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NAG Toolbox: nag_rand_bb_make_bridge_order (g05xe)

 Contents

    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example

Purpose

nag_rand_bb_make_bridge_order (g05xe) takes a set of input times and permutes them to specify one of several predefined Brownian bridge construction orders. The permuted times can be passed to nag_rand_bb_init (g05xa) or nag_rand_bb_inc_init (g05xc) to initialize the Brownian bridge generators with the chosen bridge construction order.

Syntax

[times, ifail] = g05xe(t0, tend, intime, move, 'bgord', bgord, 'ntimes', ntimes, 'nmove', nmove)
[times, ifail] = nag_rand_bb_make_bridge_order(t0, tend, intime, move, 'bgord', bgord, 'ntimes', ntimes, 'nmove', nmove)

Description

The Brownian bridge algorithm (see Glasserman (2004)) is a popular method for constructing a Wiener process at a set of discrete times, t0 < t1 < t2 < ,, < tN < T , for N1. To ease notation we assume that T has the index N+1 so that T=tN+1. Inherent in the algorithm is the notion of a bridge construction order which specifies the order in which the N+2 points of the Wiener process, Xt0,XT and Xti, for i=1,2,,N, are generated. The value of Xt0 is always assumed known, and the first point to be generated is always the final time XT. Thereafter, successive points are generated iteratively by an interpolation formula, using points which were computed at previous iterations. In many cases the bridge construction order is not important, since any construction order will yield a correct process. However, in certain cases, for example when using quasi-random variates to construct the sample paths, the bridge construction order can be important.

Supported Bridge Construction Orders

nag_rand_bb_make_bridge_order (g05xe) accepts as input an array of time points t1 , t2 ,, tN , T  at which the Wiener process is to be sampled. These time points are then permuted to construct the bridge. In all of the supported construction orders the first construction point is T which has index N+1. The remaining points are constructed by iteratively bisecting (sub-intervals of) the time indices interval 0,N+1 , as Figure 1 illustrates:
0 N+1 L 0 0 L 0 0 / 2 L 1 1 L 1 1 / 2 L 2 1 L 2 1 / 2 L 2 1 L 1 1 / 2 + ( ) L 2 1 - L 3 2 L 2 2 L 2 2 L 0 0 / 2 + ( ) L 2 2 - L 3 4 L 1 1 L 0 0 / 2 + ( ) L 1 1 - L 1 1 L 2 2 / 2 + ( ) L 1 1 - L 3 1 L 3 3
Figure 1
The time indices interval is processed in levels Li, for i=1,2,. Each level Li contains ni points L1i,,Lnii where ni2i-1. The number of points at each level depends on the value of N. The points Lji for i1 and j=1,2,ni are computed as follows: define L00=N+1 and set
Lji = J+ K-J/2 where J= max Lkp : 1knp , ​ 0p<i ​ and ​ Lkp < Lji ​ and ​ K = min Lkp : 1knp , ​ 0p<i ​ and ​ Lkp > Lji  
By convention the maximum of the empty set is taken to be to be zero. Figure 1 illustrates the algorithm when N+1 is a power of two. When N+1 is not a power of two, one must decide how to round the divisions by 2. For example, if one rounds down to the nearest integer, then one could get the following:
L 0 0 L 0 0 / 2 L 1 1 L 1 1 / 2 L 2 1 L 2 1 L 1 1 / 2 + ( ) L 2 1 - L 3 2 L 2 2 L 2 2 L 0 0 / 2 + ( ) L 2 2 - L 1 1 L 0 0 / 2 + ( ) L 1 1 - L 1 1 L 2 2 / 2 + ( ) L 1 1 - L 3 1 L 3 3 0 N+1
Figure 2
From the series of bisections outlined above, two ways of ordering the time indices Lji are supported. In both cases, levels are always processed from coarsest to finest (i.e., increasing i). Within a level, the time indices can either be processed left to right (i.e., increasing j) or right to left (i.e., decreasing j). For example, when processing left to right, the sequence of time indices could be generated as:
N+1 L11 L12 L22 L13 L23 L33 L43  
while when processing right to left, the same sequence would be generated as:
N+1 L11 L22 L12 L43 L33 L23 L13  
nag_rand_bb_make_bridge_order (g05xe) therefore offers four bridge construction methods; processing either left to right or right to left, with rounding either up or down. Which method is used is controlled by the bgord argument. For example, on the set of times
t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 T  
the Brownian bridge would be constructed in the following orders:
bgord=1 (processing left to right, rounding down)
T t6 t3 t9 t1 t4 t7 t11 t2 t5 t8 t10 t12  
bgord=2 (processing left to right, rounding up)
T t7 t4 t10 t2 t6 t9 t12 t1 t3 t5 t8 t11  
bgord=3 (processing right to left, rounding down)
T t6 t9 t3 t11 t7 t4 t1 t12 t10 t8 t5 t2  
bgord=4 (processing right to left, rounding up)
T t7 t10 t4 t12 t9 t6 t2 t11 t8 t5 t3 t1 .  
The four construction methods described above can be further modified through the use of the input array move. To see the effect of this argument, suppose that an array A holds the output of nag_rand_bb_make_bridge_order (g05xe) when nmove=0 (i.e., the bridge construction order as specified by bgord only). Let
B = tj : j=movei, i=1,2,,nmove  
be the array of all times identified by move, and let C be the array A with all the elements in B removed, i.e.,
C = Ai : Ai Bj , i=1,2,,ntimes , j=1,2,,nmove .  
Then the output of nag_rand_bb_make_bridge_order (g05xe) when nmove>0 is given by
B1 B2 Bnmove C1 C2 Cntimes-nmove  
When the Brownian bridge is used with quasi-random variates, this functionality can be used to allow specific sections of the bridge to be constructed using the lowest dimensions of the quasi-random points.

