Deriving the Term Structure of Banking Crisis Risk with a Compound Option Approach: The Case of Kazakhstan
Stefan Eichler, Alexander Karmann, Dominik Maltritz
Discussion paper, Series 2: Banking and financial studies, No. 01/2010,
No. 1,
2010
Abstract
We use a compound option-based structural credit risk model to infer a term structure of banking crisis risk from market data on bank stocks in daily frequency. Considering debt service payments with different maturities this term structure assigns a separate estimator for short- and long-term default risk to each maturity. Applying the Duan (1994) maximum likelihood approach, we find for Kazakhstan that the overall crisis probability was mainly driven by short-term risk, which increased from 25% in March 2007 to 80% in December 2008. Concurrently, the long-term default risk increased from 20% to only 25% during the same period.
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Dynamic Order Submission Strategies with Competition between a Dealer Market and a Crossing Network
Hans Degryse, Mark Van Achter, Gunther Wuyts
Journal of Financial Economics,
No. 3,
2009
Abstract
We analyze a dynamic microstructure model in which a dealer market (DM) and a crossing network (CN) interact for three informational settings. A key result is that coexistence of trading systems generates systematic patterns in order flow, which depend on the degree of transparency. Further, we study overall welfare, measured by the gains from trade of all agents, and compare it with the maximum overall welfare. The discrepancy between both measures is attributable to two inefficiencies. Due to these inefficiencies, introducing a CN next to a DM, as well as increasing the transparency level, not necessarily produces greater overall welfare.
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Interbank Exposures: An Empirical Examination of Contagion Risk in the Belgian Banking System
Hans Degryse, Grégory Nguyen
International Journal of Central Banking,
No. 2,
2007
Abstract
Robust (cross-border) interbank markets are important for the proper functioning of modern financial systems. However, a network of interbank exposures may lead to domino effects following the event of an initial bank failure. We investigate the evolution and determinants of contagion risk for the Belgian banking system over the period 1993–2002 using detailed information on aggregate interbank exposures of individual banks, large bilateral interbank exposures, and cross-border interbank exposures. The "structure" of the interbank market affects contagion risk. We find that a change from a complete structure (where all banks have symmetric links) toward a "multiplemoney-center" structure (where money centers are symmetrically linked to otherwise disconnected banks) has decreased the risk and impact of contagion. In addition, an increase in the relative importance of cross-border interbank exposures has lowered local contagion risk. However, this reduction may have been compensated by an increase in contagion risk stemming from foreign banks.
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Measurement Matters — Alternative Input Price Proxies for Bank Efficiency Analyses
Michael Koetter
Journal of Financial Services Research,
No. 2,
2006
Abstract
Most bank efficiency studies that use stochastic frontier analysis (SFA) employ each bank’s own implicit input price when estimating efficient frontiers. But at the same time, most studies are based on cost and/or profit models that assume perfect input markets. Traditional input price proxies therefore contain at least substantial measurement error. We suggest here two alternative input market definitions to approximate exogenous input prices. We have access to Bundesbank data, which allows us to cover virtually all German universal banks between 1993 and 2003. The use of alternative input price proxies leads to mean cost efficiency that is significantly five percentage points lower compared to traditional input prices. Mean profit efficiency is hardly affected. Across models, small cooperative banks located in large western states perform best while large banks and those located in eastern states rank lowest.
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Understanding CSR Champions: A Machine Learning Approach
Alona Bilokha, Mingying Cheng, Mengchuan Fu, Iftekhar Hasan
Annals of Operations Research,
2099
Abstract
In this paper, we study champions of corporate social responsibility (CSR) performance among the U.S. publicly traded firms and their common characteristics by utilizing machine learning algorithms to identify predictors of firms’ CSR activity. We contribute to the CSR and leadership determinants literature by introducing the first comprehensive framework for analyzing the factors associated with corporate engagement with socially responsible behaviors by grouping all relevant predictors into four broad categories: corporate governance, managerial incentives, leadership, and firm characteristics. We find that strong corporate governance characteristics, as manifested in board member heterogeneity and managerial incentives, are the top predictors of CSR performance. Our results suggest policy implications for providing incentives and fostering characteristics conducive to firms “doing good.”
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