12-17, 2022

Business Assignment代写范例-投资组合理论概述。本文是一篇留学生商业管理方向assignment写作参考，主要内容是讲述“投资组合”一词可定义为：；决定个人未来前景的所有决定”。投资组合可以包括许多类型的资产，如厂房、房地产、房地产和金融资产。投资组合理论提出了理性和谨慎的投资者应该如何利用其尽职调查使投资多样化以优化投资组合，以及与风险较小的资产相比，风险资产应该如何定价。几十年来，人们一直在投资不同的资产类别，但他们意识到风险的重要性及其负面影响，如果不加以有效处理。每个投资者都有自己的风险承受能力，投资者的风险承受力取决于其承受能力。投资组合理论是随着时间的推移而产生的，目的是有效地衡量风险，以及如何通过资产多样化来降低风险。下面就请参考这篇assignment写作范文。

**Introduction 引言**

The word “Portfolio” can be defined as; the totality of decisions determining an individual’s future prospects” (Sharpe, 1970). Portfolio can consist of many types of assets such as plant, property, real and financial assets (P.A Bowen, 1984). Portfolio theories propose how rational and prudent investors should use their due diligence to diversify their investments to optimize their portfolios, and how a risky asset should be priced as compared to less risky asset. People have been investing in the different assets class since decades but then they realize the importance of risk and its negative implications, if not treated effectively. Every investor has his own tolerance of risk and investor’s defines it in his ability of taking it. The portfolio theories have been derived over time in order to effectively measure the risk and how it can be reduced by diversify in their asset.

**Assignment 1: “The Legacy of Modern Portfolio Theory”“现代投资组合理论的遗产”**

This assignment covers the highlights of modern portfolio theory, describing how risk and its effects are measured and how planning and asset allocation can help you do something about it. Modern portfolio theory is the theoretical conflicting of conventional stock picking. It is being put forward by the economists, who try to understand the phenomena of the market as a whole, instead of business analysts, who look for individual investment opportunities. Investments are explained statistically, as how much investor expected long-term return rate and their expected short-term volatility. It measures how much expected return can deviate much worse than average an investment’s bad years are likely to be. The goal of the theory is to identify your adequate level of risk tolerance, and then to come up with a portfolio with the maximum expected return for that level of standard deviation (risk).

本文涵盖了现代投资组合理论的重点，描述了如何衡量风险及其影响，以及规划和资产配置如何帮助您解决这些问题。现代投资组合理论是传统股票选择的理论冲突。这是由经济学家提出的，他们试图理解整个市场的现象，而不是商业分析师，他们寻找个人投资机会。对投资进行统计解释，包括投资者预期的长期回报率和预期的短期波动率。它衡量的是预期回报的偏离程度，远比投资糟糕年份的平均水平差。该理论的目标是确定您的风险承受能力水平，然后针对该标准差（风险）水平提出具有最大预期回报的投资组合。

The portfolio it assumes that the investment universe consists only of two market securities, the risk free asset and risky assets. But the actual investment universe is much broader than that being put forward. The optimal level of investment is to invest on efficient frontier but doing this would mean to calculate the millions of covariance among the securities. This calculation could make the life of analyst as difficult as one could have ever imagined. To think practically, it’s better to put portfolio theory to work means investing in a limited number of index securities rather than a huge number of individual stocks and bonds. Index investing is the point the where portfolio theory starts to rely on the efficient market hypothesis. When you buy an index based portfolio strategy you’re allocating your money the same way the whole market is – which is a high-quality thing if you believe the market has a plan and it is efficient. This is why portfolio theory is one of the branches of economics rather than finance: instead of only studying financial statements and different financial ratios, you study the aggregate behavior of investors, some of whom seemingly have studied financial statements so that market valuations will reflect their due diligence and prudence.

