现代投资理论的发展历程现代资产组合投资理论 1 的源头最早可以追溯到1952 年,在那一年哈里.马科维茨发表了一篇名为《资产组合选择》的论文。
在这篇论文中，马科维茨第一次阐明了如何寻找有效投资组合边界，在这—边界上的任一资产组合都有着相对于它们所面临的风险而言最大的预期回报率。
但是寻找有效边界这一技术从计算的角度来看是极为复杂的，尤其在当时的计算机技术水平还不发达的情况下更是如此。
不过计算机领域中的近期发展已经使我们可以有机会很方便的在办公桌前就可以应用这一技术。
在以往的日子里，马科维茨的资产组合最优化技术主要还是运用于资产的配置决策当中，投资者利用它来决定投资在诸如股票、债券和房地产等一些基本资产类别中的比重。
在几种资产中进行选择并达到最优化所需要的计算能力仅仅是对千种资产进行最优组合所需计算的冰山一角，幸而我们目前已经有了这种计算能力。
与此同时，现在也有许多专业的数据供应者，他们将提供大量的用子解决最优化配置问题所必需的数据,这也是极为重要的一个发展。
我们正在迈入一个资产组合最优化技术成为构建股票组合的基石的时代。
在资产组合技术广泛应用到现实世界之前，三位经济学家各自独立的开始研究下面这个问题:假设每个人都运用资产组合技术来进行投资并都投资在组合的有效边界之上，这将对证券定价有什么样的影响，为了回答这一问题，Sharpe (1964)、Lintner (1965)和 Mossin (1966)建立了资本资产定价模型(CAPM) 这一模型在之后15年时间里一直是金融领域中最为重要的模型。
在成为金融学入门教材的重要内容之后，这一模型在现实中被广泛运用于各个领域，包栝衡量资产组合的业绩、对证券进行估价、进行资本预算决策以及应用T•管理公共事业等。
然而在1976年，这一模型受到了Richard Ro 1(1977-1978)的质疑。
他认为这一模型应该被抛弃，原因就在于它无法实证地证明它在实际预测上的准确性。
这一有争议的问题至今仍然是各方面讨论的热点。
与此同时，Steve Ross (1976)又建立了一个与资本资产定价模型相抗衡的定价模型。
这一理论模型被称为套利定价模型3。
其主要观点是任何资产的预期收益应与其风险密切相关，最终达到没有任何-个投资者可以通过套利来获取无风险收益的状态。
这一理论并不需要非常强的理论假设，而且Roll和Ross (1984)认为至少在原理上这一理论是可以被验证的。
就目前而言，尽管资本资产定价模型受到严重的质疑，但它依然是现实中应用最为广泛的模型。
但不可忽视的是套利定价模型也在不断的扩大自己的影响。
在金融领域中，如何对以证券为标的的期权合约进行定价一直困扰着众多研究者。
这一难题的解决依赖于1973年Fisher Black 和 Myron Scholes发表的研究成果。
他们认为人们可以同时在期权市场和其标的股票电场反向操作来建立无风险的对冲头寸。
建立对冲头寸会有一些资金成本，但对冲头寸却是无风险的。
因而期权就可以在保证对冲投资头寸获取无风险的回报率这一前提下根据股票的价格来进行定价。
他们据此建立了Black-Schoies期权定价模型4。
Black-Scholes模型在投资领域已经越来越流行。
在此之后期权受到研究上的广泛重视并且期权交易也日益增多。
由于期权交易是极为复杂的，交易商们需要更为精确的模型。
Black-Scholes模型尽管仍然是最为广泛应用的，但自1973年以来，许多新的替代的模型已经被开发出来。
这些更为精确的期权定价方法已经开始影响交易商的行为和期权交易所的期权价格。
尽管研究者们不断试图发现证券市场价格结构的本质,但市场价格结构的有效性依然受到质疑。
1965年Eugene Fama在商务周刊上发表他的博士论文。
在这篇文章中，他极具说服力的提出了一个令当时的研究者震惊的结论。
他认为每时每刻至少有成千上万的高智商的拥有大量信息的专业投资者在积极寻找被错误定价的证券，在这种不断寻找的过程中，这些专业人士不断进行交易进而影响价格。
因而在任意时点上看证券价格都将反映这些投资者的集体智慧和他们拥有的信息。
如果信息能够快速有效地被反映到证券价格中去的话，那么通过任何形式的证券分析进行投资试图超越市场获得更髙收益都是不可能的。
这一有争议的论点被称之为有效市场假设5,至今它仍是悬而未决的一个问题。
这场争论引发了大量的实证性的研究来判断证券价格中所反映的信息的数量和质量。
最初大部分的研究结果都明确的支持市场是髙度有效的。
这些研究的成果在现实中也产生了很大的影响，许多新成立的投资基金都不再以超越市场为目标。
它们奉行的理念是试图超越市场是浪费时间与金钱，相反它们仅仅试图达到与市场有相同的表现，获得市场平均的收益水平。
在过去几年中许多论文开始严厉的批评一些主流的现代金融理论在实际预测中的有效性。
在他们的研究中，以往所强调的对证券定价极为重要的风险标准对于市场而言是并不显著的，股票市场也并不像我们依据二十年来公布的数据所认为的那样有效。
因而，关于通过市场对证券进行定价的本质的观点正在不断发生变化。
然而在评价这些观点的实际价值的时候，将工具和理论区分开来是极为重要的。
一种工具帮助你实现一个目标，例如利用马科维茨的资产组合投资技术可以在保持预期收益率的同时降低风险。
一种金融理论则用来预测或解释我们在金融市场上所看到的各种行为。
例如，我们必须依据一种理论比如说CAPM来解释如果人们都使用马科维茨的方法投资股票时如何给股票定价的问题。
同时我们知道资产组合投资技术并没有被足够多的人使用,更谈不上被全部的投资者使用了。
而这也许就是CAPM无法充分有效应用的主要原因。
然而正如我们所看到的，尽管资产组合投资技术没有被充分使用，它在控制股票投资组合风险上仍然有很大的作用。
因此理论预测的欠缺并不意味着它所依据的工具或技术有缺陷。
在实际中，我们必须重视以下几个方面的事实:a)这种技术是极为有用的I；b)这种技术一直被低估，没有充分使用；c)仅有一小部分投资者使用它导致为投资界所接受的CAPM理论模型在应用时存在缺陷。
只有了解了这些事实，你才能比那些仍无视于此的人们更有优势，更有可能获取更髙的收益。
注释：1. Portfolio theory资产组合投资理论：马科维茨是当代投资组合理论的创始人。
该理论指出，组合证券的风险与收益不仅取决于组合证券中单个证券的风险与收益，还取决于不同证券之间的相关性.2. Capital asset pricing model (CAPM)资本资产定价模由成廉S普和约翰林特在20世纪60年代同时并独立提出，该模型掲示了如果每一投资者都根据马科维茨的投资粗合理论来投资，证券将如何定价，资本资产定价模型讨论的基本内容就是证券的预期收益.R风险和证券价值之间的关系。
3. Arbitrage pricing丨beory套利定价模型：最早由耶鲁大学斯蒂芬_罗斯于1976年提出，该理论遵循资本资产定价模型（CAPM)的居设，即投资者获得的回报是承受系统性风险的补偿.但APT理论认为证券的预期收益并不只对市场组合的风险变化做出反应，而受经济中许多其他因泰的影响，如国际形势，价格指数、政府的金融财政政策等。
因此在为资产定价时必须先找出这些因素以及证券收益对这些因素变动的敏感性。
4. Black-Scholes期权定价模型：这一模型是由布莱克和斯科尔斯在1973年提出的，斯科尔斯也因此获得1997年的诺贝尔经济学奖.这一模型使我们能够依据股票的波动性、股票价格、期权执行价格、期权到期日以R市场无风险套利来计算期扠的精确价值。
5. Efficienl markeUEMH>有效市场假设：法马教授定义了强效率市场、半效率市场和弱效串市场，强效串市场的含义是非预期收益与任何公开的或内部的信息都不相关.半效率市场的含义是非预期收益与任何公开信息不相关。
弱效率市场的含义是现在的非预期收益与以前的非預期收益不相关，知道以前的数据对预测未来的收益亳无帮助。
