A key task in value investing is determining the “normal” earning power of a company in any given year.一個重要任務是確定價值投資“正常”的盈利能力的公司在任何一年。
People use a variety of methods to do this, the most famous being Benjamin Graham's average earnings from the company's previous 7-10 years of operation.人們用不同的方法來做到這一點，最著名的是本傑明格雷厄姆的平均收入從該公司以前的7-10年的運作。
Here's a technique I use to get a sense of a company's historical normal earning power while weighing the highest and lowest earning years a little less.這裡我使用的技術得到一個感覺是公司歷史正常的收益能力，而體重的最高和最低的年收入少。
The method is called the Program Evaluation and Review Technique (PERT) and is a project management tool invented by Booz Allen Hamilton and the US Navy to build the Polaris missile system in the late 1950s.這種方法被稱為計劃評審技術（PERT），是一個項目管理工具，發明了博思艾倫和美國海軍建立北極星導彈系統在50年代末。 It was designed to determine likely schedule outcomes for specific project tasks based on estimates of the most likely, optimistic, and pessimistic times for completion.它的目的是確定可能的結果具體安排項目任務的基礎上估計最有可能的，樂觀和悲觀的時間完成。 [1] [1]
Here's how it works.下面是它的工作原理。
Let's say you have earnings from operations per share for a company for a 10-year period.假設你有來自運營的盈利為每股公司的10年時間。
Instead of using a straight average, note the best year and the worst year.而不是使用直線平均，注意最好的一年，最糟糕的一年。
Label the best year the optimistic earning power of the company and the worst year the pessimistic earning power of the company.標籤最好的一年樂觀的盈利能力的公司和最差的一年的悲觀盈利能力的公司。
You could determine the most likely earning power in a variety of ways.你可以決定最有可能的盈利能力的多種方式。
What I do is take the average of the remaining 8 numbers.我做的是採取平均其餘8號碼。
Then multiply the most likely earning power by 4 and add the optimistic and pessimistic numbers to that figure.然後乘最可能的盈利能力4，添加樂觀和悲觀的數字，這個數字。
Divide the total by 6.總額除以6。
The result is called the expected value and is a normalized answer.結果稱為預期值，是一個標準化的答案。 [2] [2]
For example, let's say the reported earnings per share for a company for the years 1998-2007 are:例如，假設報告的每股收益為公司數年的1998-2007如下：
$1.22, $2.12, $2.62, $2.75, $2.59, $3.42, $3.26, $3.82, $4.25, and $.72. 1.22美元，2.12美元，2.62美元，2.75美元，2.59美元，3.42美元，3.26美元，3.82美元，4.25美元和0.72美元。
$4.25 is your optimistic year and $.72 is your pessimistic one. 4.25美元，今年是你的樂觀和0.72美元是您的悲觀。
The straight average of the rest is $2.73 and is your most likely number.直平均其餘為2.73元，是你最有可能數目。
4 X 2.73= 10.92. 4 × 2.73 = 10.92。
Adding $4.25 and $.72 gives you $15.89.添加4.25美元和0.72美元給你十五點八九美元。
Now divide by 6 to get $2.65.現在，除以6得到2.65美元。
Using the PERT method, $2.65 would be your mean or “normalized” earnings per share for this company based on the 10-year historical record.使用PERT方法，將2.65美元的平均或“標準化”的每股收益為這家公司基於10年的歷史記錄。 [3] [3]
The standard deviation (SD) is equal to the pessimistic number minus the optimistic number divided by 6.標準偏差（處）等於悲觀數目減去樂觀的人數除以6。
In this case the SD is (.72-4.25)/6= -.59在這種情況下，SD是（.72-4.25）/ 6 = -. 59
If this company's earnings are normally distributed, that means that 68.4% of the time they will fall within plus or minus 1 SD of the $2.65 mean (between $2.06 & $3.24), 95.4% of the time they will fall within plus or minus 2 SD of the mean (between $1.47 and $3.83), and 99.7% of the time they will fall within plus or minus 3 SD of the mean ($.88 and $4.42). 如果這家公司的盈利通常分佈，這意味著68.4％的時間則屬於正負1標準差的平均2.65美元（2.06美元之間＆$ 3.24），95.4％的時間則屬於正負2標清平均數（1.47美元至3.83美元的），和99.7％的時間則屬於正負3 692000平均（0.88美元美元和4.42）。 [4] [4]
