what are the drawbacks of DCF compared to other methods? All have estimates and assumptions. What makes DCFtop
462874
DCF methods value the underlying cash flows that a group of assets produce, discounted by the risk of those cash flows.  While this method is very helpful for determining the intrinsic value of the assets or business, it has a few shortcomings.  First, this method relies heavily on assumptions for cash flows, risks, and terminal values.  The output you receive can only be as good as the assumptions you use.  Many times, there are important items omitted or bad assumptions that cause the DCF to be wrong.  Second, the market prices things in such a way that the DCF is not always the best method.  For example, before the tech bubble burst, DCFs were showing values of tech stock that were orders of magnitute less than the relative or market valuations.  Third, since a business is a portfolio of projects, the options (to expand, abandon, special strategic options, etc) may not be taken into account with the DCF and to do so is often very difficult.  Since real options are extremely difficult to price, many analysts exclude them from their calculations, understating the true value of the firm.  There are many many more shortcomings with DCF methods.\n\nDespite these shortcomings, the DCF is a very useful tool.  The trick is to understand the limitations of DCF methology and to incorporate it into a larger valuation frame work.  Typically the DCF will understate value while relative valuation overstates the value.  The differential between the two values can be used to approximate the relevance of the DCF.  If the DCF is significantly different than the relative value, you may want to check your assumptions (and maybe solve for input values that force the output to be similar to the relative value and determine if the new inputs are reasonable).  \n\nIf you are reading Valuation by Copeland, Kohler, and Murrin (published by McKenzey and Company), you have a really good text.  If not, pick up a copy of the 3rd edition.  It is really a good professional's guide to appropriate application of DCF techniques.  I know that Intel Capital uses that text as the format for its DCFs.
452512
I have seen a number of these pro and con.   The con ones are full of really bad science which sound good if you don't know the science (i.e. shadows etc).\n\nIt happened get used to it folks are just trying to get another multi-million dollar conspiracy industry going :-)
712311
www.cabrillo.edu/~cfigueroa/4A/4Aexamples/4Aexample9-F06.pdf
693372
The field, be it finite or whatever, makes no difference. Use common methods of linear algebra you know. You should just remember to add, multiply, divide, etc in your field correctly.
852284
It is sufficient, but it is not optimal.  Calculations of distance (for instance) in a GIS require formulas to be written within the SQL.  A QL that has these calculations supplied is better.
353301
See p. 541 of Econometric Foundations by Mittelhammer, Judge and Miller.  Will be a bit tough to explain on Yahoo.  Actually, I don't like this book, but none of my other ones have this.
811211
If you add DCl or DNO3 to D2O, you will get D3O+.\nD3O will not be stable and very hard to make.
46182
i think it would be f-critical times Degress fredom alpha.  but i am not 100%.  i'm going with that b/c i dont think there is addition in that function.  the real question is how much turkey is there in the turkey test?
215463
rdDONTrdPOSTrdSTUPIDsQUESTIONSsd.
612525
We can have a simple linear function such as F(X)= X times a Constant C. This type of function is used everyday when we convert "one thing" to "another". One currency to another (i.e. exchange rate); metric and a myriad of other conversions. How about taxes like the sales tax. You pay so much per gallon of gas; so much per unit of power used for electricity etc.\nHowever we can also have a function F(X1,X2,X3...Xn)= C which can be quite complicated and which is a function of many inputs X1,X2,X3....Xn. Such a function could be used in computer modelling for weather and economic forecasts, navigation, traffic control etc. hope that helps somewhat
1005792
I did.  You can usually get a much better (and fixed rather than variable) interest rate that way.  I am not sure what the cons are, I only know the pros.
199797
The tradeoffs are always the same when implementing types or subtypes when creating anything..logical or not, schema or not.....it's all a means to an end that is an effect based on cause...
458677
There's a very explicit algorithm which explains\nhow to handle number, operators (including left\nor right precedence), functions, etc. on the \nWikipedia site for RPN (see reference #1).\n\nMostly, it's very straight-forward.  If it's an operand\n(ie. a number), then push it on the stack.  If it's an\noperator, then pop off as many operands are needed and\nevaluate.\n\nBut do look at the full algorithm for the details.\n\nOh yeah, for a full-blown implementation, see the source\ncode to the Unix "dc" (desk calculator) program.  The\nSolaris source is at reference #2.
