Calculating a stock's price target
The price-earnings ratio is calculated as the market value per share divided by the earnings per share over the past 12 months. In your example, you state that the company earned $0.35 over the past quarter. That is insufficient to calculate the price-earnings ratio, and probably why the PE is just given as 20. So, if you have transcribed the formula correctly, the calculation given the numbers in your example would be: 0.35 * 4 * 20 = $28.00 As to CVRR, I'm not sure your PE is correct. According to Yahoo, the PE for CVRR is 3.92 at the time of writing, not 10.54. Using the formula above, this would lead to: 2.3 * 4 * 3.92 = $36.06 That stock has a 52-week high of $35.98, so $36.06 is not laughably unrealistic. I'm more than a little dubious of the validity of that formula, however, and urge you not to base your investing decisions on it.
"The answer depends on what is your portfolio's objective.   If you are operating a multi-asset class portfolio (i.e. your portfolio has both bonds and stocks) and are targeting absolute returns, then yes, comparing a stock's beta (or correlation) to a bond benchmark makes sense. What you do with this stock's ""bond beta"" information further depends on what kind of return profile you want your multi-asset class portfolio to have. If you want stocks that appreciate in price when bond prices decline, then of course you want to buy ""negative bond beta"" stocks.  If you are operating a purely relative equity portfolio (i.e. you are benchmarked to the stock market), then comparing the ""bond beta"" is of little use to you.  Hope this helps." In addition to the answer by Craig Banach: Sometimes brands are owned by publicly traded companies which have a very diverse product portfolio. In case of Microsoft their stock price and dividend will not be controlled solely by that one product they make but also by their many other products (plus a billion other factors which can influence a stock price). So when you want to bet specifically on the success of Windows Phone then betting on the Microsoft Corporation as a whole might not achieve that goal. However, you can also try to find companies whose success depends indirectly on the success of the product. That can be suppliers (someone who makes a specific part which is only used for Windows phones), companies which make Windows Phone specific accessories or software developers who make applications which specifically target the Windows Phone ecosystem. When the product portfolio of these companies is far narrower than that of Microsoft they might be more dependent on the success of Windows Phone than Microsoft themselves. But as always, keep in mind that the success of their products is not the only factor which decides the stock value of a company. The stock market is far more complex than that. "There are a few different ""kinds"" of implied volatility. They are all based on the IVs obtained from the option pricing model you use. (1) Basically, given a few different values (current stock price, time until expiration, right of option, exercise style, strike of the option, interest rates, dividends, etc), you can obtain the IV for a given option price. If you look at the bid of an option, you can calculate the IV for that bid. If you look at the ask, there's a different IV for the ask. You can then look at the mid price, then you have a different IV, and so on and so on. And that's for each strike, in each expiration cycle! So you have a ton of different IVs. (2) In many option trading platforms, you'll see another kind of IV: the IV for each specific expiration cycle. That's calculated based on some of the IVs I mentioned on topic (1). Some kind of aggregation (more on this later). (3) Finally, people often talk about ""the IV of stock XYZ"". That's, again, an aggregation calculated from many of the IVs mentioned on topic (1). Now, your question seems to be: which IVs, from which options, from which months, with which weight, are part of the expiration cycle IV or for the IV of the stock itself? It really depends on the trading platform you are talking about. But very frequently, people will use a calculation similar to how the CBOE calculates the VIX. Basically, the VIX is just like the IV described on topic (3) above, but specifically for SPX, the S&P 500 index. The very detailed procedure and formulas to calculate the VIX (ie, IV of SPX) is described here: http://cfe.cboe.com/education/vixprimer/about.aspx If you apply the same (or a similar) methodology to other stocks, you'll get what you could call ""the IV of stock XYZ""." "Just to be clear to start, beta is a statistical property.  So if your beta is 0.8 over a period of time.  Stock X moved on average 0.8 for a point move in the index. We might hope this property is persistent and it seems to be fairly persistent (predictable) but it doesn't have to be. Also it is important to note this is not a lag in time.  Beta is a measure of the average size of a move in the stock at the same time as a move in the index.  