免费成人三级,欧美精品色综合,欧美xxxx综合视频,日本欧美电影在线观看

代寫MTH5510、代做Matlab程序語言

時間:2024-08-13  來源:  作者: 我要糾錯



MTH5510: QRM - Exercises Set 2
Due date: August 12, 2024;12:00pm;
Analysis the output of the Matlab code is mandatory. I am not interested just to the Matlab code.
Hand in stapled hardcopy at the beginning of the tutorial session
Note: You might want to use Matlab for this exercise; adequately report and comment on your
results (For a quick introduction to Matlab visit http://www.mathworks.com/access/helpdesk/
help/pdf_doc/matlab/getstart.pdf)
Exercise I: This question deals with a portfolio of five stocks. At time t, the values of the stocks
are S1,t = 100, S2,t = 50, S3,t = 25, S4,t = 75, and S5,t = 150. The portfolio consists of 1 share
of S1, 3 shares of S2, 5 shares of S3, 2 shares of S4, and 4 shares of S5. These risk factors are
logarithmic prices and the factor changes have mean zero and standard deviations 10?3, 2 · 10?3,
3 · 10?3, 1.5 · 10?3, and 2.5 · 10?3, respectively. The risk factors are independent.
1. Compute VaRα, VaR
mean
α , and ESα using Monte Carlo with 10,000 simulations. Do this for
α = {0.90, 0.91, . . . , 0.99}. Also use the following distributions for the risk factor changes:
 For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ ~ t(3, μ, σ) for appropriate values of μ and σ
 For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ ~ t(10, μ, σ) for appropriate values of μ and σ
For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ ~ t(50, μ, σ) for appropriate values of μ and σ
 For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ ~ N (μ, σ2)
Plot the results.
2. Comment on the following:
 The value of VaRα compared to VaRmeanα
 The value of VaRα and ESα as compared between the four distributions. Are the results
what you expected?
Exercise II: This question deals with delta hedged call option. The following are the Black-
Scholes parameters for a European call option at time t = 0:
T = 0.5
rt = 0.05
σt = 0.2
St = 100
K = 100.
1
The portfolio consists of long position on the call option, and the corresponding position in the
stock which makes the portfolio delta neutral. Let ? = 1day, Z1 = log(S), and Z2 = σ (r
will be considered in this problem). The risk factor changes are normally distributed with mean
zero. Their standard deviations over one day are 10?3 and 10?4 and their correlation is ?0.5.
(a) Compute V aRα, V aR
mean
α , and ESα for α = 0.95 and α = 0.99 using the following
methods:
 Monte Carlo full revaluation with 10,000 simulations
 Monte Carlo on the linearized loss with 10,000 simulations
 Variance-covariance method
Do not neglect the time derivative in any linearizion in this question.
Exercise III: Let L have the Student t distribution with ν degree of freedom. Derive the
formula
ESα(L) =
(
gν(t
?1
ν (α))
1? α
)(
ν + (t?1ν (α))2
ν ? 1
)



請加QQ:99515681  郵箱:99515681@qq.com   WX:codinghelp

標簽:

掃一掃在手機打開當前頁
  • 上一篇:代寫COMP4337、代做Python編程設計
  • 下一篇:代寫GA.2250、Python/Java程序語言代做
  • 無相關信息
    昆明生活資訊

    昆明圖文信息
    蝴蝶泉(4A)-大理旅游
    蝴蝶泉(4A)-大理旅游
    油炸竹蟲
    油炸竹蟲
    酸筍煮魚(雞)
    酸筍煮魚(雞)
    竹筒飯
    竹筒飯
    香茅草烤魚
    香茅草烤魚
    檸檬烤魚
    檸檬烤魚
    昆明西山國家級風景名勝區
    昆明西山國家級風景名勝區
    昆明旅游索道攻略
    昆明旅游索道攻略
  • 福建中專招生網 NBA直播 短信驗證碼平臺 WPS下載

    關于我們 | 打賞支持 | 廣告服務 | 聯系我們 | 網站地圖 | 免責聲明 | 幫助中心 | 友情鏈接 |

    Copyright © 2025 kmw.cc Inc. All Rights Reserved. 昆明網 版權所有
    ICP備06013414號-3 公安備 42010502001045

    主站蜘蛛池模板: 开阳县| 桓台县| 安达市| 克拉玛依市| 洛川县| 安泽县| 吉林省| 沿河| 泸溪县| 五峰| 泸西县| 邯郸市| 修文县| 高雄县| 满城县| 阳春市| 河西区| 长顺县| 隆德县| 罗山县| 东兴市| 清水县| 阜新| 资源县| 吉首市| 定州市| 无极县| 民乐县| 同德县| 攀枝花市| 宜阳县| 台中市| 长顺县| 江华| 阳江市| 汕头市| 日土县| 大连市| 福建省| 师宗县| 平昌县|