The
table below shows the Nov. 30, 2001 closing prices for a
few of the S & P 100 Dec., 2001 Stock Index Options as
given in Barron's. If you knew ahead of time exactly what
the stock market was going to do, all you would have to do
is buy or sell the appropriate option and you could get
very rich very quickly. The bad news is nobody knows what
the stock market is going to do.
An interesting secondary question can be
asked. Is there any combination of buying and/or selling a
mixture of these options (at the given prices) that can
guarantee a profit no matter what the market does?
Interestingly the answer is YES.
In fact, given any set of option prices
(real, arbitrary, real time, closing values, this year,
next year, etc.) there are always buy/sell combinations
that will guarantee a profit no matter what the market
does. There are a few conditions that must be met.
1) Brokerage companies will subtract commissions from the
profit shown by the calculations. (Good news - these are
usually small enough that they are not a problem.)
2) The securities laws restrict some of the combinations.
(Eliminates some of the combinations, but other
combinations are open.)
3) Once you have made your commitment, the options remain
unexercised until they expire.
4) For any combination, you have to execute all of the
orders at (or near) the given price - usually this must be
done simultaneously. (There is a long frustrating story
regarding this. If you are an outside investor, your
orders will probably never be executed. However, this is
an example of how brokerage companies operate in the
financial derivatives markets.)
For now, assume that you can buy or sell at
these actual closing prices. We will show how to calculate
a strategy that can guarantee a profit for any arbitrary
(or real) prices for any group of options. We also assume
that a malevolent manipulator can dictate any subsequent
stock market price after you have made your commitment.
Nov. 30, 2001 closing prices for a few of the S&P 100
Dec. options as reported in Barron's.
Strike
Call Put
Price
Options Options
--------------------------------
580
15.00 10.80
585
11.30 13.00
590
10.20 15.50
First, we construct a table showing the net
change in your finances if you bought (or sold) each of
the above options vs. some of the subsequent possible S
& P 100 prices when the contract expires. (The value
of the S&P 100 when you start does not matter.)
Option
Buy/Sell Strike
Buy/Sell <---- If the S&P goes
to ----->
Action Price
Price
0 560
585 610 1000
-----------------------------------------------------------------
Buy Call 580
15.00 -1,500 -1,500 -1,000
1,500 40,500
Buy Call 585
11.30 -1,130 -1,130 -1,130
1,370 40,370
Buy Call 590
10.20 -1,020 -1,020
-1,020 980 39,980
Sell Call 580
15.00 1,500
1,500 1,000 -1,500 -40,500
Sell Call 585
11.30 1,130
1,130 1,130 -1,370 -40,370
Sell Call 590
10.20 1,020
1,020 1,020 -980 -39,980
Buy Put 580
10.80 56,920
920 -1,080 -1,080 -1,080
Buy Put 585
13.00 57,200 1,200 -1,300
-1,300 -1,300
Buy Put 590
15.50 57,450 1,450 -1,050
-1,550 -1,550
Sell Put 580
10.80 -56,920 -920
1,080 1,080 1,080
Sell Put 585
13.00 -57,200 -1,200 1,300
1,300 1,300
Sell Put 590
15.50 -57,450 -1,450 1,050
1,550 1,550
(In practice,
you would want to include additional options (rows) not
included here (can only improve the final results), and
include additional S&P prices (columns).)
If you look at the table, no single row can
guarantee a profit. In fact if you sell something, and the
final S&P 100 price goes the wrong way, the loss can
be staggering. Nevertheless, a mixed strategy can be
computed that will guarantee a profit. In fact, our
calculations will find the mixed strategy that guarantees
the maximum possible profit assuming the malevolent
manipulator can designate any possible S&P 100 price
when the options are exercised.
The solution method we will use is called
Linear Programming. It is used to find the Maximum or
Minimum value of something within the bounds defined by a
series of constraints. In our case, the value that we will
maximize is: Maximum possible profit vs. any worst
possible final S & P 100 price. The constraints
involved state that our finances must show a profit of at
least this amount no matter what happens to the S & P
100.
First, we define the unknowns in the problem. They will
indicate the proportional amounts of each option contract
to include in our mixed strategy. These proportions will
sum to 1.000. (We could alternately solve for the actual
cash amount invested in each option in our mixed strategy,
but this usually leads to annoying fractions.)
Let X1 = the proportional position in buying the 580 call
at 15.00
Let X2 = the proportional position in buying the 585 call
at 11.30
Let X3 = the proportional position in buying the 590 call
at 10.20
Let X4 = the proportional position in selling the 580 call
at 15.00
Let X5 = the proportional position in selling the 585 call
at 11.30
Let X6 = the proportional position in selling the 590 call
at 10.20
Let X7 = the proportional position in buying the 580 put
at 10.80
Let X8 = the proportional position in buying the 585 put
at 13.00
Let X9 = the proportional position in buying the 590 put
at 15.50
Let X10 = the proportional position in selling the 580 put
at 10.80
Let X11 = the proportional position in selling the 585 put
at 13.00
Let X12 = the proportional position in selling the 590 put
at 15.50
and finally
Let X13 = the guaranteed profit vs. the worst possible
outcome for the S & P
Next, we define what we want to maximize/minimize.
In this case:
Maximize Z = X13
The first five constraint equations state
that our results must be positive for any possible S &
P result. Each equation uses a column from the above
table. The "-X13" term appears in each of the 5 equations
as it must be maximized.
Eq. 1) - If the S & P 100 goes to 0:
-1500X1 -1130X2 -1020X3 +1500X4 +1130X5 +1020X6 +56920X7
+57200X8 +57450X9 -56920X10 -57200X11 -57450X12 -X13 >=
0
etc. through Eq.5)
If the S & P 100 goes to 1000:
40500X1 +40370X2 +39980X3 -40500X4 -40370X5 -39980X6
-1080X7 -1300X8 -1550X9 +1080X10 +1300X11 +1550X12 - X13
>= 0
and finally the sum of the proportions must equal 1.000
Eq. 6)
X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 + X10 + X11 +
X12 = 1
These 6 equations form a Linear Programming
system that can be solved by various packages including
spreadsheets. The solution gives:
X2 (Buy 585 Call at 11.30) = .25
X6 (Sell 590 Call at 10.20) = .25
X9 (Buy 590 Put at 15.50) = .25
X11 (Sell 585 Put at 13.00) = .25
X13 = 35
In English this means: For each package
(mixed strategy) that includes 1/4 of an option contract
as indicated above, you are guaranteed to make a profit of
at least $35.
This solution technique can be used on any
family of options as long as they are for the same
security and expire at the same time. The only restriction
is they can not be exercised prematurely. There is always
a mixed strategy that will guarantee a profit. (In theory
it's possible to have a worst case of "break even", but this
will probably never happen in practice.) The bad news is
that an outside investor must have some brokerage company
execute the mixed strategy on an "all or none" basis.
Unfortunately, this has proven to be virtually impossible.
However, it is an example of the action in derivatives
that many brokerage companies use.
For another example using Linear Programming, please see
the author's web page at:
http://www.durangobill.com/TravelingSalesman/TravelingSalesman.html
The Traveling Salesman Problem
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