Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.682165
Title: Application of dynamic factor modelling to financial contagion
Author: Sakaria, Dhirendra Kumar
ISNI:       0000 0004 5923 1591
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2016
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Abstract:
Contagion has been described as the spread of idiosyncratic shocks from one market to another in times of financial turmoil. In this work, contagion has been modelled using a global factor to capture the general market movements and idiosyncratic shocks are used to capture co-movements and volatility spill-over between markets. Many previous studies have used pre-specified turmoil and calm periods to understand when contagion occurs. We introduce time-varying parameters which model the volatility spillover from one country to another. This approach avoids the need to pre-specify particular types of periods using external information. Efficient Bayesian inference can be made using the Kalman filter in a forward filtering and backward sampling algorithm. The model is applied to market indices for Greece and Spain to understand the effect of contagion during the European sovereign debt crisis 2007-2013 (Euro crisis) and examine the volatility spillover between Greece and Spain. Similarly, the volatility spillover from Hong Kong to Singapore during the Asian financial crisis 1997-1998 has also been studied. After a review of the research work in the financial contagion area and of the definitions used, we have specified a model based on the work by Dungey et al. (2005) and include a world factor. Time varying parameters are introduced and Bayesian inference and MCMC simulations are used to estimate the parameters. This is followed by work using the Normal Mixture model based on the paper by Kim et al. (1998) where we realised that the volatility parameters results depended on the value of the ‘mixture offset’ parameter. We propose method to overcome the problem of setting the parameter value. In the final chapter, a stochastic volatility model with with heavy tails for the innovations in the volatility spillover is used and results from simulated cases and the market data for the Asian financial crisis and Euro crisis are summarised. Briefly, the Asian financial crisis periods are identified clearly and agree with results in other published work. For the Euro crisis, the periods of volatility spillover (or financial contagion) are identified too, but for smaller periods of time. We conclude with a summary and outline of further work.
Supervisor: Griffin, Jim Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.682165  DOI: Not available
Keywords: QA Mathematics (inc Computing science)
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