Matematik simulation and monte carlo with applications in finance and mcmc phần 2 pdf

Matematik simulation and monte carlo with applications in finance and mcmc phần 1 pps

Matematik simulation and monte carlo with applications in finance and mcmc phần 1 pps

... 16, 20 , 20 , 18, 22 , 23 , 26 , 25 , 29 , 27 , 26 , 30, 27 , 29 , 27 , 25 , 26 , 30, 30, 27 , 28 , 23 , 25 , 21 , 24 , 22 , 23 , 22 , 25 , 22 , 22 , 25 , 25 , 23 , 19, 19, 19, 21 , 23 , 25 , 24 , 26 , 24 , 27 , 24 , 27 , 29 , 29 , 29 , ... (op (2, res[i]), i=11 100); data = 29 , 30, 30, 28 , 25 , 30, 26 , 30, 26 , 23 , 25 , 25 , 28 , 30, 24...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 2 pdf

Matematik simulation and monte carlo with applications in finance and mcmc phần 2 pdf

... 1 29 130 2 31 −1 630360016 0 1 29 2 92 164 2 16 29 3 Odd 1 20 107 145 2 31 −1 950,706,376 0 2 31 −1 7 42, 938 ,28 5 0 2 31 −1 1 ,22 6,874,159 0 2 31 −1 62, 089,911 0 2 31 −1 1,343,714,438 0 U0 1 ... stdnormal:=proc() local r1,r2,r3,E1,E2; do; r1:=evalf(rand()/10ˆ 12) ; r2:=evalf(rand()/10ˆ 12) ; E1:=-ln(r1); E2:=-ln(r2); if E2 > 05 ∗ E1-1 2 then break end if; en...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 3 ppsx

Matematik simulation and monte carlo with applications in finance and mcmc phần 3 ppsx

... = ⎧ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎩ 1/ √ 2 e √ 2x+1 1/ √ 2 +2 1/ √ 2 +1/ √ 2 = 1 4 e √ 2x+1  x<− √ 2 2   1/ √ 2 +x +1/ √ 2 1/ √ 2 +2 1/ √ 2 +1/ √ 2 = √ 2x +2 4  x≤ √ 2 2   4/ √ 2 −1/ √ 2 e − √ 2x+1 1/ √ 2 +2 1/ √ 2 ... e.s.e.      vrr 1 52 5 12 6 .2 0013 82 0000 92 3 001399 000031 29 1 52 5 12 6.5 000474 0000 32 9 000498...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 4 pptx

Matematik simulation and monte carlo with applications in finance and mcmc phần 4 pptx

...  2 G/X 2 =−1/X 2 , and G/t =0. Using Itô’s lemma, dG = G X dX + G t dt + 1 2 b 2  2 G X 2 dt = dX X −  2 X 2 dt 2X 2 = Xdt +XdB X −  2 dt 2 =   −  2 2  dt +dB Comparing this with Equation (6.3), ... R 2 , W 1 =  −ln R 1  2/ 3  W 2 =  −ln R 2  2/ 3  122 Simulation and finance simulation. Then for a path in the jth stratum,...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 5 ppsx

Matematik simulation and monte carlo with applications in finance and mcmc phần 5 ppsx

... 23 49 0514 24 04 0 028 2 (171,544)  2 600 7168 0390 72 25 00390 (51,164)  2 660 22 74 0 28 3 23 09 00096 (447,1 420 )  2 720 2 74 0100 2 87 00 029 7 (585,1869) a 10 000 paths. b 25 replications, ... 2. 803064014] [1.5968 724 39, 2. 03 624 3709, 2. 0 429 995 52, 2. 341445360, 2. 513656874, 2. 9879858 32, 3.185 727 007, 3.370 120 4 32] [0.9566889486, 1.35 824...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 6 doc

Matematik simulation and monte carlo with applications in finance and mcmc phần 6 doc

... is   − f   x 2 +y 2  / 2  x 2 +y 2 dy =   0 f   x 2 +y 2  /  x 2 +y 2  dy and similarly for Y . (a) Here, f XY  x y  =  1/ 2   exp  −x 2 /2 −y 2 /2  , which is separable in x and y, showing that X and ... number in [0,1) insert R= x/61. Answers: (a)  = 60, (b)  = 30. Simulation and Monte Carlo: With applications in fi...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 7 ppt

Matematik simulation and monte carlo with applications in finance and mcmc phần 7 ppt

... j,x1,x2,y1,y2,d; for j from 1 to n do; x1:= rand()/10^ 12; y1:=rand()/10^ 12; x2:=rand()/10^ 12; y2:=rand()/10^ 12; d [ j ] :=sqrt((x1-x2) ^2+ (y1-y2) ^2) ; end do; seq(d [ j ] ,j=1 n); end proc: 2 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 > ... random number generator ‘schrage’. The final execution group sets an (initial) seed and calls ‘expon’ three times. 2 6 6 6 6 6 6 6 4 Simulation...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 8 pot

Matematik simulation and monte carlo with applications in finance and mcmc phần 8 pot

... ¼ 1 52. 688 ‘seed’ ¼ 639156 ‘mean’ ¼ 2. 1670967 62, ‘standard error’ ¼ 0.0 025 07078 421 t4: ¼ 21 .531 2 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 > estimated_vrr:=( .25 07078 421 e -2/ .9 127 721 506e -2) ^( -2) ; estimated_efficiency:=t3*estimated_vrr/t4; estima ted_vrr:=13 .25 528 056 estimated_efficiency:= 12. 620 55880 2 6 6 6 6 6 6 6 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 9 ppt

Matematik simulation and monte carlo with applications in finance and mcmc phần 9 ppt

... 4:mu:=0.15:beta: =2. 5: n: =25 : beta1:=1/beta: bet a2:=evalf(GAMMA(beta1+1)): beta3:=evalf(GAMMA (2/ beta+1)): t0:= [ 3.3,1.4,5.7,3.3,0.1,1 .2, 2.1,5.6,3 .2, 2,6,7.1,3.3, 4.5,5.3, 2. 5,4.4 ,2. 5,4.8,3.5,infinity,infinity,infinit y, infinity,infinity ] : print("_______________________INPUT DATA____________________"); seeda:=87341:seedb:=6 428 7: print("Arriv al ... seed:=rando...

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Matematik simulation and monte carlo with applications in finance and mcmc phần 10 potx

Matematik simulation and monte carlo with applications in finance and mcmc phần 10 potx

... ‘is’, 1.9584973 32 1. 0. 3 .2. 1. 1. 0. 4 .2. 5. 0. 4 .2. 5. 0. 4 .2. 2. 0. 1. 2. 0. 2. 1. .1e2 0. .2. 1 .1e2 0. .2. 1 .2e2 0. .6.4 .2 .1e2 0. .2. 1 prior and posterior densities lambda[10] prior and posterior ... values against iteration number 320 0 3000 28 00 26 00 24 00 22 00 0 1000 20 00 3000 4000 5000 0 20 00 22 00 24 00 26 00 28 00 3000 320 0 0.0015 0.001 0.0...

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