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Namely, if it is possible to generate fixed income returns with non fixed income products, why not do so And if it is possible to outperform traditional fixed income products with non fixed income securities and for comparable levels of risk, why ever buy another note or bond Again, if investors are constrained to hold only fixed income products, then the choice is clear; they hold only the true fixed income portfolio If they want only to create a fixed income exposure to the marketplace and are indifferent as to how this is achieved, then there are choices to make How can investors choose between a true and synthetic fixed income portfolio Perhaps on the basis of historical risk/return profiles.



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Because all the model elements shown in Fig. 3.5.2 are available in the CAD program SPICE, the simulation results given below can be obtained by using SPICE [13]. For an asymmetric coupled two-line system (also called a 4-port), the SPICE model, model parameters, and its step response are shown in Figs. 3.5.3a e. The step





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15 Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation Nucleic Acids Res 2002;30:e15 16 Smyth GK, Speed T Normalization of cDNA microarray data Methods 2003;31: 265 273 17 Berger JA, Hautaniemi S, Jarvinen AK, Edgren H, Mitra SK, Astola J Optimized LOWESS normalization parameter selection for DNA microarray data BMC Bioinform 2004;5: 194 18 Colantuoni CHG, Zeger S, Pevsner J Local mean normalization of microarray element signal intensities across an array surface: quality control and correction of spatially systematic artifacts Biotechniques 2002;32:1316 1320 19 Holter NS, Mitra M, Maritan A, Cieplak M, Banavar JR, Fedoroff NV Fundamental patterns underlying gene expression pro les: simplicity from complexity Proc Natl Acad Sci USA 2000;97:8409 8414 20.

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If the synthetic fixed income portfolio can outperform the true fixed income portfolio on a consistent basis at the same or a lower level of risk, then investors might seriously want to consider owning the synthetic portfolio A compromise would perhaps be to own a mix of the true and synthetic portfolios For our third example, consider the TED spread, or Treasury versus Eurodollar spread A common way of trading the TED spread is with futures contracts For example, to buy the TED spread, investors buy three-month Treasury bill futures and sell three-month Eurodollar futures They would purchase the TED spread if they believed that perceptions of market risk or volatility would increase In short, buying the TED spread is a bet that the spread will widen.

where the norms on the right-hand side are the vector Holder norms and the induced matrix norms on the left are called subordinate to the corresponding Holder norms. The 2-norm de ned in this way is also called the spectral norm of A. It has the properties: kdiagi li k2 max jli j

Bolstad BM, Irizarry RA, Astrand M, Speed TP, A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bioinformatics 2003;19:185 193 21 Wol nger RD, Gibson G, Wol nger ED, Bennett L, Hamadeh H, Bushel P, Afshari C, Paules RS Assessing gene signi cance from cDNA microarray expression data via mixed models J Comput Biol 2001;8:625 637 22 Schadt EE, Li C, Ellis B, Wong WH, Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data J Cell Biochem Suppl 2001;37:120 125 23 Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP Exploration, normalization, and summaries of high density oligonucleotide array probe level data Biostatistics 2003;4:249 264 24 Yu X, Chu TM, Gibson G, Wol nger RD, A mixed model approach to identify yeast transcriptional regulatory motifs via microarray experiments Stat Appl Genet Mol Biol 2004;3:article22 25.

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