How to accurately calculate Apple's EPS
On closer look, it appears that Google Finance relies on the last released 10-k statement (filing date 10/30/2013), but outstanding shares as of last 10-Q statement. Using these forms, you get ($37,037M / 5.989B ) = $6.18 EPS. I think this is good to note, as you can manually calculate a more up to date EPS value than what the majority of investors out there are relying on.
Profit after tax can have multiple interpretations, but a common one is the EPS (Earnings Per Share).  This is frequently reported as a TTM number (Trailing Twelve Months), or in the UK as a fiscal year number.  Coincidentally, it is relatively easy to find the total amount of dividends paid out in that same time frame. That means calculating div cover is as simple as:  EPS divided by total dividend.  (EPS / Div). It's relatively easy to build a Google Docs spreadsheet that pulls both values from the cloud using the GOOGLEFINANCE() function.  I suspect the same is true of most spreadsheet apps.  With a proper setup, you can just fill down along a column of tickers to get the div cover for a number of companies at once. "What you are seeking is termed ""Alpha"", the mispricing in the market. Specifically, Alpha is the price error when compared to the market return and beta of the stock. Modern portfolio theory suggests that a portfolio with good Alpha will maximize profits for a given risk tolerance. The efficient market hypotheses suggests that Alpha is always zero. The EMH also suggests that taxes, human effort and information propagation delays don't exist (i.e. it is wrong). For someone who is right, the best specific answer to your question is presented Ben Graham's book ""The Intelligent Investor"" (starting on page 280). And even still, that book is better summarized by Warren Buffet (see Berkshire Hathaway Letters to Shareholders). In a great disservice to the geniuses above it can be summarized much further: closely follow the company to estimate its true earnings potential... and ignore the prices the market is quoting. ADDENDUM: And when you have earnings potential, calculate value with: NPV = sum(each income piece/(1+cost of capital)^time) Update: See http://finance.fortune.cnn.com/2014/02/24/warren-buffett-berkshire-letter/ ""When Charlie Munger and I buy stocks..."" for these same ideas right from the horse's mouth" i will not calculate it for you but just calculate the discounted cash flow (by dividing with 1.1 / 1.1^2 / 1.1^3   ...)of each single exercise as stated and deduct the 12.000 of the above sum.  in the end compare which has the highest npv P/E can use various estimates in its calculation as one could speculate about future P/E rations and thus could determine a future valuation if one is prepared to say that the P/E should be X for a company. Course it is worth noting that if a company isn't generating positive earnings this can be a less than useful tool, e.g. Amazon in the 1990s lost money every quarter and thus would have had a N/A for a P/E. PEG would use P/E and earnings growth as a way to see if a stock is overvalued based on projected growth. If a company has a high P/E but has a high earnings growth rate then that may prove to be worth it. By using the growth rate, one can get a better idea of the context to that figure. Another way to gain context on P/E would be to look at industry averages that would often be found on Yahoo! Finance and other sites. "I had  both closing price and adjusted price of Apple showing the same amount after ""download data"" csv file was opened in excel. https://finance.yahoo.com/quote/AAPL/history?period1=1463599361&period2=1495135361&interval=div%7Csplit&filter=split&frequency=1d Its frustrating. My last option was to get the dividends history of the stock and add back to the adjusted price to compute the total return for a select stock for the period." "To add to @keshlam's answer slightly a stock's price is made up of several components: the only one of these that is known even remotely accurately at any time is the book value on the day that the accounts are prepared. Even  completed cashflows after the books have been prepared contain some slight unknowns as they may be reversed if stock is returned, for example, or reduced by unforeseen costs.  Future cashflows are based on (amongst other things) how many sales you expect to make in the future for all time. Exercise for the reader: how many iPhone 22s will apple sell in 2029? Even known future cashflows have some risk attached to them; customers may not pay for goods, a supplier may go into liquidation and so need to change its invoicing strategy etc.. Estimating the risk on future cashflows is highly subjective and depends greatly on what the analyst expects the exact economic state of the world will be in the future. Investors have the choice of investing in a risk free instrument (this is usually taken as being modelled by the 10 year US treasury bond) that is guaranteed to give them a return. To invest in anything riskier than the risk free instrument they must be paid a premium over the risk free return that they would get from that. The risk premium is related to how likely they think it is that they will not receive a return higher than that rate. Calculation of that premium is highly subjective; if I know the management of the company well I will be inclined to think that the investment is far less risky (or perhaps riskier...) than someone who does not, for example. Since none of the factors that go into a share price are accurately measurable and many are subjective there is no ""right"" share price at any time, let alone at time of IPO. Each investor will estimate these values differently and so value the shares differently and their trading, based on their ever changing estimates, will move the share price to an indeterminable level. In comments to @keshlam's answer you ask if there is enough information to work out the share price if a company buys out the company before IPO. Dividing the price that this other company paid by the relative ownership structure of the firm would give you an idea of what that company thought that the company was worth at that moment in time and can be used as a surrogate for market price but it will not and cannot accurately represent the market price as other investors will value the firm differently by estimating the criteria above differently and so will move the share price based on their valuation." As others have pointed out, the value of Apple's stock and the NASDAQ are most likely highly correlated for a number of reasons, not least among them the fact that Apple is part of the NASDAQ. However, because numerous factors affect the entire market, or at least a significant subset of it, it makes sense to develop a strategy to remove all of these factors without resorting to use of an index. Using an index to remove the effect of these factors might be a good idea, but you run the risk of potentially introducing other factors that affect the index, but not Apple. I don't know what those would be, but it's a valid theoretical concern.  