它假设投资领域仅由两种市场证券组成，即无风险资产和风险资产。但实际的投资范围比提出的要广得多。最佳投资水平是投资于有效前沿，但这样做意味着计算证券之间的数百万协方差。这种计算可能会使分析师的生活变得像人们想象的那样困难。从实际情况来看，将投资组合理论付诸实施意味着投资于数量有限的指数证券，而不是大量的股票和债券。指数投资是投资组合理论开始依赖于有效市场假说的一点。当你购买基于指数的投资组合策略时，你的资金分配方式与整个市场相同——如果你相信市场有计划且效率高，那么这是一件高质量的事情。这就是为什么投资组合理论是经济学而不是金融学的分支之一：你研究的不是财务报表和不同的财务比率，而是投资者的总体行为，其中一些人似乎研究过财务报表，以便市场估值反映出他们的尽职调查和谨慎。

**Assignment 2: “Theory of portfolio and risk based on incremental entropy”“基于增量熵的投资组合和风险理论”**

The assignment has used incremental entropy to optimize the portfolios. This novel portfolio theory has been based on incremental entropy that carries on some facet of Markowitz’s (1959, 1991) theory, but it highlights that the incremental speed of capital is a more objective criterion for assessing portfolios. The performance of the portfolio just cannot be justified with the returns because we have to keep in mind the risk of achieving those returns. Given the probability forecasts of returns, we can obtain the best possible investment ratio. Combining the new portfolio theory and the general theory of information, we can approach a meaning-explicit measure, which represents the increment of capital-increasing speed after information is provided. The assignment has used example to make it more clear that as we try to become rich within days there involve high risk of even losing those money which we at-least own at present. The ineffective investment is like a coin toss either you have all the money in your pocket or you end having nothing in your pocket. The same being very risk averse would not help you become rich. You there has to be a balance in selecting the portfolio and this assignment explain the optimal investment ratio. (pg 1)

本文使用了增量熵来优化投资组合。这一新颖的投资组合理论以增量熵为基础，它继承了Markowitz理论的某些方面，但它强调资本的增量速度是评估投资组合的更客观的标准。投资组合的表现不能用回报来证明，因为我们必须牢记实现这些回报的风险。给定回报的概率预测，我们可以获得最佳可能的投资比率。结合新的投资组合理论和信息的一般理论，我们可以找到一个意义明确的度量，它表示信息提供后资本增长速度的增量。这篇文章用了一个例子来更清楚地说明，当我们试图在几天内变得富有的时候，我们甚至有很高的风险失去那些我们目前至少拥有的钱。无效的投资就像掷硬币，要么你口袋里有钱，要么你兜里一无所有。同样，非常厌恶风险也无助于你致富。你必须在选择投资组合时保持平衡，本文将解释最佳投资比例。

Markowitz explains us that an efficient portfolio is either a portfolio that offers the maximum expected return for a given level of risk, or one with the minimum level of risk for a given expected return. There is no objective criterion to define the maximum effectiveness of a portfolio given the expected return and risk level and different expects have different view about it. The Markowitz’s efficient portfolio tells us about the indifference curve of the investor and about the market portfolio. It is not the portfolio which we need for the fastest increment of capital. So, this assignment has derived a new mathematical model.

Markowitz向我们解释说，有效的投资组合要么是在给定风险水平下提供最大预期回报的投资组合，要么是在特定预期回报下具有最小风险水平的投资组合。考虑到预期回报和风险水平，没有客观标准来定义投资组合的最大有效性，不同的预期对此有不同的看法。马科维茨的有效投资组合告诉我们投资者的无差异曲线和市场投资组合。这不是我们需要的最快资本增长的投资组合。因此，本文导出了一个新的数学模型。

The model explains that when gain and loss are have equal chance of occurring, if the loss is up to 100 percent, one should not risk more than 50 percent of fund no matter how lofty the possible gain might be. This conclusion has a great importance and significant for risky investments, such as futures, options, etc. Most of the new investors of future markets lose all of their money very fast because the investment ratios are not well controlled and generally too large. we can obtain the optimal ratios of investments in different securities or assets when probability forecasts of returns are given.

