December 21, 2012 Options Expirations and Update

Closed:
 Pos    Symbol                   Price     Comm       Net
 -2 RIG 22DEC12 47.0 C            0.00     0.00        0.00
     Basis 11/19/2012:                              (199.22)
     Profit/(Loss):                                  199.22

 -5 CREE 22DEC12 15.0 P           0.00     0.00        0.00
     Basis 05/21/2012:                              (473.57)
     Profit/(Loss):                                  473.57

     Value 08/31/2012:                               (68.97)

     Post-August Profit/(Loss):                       68.97

 -4 DOW 22DEC12 25.0 P            0.00     0.00        0.00
     Basis 04/26/2012:                              (338.85)
     Profit/(Loss):                                  338.85

     Value 08/31/2012:                              (248.12)

     Post-August Profit/(Loss):                      248.12

 -3 NE 22DEC12 30.0 P             0.00     0.00        0.00
     Basis 04/23/2012:                              (496.72)
     Profit/(Loss):                                  496.72

     Value 08/31/2012:                              (199.08)

     Post-August Profit/(Loss):                      199.08

 -3 POT 22DEC12 32.5 P            0.00     0.00        0.00
     Basis 04/23/2012:                              (387.82)
     Profit/(Loss):                                  387.82

     Value 08/31/2012:                              (150.20)

     Post-August Profit/(Loss):                      150.20


 -5 TIE 22DEC12 10.0 P            0.00     0.00        0.00
     Basis 04/23/2012:                              (222.37)
     Profit/(Loss):                                  222.37

     Value 08/31/2012:                              (142.82)

     Post-August Profit/(Loss):                      142.82

Also since the last update, $7,500.00 was withdrawn from the account on December 4, $112.50 in dividends was paid on December 1 for 500 shares INTC, $82.50 was paid December 12 on 300 shares WAG, $142.00 was paid December 14 on 400 shares WM, $172.00 in dividends became payable December 12 on 400 shares ARCC, $102.00 became payable December 18 on 200 shares CSE, $10.00 became payable December 5 on 100 shares FTR, $190.00 became payable December 20 on 1,000 shares GE, $6.56 interest accrued and $8.33 was paid.

The Black-Scholes Risk-Neutral Pricing Probability Distribution Function

I wrote previously that the Black-Scholes options pricing model replaces the equity drift μ with r - ½σ²,  where r is the riskless interest rate and σ is the stochastic element of the equity's price movement. This substitution has the effect of eliminating the equity drift coefficient from the model, and obviating the need to decide what the drift coefficient actually is.

The reasoning given by Black and Scholes in their paper that introduced their model (as well as one of the very first uses of risk-neutral pricing generally) were (1) that, through continuous rebalancing, the second-order (dz²) stochastic terms in the return on a portfolio became riskless (this argument implicitly relies upon Itō's Lemma, although the paper did not explicitly refer to it), and (2) that even if they were not riskless due to discontinuity, the second-order terms should be subject to the riskless interest rate because they are uncorrelated with the market rate of return. Thus, they argued, second-order terms must be priced with the riskless interest rate directly, and any risk premium must apply only to any first-order stochastic terms.

This can only be achieved by adapting only the drift coefficient -- and not the stochastic coefficient -- in constructing a risk-neutral probability distribution. This means replacing the equity drift μ with r - ½σ².

And this is all roughly consistent with traditional utility theory.

Delta Hedge

A delta hedge is a portfolio made from two or more distinct securities that are related to the same underlying security. The delta hedge is designed to cancel out, at least instantaneously, the first order relationship (delta) of any constituent securities to the underlying security.

Itō's Lemma

Itō's Lemma is a theorem of stochastic calculus that holds that within a closed integral, dz² can be replaced by dt, where dz is a stochastic variable with order of magnitude equal to the square root of dt. The Lemma is sometimes erroneously stated as "dz² equals dt," which is not generally true. Integration, with continuity, invokes the Law of Large Numbers. In the absence of continuity the variance of dz² is proportional to Δt, length of measurement intervals taken over the range.

Itō's Lemma is significant in finance because it provides the basis according to which a delta hedge is assumed to be riskless, an assumption that is essential to the Black-Scholes Equation.

The Lognormal Distribution and Risk-Neutral Pricing

I wrote previously that the ergodic property of the normal distribution is so useful that it often makes sense to assume a normal distribution even in the face of evidence to the contrary.

