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on Risk Management |
| By: | Matthias Fleckenstein; Francis A. Longstaff; Hanno Lustig |
| Abstract: | We study the nature of deflation risk by extracting the objective distribution of inflation from the market prices of inflation swaps and options. We find that the market expects inflation to average about 2.5 percent over the next 30 years. Despite this, the market places substantial probability weight on deflation scenarios in which prices decline by more than 10 to 20 percent over extended horizons. We find that the market prices the economic tail risk of de- flation very similarly to other types of tail risks such as catastrophic insurance losses. In contrast, inflation tail risk has only a relatively small premium. De- flation risk is also significantly linked to measures of financial tail risk such as swap spreads, corporate credit spreads, and the pricing of super senior tranches. These results indicate that systemic financial risk and deflation risk are closely related. |
| JEL: | E31 G13 |
| Date: | 2013–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:19238&r=rmg |
| By: | Sant'Anna, Pedro H. C. |
| Abstract: | This article proposes a new diagnostic test for dynamic count models, which is well suited for risk management. Our test proposal is of the Portmanteau-type test for lack of residual autocorrelation. Unlike previous proposals, the resulting test statistic is asymptotically pivotal when innovations are uncorrelated, but not necessarily iid nor a martingale difference. Moreover, the proposed test is able to detect local alternatives converging to the null at the parametric rate T^{1/2}, with T the sample size.The finite sample performance of the test statistic is examined by means of a Monte Carlo experiment. Finally, using a dataset on U.S. corporate bankruptcies, we apply our test proposal to check if common risk models are correctly specified. |
| Keywords: | Time Series of counts; Residual autocorrelation function; Model checking; Credit risk management. |
| JEL: | C12 C22 C25 G3 G33 |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:48376&r=rmg |
| By: | Pinar Yesin (Swiss National Bank) |
| Abstract: | Foreign currency loans to the unhedged non-banking sector are remarkably prevalent in Europe and create a significant exchange-rate-induced credit risk to European banking sectors. In particular, Swiss franc (CHF)-denominated loans, popular in Eastern European countries, could trigger simultaneous bank failures if depreciation of the domestic currencies prevents borrowers from servicing the loans. Foreign currency loans thus pose a systemic risk from a “common market shock” perspective. The author uses a novel dataset of foreign-currency loans from 17 countries for 2007-11 (collected by the Swiss National Bank) and builds on the method suggested by Ranciere, Tornell, and Vamvakidis (2010) to quantify this systemic risk. The author finds that systemic risk is substantial in the non-euro area, while it is relatively low in the euro area. However, CHF-denominated loans are not the underlying source of the high systemic risk: Loans denominated in other foreign currencies (probably to a large extent in euros) contribute significantly more to the systemic risk in the non-euro area than CHF-denominated loans. Furthermore, systemic risk shows high persistence and low volatility during the sample period. The author also finds that banks in Europe have continuously held more foreign-currency-denominated assets than liabilities, indicating their awareness of the exchange-rate-induced credit risk they face. |
| Date: | 2013–06 |
| URL: | http://d.repec.org/n?u=RePEc:szg:worpap:1306&r=rmg |
| By: | Jose Manuel Feria-Dominguez (Department of Finance and Accounting, Universidad Pablo de Olavide); Enrique Jimenez-Rodriguez (Department of Finance and Accounting, Universidad Pablo de Olavide); Ines Merino Fernandez-Galiano (Department of Finance and Accounting, Universidad Pablo de Olavide) |
| Abstract: | This paper isolate the corporate reputational risk incurred by Oil and Gas companies, listed in the NYSE, derived from recent medium sized and large oil spill disasters occurred from 2005 to 2011 in the US. For this purpose, we conduct a standard short-horizon daily event study analysis to calibrate the potential impact of such environmental episodes on the market value of the firms analyzed. Since the accidental spillages are proved to have a negative effect on the cumulative abnormal returns (henceforth, CAR) of the firm’s stock, reputational risk can be identified by adjusting abnormal returns by a certain Loss Ratio, in order to capture the difference between the plummeted firm’s market value and the operational loss incurred by the company. The new magnitude, CAR (Rep), is then introduced to disentangle operational losses from reputational damage. |
| Keywords: | Corporate Reputational Risk; abnormal returns; sevent study; oil spills |
| Date: | 2013–07 |
| URL: | http://d.repec.org/n?u=RePEc:pab:fiecac:13.02&r=rmg |
| By: | Victoria Galsband; Thomas Nitschka |
| Abstract: | We take the perspective of a US investor to assess cross-sectional differences in 19 bilateral, conditional currency excess returns in an empirical model that distinguishes between US-specific and global risks, conditional on US bull (upside) or bear (downside) markets. At first glance, our results suggest that global downside risk is compensated in average bilateral currency excess returns. Further analysis, however, reveals that downside risk and financial market volatility exposures are closely related. Moreover, the downside risk evidence is mostly driven by emerging markets' currencies. We conclude that downside risk models do not fully address the issue of foreign currency excess returns being largely unrelated to standard risk factors. |
