|
on Risk Management |
Issue of 2009‒03‒07
ten papers chosen by |
By: | Iman van Lelyveld; Franka Liedorp; Manuel Kampman |
Abstract: | We analyse the effect of failing reinsurance cover on the stability of Dutch insurers. As insurers often reinsure themselves with other (re)insurers, losses could spread contagiously through the sector. Using a unique and confidential data set on reinsurance exposures, we perform a scenario analysis to measure contagion risks. Based on current exposures, we find no evidence of systemic risk in the Netherlands, even if multiple reinsurance companies fail simultaneously. Next, we analyse to what extent the financial position of individual primary insurers is affected following a particular shock, considering solvency, capital and profit levels. The life insurance industry is hardly affected by reinsurance failures. The non-life industry, however, is vulnerable to a crisis in the European reinsurance market. We also find that members of smaller insurance groups are particularly exposed. |
Keywords: | reinsurance; contagion; simulation. |
JEL: | G20 G22 |
Date: | 2009–02 |
URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:201&r=rmg |
By: | Fulvio Corsi; Davide Pirino; Roberto Reno |
Abstract: | This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is correctly separated into its continuous and discontinuous component. To this purpose, we introduce the concept of threshold multipower variation (TMPV), which is based on the joint use of bipower variation and threshold estimation. With respect to alternative methods, our TMPV estimator provides less biased and robust estimates of the continuous quadratic variation and jumps. This technique also provides a new test for jump detection which has substantially more power than traditional tests. We use this separation to forecast volatility by employing an heterogeneous autoregressive (HAR) model which is suitable to parsimoniously model long memory in realized volatility time series. Empirical analysis shows that the proposed techniques improve significantly the accuracy of volatility forecasts for the S&P500 index, single stocks and US bond yields, especially in periods following the occurrence of a jump. |
Keywords: | volatility forecasting, jumps, bipower variation, threshold estimation, stock, bond |
JEL: | G1 C1 C22 C53 |
Date: | 2009–03 |
URL: | http://d.repec.org/n?u=RePEc:hst:ghsdps:gd08-036&r=rmg |
By: | Nicole Branger; Holger Kraft; Christoph Meinerding |
Abstract: | Stocks are exposed to the risk of sudden downward jumps. Additionally, a crash in one stock (or index) can increase the risk of crashes in other stocks (or indices). Our pape explicitly takes this contagion risk into account and studies its impact on the portfolio decision of a CRRA investor both in complete and in incomplete market settings. We find that the investor significantly adjusts his portfolio when contagion is more likely to occur. Capturing the time dimension of contagion, i.e. the time span between jumps in two stocks or stock indices, is thus of first-order importance when analyzing portfolio decisions. Investors ignoring contagion completely or accounting for contagion while ignoring its time dimension suffer large and economically significant utility losses. These losses are larger in complete than in incomplete markets, and the investor might be better off if he does not trade derivatives. Furthermore, we emphasize that the risk of contagion has a crucial impact on investors' security demands, since it reduces their ability to diversify their portfolios. |
JEL: | G12 G13 |
Date: | 2009–02 |
URL: | http://d.repec.org/n?u=RePEc:fra:franaf:198&r=rmg |
By: | Ojo, Marianne |
Abstract: | This paper traces the developments that have contributed to the importance of risk in regulation. Not only does it consider theories associated with risk, it also discusses explanations as to why risk has become so important within regulatory and governmental circles. Two forms of risk regulation, namely risk based regulation and meta regulation are considered. As well as considering the application of both in jurisdictions such as the UK, the paper places greater focus in discussing the importance of meta regulation in jurisdictions such as Germany, Italy and the US. The preference for meta regulation is based on the premises, not only of the advantages considered in this paper but also on the application of Basel 11 in several jurisdictions. Whilst meta regulation also has its disadvantages, the impact of risk based regulation on the use of external auditors plays a part in the preference for meta regulation. |
Keywords: | meta regulation; enforced self regulation;risk; compliance |
JEL: | K2 |
Date: | 2009–03 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:13723&r=rmg |
By: | Michel Aglietta; Ludovic Moreau; Adrian Roche |
Abstract: | The 2007/2008 global credit crisis was born out of opaque securitization transactions. Introducing structured products risk estimation techniques shows how the most basic investment analysis could not be done without detailed and updated knowledge on the assets of the pool. Access to such details was crucial for investors to perform an autonomous valuation, the lack of which led to a pervading acceptance of ratings at face value. The crisis brought numerous delusions to naïve users of these privately issued opinions. Coming back to the central role that investor played during the previous speculative episode and introducing a theoretical discussion on the dynamics of market finance, it is shown that trusting market discipline and due diligence was bound to end up being misguiding. Given that unprecedented rating volatility brought a share of the blame game to rating firms, strategies that would aim at securing an informed use of ratings are finally outlined. |
Keywords: | financial crisis, credit risk, rating agencies |
JEL: | G11 G12 G29 |
Date: | 2009 |
URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2009-3&r=rmg |
By: | Che, Natasha Xingyuan |