Before going to that extreme, however, it is sometimes possible to arrive at a normal distribution by looking at a function of an original variable rather than the variable itself. One example of this is the lognormal distribution, which is a distribution whose log is a normal distribution. In finance, the future price of a stock is often considered to have a lognormal distribution, which gives the rate of return on the stock a normal distribution.

In considering a lognormal distribution, we generally refer to aspects of its log. In particular, we usually define a particular lognormal distribution based upon the mean, μ, and variance, σ², of the log.

There are any number of things to be known about lognormal distributions, but the most important fact about them for my purposes is that the expected value of a lognormal distribution is exp(μ + ½σ²).

Getting back to finance, the future price of a stock at time t can be considered to have a lognormal distribution with log-mean lnS + μt and log-variance σ²t, where S is the price of the stock at time 0. (here I have effectively used μ and σ² as the mean and variance of the instantaneous rate of return of the stock, so that at any given point in time in the future t the rate of return on the stock will have mean μt and variance σ²t). This gives the expected value of the stock at time t as exp(lnS + μt + ½σ²t).

Under a risk-neutral pricing regime, however, the expected future price of the stock should be exp(lnS + rt), where r is the riskless interest rate. So if we want to preserve the lognormal distribution of the stock price, we somehow have to adapt our real world expectations into risk-neutral probabilities so that exp(lnS + μt + ½σ²t) equals exp(lnS + rt), or more simply so that μ + ½σ² equals r.

One method to accomplish this is simply to replace μ with r - ½σ². And this is precisely what the Black-Scholes options pricing model does, about which more later.

Risk Arbitrage

Conventional arbitrage is most succinctly defined as creating a portfolio with zero cost that has no possibility of a negative future value, and at least some possibility of a positive future value. There would be no reason that an investor would not create as much of this portfolio as possible -- it costs zero -- and maximize his possible future value.

Conventional arbitrage is riskless: there is no possibility of any loss. There are sometimes references to "risk arbitrage," which is (vaguely) taking a position that has a better return than its risk profile would suggest.

I have developed a more precise definition of risk arbitrage, based on the ability to short a portfolio with very little likelihood of loss. In particular, if for any positive x, positive or negative y, and positive z, a portfolio can be created to short for which the probability of any future positive value at all is less than x, the expected rate of return is less than y, and the maximum future value is less than z, then an opportunity for risk arbitrage exists.

This definition relies on the fact that prices are set at the margin: if any investor is willing to entertain the possibility of additional risk, then regardless of how small z is set (which will tend to diminish the size of the short position taken), the price paradigm will be broken.

Basically, the choice of z sets the maximum loss from shorting the portfolio, and then x and y can be selected to make arbitrarily remote the probability of any loss and arbitrarily small the expected loss: if no one is interested in selling short a portfolio that has 1% chance of having any positive future value at all at a given future point in time and that has -50% expected rate of return, how about a portfolio with 0.5% chance of having any positive future value and that has -75% expected rate of return? And the probability of future value, and the expected future value, can be continually reduced until a reasonable investor would not be able to resist at least a taste.

Laws of Price: Prices Are Set At The Margin

In a free market, a prevailing price means just one thing: that the demand and the supply are (for a moment) equal at that price.

In a grand sense, this is not a very powerful meaning: we conventionally think of the value of portfolios as the sum of the products of the positions in every investment and the last price of the particular investment. So with 1,000,000 shares of IBM trading at $200.00 a share, this would have a value of $200,000,000.00. But if someone holding this position were to try to convert it to cash all at once, he would almost certainly net less than $200,000,000.00: his position is equivalent to about 25% of the average daily volume of the stock, and it is unlikely that buyers would arrive conveniently to absorb the additional sales that he has introduced, and leave the stock price unaffected.

But in a microscopic sense, it is quite a powerful meaning. In particular, if there is reason to believe that a realistic investor would want to buy rather than sell (or vice versa) a particular position at a given price, then it does not matter that this tendency would be exhausted with just a tiny position: the price cannot be expected to hold, other things being equal.

The latter fact is central to my understanding of the pricing of financial risk.

