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on Risk Management |
| By: | Gao, Jiti; McAleer, Michael; Allen, Dave |
| Abstract: | This paper gives an overview about the sixteen papers included in this special issue. The papers in this special issue cover a wide range of topics. Such topics include discussing a class of tests for correlation, estimation of realized volatility, modeling time series and continuous-time models with long-range dependence, estimation and specification testing of time series models, estimation in a factor model with high-dimensional problems, finite-sample examination of quasi-maximum likelihood estimation in an autoregressive conditional duration model, and estimation in a dynamic additive quantile model. |
| Keywords: | Continuous-time model; correlation test; dynamic additive model; estimation of realized volatility; factor model; long-range dependence |
| JEL: | C5 |
| Date: | 2006–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:11978&r=rmg |
| By: | Lennart Hoogerheide (Erasmus University Rotterdam); Herman K. van Dijk (Erasmus University Rotterdam) |
| Abstract: | An efficient and accurate approach is proposed for forecasting Value at Risk [VaR] and Expected Shortfall [ES] measures in a Bayesian framework. This consists of a new adaptive importance sampling method for Quantile Estimation via Rapid Mixture of <I>t</I> approximations [QERMit]. As a first step the optimal importance density is approximated, after which multi-step `high loss' scenarios are efficiently generated. Numerical standard errors are compared in simple illustrations and in an empirical GARCH model with Student-<I>t</I> errors for daily S&P 500 returns. The results indicate that the proposed QERMit approach outperforms several alternative approaches in the sense of more accurate VaR and ES estimates given the same amount of computing time, or equivalently requiring less computing time for the same numerical accuracy. |
| Keywords: | Value at Risk; Expected Shortfall; numerical accuracy; numerical standard error; importance sampling; mixture of Student-<I>t</I> distributions; variance reduction technique |
| JEL: | C11 C15 C53 D81 |
| Date: | 2008–10–02 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20080092&r=rmg |
| By: | Zhang, Rui (Carolyn); Houston, Jack E.; V. Vedenov, Dmitry V.; Barnett, Barry J. |
| Abstract: | The main objective of this study is to compare the impacts of government payments and crop insurance policies on the use of futures and options measured from a downside risk hedge model with the impacts analyzed by the expected utility (EU) hedge model. Understanding the effects of government-provided risk management tools on the private market risk management tools, such as futures and options, provides value to both crop farmers and policy makers. Comparison of the impacts from the two hedge models shows that crop farmer will hedge less in futures under the LPM2 model than under the EU hedge model. This finding indicates that model misspecification is another reason for the phenomenon that farmers actually hedge less in futures than predicted by the EU model. From the perspective of exploring new research techniques, this study applied two relatively new simulation concepts, copula simulation and conditional kernel density approach, to make the simulation assumptions less restrictive and more consistent with observations. The copula simulation applied in this study allows yield and price to have more flexible joint distribution functions than multivariate normal; the conditional kernel density approach used in farm yield simulation enables the variance of farm yield varies with county yield rather than being constant. |
| Keywords: | Down-side Risk, LPM2 Hedge Model, Government Payments, Crop Insurance Policies, Copula Simulation, Conditional Kernel Density, Agricultural Finance, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:nccest:37610&r=rmg |
| By: | Dimitri Vayanos; Paul Woolley |
| Abstract: | We propose a rational theory of momentum and reversal based on delegated portfolio management. A competitive investor can invest through an index fund or an active fund run by a manager with unknown ability. Following a negative cashflow shock to assets held by the active fund, the investor updates negatively about the manager's ability and migrates to the index fund. While prices of assets held by the active fund drop in anticipation of the investor's outflows, the drop is expected to continue, leading to momentum. Because outflows push prices below fundamental values, expected returns eventually rise, leading to reversal. Fund flows generate comovement and lead-lag effects, with predictability being stronger for assets with high idiosyncratic risk. We derive explicit solutions for asset prices, within a continuous-time normal-linear equilibrium. |
| JEL: | D5 D8 G1 |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:14523&r=rmg |
| By: | Kimie Harada; Takatoshi Ito |
| Abstract: | In the late 1990s, several large Japanese banks failed for the first time in its postwar history. As the financial environment was deteriorating further, several remaining banks decided to merge among themselves, presumably, to make their operations more efficient to avoid failures. This paper defines, calculates and analyzes the distance to default (DD), a concept of credit risk in corporate finance, of Japanese large banks. The DD helps us to answer a question whether mergers in the late 1990s and 2000s made the merged banks financially more robust as intended. The novelty of the paper is to develop a method of analyzing the DD for banks that experience a merger, and to apply the method to the Japanese banking data. Our findings include: (1) A merged bank fundamentally inherits financial soundness of pre-merged banks, without adding special value from the merger. A merger of sound (unsound) banks produced a sound (unsound, respectively) merged financial institution; and (2) In some cases, a merged bank experienced a negative DD right after the merger. The findings are consistent with a view that a primary objective of a merger was to take advantage of the perceived too-big-to-fail policy, rather than to pursue a radical reform. Another interpretation is that mergers with intention of enhancing efficiency resulted in failed implementation of true operational efficiency, such as quick integration of computer operation systems and elimination of duplicating branches. |
| JEL: | G19 G21 |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:14518&r=rmg |
| By: | Dahlgran, Roger A.; Ma, Xudong |
| Abstract: | This study focuses on hedging effectiveness defined as the proportionate price risk reduction created by hedging. By mathematical and simulation analysis we determine the following: (a) the regression R2 in the hedge ratio regression will generally overstate the amount of price risk reduction that can be achieved by hedging, (b) the properly computed hedging effectiveness in the hedge ratio regression will also generally overstate the amount of risk reduction that can be achieved by hedging, (c) the overstatement in (b) declines as the sample size increases, (d) application of estimated hedge ratios to non sample data results in an unbiased estimate of hedging effectiveness, (e) application of hedge ratios computed from small samples presents a significant chance of actually increasing price risk by hedging, and (f) comparison of in sample and out of sample hedging effectiveness is not the best method for testing for structural change in the hedge ratio regression. |
| Keywords: | out of sample, post sample, hedging, effectiveness, forecasts, simulation, Agricultural Finance, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:nccest:37604&r=rmg |
| By: | McKenzie, Andrew; Singh, Navinderpal |
| Abstract: | It is well documented that €ܵnanticipatedÂ€Ý information contained in USDA crop reports induces large price reactions in corn and soybean markets. Thus, a natural question that arises from this literature is: To what extent are futures hedges able to remove or reduce increased price risk around report release dates? This paper addresses this question by simulating daily futures returns, daily cash returns and daily hedged returns around report release dates for two storable commodities (corn and soybeans) in two market settings (North Central Illinois and Memphis Tennessee). Various risk measures, including €ܖalue at Risk,Â€Ý are used to determine hedging effectiveness, and €Ünalysis of VarianceÂ€Ý is used to uncover the underlying factors that contribute to hedging effectiveness. |
| Keywords: | USDA Crop Reports, Storage Hedging, Value At Risk, Analysis of Variance, Agricultural Finance, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:nccest:37617&r=rmg |