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on Risk Management |
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Issue of 2012‒10‒13
nine papers chosen by |
| By: | Francq, Christian; Zakoian, Jean-Michel |
| Abstract: | This paper introduces the concept of risk parameter in conditional volatility models of the form $\epsilon_t=\sigma_t(\theta_0)\eta_t$ and develops statistical procedures to estimate this parameter. For a given risk measure $r$, the risk parameter is expressed as a function of the volatility coefficients $\theta_0$ and the risk, $r(\eta_t)$, of the innovation process. A two-step method is proposed to successively estimate these quantities. An alternative one-step approach, relying on a reparameterization of the model and the use of a non Gaussian QML, is proposed. Asymptotic results are established for smooth risk measures as well as for the Value-at-Risk (VaR). Asymptotic comparisons of the two approaches for VaR estimation suggest a superiority of the one-step method when the innovations are heavy-tailed. For standard GARCH models, the comparison only depends on characteristics of the innovations distribution, not on the volatility parameters. Monte-Carlo experiments and an empirical study illustrate these findings. |
| Keywords: | GARCH; Quantile Regression; Quasi-Maximum Likelihood; Risk measures; Value-at-Risk |
| JEL: | C13 C22 |
| Date: | 2012–10–04 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:41713&r=rmg |
| By: | Khalfaoui, R; Boutahar, M |
| Abstract: | We analyzed the volatility dynamics of three developed markets (U.K., U.S. and Japan), during the period 2003-2011, by comparing the performance of several multivariate volatility models, namely Constant Conditional Correlation (CCC), Dynamic Conditional Correlation (DCC) and consistent DCC (cDCC) models. To evaluate the performance of models we used four statistical loss functions on the daily Value-at-Risk (VaR) estimates of a diversified portfolio in three stock indices: FTSE 100, S&P 500 and Nikkei 225. We based on one-day ahead conditional variance forecasts. To assess the performance of the abovementioned models and to measure risks over different time-scales, we proposed a wavelet-based approach which decomposes a given time series on different time horizons. Wavelet multiresolution analysis and multivariate conditional volatility models are combined for volatility forecasting to measure the comovement between stock market returns and to estimate daily VaR in the time-frequency space. Empirical results shows that the asymmetric cDCC model of Aielli (2008) is the most preferable according to statistical loss functions under raw data. The results also suggest that wavelet-based models increase predictive performance of financial forecasting in low scales according to number of violations and failure probabilities for VaR models. |
| Keywords: | Dynamic conditional correlations; Value-at-Risk; wavelet decomposition; Stock prices |
| JEL: | D53 C53 G11 C52 |
| Date: | 2012–09–24 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:41624&r=rmg |
| By: | Das, Udaibir S. (Asian Development Bank Institute); Oliva, Maria A. (Asian Development Bank Institute); Tsuda, Takahiro (Asian Development Bank Institute) |
| Abstract: | We examine some of the macro-financial dimensions of sovereign risk and propose a conceptual framework that captures risks other than just the default risk. Morphed under a multi-dimensional notion of sovereign risk, we argue that the existing empirical methodologies to measure sovereign risk cover only partial aspects of sovereign risk and fail to capture its macro-financial dimensions. We highlight a menu of tools that could be used to tackle the broader notion of sovereign risk, and suggest that authorities should actively use them to manage the macro financial dimensions of sovereign risk and before those risks feed into the real economy. |
| Keywords: | sovereign risk; default risk; macro-financial dimensions |
| JEL: | E43 F30 F34 |
| Date: | 2012–10–02 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbiwp:0383&r=rmg |
| By: | Peter Zweifel (Department of Economics, University of Zurich); Dieter Pfaff (Department of Business Administration (IBW), University of Zurich); Jochen Kühn |
| Abstract: | This paper contains a critique of solvency regulation such as imposed on banks by Basel I and II. Banks’ investment divisions seek to maximize the expected rate of return on risk-adjusted capital. For them, a higher solvency level lowers the cost of refinancing but ties costly capital. Sequential decision making by banks is tracked over three periods. In period 1, exogenous changes in expected returns and volatility occur, causing a pair of optimal adjustments of solvency in period 2. In period 3, the actual adjustment of solvency constitutes an exogenous shock, triggering portfolio adjustments in terms of expected return and volatility which move the bank along an endogenous efficiency frontier. Both Basel I and II are shown to modify the slope of this frontier, inducing senior management to opt for higher volatility in several situations. Therefore, both types of solvency regulation can run counter their stated objective, which may also be true of Basel III. |
| Keywords: | regulation, banks, solvency, Basel I, Basel II, Basel III |
| JEL: | G15 G21 G28 L51 |
| Date: | 2012–05 |
| URL: | http://d.repec.org/n?u=RePEc:zrh:wpaper:303&r=rmg |
| By: | Flavia Barsotti (ISFA, University Lyon 1, France); Simona Sanfelici (Dipartimento di Economia, Universita' di Parma) |
| Abstract: | Equity returns and firm's default probability are strictly interrelated financial measures capturing the credit risk profile of a firm. Following the idea proposed in [20] we use high-frequency equity prices in order to estimate the volatility risk component of a firm within Merton [17] structural model. Differently from [20] we consider a more general framework by introducing market microstructure noise as a direct effect of using noisy high-frequency data and propose the use of non- parametric estimation techniques in order to estimate equity volatility. We conduct a simulation analysis to compare the performance of different non-parametric volatil- ity estimators in their capability of i) filtering out the market microstructure noise, ii) extracting the (unobservable) true underlying asset volatility level, iii) predicting default probabilies calibrated from Merton [17] model. |
| Keywords: | market microstructure noise, high-frequency data, non-parametric volatility estimation, Merton model, default probabilities, volatility risk |
