Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic...

Abstract The foremost concern of a modern risk manager is to estimate Value-at-Risk (VaR), that is the maximum loss likely to occur over the next two weeks for a given confidence level. Although widely spread as a standard measure for quantifying market risk, most of the techniques involved in measuring VaR are based on unrealistic assumptions. The purpose of this paper is to highlight the defi...

We thank seminar participants at the OCC and the 1996 Chicago Fed Bank Structure Conference for their comments. We also thank Rene Stulz for comments and suggestions and Amy Crews for guidance concerning kernel estimation. The views expressed herein are those of the authors and do not necessarily represent the views of the Chase Manhattan Bank or any of its staff or of the Office of the Comptro...

We thank seminar participants at the OCC and the 1996 Chicago Fed Bank Structure Conference for their comments. We also thank Rene Stulz for his suggestions. The views expressed herein are those of the authors and do not necessarily represent the views of the Office of the Comptroller of the Currency or members of its staff. Address correspondence to Barry Schachter, mail stop 6-8, In this pape...

Current practice largely follows restrictive approaches to market risk measurement, such as historical simulation or RiskMetrics. In contrast, we propose flexible methods that exploit recent developments in financial econometrics and are likely to produce more accurate risk assessments, treating both portfoliolevel and asset-level analysis. Asset-level analysis is particularly challenging becau...

This research estimates portfolio VaR (Value-at-Risk) on G7 exchange rates using a GJR-GARCH-EVT (extreme value theory)-Copula based approach. We first extracts the filtered residuals from each return series via an asymmetric GJR-GARCH model, then constructs the semi-parametric empirical marginal cumulative distribution function (CDF) of each asset using a Gaussian kernel estimate for the inter...

The Value-at-Risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing do not provide satisfactory evaluation of possible losses. In this paper we review the recent advances in the VAR methodologies. The proposed improvements sti...

This paper proposes an improved procedure for stochastic volatility model estimation with an application in risk management. This procedure is composed of the following instrumental components: Fourier transform method for volatility estimation with a price correction scheme, and importance sampling for extremal event probability estimation with applications to estimate Value-at-Risk and condit...

This paper reports the construction and testing of a historical environmental simulation model, Búmodel (bú: Icelandic farm estate or enterprise). The model permits the investigation of historical grazing management under variable environmental conditions in Iceland through the prediction of spatial and temporal patterns of vegetation biomass and utilisation. Input parameters of the model are e...

We examine the influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities by comparing three GFDL climate models used for the CMIP5. The base model ESM2M is closely related to GFDL’s CMIP3 climate model CM2.1, and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal c...