Net income correlation with Stock Price
Ideally, stock price reflects the value of the company, the dividends it is expected to pay, and what people expect the future value of the company to be. Only one of those (maybe one and a half) is related to current  sales, and not always directly. Short-term motion of a stock is even less directly linked, since it also reflects previous expectations. A company can announce disappointing sales and see its stock go up, if the previous price was based on expecting  worse news. A company's stock price will reflect the general sentiment about a company's value now and in the future. Net income is only one figure. You need to crack open the net summary and see what's inside it. In the financials you reference in your question (http://www.marketwatch.com/investing/stock/FTNT/financials), you'll also notice that  Ultimately, the stock price is just a reflection on what the market feels its (current) future is worth (you, me, other investors with future value calculators and strong opinions on what would provide value for them).
"Yes, there are non-stock analogs to the Price/Earnings ratio. Rental properties have a Price/Rent ratio, which is analogous to stocks' Price/Revenue ratio.  With rental properties, the ""Cap Rate"" is analogous to the inverse of the Price/Earnings ratio of a company that has no long-term debt. Bonds have an interest rate.  Depending on whether you care about current dividends or potential income, the interest rate is analogous to either a stock's dividend rate or the inverse of the Price/Earnings ratio." "Note that we do not comment on specific stocks here, and have no place doing so. If your question is only about that specific stock then it is off topic. I have not tried to answer that part below. The key to valuation is predicting the net present value of all of a company's cash flows; i.e. of their future profits and losses. Through a number of methods to long to explain here investment banks and hedge funds work out what they expect the company's cash flows to be and trade so that these future profits, losses etc. are priced into the stock price. Since future cash flows, profits or whatever you want to call them are priced in, the price of a stock shouldn't move at all on an earnings statement. This begs the question ""why do some stock prices move violently when they announce earnings?"" The models that the institutional investors use are not perfect and cannot take into account everything. An unexpected craze for a product or a supply chain agreement breaking down on not being as good as it seems will not be factored into this pricing and so the price will move based on the degree to which expectation is missed or exceeded. Since penny socks are speculative their value is based far more on the long term expected cash flows and less on the short run cash flows. This goes a long way to explaining why some of the highest market capitalisation penny stocks are those making consistent losses. This means that they can be far less susceptible to price movements after an earnings announcement even if it is well out of the consensus range. Higher (potential) future value comes with the higher risks of penny stocks which discounts current value. In the end if people's expectation of the company's performance reflects reality then the profitability is priced in and there will be no price movement. If the actuality is outside of the expected range then there will be a price movement." "The charts on nasdaq.com are log based, if you look closely you can see that the spacing between evenly incremented prices is tighter at the top of the chart and wider at the bottom.   It's easiest to see on a stock with a wide price range using candlestick where you can clearly see the grid.  I'm also not seeing the ""absurdism"" you indicate when I look at google finance with the settings ticked to use log on the price axis.  I see what I'd expect which is basically a given vertical differential on the price axis representing the same percentage change in price no matter where it is located. For example if I look at GOOG from the earliest date they have (Aug 20 2004) to a nice high point (dec 7 2007) I see a cart where the gap from the the bottom of the chart (seems to be right around 100) to the 200 point, (a 100% increase) is the same as from 200 to 400 (a 100% increase) is the same as 400 to 800 (a 100# increase)   That's exactly what I expect from a 'log' chart on a financial site, each relative move up or down of the same distance, represents the same relative change in value. So I'm having difficulty understanding what your complaint is. (note: I'm using chrome, which is the browser I'd expect to work best with any google website.  results with other browsers could of course vary)  If you want to do some other wacky math with the axis then I humbly suggest that something like Excel is your friend.   Goto the charts at nasdaq.com  get the chart displaying the period you care about, click the chart to display the unlying data, there will be an option to download the data.  cram it into excel and go wild as you want with charting it out.  e.g. note that step 2 links to client side javascript, so you will need javascript enabled, if you are running something like noscript, disable it for this site.  Also since the data opens in a new window, you may also need to enabled 'popups' for the site. (and yes, I sometimes get an annoying news alert advert popup  and have to close it when the chart first appears.. oh well it pays the rent and nasdaq is not charging you so for access so such is the price for a free site. )" The short answer to your question is yes.  Company performance affects stock price only through investors' views. But note that selling for higher and lower prices when the company is doing well or poorly is not an arbitrary choice.  A stock is a claim on the future cash flows of the firm, which ultimately come from its future profits.  If the company is doing well, investors will likely expect that there will large cash flows (dividends) in the future and be willing to pay more to hold it (or require more to sell it).   The price of a stock is equal what people think the future dividends are worth.  