References

Glasserman P (2004) Monte Carlo Methods in Financial Engineering Springer

Parameters

Compulsory Input Parameters

1:     t0 – double scalar
t0, the start value of the time interval on which the Wiener process is to be constructed.
2:     tend – double scalar
T, the largest time at which the Wiener process is to be constructed.
3:     intimentimes – double array
The time points, t1,t2,,tN, at which the Wiener process is to be constructed. Note that the final time T is not included in this array.
Constraints:
  • t0<intimei and intimei<intimei+1, for i=1,2,,ntimes-1;
  • intimentimes<tend.
4:     movenmove int64int32nag_int array
The indices of the entries in intime which should be moved to the front of the times array, with movej=i setting the jth element of times to ti. Note that i ranges from 1 to ntimes. When nmove=0, move is not referenced.
Constraint: 1movejntimes, for j=1,2,,nmove.
The elements of move must be unique.

Optional Input Parameters

1:     bgord int64int32nag_int scalar
Default: 1
The bridge construction order to use.
Constraint: bgord=1, 2, 3 or 4.
2:     ntimes int64int32nag_int scalar
Default: the dimension of the array intime.
N, the number of time points in the Wiener process, excluding t0 and T.
Constraint: ntimes1.
3:     nmove int64int32nag_int scalar
Default: the dimension of the array move.
The number of elements in the array move.
Constraint: 0nmoventimes.

Output Parameters

1:     timesntimes – double array
The output bridge construction order. This should be passed to nag_rand_bb_init (g05xa) or nag_rand_bb_inc_init (g05xc).
2:     ifail int64int32nag_int scalar
ifail=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

Errors or warnings detected by the function:
   ifail=1
Constraint: bgord=1, 2, 3 or 4 
   ifail=2
Constraint: ntimes1.
   ifail=3
Constraint: 0nmoventimes.
   ifail=4
Constraint: intime1>t0.
Constraint: intimentimes<tend.
Constraint: the elements in intime must be in increasing order.
   ifail=5
Constraint: moveintimes for all i.
Constraint: movei1 for all i.
   ifail=6
Constraint: all elements in move must be unique.
   ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
   ifail=-399
Your licence key may have expired or may not have been installed correctly.
   ifail=-999
Dynamic memory allocation failed.

Accuracy

Not applicable.

Further Comments

None.

Example

This example calls nag_rand_bb_make_bridge_order (g05xe), nag_rand_bb_init (g05xa) and nag_rand_bb (g05xb) to generate two sample paths of a three-dimensional free Wiener process. The array move is used to ensure that a certain part of the sample path is always constructed using the lowest dimensions of the input quasi-random points. For further details on using quasi-random points with the Brownian bridge algorithm, please see Brownian Bridge in the G05 Chapter Introduction.
function g05xe_example


fprintf('g05xe example results\n\n');

% Get information required to set up the bridge
[bgord,t0,tend,ntimes,intime,nmove,move] = get_bridge_init_data();

% Make the bridge construction bgord
[times, ifail] = g05xe( ...
                        t0, tend, intime, move, 'bgord', bgord);

