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日在險價值

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出自 MBA智库百科(https://wiki.mbalib.com/)

(重定向自Daily Value at Risk)

日在險價值(Daily Value at Risk,DVaR)

什麼是日在險價值

  VaR(Value at Risk)按字面解釋就是“在險價值”,其含義指:在市場正常波動下,某一金融資產或證券組合的最大可能損失。更為確切的是指,在一定概率水平(置信度)下,某一金融資產或證券組合價值在未來特定時期內的最大可能損失。

  日在險價值(DVaR)採用歷史模擬法,利用兩年的歷史數據進行計算,同時利用返回檢驗(Back-testing)方法進行校驗。而年在險收益(Annual Earnings at Risk,AEaR)主要度量年收益對市場利率變動的敏感性,置信區間為99%,時間跨度為一年,主要用來度量結構性利率風險和結構資產管理風險。


  Daily Value at Risk is a financial services firm's estimate of the volatility it expects of its investments in the capital markets. Specifically, it is the most money the firm thinks it will lose in a single day at a 99% confidence level. Stated otherwise, excluding the very worst 1% of days, what's the most money a firm expects to lose in a single day? Value at risk is a useful relative measure of how aggressively a company is investing its own assets. Larger value at risk indicates a company has more to lose - but in all likelihood, more to gain as well.

  While companies will sometimes lose more money in a single day than their "daily value at risk", this should occur infrequently if the company is modeling its risk correctly. If the value at risk is calculated at a 99% confidence interval, losing more money than the daily value at risk should occur around 1 in 100 days, or about 3 or 4 days out of the year. However, firms calculate daily value at risk by modeling out past market behavior. Assumptions can vary between firms and flawed assumptions can lead to flawed results. Additionally, if markets begin behaving in ways they haven't behaved in the past, the historical assumptions underlying Value at Risk models may no longer apply.

  Although the industry standard is to calculate average daily value at risk at a 99% confidence level, banks can calculate this number at difference confident intervals - for example, at a 95% confidence interval, which would result in a smaller value at risk - but less confidence in whether this decline will be exceeded on any given day. It is also possible to calculate Value at Risk over larger timeframes, such as weekly or monthly.

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