journal of Empirical Finance, 18, 147-159, 2011.
Connor, G., Suurlaht, A., Dynamic stock market covariances in the Eurozone, Journal of International Money and Finance, 37, 353-370, 2013.
Connolly, R. A., Wang, F. A., International equity market comovements : Economic fundamentals or contagion?, Pacific-Basin Finance Journal, 11, 23-43, 2003.
Christoph, H., Stefan, M., Marc, P., Accurate value-at-risk forecasting based on the normal-GARCH model, Computational Statistics and Data Analysis, 51, 2295-2312, 2006.
Choi, W. S., Price discovery and asymmetric volatility spillover under time-varying correlation framework, Korean Industrial Economics Association, 20(2) 649-673, 2007.
Chkili, W., Hammoudeh, S., Nguyen, D. K., Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory, Energy Economics, 41, 1-18, 2014.
Chin W. C., Heavy-tailed value-at-risk analysis for Malaysian stock exchange, Physica A, 387, 4285-4298, 2008.
Cherif, G., Richard, D. F., Forecasting value at risk allowing for time variation in the variance and kurtosis of portfolis returns, International Journal of Forecasting, 18, 409-419, 2002.
Chang, C. L., McAleer, M., Tansuchat, R., Conditional correlations and volatility spillovers between crude oil and stock index returns, North American Journal of Economics and Finance, 25, 116-138, 2013.
Chang, C. L., McAleer, M., Tansuchat, R., Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets, Energy Economics, 32, 1445-1455, 2010.
Chan, N. H., Deng, S. J., Peng, L., Xia, Z., Interval estimation of value-at-risk based on GARCH models with heavy-tailed innovations, Journal of Econometrics, 137, 556-576, 2007.
Celik, S., The more contagion effect on emerging markets : The evidence of DCC-GARCH model, Economic Modelling, 29, 1946-1959, 2012.
Caporin, M., Angel, J., Martin, J., Gonzalez-Serrano, L., Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises, International Finance Markets, Institutions and Money, 31, 159-177, 2014.
Cajueiro, D. O., Tabak, B. M., Testing for time-varying long-range dependence in volatility for emerging markets, Physica A, 346, 577-588, 2005.
Buttner, D., Hayo, B., Determinants of European stock market integration, Economic Systems, 35, 574-585, 2011.
Brooks, C., Persand, G., Volatility forecasting for risk management, Journal of Forecasting, 22, 1-22, 2003.
Bracker, K., Docking, D. S., Koch, P. D., Economic determinants of evolution in international stock market integration, Journal of Empirical Finance, 6, 1-27, 1999.
Booth, G. G., Martikainen, T., Tse, Y., Price and volatility spillovers in Scandinavian stock markets, Journal of Banking and Finance, 21, 811-823, 1997.
Bollerslev, T., Wooldridge, J. M., Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariance, Econometric Reviews, 11, 143-172, 1992.
Bollerslev, T., Mikkelsen, H. O., Modeling and pricing long memory in stock market volatility, Journal of Econometrics, 73, 151-184, 1996.
Bentes, S. R., Measuring persistence in stock market volatility using the FIGARCH approach, Physica A, 408, 190-197, 2014.
Ben-zion, U., Choi, J. J., Hauser, S., The price linkages betwen country funds and national stock markets : Evidence from cointegration and causality tests of Germany, Japan and UK funds, Journal of Business Finance and Accounting, 23, 1005-1017, 1996.
Basel, M. A. A., Valentina, C., Predicting the volatility of the S&P 500 stock index via GARCH models : the role of asymmetrics, International Journal of Forecasting, 21, 167-183, 2005.
Baillie, R. T., Bollerslev, T., Mikkelson, H., Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 74, 3-30, 1996.
Atilla, C., Forecasting electricity price volatility with the Markov-switching GARCH model : Evidence from the Nordic electric power market, Electric Power Systems research, 101, 61-67, 2013.
Asai, M., Brugal, I., Forecasting volatility via stock return, range, trading volume and spillover effect : The case of Brazil, North American Journal of Economics and Finance, 25, 202-213, 2013.
Artzner, P. F., Delbain, F., Eber, J. M., Health, D., Coherent measures of risk, Mathematical Finance, 9, 203-228, 1999.
Arshanapalli, B., Doukas, J., International stock market linkages : Evidence from the pre and post October 1987 period, Journal of Banking and Finance, 17, 193-208, 1993.
Arouri, M. E., Jouini, J., Nguyen, D. K., Volatility spillovers between oil prices and stock sector returns : Implications for portfolio management, Journal of International Money and Finance, 30, 1387-1405, 2011.
Andersen, T. G., Bollerslev, T., Diebold, F. X., Ebens, H., The distribution of realized stock return volatility, Journal of Financial Economics, 61, 43-76, 2001.
Andersen, T. G., Bollerslev, T., Answering the skeptics : Yes, Standard volatility models do provide accurate forecasts, International Economic Review, 39, 885-905, 1998.
Amelie, C., The day-of-the week effects on the volatility : The role of the asymmetry, European Journal of Operational Research, 202, 143-152, 2010.
Aloui, R., Aissa, M. S. B., Nguyen, D. K., Conditional dependence structure between oil prices and exchange rates : A couple-GARCH approach, Journal of International Money and Finance, 32, 719-738, 2013.
Aloui, C., Mabrouk, S., Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models, Energy Policy, 38, 2326-2339, 2010.
Aloui, C., Hamida, H. B., Modelling and forecasting value at risk and expected shortfall for GCC stock markets : Do long memory, structual breaks, asymmetry, and fat-tails matter? North American Journal of Economics and Finance, 29, 349-380, 2014.
Allen, D. E., Amram, R., McAleer, M., Volatility spillovers from the Chinese stock market to economic neighbours, Mathematics and Computers in Simulation, 94, 238-257, 2013.
Alagidede, P., Panagiotidis, T., Modelling stock returns in Africa’s emerging equity markets, International Review of Financial Analysis, 18, 1-11, 2009.
Ahmad, W., Sehgal, S., Bhanumurthy, N. R., Eurozone crisis and BRIICKS stock markets : Contagion or market interdependence?, Economic Modelling, 33, 209-225, 2013.
Acerbi, C., Tasche, D., On the coherence of expected shortfall, Journal of Banking and Finance, 26, 1487-1503, 2002.
Abad, P., Benito, S., A detailed comparison of value at risk estimates, Mathematics and Computers in Simulation, 94, 258-276, 2013.
AR(1)-APARCH 모형을 이용한 VaR 사후검정 분석 : 비대칭적이고 꼬리가 두터운 분포도를 중심으로