November 30, 2012 Update

    Cash:                             $     15.48
    Accrued Dividends:                     337.00
    Interest Accruals:                      (7.50)
    Stocks:                            120,665.58
    Options:                            (8,294.33)

  Account Value:                      $112,716.23

  Equity:                             $120,912.18
  Margin Requirement:                   73,669.98
  Available Funds:                      47,242.20

  Regulation T Margin Requirement:     102,157.88
  Special Memorandum Acct:              37,567.91

The account value of $112,716.23 compares with the value a month earlier of  $114,712.06, a return of -1.74%. However, this does not take into account $2,500.00 withdrawn from the account during the month. Adding this in to the final value gives a return for the month of 0.44%.

This compares with the change in the S&P 500 Index from 1,412.16 to 1,416.18. Adding an estimate of a quarter percent dividend payment (one twelfth of 3%), this gives a return of 0.53% for the S&P 500, so my portfolio underperformed the market in the month of November.

November 30, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -2    HES 18MAY13 37.5 P         0.85     1.52     (168.48)

November 29, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -4    MDT 18MAY13 30.0 P         0.20     1.52      (78.48)

November 28, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -3    WFC 20JUL13 25.0 P         0.57     1.14     (169.86)

November 27, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -3    KSS 20JUL13 40.0 P         1.05     3.70     (311.30)

November 26, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -2    TGT 20JUL13 50.0 P         0.82     0.76     (163.24)

November 23, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net
 -2    FDX 20JUL13 65.0 P         1.15     0.76     (229.24)

November 19, 2012 Trades

Opened:
 Pos    Symbol                   Price     Comm       Net
 -4    BMY 19JAN13 33.0 C         0.35     3.04     (136.96)

 -2    RIG 22DEC13 47.0 C         1.00     0.78     (199.22)

November 16, 2012 Options Expirations and Update

Closed:
 Pos    Symbol                   Price     Comm       Net
 -4 BMY 17NOV12 35.0 C            0.00     0.00        0.00
     Basis 10/19/2012:                               (64.96)
     Profit/(Loss):                                   64.96


 -2 RIG 17NOV12 50.0 C            0.00     0.00        0.00
     Basis 10/19/2012:                              (231.24)
     Profit/(Loss):                                  231.24


 -2 COP1 17NOV12 60.0 P           0.00     0.00        0.00
     Basis 03/22/2012:                              (294.55)
     Profit/(Loss):                                  294.55


     Value 08/31/2012:                               (43.43)

     Post-August Profit/(Loss):                       43.43


 -2 HES 17NOV12 40.0 P           0.00     0.00        0.00
     Basis 03/22/2012:                              (347.08)
     Profit/(Loss):                                  347.08


     Value 08/31/2012:                              (145.47)

     Post-August Profit/(Loss):                      145.47


 -2 MDT 17NOV12 29.0 P           0.00     0.00        0.00
     Basis 03/23/2012:                              (225.10)
     Profit/(Loss):                                  225.10


     Value 08/31/2012:                               (44.41)

     Post-August Profit/(Loss):                       44.41

Also since the last update, $112.40 in dividends was paid on November 15 for 200 shares of PG, and $8.98 interest accrued and $3.98 was paid.

November 9, 2012 Trades

Closed:
 Pos    Symbol                   Price     Comm       Net
 400 STX SEAGATE TECH PLC        29.61     0.24   11,623.76
     Basis 10/19/2012:                            11,160.00 
     Profit/(Loss):                                  463.76

 -4 STX 17NOV12 27.0 C            2.61     0.00   (1,044.00)
     Basis 10/22/2012:                              (796.95)
     Profit/(Loss):                                 (247.05)

Opened:

 Pos    Symbol                   Price     Comm       Net
 -5 STX 19JAN13 24.0 P            0.38     3.80     (186.20)

The STX call options were exercised against me prior to their expiration date in order to capture a dividend with ex-dividend date of October 9.

November 7, 2012 Trade and Update

Opened:
 Pos    Symbol                   Price     Comm       Net

 -5    CE 22JUN13 25.0 P          0.65    (0.20)     (325.20)

On November 2, $2,500.00 was withdrawn from the account.

On November 1, $136.00 was paid on 400 shares of BMY; on November 5, a dividend of $112.50 became payable December 1 on 500 shares of INTC; on November 7, $82.51 became payable December 12 on 300 shares of WAG; and since the last update $3.98 in accrued interest was paid and an additional $4.92 interest was accrued.