The Development of Modern Investment Theory The beginnings of modem portfolio theory1 date back to 1952 when Harry Markowitz(1952) published a paper entitled “Portfolio Selection”. In it, he showed how to create a frontier of investment portfolios, such that each of them had the greatest possible expected rate of return, given their level of risk. The technique was, computationally, very complex, especially given the technology of the time. However, recent advances in computer technology have given us the opportunity to employ this technology conveniently at our desktops. In the past, Maiicowitz portfolio optimization was employed, for the most part, in the asset allocation decision. Here the investor decides the relative amounts to invest in a few basic asset classes such as stock, bonds, and real estate. The computing power needed to optimize over a few asset classes is only a tiny traction of that required to optimize over thousands of stocks. Nevertheless, we now have that power. Importantly as well, there are many vendors who will make available to you the quantitative data required for solving the optimization problem. We are entering an era when portfolio optimization comes into its own as an important element in the construction of stock portfolios.Prior to the dissemination of portfolio theory into the real word, three individuals simultaneously and independently asked themselves the following question: Suppose everyone managed his or her investments using portfolio theory and invested in the portfolios cm the frontier. How would that affect the pricing of securities? In answering this question, Sharpe (1964), Limner (1965)，and Mossin (1966) developed what became known as the capital asset pricing model (CAPM)2. This model reigned as the premier model in the field of finance for nearly 15 years. In addition to finding its way into the elementary textbooks in finance, it became widely used in the real world to measure portfolio performance, value securities, make capital budgeting decisions, and even regulate public utilities. In 1976，however, the model was called into question by Richard Roll (1977，1978), who argued that the model should be discarded because it was impossible empirically to verify its single economic prediction. This controversial issue is still the subject of heated debate today. At the same time, an alternative to the capital asset pricing model was being developed by Steve Ross (1976). This model was called the arbitrage pricing theory3.This theory argued that expected return must be related to risk in such a way that no single investor could create unlimited wealth through arbitrage. The theory was less demanding in terms of its assumptions, and both Roll and Ross (1984) argue that it is testable, at least in principle. At this point, although it is being seriously called into question, the capital asset pricing model is still widely used in the real world The arbitrage pricing theory, however, seems to be gaining momentum.The question of how to price option contracts to buy and sell securities long puzzled researchers in finance until a paper by Fisher Black and Myron Scholes was published in 1973. They argued that you could create a riskless hedged position with an option by taking a position in both the option and the stock it is written on. It will cost you money to set up the hedge, but since it is riskless, the option must be priced relative to the stock so that you get the riskless rate of return on your hedgedinvestment. They developed a model that would price the option so as to produce this result. The Black-Scholes model4 has become extremely popular in the investment community. Options have literally exploded in terms of variety and volume of trading. Option traders are extremely sophisticated. The Black-Scholes model remains the most widely used, but since 1973 many alternative models have