% Initialize the Brownian bridge generator
[rcomm, ifail] = g05xa( ...
                        t0, tend, times);

% Get additional information required by the bridge generator
[npaths,d,start,a,term,c] = get_bridge_gen_data();

% Generate the Z values
[z] = get_z(npaths, d, a, ntimes);

% Call the Brownian bridge generator routine
[z, b, ifail] = g05xb( ...
                       npaths, start, term, z, c, rcomm, 'a', a);

% Display the results
for i = 1:npaths
  fprintf('Weiner Path %d, %d time steps, %d dimensions\n', i, ntimes+1, d);
  w = transpose(reshape(b(:,i), d, ntimes+1));

  ifail = x04ca('G', ' ', w, '');

  fprintf('\n');
end



function [bgord,t0,tend,ntimes,intime,nmove,move] = get_bridge_init_data()
  % Set the basic parameters for a Wiener process
  t0 = 0;
  ntimes = int64(10);

  % We want to generate the Wiener process at these time points
  intime = 1.71*double(1:ntimes) + t0;
  tend = t0 + 1.71*double(ntimes + 1);

  % We suppose the following 3 times are very important and should be
  % constructed first. Note: these are indices into intime
  nmove= int64(3);
  move = [int64(3), 5, 4];
  bgord = int64(3);

function [npaths,d,start,a,term,c] = get_bridge_gen_data();
  % Set the basic parameters for a non-free Wiener process
  npaths = int64(2);
  d = 3;
  a = int64(0);
  start = zeros(d, 1);
  term  = zeros(d, 1);

  % As a = 0, term need not be initialized

  % We want the following covariance matrix
  c = [ 6,   1,  -0.2; 
        1,   5,   0.3;  
       -0.2, 0.3, 4  ];

  % Cholesky factorize of the covariance matrix c
  [c, info] = f07fd('l', c);

function [z] = get_z(npaths, d, a, ntimes)
  idim = d*(ntimes+1-a);

  % We now need to generate the input pseudorandom points

  % First initialize the base pseudorandom number generator
  state = initialize_prng(int64(6), int64(0), [int64(1023401)]);

  % Scrambled quasi-random sequences preserve the good discrepancy
  % properties of quasi-random sequences while counteracting the bias
  % some applications experience when using quasi-random sequences.
  % Initialize the scrambled quasi-random generator.
  [iref, state] = initialize_scrambled_qrng(int64(1), int64(2), ...
                                            idim, state);

  % Generate the quasi-random points from N(0,1)
  xmean = zeros(idim, 1);
  std   = ones(idim, 1);
  [z, iref, ifail] = g05yj( ...
                            xmean, std, npaths, iref);
  z = z';

function [state] = initialize_prng(genid, subid, seed)
  % Initialize the generator to a repeatable sequence
  [state, ifail] = g05kf( ...
                          genid, subid, seed);


function [iref, state] = initialize_scrambled_qrng(genid,stype,idim,state)
  iskip = int64(0);
  nsdigits = int64(32);
  [iref, state, ifail] = g05yn( ...
                                genid, stype, int64(idim), ...
                                iskip, nsdigits, state);
g05xe example results

Weiner Path 1, 11 time steps, 3 dimensions
              1          2          3
  1     -2.1275    -2.4995    -6.0191
  2     -6.1589    -1.3257    -3.7378
  3     -5.1917    -3.1653    -6.2291
  4    -11.5557    -5.9183    -5.9062
  5     -9.2492    -5.7497    -4.2989
  6     -6.7853   -13.9759    -0.8990
  7    -12.7642   -15.6386    -3.6481
  8    -12.5245   -11.8142     3.3504
  9    -15.1995   -15.5145     0.5355
 10    -16.0360   -14.4140     0.0104
 11    -22.6719   -14.3308    -0.2418

Weiner Path 2, 11 time steps, 3 dimensions
              1          2          3
  1     -0.0973     3.7229     0.8640
  2      0.8027     8.5041    -0.9103
  3     -3.8494     6.1062     0.1231
  4     -6.6643     4.9936    -0.1329
  5     -6.8095     9.3508     4.7022
  6     -7.7178    10.9577    -1.4262
  7     -8.0711    12.7207     4.4744
  8    -12.8353     8.8296     7.6458
  9     -7.9795    12.2399     7.3783
 10     -6.4313    10.0770     5.5234
 11     -6.6258    10.3026     6.5021


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