Estimation and prediction of an Index of Financial Safety of Tunisia

Matkovskyy, Roman and Bouraoui, Taoufik and Hammami, Helmi (2015): Estimation and prediction of an Index of Financial Safety of Tunisia. Published in: Research in International Business and Finance , Vol. 38, (September 2016): pp. 485-493.

Abstract

This paper analyses the strength of the financial system of Tunisia through the construction of an Index of Financial Safety (IFS). Over the period 2000Q1 – 2014Q3, the IFS is built using a wide range of financial and macroeconomic indicators. The empirical results show that it can capture the disturbances in Tunisian financial system with sufficient accuracy. The nonlinear autoregressive with exogenous input (NARX) model with Levenberg-Marquardt algorithm of training was selected to forecast changes in IFS, and provides significant results.

• Item Type: MPRA Paper
• Language: English
• Keywords: index of financial safety of a country; IFS; nonlinear autoregressive with exogenous input (NARX) model; neural networks
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; G - Financial Economics > G1 - General Financial Markets > G10 - General; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

References

Angelopoulou, E., Balfoussia, H., and Gibson, H.D. (2014) Building a financial conditions index for the euro area and selected euro area countries: What does it tell us about the crisis?, Economic Modelling, 38, 392-403.

Babihuga, R. (2007) Macroeconomic and Financial Soundness Indicators: An empirical investigation, IMF Working Paper 07/115, 1-30.

Batini, N. and Turnbull, K. (2002) A dynamic monetary conditions index for the UK, Journal of Policy Modeling, 24, 257-281.

Block, S. A. (2001) Political business cycles, democratization, and economic reform: the case of Africa, Journal of Development Economics, 67, 205–228

Blomstrom, M., Globerman, S. and Kokko, A. (2000) The Determinants of Host Country Spillovers from Foreign Direct Investment. CEPR discussion paper 2350.

Bohn, H., Tesar, L. (1996) U.S. equity investment in foreign markets: portfolio rebalancing or return chasing? American Economic Review, 86, 77–81

Borensztein, E., J. De Gregorio, and Lee, J-W. (1998) How Does Foreign Direct Investment Affect Economic Growth? Journal of International Economics, 45, 115-135.

Brennan, M., Cao, H. (1997) International portfolio investment flows, Journal of Finance, 52, 1851–1880.

Busse, M. and Hefeker, C. (2007) Political risk, institutions and foreign direct investment, European Journal of Political Economy, 23, 397–415.

Caggiano, G., Calice, P. and Leonida, L. (2014) Early warning systems and systemic banking crises in low income countries: A multinomial logit approach, Journal of Banking & Finance, 47, 258-269.

Catullo, E., Gallegati, M. and Palestrini, A. (2015) Towards a credit network based early warning indicator for crises, Journal of Economic Dynamics and Control, 50, 78-97.

Cihak, M. and Schaeck, K. (2010) How well do aggregate prudential ratios identify banking system problems?, Journal of Financial Stability, 6, 130-144.

Cohen, W.M. and Levinthal, D.A. (1989) Innovation and learning: the two faces of R&D. Economic Journal, 99, 569-596.

Demekas, D. G., B. Horváth, E. Ribakova and Yi Wu (2007) Foreign direct investment in European transition economies—The role of policies. Journal of Comparative Economics, 35, 369–386

Drehmann, M. and Juselius, M. (2014) Evaluating early warning indicators of banking crises: Satisfying policy requirements, International Journal of Forecasting, 30, 759-780.

Guihuan, Z. and Yu, W. (2014) Financial conditions index’s construction and its application on financial monitoring and economic forecasting, Procedia Computer Science, 31, 32-39

Haykin, S. (1999) Neural Networks, A Comprehensive Foundation, 2nd Edition, Prentice Hall.

Hmili, R. and Bouraoui, T. (2015) Early warning indicators of banking crisis in Asian countries, Expert Journal of Finance, 3, pp.1-8.

Horn, J. (1965) A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179-185. Kasselaki, M.T. and Tagkalakis, A.O. (2013) Financial soundness indicators and financial crisis episodes, Annals of Finance, 10, 623-669.

Kelley, C.T. (1999). Iterative Methods for Optimization. SIAM Press, Philadelphia.

Klai, N. and Omri, A. (2011) Corporate Governance and Financial Reporting Quality: The Case of Tunisian Firms. International Business Research 4, 158- 166.

Lee, Suk Hun (1993) Relative Importance of Political Instability and Economic Variables on Perceived Country Creditworthiness, Journal of International Business Studies, 24, 801-812

Leontaritis, I. L., Billings, S.A. (1985) Input-output parametric model for nonlinear systems – Part II: stochastic nonlinear systems, Int.J.Control, 41, 329-344.

Li, W.X., Chen, C.C.S. and French, J.J. (2015) Toward an early warning system of financial crises: What can index futures and options tell us?, The Quarterly Review of Economics and Finance, 55, 87-99.

Matheson, T.D. (2012) Financial conditions indexes for the United States and euro area, Economics Letters, 115, 441-446.

Matkovskyy, R. (2012) The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model, Munich Personal RePEc Archive Paper N° 42173, 1-38

Matkovskyy, R. (2013) To the problem of financial safety estimation: the index of Financial Safety of Turkey, Munich Personal RePEc Archive Paper N° 47673, 1-18

Matkovskyy, R. (2014) The Index of the Financial Safety (IFS) of a Country: Estimation and Forecast in Challenges to Financial Stability – Perspective, Models and Policies, Volume I. A Framework for Modeling Systemic Risk Drivers of Different Markets, (Ed.) R. Karkowska, ASERS, pp. 47-77.

Menezes, J.M.P. & Barreto, G. A. (2006) A new look at nonlinear time series prediction with NARX recurrent neural network, Proceedings of Ninth Brazilian Symposium on Neural Networks, pp.160 – 165

Nielsen, H.B. (1999). Damping Parameter in Marquardt’s Method. Technical Report IMM-REP-1999-05, Technical University of Denmark, 1999. Available at http://www.imm.dtu.dk/˜hbn.

Nocedal, J. and Wright, S.J. (1999). Numerical Optimization. Springer, New York.

Osborne-Kinch, J. and Holton, S. (2010) A discussion of the monetary condition index, Quarterly Bulletin, 01, 68-80.

Siegelmann, Hava T., Horne G. & Lee G.C. (1997) Computational capabilities of recurrent NARX neural network” IEEE Transactions on Systems, Man and Cybernetics, Part B, 27, 208-215.

Tesar, L., Werner, I. (1994) International equity transactions and U.S. portfolio choice J. Frankel (Ed.), The Internationalization of Equity Markets, University of Chicago Press, pp. 185–220.

World Bank. (2014). The unfinished revolution : bringing opportunity, good jobs and greater wealth to all Tunisians. Washington, DC : World Bank Group.

Xu, B. (2000) Multinational enterprises, technology diffusion, and host country productivity, Journal of Development Economics, 62, 477-493.