该模型解释说，当收益和损失发生的机会相等时，如果损失达到100%，则无论可能的收益有多高，都不应承担超过50%的基金风险。这一结论对风险投资（如期货、期权等）具有重要意义。大多数期货市场的新投资者很快就失去了所有的资金，因为投资比率没有得到很好的控制，而且通常太大。当给出收益的概率预测时，我们可以获得不同证券或资产的最优投资比例。

Comparison with Markowitz’s theory 与马科维茨理论的比较

The new theory supports Markowitz’s conclusions that investment risk can be reduced by effective portfolio, but there are some obvious differences: The new theory uses geometric mean return as the objective criterion for optimizing portfolio and gives some formulas for optimizing investment ratios; and . The new theory makes use of extent and possibility of gain and loss rather than expectation of return and standard deviation (risk) of the return to explain investment value.

新理论支持Markowitz的结论，即有效投资组合可以降低投资风险，但有一些明显的区别：新理论使用几何平均收益作为优化投资组合的客观标准，并给出了一些优化投资比率的公式；新理论利用收益和损失的程度和可能性，而不是收益预期和收益标准差（风险）来解释投资价值。

Assignment 3: “On the competitive theory and practice of portfolio selection”“关于投资组合选择的竞争理论和实践”

To select an optimal level of portfolio has always been a basic and fundamental problem in the field of computation finance. There are lots of securities are available including the cash and the basic online problem is to agree on a portfolio for the ith trading period based on the series of price for the scheduled i-1 trading period. There has been increasing interest but also mounting uncertainty relating to the value of competitive theory of online portfolio selection algorithms. Competitive analysis is based on the worst and most unexpected case scenarios and viewpoint; such a point of view is conflicting with the most widely used analysis and theories being adopted by the investors based on the statistical models and assumptions. Surprisingly in some of the initial experiments result shows that some algorithms which have enjoyed a highly regarded repute seems to outperform the historical sequence of data when seen in relation to competitive worst case scenarios. The emerging competitive theory and the algorithms are directly related to the studies in information theory and computational learning theory, in fact some of the algorithms have been the broken new ground and set new standards within the information and computational theory learning based communities. The one of the primary goal and objective of this paper is understand the extent to which competitive portfolio algorithms are in reality learning and are they really contributing to the welfare of the investor. In order to find out so they have used set of different strategies this can be adapted to data sequence. This is being presented in a mixture of both strong theoretical and experimental results. It has also been compared with the performance of existing and new algorithms and respects to standard series of the historical sequence data and it also present the experiments from other three data sequence. It is being concluded that there is huge potential for selecting portfolio through algorithms that are being derived from competitive force and as well as derived from the statistical properties of data.

选择最优投资组合水平一直是计算金融领域的一个基本问题。有很多证券可用，包括现金，基本的在线问题是根据计划的i-1交易期的系列价格，就第i个交易期的投资组合达成一致。人们对在线投资组合选择算法的竞争理论的价值越来越感兴趣，但也越来越不确定。竞争分析基于最坏和最意想不到的案例场景和观点；这种观点与投资者基于统计模型和假设所采用的最广泛的分析和理论相冲突。令人惊讶的是，在一些最初的实验中，结果显示，当与竞争性最坏情况场景相关时，一些享有极高声誉的算法似乎优于历史数据序列。新兴的竞争理论和算法与信息理论和计算学习理论的研究直接相关，事实上，其中一些算法已经在基于信息和计算理论学习的社区中开辟了新的领域并制定了新的标准。本文的主要目标之一是了解竞争性投资组合算法在现实学习中的应用程度，以及它们是否真正有助于投资者的福利。为了找出原因，他们使用了一组不同的策略，这可以根据数据序列进行调整。这是一个强有力的理论和实验结果的混合物。它还与现有和新算法的性能进行了比较，并与标准系列的历史序列数据进行了比较。人们得出的结论是，通过从竞争力以及从数据的统计特性中得出的算法来选择投资组合具有巨大的潜力。

**Assignment 4: “International property Portfolio Strategies”“国际房地产投资组合策略”**

The assignment talks about the investment decisions regarding real estate, and try to put in the Markowitz mean variance formula to analyze the real estate market. They are not confined only to local real estate diversification but they are also including international diversification. Markowitz mean variance continuum and graph is useful in analyzing the efficient securities, and they help in the selection of an optimal portfolio on envelope curve taking into account the risk preferences of an investor. But when analysts try to incorporate real estate market to the Markowitz theory the major problems regarding liquidity, heterogeneity, indivisibility and information are faced by them which restrict them from further optimal analysis.

