A cute equity exchange simulation

From: John Conover <john@email.johncon.com>
Subject: A cute equity exchange simulation
Date: 9 Jun 2003 01:46:10 -0000




Suppose there is an equity exchange that is in the doldrums. Suppose
that the Shannon probability of all equity time series is p =
0.50706713781, and the deviation of the marginal increments of all
equity time series is rms = 0.0283-there is no clear advantage of any
stock over any other. (The median values, measured over the last
century for the daily closes of all equities in the US equity markets
was about p = 0.51, and rms = 0.02, giving an average of the marginal
increments of 0.0004, which is optimal.) Note that all that was done
was to increase the rms, over the empiricals from the last century, by
about sqrt (2) = 1.414, (which, by the way, is were the rms has been
running on the US exchanges since mid 2000.)

Note that the average daily gain is positive, (0.0004,) and p > 0.5,
(0.50706713781). Does that mean that the equities in the exchange will
increase in gain?

Its counter intuitive, but the answer is no. In point of fact, the
gain for each equity is 0.999999501, (which is as close to unity as I
could get it; its from the G = ((1 + rms)^p) * ((1 - rms)^(1 - p))
equation.)

If you make a 300 record file, (call it toy):

    0, p = 0.50706713781, f = 0.0283
    1, p = 0.50706713781, f = 0.0283
    2, p = 0.50706713781, f = 0.0283
    3, p = 0.50706713781, f = 0.0283
        .
        .
        .
    297, p = 0.50706713781, f = 0.0283
    298, p = 0.50706713781, f = 0.0283
    299, p = 0.50706713781, f = 0.0283

and then do the following simulation command:

    tsinvestsim toy 100000 | tsinvest -i -t -j -D 0.99

the output file will look like:

    0       1.00    1000.00
    1       1.00    1000.00
    2       1.00    1000.00
    3       1.00    1014.15
    4       1.00    1023.91
    5       1.00    1026.23
    6       1.00    1031.45
    7       1.00    1032.04
    8       1.00    1026.20
    9       1.00    1047.69
    10      1.00    1055.99
        .
        .
        .
    99990   445812853.71    1121509574374138624.00
    99991   452932492.58    1118970476697741568.00
    99992   457366276.37    1125937186885675392.00
    99993   457902652.40    1140594637184596480.00
    99994   433244855.97    1136721177796702592.00
    99995   428366633.48    1132217488490292480.00
    99996   429892231.06    1144393355361525248.00
    99997   435642002.06    1143745628722392448.00
    99998   419691487.07    1139214108541371904.00
    99999   419799293.93    1159847554475297280.00

meaning that if you invested one thousand dollars in the exchange's
index, at the end of about four centuries, (100,000 trading days is
about 395 calendar years,) you would have 419799293.93 * 1000 =
419,799,293,930.00 dollars. However, if you let tsinvest shuffle its
money around in its portfolio of ten stocks, you would have
1,159,847,554,475,297,280.00 dollars!!!

The distribution of the values of the 300 equities in time interval
99999 is, (zing down to the last one):