October 31, 2012 Update

    Cash:                             $(10,702.86)
    Accrued Dividends:                     454.40
    Interest Accruals:                      (2.50)
    Stocks:                            132,831.48
    Options:                            (7,868.46)

  Account Value:                      $114,712.06

  Equity:                             $122,450.40
  Margin Requirement:                   69,555.99
  Available Funds:                      52,894.41

  Regulation T Margin Requirement:     101,076.94
  Special Memorandum Acct:              38,138.34

Interest of $2.50 accrued on margin loan since the last update.

The account value of $114,712.06 compares with the value a month earlier of  $115,859.78, a return of -0.99%. However, this does not take into account $2,500.00 withdrawn from the account during the month. Adding this in to the final value gives a return for the month of 1.17%.

This compares with the change in the S&P 500 Index from 1,440.67 to 1,412.16. Adding an estimate of a quarter percent dividend payment (one twelfth of 3%), this gives a return of -1.73% for the S&P 500, so my portfolio outperformed the market in the month of October.

The Normal Distribution and Ergodicity

The normal distribution, which is represented by the familiar bell curve, is probably the most important probability distribution in statistics. The reason for this is the Central Limit Theorem, which holds that the sum of a large number of identically distributed but independent random outcomes will tend toward having a normal distribution as the number of included results increases, regardless of their original probability distribution.

For the purposes of finance, an important aspect of the Central Limit Theorem is that normal distributions will be ergodic, which is to say that they will exhibit the fractal quality of having indistinguishable characteristics regardless of at what scale they are viewed: a variable that moves with instantaneous, normally distributed perturbations will create a time path that looks the same whether you are looking at movements over one minute, one day, one month, or several years. The reason for this is that, as with every other sort of variable, sums of normally distributed variables tend to be normally distributed variables; the exception is that normally distributed variables also start that way.

To a very broad degree in finance, measurement time sequences are arbitrary. There is no reason to think that the "proper" span of time over which to consider results is a minute, a day, a month, or a year. There are some cosmological conditions -- such as the passing of night and day and the changing of the seasons -- and some social conditions -- such as regularly scheduled weekends and holidays during which financial and economic activity is restricted -- that will create regular cycles that might be taken into account for the purpose of measuring financial results, but beyond this there is no reason to think that any span of measurement is better than any other.

The usefulness of the normal distribution's ergodic property is so great that, in my estimation, it is often worthwhile to use the distribution even when it is known not to match experience for the purpose to which it is put.

October 25, 2012 Trade and Update

Opened:
 Pos    Symbol                   Price     Comm       Net

 -2    NSC 22JUN13 50.0 P         1.35     0.02     (269.98)

Also on October 25, a $170.00 dividend was paid on 1,000 shares of GE.

October 23, 2012 Trade

Opened:
 Pos    Symbol                   Price     Comm       Net

 -3    HON 22JUN13 90.0 P         0.90     2.28     (267.72)

October 22, 2012 Trades

Opened:
 Pos    Symbol                   Price     Comm       Net
 -4    BMY 17NOV12 35.0 C         0.17     3.04      (64.96)

 -5    INTC 20NOV13 25.0 C        0.43     3.80     (211.20)

 -2    RIG 17NOV12 50.0 C         1.16     0.76     (231.24)

 -4    STX 17NOV12 27.0 C         2.00     3.05     (796.95)

Probability Distribution Functions and Random Variables

A probability distribution function (p.d.f.) is the collected measure of the likelihoods of each possible outcome of a random event. So a p.d.f. for the future price of a particular stock would give a likelihood of each possible future stock price, from zero on up.

Probability distribution functions have a couple qualities:

1. they must be strictly non-negative; and
2. the sum of all probabilities under a p.d.f. must be one.

If a random variable has a known p.d.f., two important values can be determined for it: its expected value, or mean, which is sometimes designated with the Greek letter μ; and variance, which is designated with σ². Variance is the expected value of the square of the difference between a random variable and its expected value.

There are a lot of things of interest about mean and variance, but for my purpose, only a couple are important.

First, the square root of variance, σ, or standard deviation, can be used as a measure of confidence intervals for a random variable: for a normally distributed variable, for example, the span within about 1.96 standard deviations of the mean of the variable forms a 95% confidence interval.