Abstract: | Most traditional explanations for the decreasing aggregate output volatility - so-called "Great Moderation" - fail to accommodate, or even directly contradict, another aspect of empirical data: the average sales volatility for publicly-traded US firms has been increasing during the same period. The paper aims to reconcile the opposite trends of firm-level and aggregate volatilities. I argue that the rise of organization capital, or firm-specific intangible capital, is the origin of the volatility divergence. Firms in the modern economy have been investing heavily in intangible and organizational assets, such as R&D, management processes, intellectual property, software, and brand name - the "soft" capitals that distinguish a firm from the sum of its physical properties. Most intangible assets are firm-specific, inseparable from the company that originally produced them, and difficult to trade on outside market. Investing in these organization-specific capitals insulates a firm from market-wide shocks, but introduces higher firm-specific risk that does not equally affect its peers. When value creation is increasingly relying on organization capital, the impact of idiosyncratic risk factor rises, while that of general risk factor declines. The former elevates firm-level volatility; the latter reduces aggregate volatility, mainly through weakening the positive co-movements among firms. Therefore, the decrease in aggregate output volatility is not because of less turbulent macro environment, but a result of more heterogeneity among production units. In this sense, the Great Moderation is rather a story of "Great Dissolution". It may indicate greater economic uncertainty faced by individual agents, instead of less. My empirical investigation found that, consistent with the paper's hypotheses, firm-level volatility increases with organizational investment, but general factors' impact on firm performance and a firm's correlation with others decrease with organizational investment. Simulations of the general equilibrium model featuring organization capital investment are capable of replicating the volatility trends at both aggregate and firm level for the past two decades. |
Keywords: | organization capital; intangible capital; great moderation; firm volatility; business cycle; business investment |
JEL: | D21 E22 D58 E10 E32 C23 E23 D24 |
Date: | 2009 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:13701&r=rmg |
By: | Ferreira, Thiago Revil T.; Torres-Martínez, Juan Pablo |
Abstract: | We analyze the possibility of the simultaneous presence of three key features in price-taking credit markets: infinity horizon, collateralized credit operations and effective additional enforcement mechanisms, i.e. those implying payments besides the value of the collateral guarantees. We show that these additional mechanisms, instead of strengthening, actually weaken the restrictions that collateral places on borrowing. In fact, when collateral requirements are not large enough in relation to the effectiveness of the additional mechanisms, lenders anticipate total payments exceeding the value of the collateral requirements. Thus, by non-arbitrage, they lend more than the value of these guarantees. In turn, in the absence of other market frictions such as borrowing constraints, agents may indefinitely postpone their debts, implying the collapse of the agent's maximization problem and of such credit markets. |
Keywords: | Effective default enforcements; Collateral guarantees; Individual's optimality. |
JEL: | D53 D52 |
Date: | 2009–03 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:13781&r=rmg |
By: | Federico M. Bandi; Roberto Reno |
Abstract: | Using recent advances in the nonparametric estimation of continuous-time processes under mild statistical assumptions as well as recent developments on nonparametric volatility estimation by virtue of market microstructure noise-contaminated high-frequency asset price data, we provide (i) a theory of spot variance estimation and (ii) functional methods for stochastic volatility modelling. Our methods allow for the joint evaluation of return and volatility dynamics with nonlinear drift and diffusion functions, nonlinear leverage effects, jumps in returns and volatility with possibly state-dependent jump intensities, as well as nonlinear risk-return trade-offs. Our identification approach and asymptotic results apply under weak recurrence assumptions and, hence, accommodate the persistence properties of variance in finite samples. Functional estimation of a generalized (i.e., nonlinear) version of the square-root stochastic variance model with jumps in both volatility and returns for the S&P500 index suggests the need for richer variance dynamics than in existing work. We find a linear specification for the variance's diffusive variance to be misspecified (and inferior to a more flexible CEV specification) even when allowing for jumps in the variance dynamics. |
Keywords: | Spot variance, stochastic volatility, jumps in returns, jumps in volatility, leverage effects, risk-return trade-offs, kernel methods, recurrence, market microstructure noise. |
Date: | 2009–03 |
URL: | http://d.repec.org/n?u=RePEc:hst:ghsdps:gd08-035&r=rmg |
By: | Xiaohong Chen (Cowles Foundation, Yale University); Wei Biao Wu (Dept. of Statistics, University of Chicago); Yanping Yi (Dept of Economics, New York University) |
Abstract: | This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant distributions and parametric copula functions; where the copulas capture all scale-free temporal dependence and tail dependence of the processes. The Markov models generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student's t copulas (with tail dependence) are all geometric ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We show that the sieve MLEs of any smooth functionals are root-n consistent, asymptotically normal and efficient; and that the sieve likelihood ratio statistics is chi-square distributed. We present Monte Carlo studies to compare the finite sample performance of the sieve MLE, the two-step estimator of Chen and Fan (2006), the correctly specified parametric MLE and the incorrectly specified parametric MLE. The simulation results indicate that our sieve MLEs perform very well; having much smaller biases and smaller variances than the two-step estimator for Markov models generated by Clayton, Gumbel and other copulas having strong tail dependence. |
Keywords: | Copula, Tail dependence, Nonlinear Markov models, Geometric ergodicity, Sieve MLE, Semiparametric efficiency, Sieve likelihood ratio statistics, Value-at-Risk |
JEL: | C14 C22 |
Date: | 2009–02 |
URL: | http://d.repec.org/n?u=RePEc:cwl:cwldpp:1691&r=rmg |
By: | Kousky, Carolyn (Resources for the Future); Cooke, Roger M. (Resources for the Future) |
Abstract: | Adapting to climate change will not only require responding to the physical effects of global warming, but will also require adapting the way we conceptualize, measure, and manage risks. Climate change is creating new risks, altering the risks we already face, and also, importantly, impacting the interdependencies between these risks. In this paper we focus on three particular phenomena of climate related risks that will require a change in our thinking about risk management: global micro-correlations, fat tails, and tail dependence. Consideration of these phenomena will be particularly important for natural disaster insurance, as they call into question traditional methods of securitization and diversification. |
Keywords: | tail dependence, micro-correlations, fat tails, damage distributions, climate change |
JEL: | Q54 G22 C02 |
Date: | 2009–02–04 |
URL: | http://d.repec.org/n?u=RePEc:rff:dpaper:dp-09-03&r=rmg |