本文讨论了房地产投资决策，并试图运用Markowitz均值方差公式对房地产市场进行分析。它们不仅限于本地房地产多元化，还包括国际多元化。Markowitz均值-方差连续体和图表在分析有效证券时非常有用，它们有助于在考虑投资者风险偏好的情况下选择包络曲线上的最优投资组合。但是，当分析师试图将房地产市场纳入Markowitz理论时，他们面临的主要问题是流动性、异质性、不可分割性和信息，这些问题限制了他们进行进一步的优化分析。

Many investors have tried to support the theory to make a portfolio by considering property as asset like equity and bond investments; although there are a lot of differences among the characteristics of assets discussed above, but one can diversify its portfolio by investing in real assets, analysts argue. The discussion was dominated by the concept of international diversification of assets including real estate. To support the analysis in UK the (Sweeney , 1988-1989) work in cited most of the times, he came up with the famous model of real estate to come up with efficient diversification strategy, he used rental value of for different countries and came up with the model of risk return theory; after that a lot of analysts including: [Baum and Schofield (1991), Brühl and Lizieri (1994), Gordon (1991), Hartzell et al. (1993), Johnson (1993), Sweeney (1993), Vo(1993) and Wurtzebach (1990)], have come up with analysis to support international diversification; but the result was somehow was not justifying the inculcation of real estate to portfolio theory, because those assets were not correlated at all when inspected for the risk return behavior during last decade or so. This can be attributed to the failure of mean variance model to produce results, the main problems facing would be regarding data collection, technicalities, omitted categories, and ex post analysis.

许多投资者试图通过将房地产视为资产（如股票和债券投资）来支持投资组合的理论；分析人士认为，尽管上述资产的特征有很多不同，但通过投资实物资产，可以实现投资组合的多样化。讨论主要是包括房地产在内的资产的国际多样化概念。为了支持英国的分析，的工作在大多数时候被引用，他提出了著名的房地产模型，以提出有效的多元化策略，他使用了不同国家的租金价值，并提出了风险回报理论模型；之后，许多分析师，包括：[Baum和Schofield，Brühl和Lizieri，Gordon、Hartzell等人，Johnson、Sweeney和Vo以及Wurtzebach，都提出了支持国际多元化的分析；但其结果不知何故并不能证明将房地产引入投资组合理论是合理的，因为在过去十年左右的风险回报行为中，这些资产根本不相关。这可归因于均值-方差模型未能产生结果，面临的主要问题是数据收集、技术性、遗漏类别和事后分析。

This is almost irrational and impossible to find the most efficient way to diversify a portfolio by including real asset as a separate asset, because of area problems, different locality, pricing conditions, economic conditions, liquidity differences, and data collection problems. As real estate market is highly uncorrelated even within the industry so the data sets are very difficult to find for analysis because of lack of empirical data on this market.