In your question, you said you wanted to subtract them from each other, and only see an Apple curve moving around a horizontal line. The basic strategy I plan to use is similar but even simpler. Instead of graphing Apple's stock price, we can plot the difference between its stock price on business day t and business day t-1, which gives us this graph, which is essentially what you're looking for:  While this is only the preliminaries, it should give you a basic idea of one procedure that's used extensively to do just what you're asking. I don't know of a website that will automatically give you such a metric, but you could download the price data and use Excel, Stata, etc. to analyze this.  The reasoning behind this methodology builds heavily on time series econometrics, which for the sake of simplicity I won't go into in great detail, but I'll provide a brief explanation to satisfy the curious. In simple econometrics, most time series are approximated by a mathematical process comprised of several components: In the simplest case, the equations for a time series containing one or more of the above components are of the form that taking the first difference (the procedure I used above) will leave only the random component. However, if you want to pursue this rigorously, you would first perform a set of tests to determine if these components exist and if differencing is the best procedure to remove those that are present. Once you've reduced the series to its random component, you can use that component to examine how the process underlying the stock price has changed over the years. In my example, I highlighted Steve Jobs' death on the chart because it's one factor that may have led to the increased standard deviation/volatility of Apple's stock price. Although charts are somewhat subjective, it appears that the volatility was already increasing before his death, which could reflect other factors or the increasing expectation that he wouldn't be running the company in the near future, for whatever reason. My discussion of time series decomposition and the definitions of various components relies heavily on Walter Ender's text Applied Econometric Time Series. If you're interested, simple mathematical representations and a few relevant graphs are found on pages 1-3. Another related procedure would be to take the logarithm of the quotient of the current day's price and the previous day's price. In Apple's case, doing so yields this graph:  This reduces the overall magnitude of the values and allows you to see potential outliers more clearly. This produces a similar effect to the difference taken above because the log of a quotient is the same as the difference of the logs The significant drop depicted during the year 2000 occurred between September 28th and September 29th, where the stock price dropped from 26.36 to 12.69. Apart from the general environment of the dot-com bubble bursting, I'm not sure why this occurred. Another excellent resource for time series econometrics is James Hamilton's book, Time Series Analysis. It's considered a classic in the field of econometrics, although similar to Enders' book, it's fairly advanced for most investors.  I used Stata to generate the graphs above with data from Yahoo! Finance: There are a couple of nuances in this code related to how I defined the time series and the presence of weekends, but they don't affect the overall concept. For a robust analysis, I would make a few quick tweaks that would make the graphs less appealing without more work, but would allow for more accurate econometrics. I'm not sure i understand the strategy of going upmarket so fast. If this is right it will be a 25% increase which is a lot. Apple isn't hurting for profits and most of their growth is in services, which depend on a large install base.  Premium is fine, but going luxury seems counter-productive. "The best place to start looking is the companies ""Balance Sheet"" (B/S).  This would show you the total shares ""outstanding."" The quarterly B/S's arent audited but a good starting point.  To use in any quant method, You also need to look a growth the outstanding shares number. Company can issue shares to any employee without making a filing.  Also, YOU will NEVER know exactly the total number because of stock options that are issued to employees that are out of the money arent account for. Some companies account for these, some dont.  You should also explore the concepts of ""fully dilute"" shares and ""basis"" shares. These concepts will throw-off your calc if the company has convertible bonds." "A Bloomberg terminal connected to Excel provides the value correcting splits, dividends, etc. Problem is it cost around $25,000. Another one which is free and I think that takes care of corporate action is ""quandl.com"". See an example here." "You asked 3 questions here. It's best to keep them separate as these are pretty distinct, different answers, and each might already have a good detailed answer and so might be subject to ""closed as duplicate of..."" That said, I'll address the JAGLX question (1). It's not an apples to apples comparison. This is a Life Sciences fund, i.e. a very specialized fund, investing in one narrow sector of the market. If you study market returns over time, it's easy to find sectors that have had a decade or even two that have beat the S&P by a wide margin. The 5 year comparison makes this pretty clear. For sake of comparison, Apple had twice the return of JAGLX during the past 5 years. The advisor charging 2% who was heavy in Apple might look brilliant, but the returns are not positively correlated to the expense involved. A 10 or 20 year lookback will always uncover funds or individual stocks that beat the indexes, but the law of averages suggests that the next 10 or 20 years will still appear random." Outside of software that can calculate the returns:  You could calculate your possible returns on that leap spread as you ordinarily would, then place the return results of that and the return results for the covered call position side by side for any given price level of the stock you calculate, and net them out. (Netting out the dollar amounts, not percentage returns.)  Not a great answer, but there ya go. Software like OptionVue is expensive Not quite. The EPS is noted as ttm, which means trailing twelve months  --- so the earnings are taken from known values over the previous year. The number you quote as the dividend is actually the Forward Annual Dividend Rate, which is an estimate of the future year's dividends. This means that PFE is paying out more in the coming year (per share) than it made in the previous year (per share). It is a good enough approximation. With a single event you can do it your way and get a better result, but imagine that the $300 are spread over a certain period with $10 contribution each time? Then recalculating and compounding will be a lot of work to do. The original ROI formula is averaging the ROI by definition, so why bother with precise calculations of averages that are imprecise by definition, when you can just adjust the average without losing the level of precision? 11.4 and 11.3 aren't significantly different, its immaterial. Note that your link shows the shares as of March 31, 2016 while http://uniselect.com/content/files/Press-release/Press-Release-Q1-2016-Final.pdf notes a 2-for-1 stock split so thus you have to double the shares to get the proper number is what you are missing. The stock split occurred in May and thus is after the deadline that you quoted.