REFERENCES


Aas, K., Czado,C., Frigessi,A., and Bakken, H., 2009. Pair-copula Constructions of
Multiple Dependence. Insurance: Mathematics and Economics, 44(2),
182–198.

Acatrinei, M., 2011. Modeling dependencies between stock index returns with dynamic
copula-GARCH and copula-vine, vol. Nonlinear Views on the
Economic Crisis, Expert Publishing House, 168-181.

Agapie, A. and Bratianu, C., 2010. Repetitive Stochastic Guesstimation for Estimating
Parameters in a GARCH(1,1) Model. Romanian Journal of Economic
Forecasting, 13(2), pp.213-222.

Aielli, G., 2009. Dynamic conditional correlations: on properties and estimation.
Technical report, Department of Statistics, University of Florence.

Alexander, C.,2000. A primer on the orthogonal GARCH model. Available at
www.icmacentre.rdg.ac.uk/pdf/orthogonal.pdf

Bauwens, L., Laurent,S. and Rombouts, J., 2006. Multivariate GARCH models: A
survey. Journal of Applied Econometrics 21, 79–109.

Bauwens, L., 2012. Handbook of Volatility Models and Their Applications. Wiley
Handbooks in Financial Engineering and Econometrics.

Billio, M. and Caporin,M., 2009. A generalized dynamic conditional correlation model
for portfolio risk evaluation. Mathematics and Computers in Simulation
19(8), 2566–2578.

Bollerslev, T., 1990. Modeling the coherence in short-run nominal exchange rates: A
multivariate Generalized ARCH model. Review of Economics and
Statistics, 72, 498-505.

Broda,S. and Paollella,M.S.(2008) CHICAGO: A Fast and Accurate Method for
Portfolio Risk. Swiss Finance Institute Research Paper No.08-08

Cappiello, L., Engle, RF., Sheppard, K., 2006. Asymmetric Dynamics in the
Correlations of Global Equity and Bond Returns. Journal of Financial
Econometrics, Oxford University Press, vol. 4(4), 37-572.

Chan and Maheu., 2002. Conditional Jump Dynamics in Stock Market Returns,
Journal of Business and Economic Statistics, vol. 20, no. 3, 377-389.

Christodoulakis, G.A., and Satchell, S.E., 2002. Correlated arch (corrarch): Modeling
the time-varying conditional correlation between financial asset
returns. European Journal of Operational Research, 351-370.

Colacito, R., Engle, RF., and Ghysels, E., 2009. A component model for dynamic
correlations. NYU Working Paper No. FIN-08-039.

Diebold and Yilmaz, 2009. Measuring Financial Asset Return and Volatility Spillovers,
with Application to Global Equity Markets. Economic Journal, vol. 119,
no. 534, 158-171.

Dueker, M.J., 1997. Markov Switching in Garch Processes and Mean-Reverting
Stock-Market Volatility. Journal of Business & Economic Statistics, vol.
15, no. 1, 26–34.

Engle, R.F., Sheppard, K., 2001. Theoretical and Empirical Properties of Dynamic
Conditional Correlation Multivariate GARCH. Mimeo, UCSD.

Engle, R.F.,2002. Dynamic conditional correlation: A Simple Class of Multivariate
Garch Models. Journal of Business & Economic Statistics, 20:339-
350.

Engle, R.F., Kroner, K.F., 1995. Multivariate Simultaneous Generalized ARCH.
Econometric Theory, 11, 122-150

Haas, M., Mittnik, S., and Paolella, M.S., 2004. A new approach to Markov-switching
GARCH. Journal of Financial Econometrics 2, 493-530.

Hafner, C. and Franses, P., 2009. A generalized dynamic conditional correlation
model: simulation and application to many assets. Econometric
Reviews 28(6), 612–631.

Hafner, C. and Linton, O., 2010. Efficient estimation of a multivariate multiplicative
volatility model. Journal of Econometrics 159(1), 55–73.

Harvey, A., Ruiz, E. and Shepherd, N., 1994. Multivariate Stochastic Variance Models.
Review of Economic Studies, vol. 61, no. 2, pp. 247-264.

Jondeau, E., Rockinger, M., 2006. The Copula-GARCH Model of Conditional
Dependencies: An International Stock Market Application. Journal of
International Money and Finance.

Kearney, C., Patton, A.J., 2000. Multivariate GARCH modelling of exchange rate
volatility transmission in the European Monetary System. Financial
Review 41: 29–48.

Matei, M., 2012. Perspectives on risk measurement: a critical assessment of PCGARCH
against the main volatility forecasting models. Romanian
Journal of Economic Forecasting, 15(1), pp.95-115.

Miron, D. and Tudor, C.,2010. Asymmetric Conditional Volatility Models:Empirical
Estimation and Comparison of Forecasting Accuracy. Romanian
Journal of Economic Forecasting, 13(3), pp.79-92.

Pelletier, D., 2006. Regime switching for dynamic correlations. Journal of
Econometrics 131, 445–473.

Rangel, J. and Engle, RF., 2009. The factor-spline-GARCH model for high and low
frequency correlations. Banco de Mexico Working Paper No. 2009-03.

Silvennoinen, A. and Teräsvirta, T., 2005. Modeling Conditional Correlations of Asset
Returns: A Smooth Transition Approach. SSE/EFI Working Paper
Series in Economics and Finance No. 577.

Silvennoinen, A. and Teräsvirta, T., 2009. Multivariate GARCH models. Handbook of
Financial Time. Series Part 1, 201–229.

Tse, Y.K., and Tsui, A.K.C., 2002. A multivariate GARCH model with time-varying
correlations. Journal of Business and Economic Statistics 20: 351–
362.

van der Weide, R., 2002. A multivariate generalized orthogonal GARCH model.
Journal of Applied Econometrics 17: 549–564.