If market participants started behaving irrationally, like not reacting to changes in the expected future cash flows, then arbitrageurs would make a ton of money trading against them until the situation was rectified. There are books on the subject of valuing stocks. P/E ratio has nothing directly to do with the value of a company. It may be an indication that the stock is undervalued or overvalued, but does not indicate the value itself. The direct value of company is what it would fetch if it was liquidated. For example, if you bought a dry cleaner and sold all of the equipment and receivables, how much would you get? To value a living company, you can treat it like a bond. For example, assume the company generates $1 million in profit every year and has a liquidation value of $2 million. Given the risk profile of the business, let's say we would like to make 8% on average per year, then the value of the business is approximately $1/0.08 + $2 = $14.5 million to us. To someone who expects to make more or less the value might be different. If the company has growth potential, you can adjust this figure by estimating the estimated income at different percentage chances of growth and decline, a growth curve so to speak. The value is then the net area under this curve.  Of course, if you do this for NYSE and most NASDAQ stocks you will find that they have a capitalization way over these amounts. That is because they are being used as a store of wealth. People are buying the stocks just as a way to store money, not necessarily make a profit. It's kind of like buying land. Even though the land may never give you a penny of profit, you know you can always sell it and get your money back. Because of this, it is difficult to value high-profile equities. You are dealing with human psychology, not pennies and dollars. I don’t know specifics of the situation but one possibility would be that Buffett may have billions in various assets etc companies he owns, stocks bonds, but if he doesn’t sell any of those stocks or cash in any of those bonds, then on paper he didn’t make any money that year because he’s letting the assets appreciate. I would say net income is the amount of income you claimed that year, so if you had sold some stock, the amount of money you sold them for would be your income. As opposed to net worth being “if they wanted to” if Buffett sold all of his stocks and assets, he would be able to get billions for it. So while he technically is worth billions, on his tax returns he doesn’t claim much income. If you believe in the efficient market hypothesis then the stock price reflects the information known to market participants. Consequently, if the 'market' expected earnings to rise, and they did, then the price won't change. Clearly there are circumstances, especially in the short term and for illiquid stocks, where this isn't true, but a lot of work points to this being the case on average. Here are a few things I've already done, and others reading this for their own use may want to try.  It is very easy to find a pattern in any set of data. It is difficult to find a pattern that holds true in different data pulled from the same population.  Using similar logic, don't look for a pattern in the data from the entire population. If you do, you won't have anything to test it against. If you don't have anything to test it against, it is difficult to tell the difference between a pattern that has a cause (and will likely continue) and a pattern that comes from random noise (which has no reason to continue). If you lose money in bad years, that's okay. Just make sure that the gains in good years are collectively greater than the losses in bad years. If you put $10 in and lose 50%, you then need a 100% gain just to get back up to $10.  A Black Swan event (popularized by Nassim Taleb, if memory serves) is something that is unpredictable but will almost certainly happen at some point. For example, a significant natural disaster will almost certainly impact the United States (or any other large country) in the next year or two. However, at the moment we have very little idea what that disaster will be or where it will hit.  By the same token, there will be Black Swan events in the financial market. I do not know what they will be or when they will happen, but I do know that they will happen. When building a system, make sure that it can survive those Black Swan events (stay above the death line, for any fellow Jim Collins fans). Recreate your work from scratch. Going through your work again will make you reevaluate your initial assumptions in the context of the final system. If you can recreate it with a different medium (i.e. paper and pen instead of a computer), this will also help you catch mistakes. "This is a classic correlation does not imply causation situation.  There are (at least) three issues at play in this question: If you are swing- or day-trading then the first and second issues can definitely affect your trading.  A higher-price, higher-volume stock will have smaller (percentage) volatility fluctuations within a very small period of time. However, in general, and especially when holding any position for any period of time during which unknowns can become known (such as Netflix's customer-loss announcement) it is a mistake to feel ""safe"" based on price alone. When considering longer-term investments (even weeks or months), and if you were to compare penny stocks with blue chip stocks, you still might find more ""stability"" in the higher value stocks.  This is a correlation alone — in other words, a stable, reliable stock probably has a (relatively) high price but a high price does not mean it's reliable. As Joe said, the stock of any company that is exposed to significant risks can drop (or rise) by large amounts suddenly, and it is common for blue-chip stocks to move significantly in a period of months as changes in the market or the company itself manifest themselves. The last thing to remember when you are looking at raw dollar amounts is to remember to look at shares outstanding.  Netflix has a price of $79 to Ford's $12; yet Ford has a larger market cap because there are nearly 4 billion shares compared to Netflix's 52m." So, the price-earnings ratio is price over earnings, easy enough. But obviously earnings are not static. In the case of a growing company, the earnings will be higher in the future. There will be extra earnings, above and beyond what the stock has right now. You should consider the future earnings in your estimate of what the company is worth now. One snag: Those extra earnings are future money. Future-money is an interesting thing, it's actually worth less than present-money- because of things like inflation, but also opportunity cost.  