Second, both mean and variance are additive, which is to say that if X and Y are random variables, then generally the mean of X+Y is the mean of X plus the mean of Y, and the variance of X and Y is the variance of X plus the variance of Y. (The latter isn't quite true, because if X and Y are not independent -- the outcome of X affects the p.d.f. of Y -- then the variance of X+Y is the variance of X plus the variance of Y plus twice the covariance of X and Y. The covariance of two random variables is the expected value of the product of the differences between the variable and their respective means. I'll almost always be assuming independence between variables, so covariance won't matter to me much.)

In combination, these two factors create an important effect: the expected value for a sum of identically distributed independent variables grows with the number of variables included in the sum, while confidence intervals for this sum grow with the square root of the number of variables included in the sum. This gives the Law of Large Numbers: the average of a number of outcomes of independent variables from an identical distribution will approach their expected value.

Risk-Neutral Pricing

I have previously introduced the concept of the "risk premium" in investing, which holds that "risky" investments should have a higher expected rate of return than "non-risky" investments. In that earlier entry, I noted that Utility Theory provides a framework for explaining why the risk premium should exist. In this entry, I will try to explain a useful way of quantifying the disposition of risk premium: "risk-neutral pricing."

Typically, the risk premium will be spoken of in terms of "expected rate of return," as in, "the expected rate of return on common stocks is around 6%, while the expected rate of return on cash is around 1%." The higher expected rate of return stated here for stocks as opposed to cash indicates a higher risk premium for stocks.

However, when option securities are considered, this way of thinking runs aground. We might consider a call option, for example, that pays in dollars the amount (if any) by which a particular stock index exceeds a given value at close of trading on a particular day, or nothing if the stock index is less than or equal to the value. But now how do we come up with an expected rate of return for this option?

If we look at the Put-Call Parity equation,

     C - P = S - X * exp(-rT),

we see that on the right hand side of the equation are terms, S and X * exp(-rT), that should have the expected returns of stocks and of cash, respectively (cash being a risk-free asset, subject to the risk-free interest rate of r).

So what if we treat the call as the difference between the index value -- discounted at the expected returns on stocks -- and a riskless payment of the strike price -- discounted at the risk-free interest rate -- on the expiration date?

This method falls apart pretty quickly. Suppose we look at just a piece of the call using this perspective: the portion from where the index equals the strike price to where it's the strike price plus one. Let's suppose also that the strike price is 1000 and the expiration date is one year in the future. So the value of the stock piece, using the expected rates of return above, will be between 1000 and 1001 discounted by 6%, or between about 943.40 and 944.34. But the value of the risk-free piece will be 1000 discounted by 1%, or about 990.10. This suggests that the value of this portion of the call option will be between -46.70 and -45.76: negative values for something that can only ever result in positive cash flow! No rational person will give you money to accept the possibility that he might give you more money later on.

The way around this is to discount everything at the risk-free interest rate: both the stock portion and the strike price portion. This gives the value of the portion of the call option we're looking at as being between 0 and 0.99, which is very consistent with the value at the end of the year being between 0 and 1.

But where does the risk premium appear?

The risk premium appears in adjustments to the probabilities of different outcomes. In particular, prices will be determined using probabilities that are different from actual expectations.

In looking at the portion of the call option where the final index value is between the strike price and the strike price plus one, I never considered the probability of this outcome: I essentially took each potential outcome -- from the index being equal to the strike price up to being that value plus one -- as given, and looked at what the value of the option would be under that outcome. To get an actual value of the call option, I'd have to assign a probability to each of the outcomes, and generate a weighted average for the option's value under all possible outcomes. In essence, the risk premium on stocks is created because the pricing probability assumes that high returns on stocks are less likely than actual expectations.

So, why use the risk-less interest rate rather than some other rate?

First of all, it would probably be more accurate to use actual expectations, and then have a different expected rate of return apply to each possible outcome. But this would create a mess: how do you figure out what expected rate of return to apply to a given outcome, and from where (without a LOT of work) do you get actual expectations?

Risk-neutral pricing takes advantage of the fact that prices based on uncertain events are based on the product of the probability of given outcomes and the expected rate of return that applies to that outcome. So rather than (more accurately) using actual expectations for the probabilities and some yet-to-be-determined expected rate of return for each outcome, risk-neutral pricing uses a single expected rate of return (the risk-free interest rate) and adjusted probabilities to come up with the same price that would result from the theoretically more accurate method of using actual expectations and variable expected rates of return.