But don't get too attached to this number: a business is a very dynamic organism and earnings may not necessarily follow a normal distribution.但不要太重視這個數目：一個企業是一個非常動態的有機體和收益不一定服從正態分佈。
Even if they do that .3% does happen: the company in our example earned $.72 in 2007, below the 99.7% probability low of $.88.即使他們這樣做，0.3％確實發生：該公司在我們的例子中獲得0.72美元在2007年，低於99.7％的概率低0.88美元。
Plus, statistically speaking, 10 data points is not a whole lot.另外，從統計數字上看，10個數據點不是一大堆。
Regardless, I've found the method a useful place to start, especially when examining companies with stable track records and business models.無論如何，我發現該方法的有益的開端，特別是在審查公司與穩定的業績和商業模式。
If you're interested in learning more about the PERT method and the normal and beta distributions as they relate to project management check out the following link:如果你有興趣了解更多有關PERT方法和正常和β分佈，因為它們與項目管理查看以下鏈接：
http://www.interventions.org/pertcpm.html http://www.interventions.org/pertcpm.html
[1] [1] http://en.wikipedia.org/wiki/Program_Evaluation_and_Review_Technique http://en.wikipedia.org/wiki/Program_Evaluation_and_Review_Technique
[2] [2] The PERT calculations are based on a beta distribution but the result is normal in the statistical sense.在PERT的計算是基於對Beta分佈，但結果是正常的統計意義。 My thanks to Mr. Ajit Mani of Intervention Ltd. of Bangalore, India for helping me understand why: “The weights are based on an approximation of the Beta Distribution, NOT the Normal.我還要感謝摩尼先生阿吉特公司的介入印度班加羅爾幫助我理解為什麼：“權數是根據對近似的Beta分佈，而不是正常。 The originators of PERT selected the Beta distribution for the following qualities: a) It is unimodal; b) Has finite and non-negative end points; c) Is not necessarily symmetrical. PERT技術的原創者選定的Beta分佈以下素質：1）這是單一方式;二）有有限的，非負結束點;三）不一定是對稱的。 The Normal distribution does not satisfy qualities b) and c).正態分佈不符合質量b）和c）。 The Normal curve is used for calculating Probability of Completing a Project by a Given Date.正態曲線用於計算概率完成項目的某一日期。 This is possible because the Project Length T e is calculated by simply adding the t e 's along the Critical Path.這是可能的，因為工程長度計算Ť e是通過添加噸 星際少年隊沿關鍵路徑。 Since the t e 's are all random variables, so is T e . 由於 T é's的所有隨機變量，因此是 T 的位置 。 'But the interesting (and fortunate, from a statistical standpoint) result is that T e does not have the same distribution as the t e 's but follows what is called a normal distribution…' Please refer Wiest and Levy, 'A Management Guide to PERT/CPM', Prentice-Hall International, Inc., Englewood Cliffs, NJ USA, 1969, Chapter 4. '但是，有趣的（幸運的，從統計學的角度來看）的結果是那件T e不具有相同的分佈為噸 星際少年隊 ，但如下的是所謂的正態分佈...'請參閱威斯特和利維，'A管理指南在計劃評審技術/ CPM的'，普倫蒂斯-廳國際公司，聯合利華，美國新澤西州，1969年，第4章。 The PERT Model.”在PERT的模型。“
[3] [3] Of course, whether the company can maintain and/or grow this normal earning power in the future without dilution is the key.當然，是否能夠保持和/或增加這種正常的盈利能力在今後未經稀釋是關鍵。
[4] [4] http://en.wikipedia.org/wiki/Normal_distribution http://en.wikipedia.org/wiki/Normal_distribution