由于地区问题、不同地区、定价条件、经济条件、流动性差异和数据收集问题，这几乎是不合理的，也不可能找到通过将真实资产作为单独资产来实现投资组合多样化的最有效方法。由于房地产市场即使在行业内也高度不相关，因此由于缺乏该市场的经验数据，很难找到数据集进行分析。

**Assignment 5: “Different risk measures: different portfolio compositions?”“不同的风险度量：不同的投资组合组成？”**

Choosing the suitable portfolio of assets in which to invest is an essential component of fund management. A large percentage of portfolio selection decisions were based on a qualitative basis, however quantitative approaches to selection are increasingly being employed. Markowitz (1952) established a quantitative framework for asset selection into a portfolio that is now well known. The measure of risk used in portfolio optimization models is the variance. Variance calculates how much deviation could be expected from the set of portfolio. The alternative methods of risk have their own theoretical and practical advantages and it is atypical that they are not used widely by investors. One of the reason may be because of the difficulty and complexity of understanding such models and then practically implementing those models and to decide in which measure of risk is best and gives the most realistic and useful results. It is important to identify the common risk measure and without doing so any attempt to measure the risk would be useless exercise. In order to cope with this, another approach is considered that is to comparing the portfolio holdings produced by different risk measures, rather than the traditional risk return trade-off. It is than being observed that whether the risk measures used produce asset allocations that are essentially the same or very different. In order to probe this concern this study tested the proposition that different measures of risk produce minimum risk portfolios that are essentially the same in terms of asset allocations, using monthly data over the period January 1987 to December 2002. The results show that the optimal portfolio compositions formed by different risk measures vary quite noticeably from measure to measure. These finding are very useful and have a practical implication for the investors because it recommend that the choice of risk model depends entirely on the individual’s attitude to risk rather than any theoretical or practical advantages of one model over another. It has been concluded that different investors have they indifference curve different from other and some of them like to take more risk as compare to other who are happy at earning low but safe returns.

选择合适的投资资产组合是基金管理的重要组成部分。很大比例的投资组合选择决策是基于定性的，但越来越多地采用定量的选择方法。Markowitz建立了一个量化框架，用于将资产选择纳入现在众所周知的投资组合。投资组合优化模型中使用的风险度量是方差。方差计算投资组合的预期偏差。替代风险方法有其自身的理论和实践优势，投资者不广泛使用这种方法是不典型的。其中一个原因可能是因为理解这些模型，然后实际实施这些模型，并决定哪种风险度量是最好的，并给出最现实和有用的结果，这是困难和复杂的。确定共同风险度量是很重要的，如果不这样做，任何衡量风险的尝试都是徒劳的。为了应对这一问题，考虑了另一种方法，即比较不同风险度量产生的投资组合持有量，而不是传统的风险收益权衡。人们还观察到，所使用的风险度量是否产生了本质上相同或非常不同的资产配置。为了探讨这一问题，本研究使用1987年1月至2002年12月期间的月度数据，检验了不同风险度量产生的最小风险投资组合在资产配置方面基本相同的命题。结果表明，不同风险度量形成的最优投资组合在不同度量之间差异很大。这些发现非常有用，对投资者具有实际意义，因为它建议风险模型的选择完全取决于个人对风险的态度，而不是一种模型相对于另一种模型的任何理论或实际优势。已经得出的结论是，不同的投资者有着不同于其他投资者的冷漠曲线，其中一些人喜欢承担更多的风险，而其他人则乐于获得低但安全的回报。

**Conclusion 结论**

It is being concluded that risk is more of a subjective term and different analysts and investor measures and perceive it in their own way. In today’s word not even a single person can underestimate the importance of risk in selecting a security and emphasized is been given to diversification through proper portfolio selection process and everyone tries to optimize their returns given a certain level of risk. In order to do so they are using different statistical measures those have been derived over time to calculate risk. So selection of such method is limited to the understanding of a certain method to a certain investor and their effectiveness of results as compare to other methods.

Assignment得出的结论是，风险更多的是一个主观术语，不同的分析师和投资者以自己的方式衡量和感知风险。用今天的话来说，即使是一个人也不能低估风险在选择证券时的重要性，并强调通过适当的投资组合选择过程实现多样化，每个人都试图在一定的风险水平下优化自己的回报。为了做到这一点，他们使用了不同的统计指标来计算风险。因此，与其他方法相比，此类方法的选择仅限于特定投资者对特定方法的理解及其结果的有效性。本站提供各国各专业留学生assignment代写或指导服务，如有需要可咨询本平台。

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