W. Härdle, T. Kleinow, G. Stahl's Applied Quantitative Finance: Theory and Computational Tools PDF

By W. Härdle, T. Kleinow, G. Stahl

ISBN-10: 3540434607

ISBN-13: 9783540434603

ISBN-10: 3662050218

ISBN-13: 9783662050217

Applied Quantitative Finance offers ideas, theoretical advancements and technique proliferation for lots of functional difficulties in quantitative finance. the mix of perform and idea supported via computational instruments is mirrored within the number of subject matters in addition to in a finely tuned stability of clinical contributions at the sensible implementation and theoretical strategies. this idea bargains theoreticians perception into the applicability of the method and, vice versa, practitioners entry to new equipment for his or her purposes.
The booklet layout of the textual content hyperlinks concept and computational instruments in an cutting edge approach. All "quantlets" for the calculation of given examples within the textual content are executable on an XploRe Quantlet Server (XQS) and will be changed via the reader through the net. The digital version could be downloaded from the website www.i-xplore.de utilizing the licence and registration quantity on the again conceal.

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Additional info for Applied Quantitative Finance: Theory and Computational Tools

Example text

3 13 Cornish-Fisher Approximations With a = (F - ifJ) j

27) where U is a suitable neighborhood of x. 28) holds. FFT-based Fourier inversion yields approximations for the cdf F on equidistant ~x-spaced grids . Depending on the smoothness of F , linear or higher-order interpolations may be used. Any monotone interpolation of {F(xo + Llxj)}j yields a quantile approximation whose interpolation error can be bounded by Llx . This bound can be improved if an upper bound on the density f in a suitable neighborhood of the true quantile is known. 2 Tail Behavior 2 If Aj = 0 for some i , t hen 1¢(t)1 = O(e- oJt / 2).

Uv is a n x 2 vector of coordinates, where the copula is calculated. Finall y we determine Xl = <1>1 1 (u) and X2 = <1>2 1 (v) to obt ain one pair ( Xl , X2 ) of ra ndom var iables with th e desired copula dependence st ruct ure. For a Monte Carlo simulat ion, thi s procedur e is performed N times to yield a sample X = (x(1), . . , x(N) ). Z. If we assume a linear position a with holdings a1, . . , an in each of the risk factors , th e change in portfolio value is approximately 2:7=1 ai . X i.

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Applied Quantitative Finance: Theory and Computational Tools by W. Härdle, T. Kleinow, G. Stahl

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