| Keywords: | CAPM, downside risk, exchange rate, forward premium puzzle, uncoveredinterest rate parity, upside risk |
| JEL: | F31 G15 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:snb:snbwpa:2013-07&r=rmg |
| By: | David Crainich (CNRS-LEM and IESEG School of Management); Louis Eeckhoudt (IESEG School of Management (LEM-CNRS) and and CORE (Université Catholique de Louvain)); James K. Hammitt (Harvard University (Center for Risk Analysis), Cambridge - Toulouse School of Economics (LERNA-INRA)) |
| Abstract: | The relationship between willingness to pay (WTP) to reduce the probability of an adverse event and the degree of risk aversion is ambiguous. The ambiguity arises because paying for protection worsens the outcome in the event the adverse event occurs, which influences the expected marginal utility of wealth. Using concepts of prudence (equivalently, downside risk aversion), we characterize the marginal WTP to reduce the probability of the adverse event as the product of WTP in the case of risk neutrality and an adjustment factor. For the univariate case (e.g., risk of financial loss), the adjustment factor depends on risk aversion and prudence with respect to wealth. For the bivariate case (e.g., risk of death or illness), the adjustment factor depends on risk aversion and cross-prudence in wealth. |
| Keywords: | value per statistical life, mortality risk, risk aversion, prudence |
| JEL: | D8 I1 |
| Date: | 2013–06 |
| URL: | http://d.repec.org/n?u=RePEc:ies:wpaper:e201313&r=rmg |
| By: | Barbara Choroś-Tomczyk; Wolfgang Karl Härdle; Ostap Okhrin; |
| Abstract: | Modelling the dynamics of credit derivatives is a challenging task in finance and economics. The recent crisis has shown that the standard market models fail to measure and forecast financial risks and their characteristics. This work studies risk of collateralized debt obligations (CDOs) by investigating the evolution of tranche spread surfaces and base correlation surfaces using a dynamic semiparametric factor model (DSFM). The DSFM offers a combination of flexible functional data analysis and dimension reduction methods, where the change in time is linear but the shape is nonparametric. The study provides an empirical analysis based on iTraxx Europe tranches and proposes an application to curve trading strategies. The DSFM allows us to describe the dynamics of all the tranches for all available maturities and series simultaneously which yields better understanding of the risk associated with trading CDOs and other structured products. |
| Keywords: | base correlation, collateralized debt obligation, curve trade, dynamic factor model, semiparametric model |
| JEL: | C14 C51 G11 G17 |
| Date: | 2013–07 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2013-032&r=rmg |
| By: | Diep Duong (Rutgers University); Norman Swanson (Rutgers University) |
| Abstract: | The technique of using densities and conditional distributions to carry out consistent specification testing and model selection amongst multiple diffusion processes have received considerable attention from both financial theoreticians and empirical econometricians over the last two decades. One reason for this interest is that correct specification of diffusion models describing dynamics of financial assets is crucial for many areas in finance including equity and option pricing, term structure modeling, and risk management, for example. In this paper, we discuss advances to this literature introduced by Corradi and Swanson (2005), who compare the cumulative distribution (marginal or joint) implied by a hypothesized null model with corresponding empirical distributions of observed data. We also outline and expand upon further testing results from Bhardwaj, Corradi and Swanson (BCS: 2008) and Corradi and Swanson (2011). In particular, parametric specification tests in the spirit of the conditional Kolmogorov test of Andrews (1997) that rely on block bootstrap resampling methods in order to construct test critical values are first discussed. Thereafter, extensions due to BCS (2008) for cases where the functional form of the conditional density is unknown are introduced, and related continuous time simulation methods are introduced. Finally, we broaden our discussion from single process specification testing to multiple process model selection by discussing how to construct predictive densities and how to compare the accuracy of predictive densities derived from alternative (possibly misspecified) diffusion models. In particular, we generalize simulation Steps outlined in Cai and Swanson (2011) to multifactor models where the number of latent variables is larger than three. These final tests can be thought of as continuous time generalizations of the discrete time "reality check" test statistics of White (2000), which are widely used in empirical finance (see e.g. Sullivan, Timmermann and White (1999, 2001)). We finish the chapter with an empirical illustration of model selection amongst alternative short term interest rate models. |
| Keywords: | multi-factor diffusion process, specification test, out-of-sample forecast, jump process, block bootstrap |
| JEL: | C22 C51 |
| Date: | 2013–07–16 |
| URL: | http://d.repec.org/n?u=RePEc:rut:rutres:201312&r=rmg |