In your example both the stock and index are measured at end of day.  You can say that the stock ""lags"" behind the index because it doesn't grow as quickly as the market when the market is growing, but this is not a lag in time just a lag in magnitude.   People do occasionally calculate betas between a stock and lagged in time market prices, but this is not the commonly used meaning of beta.  This might actually be a more useful measure as then you could bet on the future of the stock given what happened today in the market, but these ""betas"" tend to be much more unstable than the synchronized version and hard to trade on. When you calculated beta you choose a time scale, in this case daily.  So if your calculation is on a day-to-day basis then you have only tested the relationship on a day-to-day basis not, for instance, on a week-to-week basis.  Now day-to-day and week-to-week betas are often related and are generally reasonably close but they do not have to be.  There can be longer term effects only picked up on the longer scale.   Stock X could day-to-day with a (average) beta of 1 to the stock market, but could have even a negative beta year-to-year with the market if the stock is counter-cyclical to longer scale trends on the market.  So beta can change with the time scale used in the calculation." You could use  the Gordon growth model implied expected return: P = D/(r-g) --&gt; r = D/P (forward dividend yield) + g (expected dividend growth). But obviously there is no such thing as a good market return proxy. "Your strategy fails to control risk. Your ""inversed crash"" is called a rally. And These kind of things often turn into bigger rallies because of short squeezes, when all the people that are shorting a stock are forced to close their stock because of margin calls - its not that shorts ""scramble"" to close their position, the broker AUTOMATICALLY closes your short positions with market orders and you are stuck with the loss. So no, your ""trick"" is not enough. There are better ways to profit from a bearish outlook." Really not sure with this one and I don't want to cheat and look up an answer.  I'd say you could find the high/low points of the stock over the last year or two and see how large the spread is between those values and the average price of the stock over the same time period. "A bit strange but okay.  The way I would think about this is again that you need to determine for what purpose you're computing this, in much the same way you would if you were to build out the model. The IPO valuation is not going to be relevant to the accretion/dilution analysis unless you're trying to determine whether the transaction was net accretive at exit. But that's a weird analysis to do. For longer holding periods like that you're more likely to look at IRR, not EPS. EPS is something investors look at over the short to medium term to get a sense of whether the company is making good acquisition decisions. And to do that short-to-medium term analysis, they look at earnings.   Damodaran would say this is a shitty way of looking at things and that you should probably be looking at some measure of ROIC instead, and I tend to agree, but I don't get paid to think like an investor, I get paid to sell shit to them (if only in indirect fashion). The short answer to your question is that no, you should not incorporate what you are calling liquidation value when determining accretion/dilution, but only because the market typically computes accretion/dilution on a 3-year basis tops. I've never put together a book or seen a press release in my admittedly short time in finance that says ""the transaction is estimated to be X% accretive within 4 years"" - that just seems like an absurd timeline.  Final point is just that from an accounting perspective, a gain on a sale of an asset is not going to get booked in either EBITDA or OCF, so just mechanically there's no way for the IPO value to flow into your accretion/dilution analysis there, even if you are looking at EBITDA/shares. You could figure the gain on sale into some kind of adjusted EBITDA/shares version of EPS, but this is neither something I've ever seen nor something that really makes sense in the context of using EPS as a standardized metric across the market. Typically we take OUT non-recurring shit in EPS, we don't add it in. Adding something like this in would be much more appropriate to measuring the success of an acquisition/investing vehicle like a private equity fund, not a standalone operating company that reports operational earnings in addition to cash flow from investing. And as I suggest above, that's an analysis for which the IRR metric is more ideally situated.  And just a semantic thing - we typically wouldn't call the exit value a ""liquidation value"". That term is usually reserved for dissolution of a corporate entity and selling off its physical or intangible assets in piecemeal fashion (i.e. not accounting for operational synergies across the business). IPO value is actually just going to be a measure of market value of equity."