    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000000
    0.000001
    0.000001
    0.000001
    0.000001
    0.000003
    0.000003
    0.000003
    0.000006
    0.000006
    0.000006
    0.000011
    0.000012
    0.000014
    0.000017
    0.000019
    0.000026
    0.000026
    0.000030
    0.000036
    0.000041
    0.000045
    0.000057
    0.000058
    0.000060
    0.000072
    0.000076
    0.000093
    0.000102
    0.000124
    0.000127
    0.000142
    0.000144
    0.000148
    0.000152
    0.000193
    0.000205
    0.000295
    0.000320
    0.000336
    0.000340
    0.000342
    0.000361
    0.000367
    0.000402
    0.000461
    0.000489
    0.000619
    0.000687
    0.000807
    0.000931
    0.001119
    0.001231
    0.001288
    0.001371
    0.001516
    0.001802
    0.002110
    0.003314
    0.003575
    0.003593
    0.004199
    0.004334
    0.004350
    0.004485
    0.004563
    0.004706
    0.004773
    0.004897
    0.005345
    0.005708
    0.006866
    0.007152
    0.007812
    0.009876
    0.010641
    0.010881
    0.011418
    0.011860
    0.012532
    0.015791
    0.015962
    0.016219
    0.016625
    0.017535
    0.018039
    0.022152
    0.022467
    0.023279
    0.023627
    0.025395
    0.026039
    0.031708
    0.033075
    0.037987
    0.038692
    0.041970
    0.045991
    0.046345
    0.048287
    0.061647
    0.069352
    0.074653
    0.076090
    0.078894
    0.102207
    0.107705
    0.109604
    0.133914
    0.138558
    0.143377
    0.149093
    0.162783
    0.172695
    0.197362
    0.199488
    0.215071
    0.234364
    0.274556
    0.276983
    0.283503
    0.287825
    0.320333
    0.357794
    0.376475
    0.449699
    0.503194
    0.507238
    0.604762
    0.619065
    0.658060
    0.743598
    0.866489
    0.971548
    1.034036
    1.061962
    1.158218
    1.184615
    1.231090
    1.528714
    1.680228
    1.967346
    2.054743
    2.179320
    2.303673
    2.614281
    2.858407
    3.106997
    3.240102
    3.305816
    3.465036
    3.985862
    4.046277
    4.116390
    4.908092
    5.090732
    5.451927
    5.866275
    6.124538
    6.200465
    7.119669
    7.394575
    7.405781
    7.948520
    7.988411
    8.075786
    8.402285
    9.269292
    10.116763
    11.049315
    13.098633
    14.222985
    14.237552
    14.748766
    19.153911
    20.875269
    22.287625
    23.748523
    28.931972
    35.370262
    39.263971
    44.725109
    45.624084
    45.689237
    47.632635
    52.648633
    55.205386
    56.690869
    61.896891
    68.903480
    74.184430
    79.533489
    85.107324
    85.274202
    85.558765
    87.492165
    93.129219
    100.229488
    109.315616
    111.353530
    112.042332
    117.889399
    119.593678
    125.180268
    126.408082
    149.538382
    155.945846
    174.600421
    181.079965
    192.757648
    195.889364
    216.840736
    271.602360
    321.130354
    404.916302
    420.967199
    463.732703
    511.640853
    515.874994
    535.261594
    560.335203
    611.055917
    659.126088
    679.410219
    712.001572
    772.316643
    831.618462
    840.544020
    992.487132
    993.296917
    1231.049863
    1628.758447
    1785.619924
    2150.844601
    2232.226585
    2564.625443
    3195.959633
    3867.235138
    6090.160795
    7837.266036
    10929.783559
    11598.159284
    12163.228420
    13261.912250
    13711.614665
    18482.897373
    19512.281679
    24624.085761
    28646.983806
    33213.149440
    38612.590757
    54703.104183
    62728.970776
    71958.311637
    98344.104000
    101788.161330
    111625.300001
    127653.107090
    135614.130061
    151161.285437
    181402.421183
    235444.174193
    317760.070900
    364274.796880
    564067.654701
    689679.005046
    814513.514611
    814879.754827
    928684.675264
    1180014.159159
    1253742.277265
    1597348.709067
    2103727.878141
    2574926.625435
    3155277.028218
    3636972.850348
    9872997.205032
    11236038.643421
    15409738.492716
    517013910.342102
    2759172586.901715
    5874488651.945198
    116730993844.217270

meaning that if you picked the right equity-a one in 300 chance-you
would have made 116,730,993,844.217270 dollars, (against the
419,799,293,930.00 dollars if you invested in the exchange's index, or
1,159,847,554,475,297,280.00 dollars if you balanced the portfolio,
daily-which is all tsinvest did with those options; there is no clear
advantage of any stock over any other, the -i means print the index
value, -t means print the time stamp, -j means the index is not to be
balanced-it is a "traditional" index that just sums the values of the
equities at any one time, and -D 0.99 allows the program to invest in
stocks that are depreciating in value-but only if balancing the
portfolio with the stocks will enhance the growth in value of the
portfolio.)

The median gain of stocks in the above table would be, (they all
started with a value of one dollar):

    G = 0.999999501^100000 = 0.951362309

which checks, (stock 150 was 0.866489, 151 0.971548.)

Why did the highest value in the distribution table =
116,730,993,844.217270? Its because it is a log normal distribution,
(ln (116730993844.217270) = 25.4831379266; 0.0283 * sqrt (100000) =
8.94924577828, or the highest valued stock was 25.4831379266 /
8.94924577828 = 2.84751794262 standard deviations, and 2.84751794262
standard deviations is 0.002203080516227658, or 1 in 453.908916971,
and 1 in 454 is very close to 1 in 300.) Which checks. (By the way, if
you take the log of the distribution table, and plot as a standard
deviation histogram, you will find that it is almost a perfect
Gaussian/normal standard deviation distribution, too.)

So, it all checks.

Why did I chose to simulate for 100,000 time intervals?

Its from the tsshannoneffective program:

    tsshannoneffective -c 0.0004 0.0283 100000
    For P = (sqrt (avg) + 1) / 2:
        P = 0.510000
        Pcomp = 0.504659
    For P = (rms + 1) / 2:
        P = 0.514150
        Pcomp = 0.511506
    For P = (avg / rms + 1) / 2:
        P = 0.507067
        Pcomp = 0.500640

which means that at the end of the simulation, tsinvest would have
determined the Shannon probability of all the stocks to within about
1%; 0.500640 / 0.50706713781 = 0.987324878, or about a 99% accuracy.

The point?

It is possible to make money in an equity market where the stock
values are going no where, (or even down.)

In point of fact, it is possible for the portfolio to be worth more,
and grow faster in value, than any stock in the portfolio, (or the
exchange for that matter.)

The point is that moving money around in the portfolio, intelligently,
is a very important investment concept, (in this case, the tsinvest
program was not all that intelligent; all it did was maintain equal
investments in each of ten stocks, daily.)

        John

--

John Conover, john@email.johncon.com, http://www.johncon.com/


Copyright © 2003 John Conover, john@email.johncon.com. All Rights Reserved.
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