been developed. Some of these more so-sophisticate approaches to valuing options are beginning to affect the behavior of traders and options prices on the floors of the options exchanges.Even as researchers were attempting to determine the nature of the pricing structure in the securities maiicets, the issue of how efficient the market was in pricing to its structure was called into question. In 1965, the Ph.D. dissertation of Eugene Fama was Business. In it, he persuasively made a startling argument. There are literally thousands of intelligent, well-informed professional investors actively searching for mispriced securities. Since upon finding them, these professionals trade and thereby affect prices, it may be that security prices at any given time reflect the collective wisdom of those who invest in them. If information rapidly and efficiently becomes impounded into the prices of securities, then it becomes impossible to “beat”：the market through any form of security analysis. This controversial issue became known as the efficient market5 controversy, and it still remains to be settled to this day. The debate spawned an extremely large number of empirical studies directed at determining the quantity and quality of information reflected in security prices. Initially, the wight of the evidence clearly favored the view that the market was highly efficient. The results of these studies had their effect in the real world. Investment funds were established that made no attempt to beat the market. Their philosophy was that this was a waste of time and money, and they would only attempt to match the market’s performance.In the past few years many papers have been published that seriously call into question the validity of the predictions of some of the major theories of modern finance. It now seems that the measures of risk predicted to be important in the pricing of securities are largely insignificant to the market. It also appears that the stock market is much less efficient than we would have thought based on the published evidence in the record two decades ago.Thus, our ideas concerning the nature of the relative pricing of securities by the market are undergoing change. However, in assessing the practical value of these ideas, it’s important to distinguish between a tool and a theory. A tool helps you accomplish an objective~say, lowering the risk of a stock portfolio, while maintaining its expected return, through the use of Markowitz portfolio optimization techniques. A financial theory predicts or explains behaviors we see in financial markets. For example, we might base a theory, like the CAPM, on how stocks would be priced if every investor used the Markowitz optimization tool to invest in stocks. Well, we know in to be the case that portfolio optimization is not even used by a significant minority, let alone all, investors. This may be the principal reason why the CAPM theory doesn't work very well. However, in spite of the fact that Investment and Finance .it is underutilized, the optimization tool remains very powerful in controllingrisk in stock portfolios. Thus, weakness in the predictions of a theory does not imply weakness in the tools or techniques upon which the theory is based. In fact, consider the following:(a)The tool is powerful,(b) it is, nevertheless, underappreciated and underutilized, and(c) it is used by only a small minority of investors, which creates weakness in a theory that is still embraced by the investment community.Knowing these facts gives you the opportunity to dominate those who, as yet, are unaware of these concepts.。