Marwan Izzeldin

Financial Markets Synchronization and Contagion: Evidence from CEE and Eurozone

We examine the synchronization of European Union (EU) financial markets before and during the recent financial crisis. A DCC-GARCH framework captures dynamic correlations and a Markov-Switching framework captures regime changes. For the 27 nations of the EU, we formulate characteristics of the crisis: transition dates, duration and intensity. As compared to established members of the EU, recent entrants to the EU entered the crisis at later dates and were less adversely affected. Consistent with the literature on financial contagion, we identify a significant strengthening of correlations between stock markets, particularly for recent entrants. Higher levels of sovereign debt and lower industrialization are associated with the intensity of the crisis experienced. In finding evidence of a core-against-periphery EU, our results refute the notion of uniform integration of EU financial markets.

Do Islamic Banks 'Live Free and Die Harder'?

Are Islamic banks inherently more stable than conventional banks? We address this question by applying a survival analysis based on the Cox proportional hazard model to a comprehensive sample of 421 banks in 20 Middle and Far Eastern countries from 1995 to 2010. By comparing the failure risk for both bank types, we find that Islamic banks have a significantly lower risk of failure than that of their conventional peers. This lower risk is based both unconditionally and conditionally on bank-specific (microeconomic) variables as well as macroeconomic and market structure variables. Our findings indicate that the design and implementation of early warning systems for bank failure should recognize the distinct risk profiles of the two bank types.

Recovering the moments of information flow and the normality of asset returns

We investigate the univariate procedure used by Ané and Geman (AG, 2000) to recover the moments of the information flow from high-frequency data, in a mixture of distributions model which generalizes the subordinated process in Clark (1973). We explain why the third and higher moments of the latent information flow cannot be accurately recovered using this procedure. We illustrate this using Monte Carlo simulations. We also show that, contrary to the claims in AG, returns conditioned on the re-centred number of trades are not approximately Gaussian. Finally, we consider the bivariate approach of Richardson and Smith (1994), inter alia, to recover the moments of information flow.

Bayesian CV@R/super-quantile regression

ABSTRACT In this paper we provide a Bayesian interpretation of the conditional value at risk, CV@R, or super-quantile regression recently developed by Rockafellar et al. [Super-quantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk, Eur. J. Oper. Res. 234 (2014), pp. 140–154]. Computations are based on particle filtering using a special posterior distribution consistent with the super-quantile concept. An empirical application to data used by RRM as well to another data set on energy prices confirms their results and shows the applicability of the new techniques.

A novel model of costly technical efficiency

This paper presents a novel model of measuring technical inefficiency based on the notion that higher efficiency requires a certain cost. First, we apply the “rational inefficiency hypothesis” of Bogetoft and Hougaard (2003) but we fail to find that it rationalizes our data set of large U.S banks with multiple inputs and outputs. In consequence, we adopt a novel model of profit maximization which explicitly incorporates the cost of technical inefficiency. The cost of inefficiency is treated as unknown and is parametrized as a function of inputs, outputs and decision-making-unit specific fixed effects. More importantly, by showing the model to be equivalent to one in which inefficiency is an arbitrary function of inputs, outputs and the inefficiency cost, we are able to determine optimal directions in the input-output space that would reduce inefficiency. Bayesian techniques organized around Markov Chain Monte Carlo are used to perform the computations and provide statistical inferences as well as useful policy measures to reduce inefficiencies in the U.S banking sector through an examination of different realistic scenarios.

Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares

Abstract Estimation of banking efficiency and productivity is essential for regulatory purposes and for testing various theories in the context of banking such as the quiet life hypothesis, the bad management hypothesis etc. In such studies it is, therefore, important to place as few restrictions as possible on the functional forms subject to global satisfaction of the theoretical properties relating to monotonicity and concavity. In this paper, we propose an alternative to nonparametric segmented concave least squares. We use a differentiable approximation to an arbitrary functional form based on smoothly mixing Cobb-Douglas anchor functions over the data space. Estimation is based on Bayesian techniques organized around Markov Chain Monte Carlo. The approximation properties of the new functional form are investigated in a Monte Carlo experiment where the true functional form is a Symmetric Generalized McFadden. The new techniques are applied to a large U.S banking data set as well as a global banking data set.

Another Great Convergence? Are Islamic and Conventional Banks Converging in Efficiency across All Countries?

This paper examines how efficiency dynamics of Islamic and conventional banks compare and how they are converging across different countries. We employ both parametric and non-parametric methods to analyse a panel of Islamic and conventional banks from 23 countries during the period 1999 to 2014. Parametric methods (stochastic frontiers methods) shows that both steady state efficiency and the speed of convergence of Islamic and conventional banks are similar. A non-parametric framework (classification trees) identifies a varying degree of alignment between the Islamic and conventional banking model across countries, which could explain the plurality in conclusions in the Islamic/conventional bank efficiency debate. We find that the alignment between the two bank types is positively related to the country’s financial depth, transparency, economic stability and banking concentration. At the bank level, the alignment in the two banking systems is associated with higher income diversification, liquidity, profitability and financial stability.

Efficiency in Islamic and Conventional Banks: Evidence from the Gulf Cooperation Council Countries

We examine efficiency in Islamic and conventional banking systems in the Gulf Cooperation Council (GCC) region (2004-2007) using financial ratio analysis (FRA) and data envelopment analysis (DEA). We find the two approaches are complementary in terms of the information they provide. From the FRA, the Islamic banking system is less cost efficient but more revenue and profit efficient than the conventional one. Bootstrapped tests confirm that these differences are significant. From the DEA, average efficiency is significantly lower in Islamic than conventional banks. A decomposition of the DEA efficiencies demonstrates that the efficiency difference is more a consequence operating under Islamic rules (i.e. the banking system itself) rather than of managerial inadequacies. Productivity growth has been slight, and can be attributed to the sluggish adaptation of inefficient banks to technological advancements.