So if you bought $100 in money that you'll have 20 years from now, you'd expect to pay less than $100. (The US government can sell you that money. It's called a Series EE Savings Bond and it would cost you $50. I think. Don't quote me on that, though, ask the Treasury.) So you can't compare future money with present-money directly, and you can't just add those dollars to the earnings . You need to compute a discount. That's what discounted cash-flow analysis is about: figuring out the future cash flow, and then discounting the future figuring out what it's worth now. The actual way you use the discount rate in your formula is a little scarier than simple division, though, because it involves discounting each year's earnings (in this case, someone has asserted a discount of 11% a year, and five years of earnings growth of 10%). Wikipedia gives us the formula for the value of the future cash flow:  essentially adding all the future cash flows together, and then discounting them by a (compounded) rate. Please forgive me for not filling this formula out; I'm here for theory, not math. :) Earnings per share are not directly correlated to share price. NV Energy, the company you cited as an example, is an electric utility. The growth patterns and characteristics of utilities are well-defined, so generally speaking the value of the stock is driven by the quality of the company's cash flow. A utility with a good history of dividend increases, a dividend that is appropriate given the company's fiscal condition, (ie. A dividend that is not more than 80% of earnings) and a good outlook will be priced competitively. For other types of companies cash flow or even profits do not matter -- the prospects of future earnings matter. If a growth stock (say Netflix as an example) misses its growth projections for a quarter, the stock value will be punished. I expected a word or two on the price elasticity of demand here :) Andrey, Your question needs slight revision in its current form. Rising prices actually do not mean increased profitability for a company. The quantity they sell also pays a huge part and actually is correlated to the price at which they sell the goods (and other factors such as the price at which their competitor sells the goods etc., but we will ignore it for simplicity).  The net profit of sales for any firm is equal to  (Qty x Sale Price) - COGS - SG&A - taxes - other expenses where, COGS means cost of goods sold SG&A means sales, general and admin costs (e.g., cleaning the inventory storage area daily so that the goods stay fresh etc.) other expenses include any miscellaneous other costs that the firm incurs to make the sale. Now, if everything in that equation remains same (COGS, SG&A, taxes, and other expenditures), rising prices will only translate into a higher profit if the quantity does not fall by the same margin. Prices may also rise simply as a response to risking COGS, SG&A or other expenditures --the latter may be observed in inflationary environments. In such a case, the supplying firm can end up losing its profit margin if the quantity falls by more than the price rise. Auto-correlation is a statistical concept for measuring repeating patterns in series.  In stocks it is of particular interest as if future prices can be reliably guessed from past prices a lot of money could be made.   Note, even in cases where auto-correlations are high and persistent (near 1) there is still some possibility that the next time period would be down even if the previous period was up.  Now the important part here is that high and persistent auto-correlation also means once the price falls the next period the price is also more likely to fall! Once one period was down the next period is more likely to be down so the price does not need to go to infinity.  Instead, it generally would display up and down trends. Now, the key word above for investing is persistence. For stocks, auto-correlations are, at best, weakly persistent at reasonable time scales.  So, even if a stock was highly auto-correlated during a previous period it is tough to make consistent money off of trading on these past trending patterns.  This does not mean some people don't try... 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. "It is important to first understand that true causation of share price may not relate to historical correlation. Just like with scientific experiments, correlation does not imply causation. But we use stock price correlation to attempt to infer causation, where it is reasonable to do so. And to do that you need to understand that prices change for many reasons; some company specific, some industry specific, some market specific. Companies in the same industry may correlate when that industry goes up or down; companies with the same market may correlate when that market goes up or down. In general, in most industries, it is reasonable to assume that competitor companies have stocks which strongly correlate (positively) with each-other to the extent that they do the same thing.  For a simple example, consider three resource companies: ""Oil Ltd."" [100% of its assets relate to Oil]; ""Oil and Iron Inc."" [50% of its value relates to Oil, 50% to Iron]; and ""Iron and Copper Ltd."" [50% of its value relates to Iron, 50% to Copper]. For each of these companies, there are many things which affect value, but one could naively simplify things by saying ""value of a resource company is defined by the expected future volume of goods mined/drilled * the expected resource price, less all fixed and variable costs"". So, one major thing that impacts resource companies is simply the current & projected price of those resources. This means that if the price of Oil goes up or down, it will partially affect the value of the two Oil companies above - but how much it affects each company will depend on the volume of Oil it drills, and the timeline that it expects to get that Oil. For example, maybe Oil and Iron Ltd. has no currently producing Oil rigs, but it has just made massive investments which expect to drill Oil in 2 years - and the market expects Oil prices to return to a high value in 2 years.  In that case, a drop in Oil would impact Oil Inc. severely, but perhaps it wouldn't impact Oil and Iron Ltd. as much. In this case, for the particular share price movement related to the price of Oil, the two companies would not be correlated. Iron and Copper Ltd. would be unaffected by the price of Oil [this is a simplification; Oil prices impact many areas of the economy], and therefore there would be no correlation at all between this company's shares. It is also likely that competitors face similar markets. If consumer spending goes down, then perhaps the stock of most consumer product companies would go down as well. There would be outliers, because specific companies may still succeed in a falling market, but in generally, there would be a lot of correlation between two companies with the same market.  In the case that you list, Sony vs Samsung, there would be some factors that correlate positively, and some that correlate negatively. A clean example would be Blackberry stock vs Apple stock - because Apple's success had specifically negative ramifications for Blackberry. And yet, other tech company competitors also succeeded in the same time period, meaning they did not correlate negatively with Apple."