楼主: launal
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[其他] 新手请问用蒙特卡洛模拟法计算VAR用什么软件好 [推广有奖]

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楼主
launal 发表于 2005-11-12 11:50:00 |AI写论文

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小妹是一新手在此请问各位大侠:用蒙特卡洛模拟法计算VAR用什么软件好。谢谢
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关键词:蒙特卡洛模拟 蒙特卡洛 模拟法 蒙特卡 VaR 蒙特卡洛 软件

沙发
qcz 发表于 2005-11-12 12:24:00
水晶球

藤椅
hmis 发表于 2005-11-12 14:17:00
好!

板凳
z1 发表于 2005-11-12 16:42:00

请问水晶球哪里能得到?

报纸
jcx350 发表于 2006-12-18 18:28:00
s-plus

地板
sunny030015 发表于 2007-1-3 00:48:00
matlab

7
peaceatchina 发表于 2007-1-4 00:22:00

@risk, or Crystal Ball

8
peterf 在职认证  发表于 2007-3-10 17:53:00
Matlab
徘徊在统计学的大门之外

9
chunxu 发表于 2007-3-12 13:15:00
FinCAD

10
no3no4 发表于 2009-6-24 19:18:51
@RISK

Value at Risk (VAR)
Anybody who owns a portfolio of investments knows there is a great deal of uncertainty about the future worth of the portfolio. The concept of value at risk (VAR) has been used to help describe a portfolio's uncertainty. Simply stated, the value at risk of a portfolio at a future point in time is usually considered to be the fifth percentile of the loss in the portfolio's value at that point in time. In other words, there is considered to be only one chance in 20 that the portfolio's loss will exceed the VAR. To illustrate the idea, suppose a portfolio today is worth $100. We simulate the portfolio's value one year from now and find there is a 5% chance that the portfolio's value will be $80 or less. Then the portfolio's VAR is $20 or 20%. The following example shows how @RISK can be used to measure VAR. The example also demonstrates how buying puts can greatly reduce the risk in a stock. The two outputs represent the range of the percentage gain if we do not buy a put vs. the percentage gain if we do buy a put. The results illustrate there is a greater chance of a big loss if we do not buy the put, although the average return is slightly higher if we do not buy the put.
Example model: Var.xls

可以在下面的页面看到
http://www.palisade.com/industry/FinanceModels.asp#var

This example was taken from Chapter 45 of Financial Models using Simulation and Optimization by Wayne Winston, published by Palisade Corporation, where a detailed, step-by-step explanation can be found. It is also explained further in the @RISK User's Guide.

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