Search results for "Value at risk"
showing 10 items of 27 documents
Comment on “A simple way to incorporate uncertainty and risk into forest harvest scheduling”
2017
In a recent research article, Robinson et al. (2016) described a method of estimating uncertainty of harvesting outcomes by analyzing the historical yield to the associated prediction for a large number of harvest operations. We agree with this analysis, and consider it a useful tool to integrate estimates of uncertainty into the optimization process. The authors attempt to manage the risk using two different methods, based on deterministic integer linear programming. The first method focused on maximizing the 10th quantile of the distribution of predicted volume subject to area constraint, while the second method focused on minimizing the variation of total quantity of volume harvested sub…
Guidelines for risk management in forest planning – what is risk and when is risk management useful?
2018
Managing forest resources occurs under various sources of uncertainty. Depending on the management problem, this uncertainty may have a substantial impact on the quality of the solution. As our knowledge on the sources and magnitude of uncertainty improves, integrating this knowledge into the development of management plans becomes increasingly useful, as additional information can improve the decision-making process. This adjustment requires a fundamental shift in how planning problems are viewed: instead of interpreting risk management as a technique needed only for addressing problems with natural hazards, risk management should be an integral part of most planning problems. Managing ri…
Data-Based Forest Management with Uncertainties and Multiple Objectives
2016
In this paper, we present an approach of employing multiobjective optimization to support decision making in forest management planning. The planning is based on data representing so-called stands, each consisting of homogeneous parts of the forest, and simulations of how the trees grow in the stands under different treatment options. Forest planning concerns future decisions to be made that include uncertainty. We employ as objective functions both the expected values of incomes and biodiversity as well as the value at risk for both of these objectives. In addition, we minimize the risk level for both the income value and the biodiversity value. There is a tradeoff between the expected val…
Integrating risk management tools for regional forest planning: an interactive multiobjective value-at-risk approach
2018
In this paper, we present an approach employing multiobjective optimization to support decision making in forest management planning under risk. The primary objectives are biodiversity and timber cash flow, evaluated from two perspectives: the expected value and the value-at-risk (VaR). In addition, the risk level for both the timber cash flow and biodiversity values are included as objectives. With our approach, we highlight the trade-off between the expected value and the VaR, as well as between the VaRs of the two objectives of interest. We employ an interactive method in which a decision maker iteratively provides preference information to find the most preferred management plan and le…
Exposure-Based Cash-Flow-At-Risk for Value-Creating Risk Management Under Macroeconomic Uncertainty
2010
A strategically minded CFO will realize that strategic corporate risk management is about finding the right balance between risk prevention and proactive value generation. Efficient risk and performance management requires adequate assessment of risk and risk exposures on the one hand and performance on the other. Properly designed, a risk measure should provide information on to what extend the firm's performance is at risk, what is causing that risk, the relative importance of non-value-adding and value-adding risk, and the possibilities to use risk management to reduce total risk. In this chapter, we present an approach – exposure-based cash-flow-at-risk – to calculating a firm's downsid…
Incorporating stand level risk management options into forest decision support systems
2018
Aim of study: To examine methods of incorporating risk and uncertainty to stand level forest decisions. Area of study: A case study examines a small forest holding from Jonkoping, Sweden. Material and methods: We incorporate empirically estimated uncertainty into the simulation through a Monte Carlo approach when simulating the forest stands for the next 100 years. For the iterations of the Monte Carlo approach, errors were incorporated into the input data which was simulated according to the Heureka decision support system. Both the Value at Risk and the Conditional Value at Risk of the net present value are evaluated for each simulated stand. Main results: Visual representation of the er…
On the Consistent Use of VaR in Portfolio Performance Evaluation: A Cautionary Note
2010
The portfolio performance measures based on the Value at Risk (VaR) concept have gained widespread popularity and are often used in empirical studies. In the majority of empirical studies, however, a VaR-based performance measure is inconsistently used. In this article, Zakamouline emphasizes how to consistently use VaR in portfolio performance evaluation. He also elaborates on a simple framework that allows the derivation of a general formula for a portfolio performance measure that is not limited to the use of VaR-based reward and risk measures, but is valid for all reward and risk measures that satisfy a few plausible properties.
An Empirical Investigation of Heavy Tails in Emerging Markets and Robust Estimation of the Pareto Tail Index
2021
In this work we analyze and compare the performances of VaR-based estimatorswith respect to three different classes of distributions, i.e., Gaussian, Stable and Pareto, and to different emerging markets, i.e., Egypt, Qatar and Mexico. This is motivated by the evidence that there are points of distinction between emerging and developed markets mainly relating to the speed and reliability of information available to investors.We propose a computational Threshold Accepting-VaR based algorithm (TAVaR) for optimally estimating the Pareto tail index. A Monte Carlo bias estimation analysis is also carried out by comparing our proposed methodology with the Hill estimator and a variant of it.
Non-Gaussian Distribution for Var Calculation: an Assessment for the Italian Market
2001
Abstract In this paper we compare different approaches to computing VaR (Value-at-Risk) for heavy tailed return series. Using data from the Italian market, we show that almost all the return series present statistically significant skewness and kurtosis. We implement (i) the stable models proposed by Rachev et al . (2000), (ii) an alternative to the Gaussian distributions based on a Generalized Error Distribution and (iii) a non-parametric model proposed by Li (1999). All the models are then submitted to backtest on out-of-sample data in order to assess their forecasting power. We observe that when the percentiles are low, all the models tested produce results that are dominant compared to …
The impact of systemic and illiquidity risk on financing with risky collateral
2015
Abstract Repurchase agreements (repos) are one of the most important sources of funding liquidity for many financial investors and intermediaries. In a repo, some assets are given by a borrower as collateral in exchange of funding. The capital given to the borrower is the market value of the collateral, reduced by an amount termed as haircut (or margin). The haircut protects the capital lender from loss of value of the collateral contingent on the borrower׳s default. For this reason, the haircut is typically calculated with a simple Value at Risk estimation of the collateral for the purpose of preventing the risk associated to volatility. However, other risk factors should be included in th…