matlab计算夏普比率代码-Commodity-Linked-Note:与商品挂钩的票据的定价和应用:金融衍生产品模型:项目报

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  • 2022-05-15 02:46
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matlab计算夏普比率代码商品挂钩票据的定价和应用 执行摘要 大多数投资者拥有股票和债券,但很少有人在其投资组合中持有商品。 大宗商品可能会从通胀中受益。 与商品相关的票据与拥有与商品相关的股票或共同基金(商品公司通常对冲他们对商品的敞口进行套期保值)有很大的不同。 大宗商品相关票据为投资者提供了商品或商品指数的表现敞口,并规定其在到期时偿还本金。 链接票据具有节税功能,可以使用应税的投资。 它们提高了投资的收益(取决于类型(结构化产品的明细/类型)。商品挂钩票据减少了投资中的波动性(或风险),能够在低收益或平稳的股票市场环境中获得正收益。该项目主要侧重于定价商品挂钩票据的方法,并通过应用带有MATLAB的蒙特卡罗模拟和最优投资组合分配的物理措施进行风险回报分析,为切实有效地代表客户进行投资策略分析,该项目还采用了计算速度,主题信念和多元化目的下为客户量身定制的交易,有助于更好地理解结构化衍生理论和定量分析方法应用于现实世界中,并使用商品挂钩票据,并且在一定程度上受本金保护注意到约翰·赫尔(John Hull)的教科书介绍了这一点。 介绍 结构化产品的创建是为了满足市场上可用的标准化
Commodity-Linked-Note-master.zip
  • Commodity-Linked-Note-master
  • Report-Data
  • PricingandApplicationofaCommodityLinkedNote1.docx.pdf
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  • Code
  • CLNRiskReturnAnalysisclient4Pmeasure.m
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  • table.csv
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  • commoditylinkednoteMCQmeasureClient4.m
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  • commoditylinkednoteMCQmeasureClient5.m
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  • CLNRiskReturnAnalysis.m
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  • CLNRiskReturnPartD.m
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  • commoditylinkednoteMC.m
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  • TermProjectMaster.m
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  • CLNRiskReturnAnalysisclient2Pmeasure.m
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  • commoditylinkednoteMCQmeasureClient2.m
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  • TermProjectMaster.asv
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  • CLNRiskReturnAnalysis (1).m
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  • CLNRiskReturnAnalysisclient1Pmeasure.m
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  • commoditylinkednoteMCQmeasureClient1.m
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  • Final report(2).docx
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  • CLNRiskReturnAnalysisclient5Pmeasure.m
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  • README.md
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内容介绍
## Pricing and Application of a Commodity-Linked Note **EXECUTIVE SUMMARY** Most investors own stocks and bonds, but very few hold commodity products in their investment portfolio. Commodities may benefit from ination. Commodity linked notes are very different from owning commodity-related stocks or mutual funds (commodity companies routinely hedge their exposure to commodities). Commodity-Linked Notes offer investors exposure to the performance of commodities or commodity indices and provide for the repayment of principal at maturity. Linked notes are tax-efficient and have access to fully taxable investments. They enhanced returns within an investment (depending on the type (Detail/of structured products). Commodity Linked notes reduced volatility (or risk) within an investment. Ability to earn a positive return in low-yield or flat equity market environments. This project focused mainly on the approaches to price commodity-linked notes and to conduct risk-return analysis given physical measures by applying Monte-Carlo Simulation with MATLAB and optimal portfolio allocation. To practically and effectively represent the investment strategy analysis for clients, the project takes also calculation speed, customized deals for clients under subject beliefs and diversification purposes into consideration. It helps to get better understanding in putting structured derivatives theory and quantitative analysis methodology into real world work and Commodity-linked notes are used and are in part motivated by principal protected notes that John Hull’s textbook introduces. **INTRODUCTION** Structured products create to meet specific needs that cannot be met from the standardized financial instruments available in the markets. Structured products can be used as an alternative to a direct investment, as part of the asset allocation process to reduce risk exposure of a portfolio, or to utilize the current market trend. In this project, we are going to develop and analyze principal protected Commodity Linked Notes. In principal protected note if you hold the notes until maturity, you will receive, at a minimum, your principal amount. In addition, you also may receive a Supplemental Redemption Amount. However, if you sell the notes prior to maturity, you may find that the market value of the notes is less than the principal amount of the notes. In this paper, we describe the methodology of our pricing models and risk analysis, and discuss the numerical results of our commodity linked model where our commodities are copper, aluminum and zinc. In risk analysis, we are using Monte-Carlo simulation and results from our risk-neutral Monte-Carlo pricing model to calculate the expected return and standard deviation that comprise the Sharpe ratio and returns on which we base our recommendations. We are using the control variate technique to improve the convergence speed of Monte-Carlo simulation We also include recommendation for a client who wants to buy the note for diversification purposes. Lastly, we proposed a business opportunity that combines USD-linked principle protected note and a market opportunity **Code** https://github.com/kwankhede/Commodity-Linked-Note/tree/master/Code **CONCLUSION** We learn about pricing models and risk analysis using Monte-Carlo simulation and optimal portfolio allocation. For recommendation for customized deals for clients under subject beliefs, we compare the mean returns and the Sharpe ratio to provide the best possible result. We successfully propose a recommendation for a client who wants to buy the note for diversification purposes. Lastly, we propose another business opportunity for the client.
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