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on Risk Management |
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Issue of 2018‒03‒05
six papers chosen by |
| By: | Fabio Cortes; Peter Lindner; Sheheryar Malik; Miguel A. Segoviano Basurto |
| Abstract: | This paper presents the Systemic Risk and Interconnectedness (SyRIN) tool. SyRIN allows a comprehensive assessment of systemic risk via quantification of the impact of risk amplification mechanisms, due to interconnectedness structures across banks and other financial intermediaries—insurance, pension fund, hedge fund and investment fund sectors, which cannot be captured when analyzing sectors independently. The tool produces various metrics to evaluate systemic risk from complementary perspectives, including tail risk, cross-entity interconnectedness and the contribution to systemic risk by different entities and sectors. SyRIN is easily implementable with publicly available data and can be adapted to cater to different degrees of institutional granularity and data availability. The framework is designed to be a tool to identify vulnerabilities from a top-down perspective that can lead to deeper analysis in specific sectors for policy formulation. |
| Date: | 2018–01–24 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:18/14&r=rmg |
| By: | Sivec, Vasja; Volk, Matjaz; Chen, Yi-An |
| Abstract: | With the new regulatory framework, known as Basel III, policymakers introduced a countercyclical capital buffer. It subjects banks to higher capital requirements in times of credit excess and is released in a financial crisis. This incentivizes banks to extend credit and to buffer losses. Due to its recent introduction empirical research on its effects are limited. We analyse a unique policy experiment to evaluate the effects of buffer release. In 2006, the Slovenian central bank introduced a temporary deduction item in capital calculation, creating an average capital buffer of 0.8% of risk weighted assets. It was released at the start of the financial crisis in 2008 and is akin to a release of a countercyclical capital buffer. We estimate its impact on bank behaviour. After its release, firms borrowing from banks holding 1 p.p. higher capital-buffer received 11 p.p. more in credit. Also we find the impact was greater for healthy firms, and it increased loan-loss provisioning for firms in default. |
| Keywords: | countercyclical capital buffer, macroprudential policy, credit, loan loss provisions |
| JEL: | G01 G21 G28 |
| Date: | 2018–01–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:84323&r=rmg |
| By: | Zintle Twala (Department of Economics, University of Pretoria, Pretoria, South Africa); Riza Demirer (Department of Economics & Finance, Southern Illinois University Edwardsville, Edwardsville, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa) |
| Abstract: | Time-varying correlations have broad implications in asset pricing, portfolio management and hedging. Numerous studies in the literature have found that the change in correlations is mainly related to the size of market movements, hence volatility. However, recent research finds that correlations varying over time do not necessarily imply that correlations depend on the size of markets movements, but that the effect of market movements is amplified in times of high financial distress, characterised by low liquidity. This paper seeks to investigate the effect of liquidity on time-varying correlations among different asset classes, namely stocks, corporate bonds and commodities. Applying regression analysis with structural breaks to correlations estimated via a rolling-window approach, we show that liquidity indeed has a significant effect on the time-variation in asset correlations, particularly in the case of how bond returns comove with other asset classes. We observe that higher liquidity risk is associated with lower correlation of bond returns with stocks as well as commodities. Our findings suggest that measures of liquidity risk can improve models of correlations and potentially help improve the effectiveness of risk management strategies during periods of turbulence. |
| Keywords: | Conditional correlation, Asset Classes, Liquidity and Volatility |
| JEL: | C22 G10 |
| Date: | 2018–02 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201808&r=rmg |
| By: | Thomas Conlon (University College Dublin); John Cotter (University College Dublin); Philip Molyneux (University of Sharjah) |
| Abstract: | Banks adhere to strict rules regarding the quantity of regulatory capital held, but have some flexibility as to its composition. In this paper, we examine bank insolvency risk (distance to default) for listed North American and European banks over the period 2002-2014, focusing on sensitivity to capital other than common equity. Decomposing tier 1 capital into equity and non-core components reveals a heretofore unidentified variation in risk reduction capacity. Greater non-core tier 1 capital is associated with increased insolvency risk for larger and more diversified banks, impairing the risk reducing capacity of aggregate tier 1 capital. Overall tier 2 capital is not linked with insolvency risk, although a conflicting relationship is isolated conditional on the level of total regulatory capital held. Finally, the association between risk and capital is weakened when the latter is defined relative to risk-weighted assets. |
| Keywords: | Regulatory Capital, Bank Risk, Regulatory Capital Arbitrage, Tier 1, Tier 2 |
| JEL: | G21 G28 G32 |
| Date: | 2018–02–19 |
| URL: | http://d.repec.org/n?u=RePEc:ucd:wpaper:201806&r=rmg |
| By: | Jean-Philippe Boussemart (University of Lille 3 and IÉSEG School of Management (LEM 9221-CNRS)); Hervé Leleu (CNRS-LEM 9221 and IÉSEG School of Management); Zhiyang Shen (Eximbank, Anhui University of Finance and Economics); Michael Vardanyan (IÉSEG School of Management (LEM-CNRS - UMR 9221)); Ning Zhu (South China University of Technology, School of Economics and Commerce) |
| Abstract: | This paper proposes a novel non-parametric approach of a banking production technology that decomposes performance into economic and risk management efficiencies. The basis of our approach is to separate the production technology into two sub-technologies. The former is the production of non-interest income and loans from a set of traditional inputs. The latter is attached to the production of interest income from loans where an explicit distinction between good and non-performing loans is introduced. Economic efficiency comes from the production of good outputs, namely interest and non-interest income, while risk-management efficiency is related to the minimization of the non-performing loans that can be considered as an unintended or bad output. The model is applied to Chinese financial data covering 30 banks from 2005 to 2012 and different scenarios are considered. The results indicate that income could be increased by an average rate of 16% while non-performing loans could be decreased by an average rate of 33%. According to our results, banking managers could strike a balance between economic performance and risk-management and make more appropriate decisions in line with their preferences. |
| Keywords: | Data Envelopment Analysis; Risk management; Economic efficiency; Banking performance; Non-performing loans |
| Date: | 2017–10 |
| URL: | http://d.repec.org/n?u=RePEc:ies:wpaper:e201709&r=rmg |
| By: | Schmalz, Martin |
| Abstract: | What is the effect of unionization on corporate financial policies? The average unionized firm responds with lower cash and higher leverage to a unionization election than the average firm escaping unionization. However, using a regression discontinuity design I find that the causal effect of unionization is close to zero on average, but heterogeneous across firms. For the subset of large and financially unconstrained firms, the causal effect is positive on leverage and negative on cash; the opposite is true for small and financially constrained firms. These results help reconcile controversially discussed views on how corporate finance and labor interact. |
| Keywords: | Capital Structure; cash; Labor Adjustment Costs; Regression Discontinuity; Risk management; Unionization |
| JEL: | G32 J50 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12595&r=rmg |