1056489
Fractional factorial plans are of immense practical utility in many fields of investigation (particularly in experimental design, quality control, and quality improvment), and research in this area is progressing at a vigorous pace with an already voluminous and growing amount of research papers published.\n\n---------------\n\nPractical applications of recursion\nThere are many practical situations in which recursion can be a valuable technique—among them is the classic programming problem called Bill of Materials. This problem has at least two different applications, which include:\n\nGiven the demand for one instance of an object, produce the Bill of Materials required to build it. \nGiven specific inventory levels of the constituent objects that comprise an object, how many objects of this kind can we build? \n\n\n----------------\n\n"Practical Fibonacci Methods For Forex Trading." It covers everything you need to know about using Fibonacci levels for entries, exits and stops.Position ,swing and intra day traders will find this information useful.You'll learn how to boost your trading skills using precision trading.
237487
Formally, the discrete cosine transform is a linear, invertible function F : RN -> RN (where R denotes the set of real numbers), or equivalently an N × N square matrix. There are several variants of the DCT with slightly modified definitions. The N real numbers x0, ..., xN-1 are transformed into the N real numbers X0, ..., XN-1. \n\nDCT-I\n \nSome authors further multiply the x0 and xN-1 terms by √2, and correspondingly multiply the X0 and XN-1 terms by 1/√2. This makes the DCT-I matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT.\n\nThe DCT-I is exactly equivalent (up to an overall scale factor of 2), to a DFT of 2N − 2 real numbers with even symmetry. For example, a DCT-I of N=5 real numbers abcde is exactly equivalent to a DFT of eight real numbers abcdedcb (even symmetry), divided by two. (In contrast, DCT types II-IV involve a half-sample shift in the equivalent DFT.)\n\nNote, however, that the DCT-I is not defined for N less than 2. (All other DCT types are defined for any positive N.)\n\nThus, the DCT-I corresponds to the boundary conditions: xn is even around n=0 and even around n=N-1; similarly for Xk.\n\nDCT-II\n \nThe DCT-II is probably the most commonly used form, and is often simply referred to as "the DCT".\n\nThis transform is exactly equivalent (up to an overall scale factor of 2) to a DFT of 4N real inputs of even symmetry where the even-indexed elements are zero. That is, it is half of the DFT of the 4N inputs yn, where y2n = 0, y2n + 1 = xn for , and y4N − n = yn for 0 < n < 2N.\n\nSome authors further multiply the X0 term by 1/√2 (see below for the corresponding change in DCT-III). This makes the DCT-II matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT of half-shifted input.\n\nThe DCT-II implies the boundary conditions: xn is even around n=-1/2 and even around n=N-1/2; Xk is even around k=0 and odd around k=N.\n\nDCT-III\n \nBecause it is the inverse of DCT-II (up to a scale factor, see below), this form is sometimes simply referred to as "the inverse DCT" ("IDCT").\n\nSome authors further multiply the x0 term by √2 (see above for the corresponding change in DCT-II). This makes the DCT-III matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT of half-shifted output.\n\nThe DCT-III implies the boundary conditions: xn is even around n=0 and odd around n=N; Xk is even around k=-1/2 and odd around k=N-1/2.\n\nDCT-IV\n \nThe DCT-IV matrix is orthogonal (up to a scale factor).\n\nA variant of the DCT-IV, where data from different transforms are overlapped, is called the modified discrete cosine transform (MDCT).\n\nThe DCT-IV implies the boundary conditions: xn is even around n=-1/2 and odd around n=N-1/2; similarly for Xk.\n\nDCT V-VIII\nDCT types I-IV are equivalent to real-even DFTs of even order. In principle, there are actually four additional types of discrete cosine transform (Martucci, 1994), corresponding to real-even DFTs of logically odd order, which have factors of N+1/2 in the denominators of the cosine arguments. However, these variants seem to be rarely used in practice.\n\n(The trivial real-even array, a length-one DFT (odd length) of a single number a, corresponds to a DCT-V of length N=1.)\n\nInverse transforms\nThe inverse of DCT-I is DCT-I multiplied by 2/(N-1). The inverse of DCT-IV is DCT-IV multiplied by 2/N. The inverse of DCT-II is DCT-III multiplied by 2/N (and vice versa).\n\nLike for the DFT, the normalization factor in front of these transform definitions is merely a convention and differs between treatments. For example, some authors multiply the transforms by  so that the inverse does not require any additional multiplicative factor.\n\nComputation\nAlthough the direct application of these formulas would require O(N2) operations, it is possible to compute the same thing with only O(N log
929935
variations matter greatly in interpreting data.  Something might seem like it is returning significantly different results than the control but stat evaluation may show that the variations are minimal at best
550682
Oy that is a great question.  I take it you taking a risk managment or a derivative course! ;)  Basically you would have to put in functions (functions of interest and volatility variations) for both and then evaluate it accordingly.  It is nearly impossible to do by hand but computer can provide you with some good insight :).  That's when 3D probability that engineers love so much kicks in.  \n\nRival