Annexe A : Programme Eviews
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Annexe B : Programme Matlab
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Annexe C : Programme R
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Bibliographie
+ Acemoglu, D., Ozdaglar, A., and Tahbaz-Salehi, A. (2014).
Systemic Risk and Stability in Financial Networks. Working Paper.
+ Acharya, V. V. and Steffen, S. (2012). Analyzing Systemic Risk
of the European Banking Sector. In: Handbook on Systemic Risk, J.-P. Fouque and
J. Langsam (Editors), Cambridge University Press.
+ Acharya, V. V. and Yorulmazer, T. (2007). Too Many to Fail - An
Analysis of Time-Inconsistency in Bank Closure Policies. Journal of Financial
Intermediation, 16, 1-31.
+ Acharya, V. V. and Yorulmazer, T. (2008). Cash-in-the-Market
Pricing and Optimal Resolution of Bank Failures. Review of Financial Studies,
21, 2705-2742.
+ Acharya, V. V., Engle, R., and Richardson, M. (2012). Capital
Shortfall: A New Approach to Ranking and Regulating Systemic Risks. The
American Economic Review, 102 (3), 59-64.
+ Acharya, V. V., Engle, R., Figlewski, S., Lynch, A., and
Subrahmanyam M. (2009). Centralized
Clearing for Credit Derivatives. Financial Markets, Institutions
and Instruments,18 (2), 168-170.
+ Acharya, V. V., Pedersen, L. H., Philippon, T., and Richardson,
M. P. (2010). Measuring Systemic Risk. Working Paper, NYU.
+ Adams, Z., Füss, R., and Gropp, R. (2010). Modeling
Spillover Effects Among Financial
Institutions: A State-Dependent Sensitivity Value-at-Risk
(SDSVaR). Approach Working Paper, European Business School.
+ Adrian, T. and Brunnermeier, M. K. (2011). CoVaR. Working
Paper, Princeton University and Federal Reserve Bank of New York.
+ Adrian, T. and Shin, H. S. (2014). Procyclical Leverage and
Value-at-Risk. Review of Financial Studies, 27, 373-403.
+ Agarwal, V., Jiang, W., Tang, Y., and Yang, B. (2013).
Uncovering Hedge Fund Skill from the Portfolio Holdings they Hide. The Journal
of Finance, 68, 739-783.
+ Ahmad, Z., and H. Ibrahim. (2002), A study of Performance of
The KLSE Syariah Index, Malaysian Management Journal 6 (1 & 2): 25-34.
+ Brasseul, J.(2004), Histoire des faits économiques,
Armand Colin,Markets Economic Letters, Vol. 22, pp. 375-380.
+ Calvet (L.) et Fisher (A.) (2007), Multi-frequency news and
stock returns, Journal of Financial Economics, vol. 86, p. 178-212.
+ Chakrabarty,K (2014), Cadre pour la conduite de la politique
macro-prudentielle en Inde : expériences et perspectives, Banque de
France
· Revue de la stabilité financière, N°
18.
+ Charles, A and Darné, O and Pop, A (2010) ,Are Islamic
Indexes More Volatile Than Conventional Indexes? Evidence from Dow Jones
Indexes, working paper, LEMNA.
Mohammed EL MASSAADI FSJES-Agdal MSDG/Finance 2021-2022
Page 113 sur 113
+ Chiadmi, MS,. Ghaiti, F. (2012), Modeling Volatility Stock
Market using the ARCH and GARCH Models: Comparative Study between an Islamic
and a Conventional Index (SP Shariah VS SP 500), International Research Journal
of Finance and Economics ISSN 1450- 2887 Issue 91.
+ Cihak, M. et H. Hesse. (2008), ,Islamic Banks and Financial
Stability : An Empirical Analysis,, IMF Working Paper.
+ Jacquier, E., N. G. Polson, P. E. Rossi (2004), «Bayesian
analysis of stochastic volatility models with fat-tails and correlated errors,
Journal of Econometrics, 122, (1), 185-212.
+ Kendall W., Liang F., Wang J., (2005). «Markov Chain Monte
Carlo, Innovations and Applications». World Scientific Publishing Co. Pte.
Ltd.
+ Paolella, M. S., (1997). «Using Flexible GARCH Models with
Asymmetric Distributions». Inst. für Statistik und Ökonometrie,
1997 - 70 pages.
+ Pesaran, B., & Pesaran, M. H. (2007). Modelling
Volatilities and Conditional Correlations in Futures Markets with a
Multivariate t Distribution (No. 2906). Institute of Labor Economics (IZA).
+ Pontines, V., & Siregar, R. Y. (2012). Exchange rate
asymmetry and flexible exchange rates under inflation targeting regimes:
Evidence from four East and Southeast Asian countries. Review of International
Economics, 20(5), 893-908.
+ Poon, S.H. (2005). «A Practical Guide to Forecasting
Financial Market Volatility», John Wiley & Sons Ltd.
+ Rachev T., Hsu S., Bagasheva S., Fabozzi J., (2008).
«Bayesian methods in finance». John Wiley & Sons, Inc.
+ Sandman, G., Koopman, S.J., (1998). «Estimation of
Stochastic Volatility Models via Monte Carlo Maximum Likelihood». Journal
of Econometrics, 87, 271-301.
+ Shephard N., (2005). «Stochastic Volatility: Selected
Readings (Advanced Texts in Econometrics)». Oxford University Press.
+ Tsay, R. S., (2010). «Analysis of Financial Time
Series». Wiley series in probability and statistics, by John Wiley &
Sons Ltd.
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