# Tag Info

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I have voted to close given that I think this is a basic financial question not allowed in here. Anyway, take a look to any Damodaran's book or to Mckinsey Valuation. Damodaran's blog even has some spreadsheets for some companies.

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I was just like you when I started out: I had learned a lot about machine learning (mainly neural networks and genetic algorithms/programming) and used it heavily. I also had learned about classic statistics but not nearly as much as about ML. The problem with ML is - as I see it today - that you are often taking a sledgehammer to crack a nut, meaning: ...

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The main reason to use traditional methods is interpretability. Specially when you are dealing with portfolios. Portfolios are nothing more than a linear combination of assets. Many Machine Learning methods are highly non-linear and therefore are hard to replicate with a real portfolio. For example if you want to minimize volatility of your emerging markets ...

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You wrote: $$d[5] = (DJIR[5] - \mu) * Covariance$$ but you left out half of it (the inverse and the transposed vector on the right side). The correct formula is $$d[5] = (DJIR[5] - \mu)^2 / Var[DJIR]$$ The covariance "matrix" becomes the variance in a 1-dimensional case (in other words $x_i$ and $y_i$ are both equal to DJIR[i] in this case) and the "matrix ...

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You can use refined methodologies but if you just need a rough estimation of liquidity, you can simply use an average of daily volume over N days. In practice, for equities, people tend to use N = 20 or 30. Once you have the average daily volume (say 100,000 shares), you compare it to your holding (say 50,000 shares) to determine the the size of your ...

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I think one of the main liquidity measures is the one from Pastor and Stambaugh (2003). You can use it for both individual stocks or indexes. Just run the following intra-month regression with daily data: $r^e_{i,d+1,t} = \theta_{i,t}+\phi_{i,t}r_{i,d,t}+\gamma_{i,t}sign(r^e_{i,d,t}) \times v_{i,d,t}+\epsilon_{i,d+1,t}$. Where $r^e_{i,d+1,t}$ is the ...

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I would consider Amihud (2002) as a good first approximation with that level of data.

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Yes, the greenshoe option, technically called overallotment option is described in the prospectus. Yes, in the event the greenshoe option is exercised by the underwriters, the company issues additional shares and receives additional proceeds. Essentially it is as though a small secondary offering took place.

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I agree with Alex C. Profit is too slippery a measure to work with. Focusing on profit raises a number of questions. Can the reported profit be trusted? Profit as a measure is much more open to manipulation than stock price. What year’s profits should be maximised? You can see straightaway that a good business decision may result in lower profits for the ...

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In a world of uncertainty no one knows what future profits will be (especially > 1 year from now). All we can do is estimate. Who should we ask? The company management has an incentive to give out estimates that may be too optimistic. If you ask the competitors they are probably too pessimistic. Fortunately we have a machine called the stock market which ...

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To answer your question consider the following example using actual prices for SPY ETF on 7/31/15: "hopey.netfonds.no" By looking at the last 19 trades that occurred at the very last second, you will see a notable price movement on prices. If you go to Google/Yahoo Finance the Closing Price for the ETF is 210.50 (largest trade at the close?) but the very ...

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