新西兰国际太平洋学院论文代写：风险值
新西兰国际太平洋学院论文代写：风险值
风险值（VAR）是一种统计技术，用于使企业能够在特定时间范围内衡量和量化企业内部或投资组合内的财务风险。风险管理者使用这种技术来有效地控制企业承担的风险水平。企业可以容易地吸收风险的水平由经理确保，以致可能没有预期的损失。
使用三种一般方法来获得有效的投资组合损失分配。时间框架，潜在损失的数额和损失金额的概率是模型考虑的三个变量。增量VAR用于测量在给定时间范围内整体考虑的投资组合的可能最坏情况（Benninga＆Wiener，33）。为了计算增量VAR，投资者需要了解投资组合的标准差及其回报率。除了有关资产的回报率以外，还需要纳入投资组合份额。
为了估计VAR，使用以下三种方法：
差异协方差（VCV），这种方法假设风险因素回报（联合）是正态分布的，投资组合价值变动与风险因素回报有线性依赖关系。
历史模拟，该技术假定未来资产回报的分配与过去遵循的分配相同。
蒙特卡罗模拟，该技术用于将来资产回报预期随机模拟。
新西兰国际太平洋学院论文代写：风险值
Value-At-Risk (VAR) is a statistical technique that is used to enable the firm to measure and quantify the financial risk within a firm or within an investment portfolio over a specific time frame. Risk manager uses this technique to effectively control the level of risk undertaken by the firm. The level up to which a firm can easily absorb risk is ensured by the manager so that there may not be a possibility of expected losses.
Three general approaches are used to obtain effective portfolio loss distribution. The time frame, the amount of potential loss and the probability of that amount of loss are three variables that are considered by the model. Incremental VAR is used to measure likely worst case scenario for the portfolio under consideration as a whole within a given time frame (Benninga & Wiener, 33). In order to calculate the incremental VAR the investor is required to have an idea about the standard deviation of portfolio and its rate of return. In addition to this rate of return of asset in question and portfolio share is also needed to be incorporated.
To estimate VAR three approaches as follows are used:
Variance-covariance (VCV), This approach assumes that risk factor returns are (jointly) normally distributed and there is linear dependence in the change in portfolio value and the risk factor returns involved.
The historical simulation, This technique assumes that the distribution followed by asset returns in the future will be same as the distribution they followed in the past.
Monte Carlo simulation, This technique is used when future asset returns are expected to be randomly simulated