| Date: | 2012–10 |
| URL: | http://d.repec.org/n?u=RePEc:flo:wpaper:2012-05&r=rmg |
| By: | Dániel Holló (Magyar Nemzeti Bank (central bank of Hungary)) |
| Abstract: | In this study, a system-wide financial stress index (SWFSI) for the Hungarian financial system is developed. The indicator measures the joint stress level of the Hungarian financial system’s main segments: the spot foreign exchange market, the foreign exchange swap market, the secondary market of government bonds, the interbank unsecured money market, the equity market and the banking segment. Stress indices of the six financial system segments are aggregated on the basis of weights which reflect their time-varying cross-correlation structure. As a result, the system-wide financial stress indicator puts greater emphasis on periods in which stress presents permanently in several market segments at the same time. Our results indicate that after February 2005 the default of Lehman Brothers and its global consequences unambiguously acted as a lasting stress event with systemic risk importance from the perspective of the stability of the Hungarian financial system. Finally, the results suggest that the Hungarian financial system’s stress level in the period under review (February 1, 2005–September 16, 2011) was driven mainly by disorders in the banking and the foreign exchange swap market segments. |
| Keywords: | financial stress, system-wide financial stress index, financial stability, systemic risk |
| JEL: | G01 G10 G20 E44 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:mnb:opaper:2012/105&r=rmg |
| By: | Fabio C. Bagliano (Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino, Italy); Claudio Morana (Department of Economics, University of Milan-Bicocca) |
| Abstract: | The recent financial crisis has highlighted the fragility of the US (and other countries') financial system under several respects. In this paper, the properties of a summary index of financial fragility, obtained by combining information conveyed by the "Agency", "Ted" and "BAA-AAA" spreads, timely capturing changes in credit and liquidity risk, distress in the mortgage market, and corporate default risk, are investigated over the 1986-2010 period. The empirical results show that observed fluctuations in the financial fragility index can be attributed to identified (global and domestic) macroeconomic (20%) and financial disturbances (40% to 50%), over both short- and long-term horizons, as well as to oil-supply shocks in the long-term (25%). The investigation of specific episodes of financial distress, occurred in 1987, 1998 and 2000, and, more recently, over the 2007-2009 period, shows that sizable fluctuations in the index are largely determined by financial shocks, while macroeconomic disturbances have generally had a stabilizing effect. |
| Keywords: | financial fragility, US, macro-?nance interface, international business cycle, factor vector autoregressive models, ?financial crisis, Great Recession |
| JEL: | C22 E32 G12 |
| Date: | 2012–09 |
| URL: | http://d.repec.org/n?u=RePEc:tur:wpapnw:011&r=rmg |
| By: | Bachev, Hrabrin |
| Abstract: | Risks management studies in the agri-food sector predominately focus on the technical methods and the capability to perceive, prevent, mitigate, and recover from diverse risks. In most economic publications the risks are usually studied as other commodity regulated by the market supply and demand, and the farmers “willingness to pay” for an insurance contract modeled. At the same time, the risk management analysis largely ignore a significant “human nature” based (bounded rationality, opportunism) risk, critical factors for the managerial choice such as the institutional environment and the transaction costs, and diversity of alternative (market, private, collective, public, hybrid) modes of risk management. This paper incorporates the interdisciplinary New Institutional Economics and presents a comprehensive framework for analyzing the risk management in the agri-food sector. First, it specifies the diverse (natural, technical, behavioral, economic, policy etc.) type of agri-food risks, and the (market, private, public and hybrid) modes of their management. Second, it defines the efficiency of risk management and identifies (personal, institutional, dimensional, technological, natural) factors of governance choice. Third, it presents stages in the analysis of risk management and for the improvement of public intervention in the risk governance. Forth, it identifies the contemporary opportunities and challenges for the risk governance in the agri-food chain. Finally, it identifies, and assesses the efficiency and prospects of major modes for risk governance in the Bulgarian dairy sector. |
| Keywords: | agri-food chain and risk management; market; private; and public governance; dairy risk management; Bulgaria |
| JEL: | L25 D81 Q12 Q18 L14 D23 Q52 O17 Q13 L22 |
| Date: | 2012–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:41651&r=rmg |
| By: | Hallegatte, Stephane |
| Abstract: | This paper investigates the link between development, economic growth, and the economic losses from natural disasters in a general analytical framework, with an application to hurricane flood risks in New Orleans. It concludes that where capital accumulates through increased density of capital at risk in a given area, and the costs of protection therefore increase more slowly than capital at risk, (i) protection improves over time and the probability of disaster occurrence decreases; (ii) capital at risk -- and thus economic losses in case of disaster -- increases faster than economic growth; (iii) increased risk-taking reinforces economic growth. In this context, average annual losses from disasters grow with income, and they grow faster than income at low levels of development and slower than income at high levels of development. These findings are robust to a broad range of modeling choices and parameter values, and to the inclusion of risk aversion. They show that risk-taking is both a driver and a consequence of economic development, and that the world is very likely to experience fewer but more costly disasters in the future. It is therefore critical to increase economic resilience through the development of stronger recovery and reconstruction support instruments. |
| Keywords: | Economic Theory&Research,Hazard Risk Management,Banks&Banking Reform,Labor Policies,Insurance&Risk Mitigation |
| Date: | 2012–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:6216&r=rmg |