So, again, why use the risk-less interest rate rather than some other rate?

The class of securities that by definition earn the risk-free interest rate -- riskless securities -- place some constraints on the adjusted pricing probabilities: the price indicated, under whatever pricing algorithm we use, for a fixed amount paid under all possible outcomes must be consistent with the risk-free interest rate. If we try to do this using some other interest rate, we will have to have our adjusted probabilities sum to less than 1 if we use an interest rate lower than the risk-free interest rate, and we will have to have our adjusted probabilities sum to more than 1 if we use an interest rate higher than the risk-free rate. The adjusted probabilities would not be proper probability distribution functions, because a proper probability distribution function will sum to exactly 1. And, if a function that did not sum to 1 was used, it would create immediate arbitrage potential in either selling a payoff under all outcomes if the function sums to less than 1, or buying a payoff under all outcomes if the function sums to more than 1

So, it is ultimately simplicity that drives us to use a single interest rate and adjusted probabilities rather than variable expected rates of returns and actual expectations. Then, having limited ourselves in this way out of concern for simplicity, we are limited to using the risk-free interest rate as our single expected rate of return for the reason given above.

Finally, the reason this method is called "risk-neutral pricing" is that, using the adjusted pricing probabilities, all securities are assumed to have an equal expected rate of return, which is consistent with a risk-neutral market.

Put-Call Parity

The "Put-Call Parity" equation is an instance of the Law of One Price. Its mathematical form is

     C - P = S - X * exp(-rT),

where S is the price of a stock at time 0, C is the price at time 0 of a European call option on S with strike price X and expiration time T, P is the price at time 0 of a European put option on S with strike price X and expiration time T, and r is the risk-free interest rate (assumed to be constant).

The term X * exp(-rT)in the equation is constant, and it represents the value at time 0 of the amount X paid with certainty at time T. Figuring out the value of a call and a put with the given strike for any given price of the stock on the expiration date will show that being long such a call and short such a put will always have the save payoff at time T as the stock itself less a payment of X at the same instant, which invokes the Law of One Price.

Put-Call Parity is model independent, meaning that it will hold regardless of under what model prices are determined. Considered differently, any model that violates Put-Call Parity cannot be realistic.

Laws of Price: The Law of One Price

I think it's a useful exercise to try clearly to state as many requirements as possible that apply to efficient free market prices. So from time to time I'll devote a post to one or more of these, which I will call "Laws of Price."

The first that I'll look at is a very widely known law with many implementations: the Law of One Price.

Very simply, the Law of One Price states that if two different portfolios of securities have exactly the same payoff at a future date under all possible outcomes, then they must have the same price. Stated differently, there can be only one price for a given pattern of future cash flows, regardless of how the pattern is achieved.

So, a bet that pays $1 if the Steelers beat the Redskins this coming Sunday, plus a bet that pays $1 if the Redskins beat the Steelers in the same game, plus a bet that pays $1 in the event of a tie in the game, should have the same price as $1 paid after the game Sunday with certainty.* If they don't, then a guaranteed profit can be made by selling the more expensive position and buying the less expensive one: simple arbitrage. (The Law of One Price is sometimes referred to with the qualification "no arbitrage," or "arbitrage free.")

* -- These bets will not in fact add up to the value of $1 paid with certainty, but this is because the sports betting market is not efficient: the bookies and the odds-makers arrange to take a percentage of each bet as their compensation, so making all of these bets will cost more than $1 paid with certainty. Also, the "frictional costs" -- costs associated with transaction fees or expenses from acquiring or disposing of positions -- of attempting arbitrage will allow some deviation of prices away from a singular price. But the prices cannot stray too far apart.

October 19, 2012 Options Expirations, Trades, and Update

Closed:
 Pos    Symbol                   Price     Comm       Net
 -4 BMY 20OCT12 34.0 C            0.00     0.00        0.00
     Basis 09/24/2012:                              (102.48)
     Profit/(Loss):                                  102.48

 -2 RIG 20OCT12 50.0 C            0.00     0.00        0.00
     Basis 09/24/2012:                              (150.48)
     Profit/(Loss):                                  150.48

 -3 WAG 20OCT12 33.0 C            2.84     2.28      854.28
     Basis 05/21/2012:                              (457.72)
     Profit/(Loss):                                 (396.56)

     Value 08/31/2012:                              (940.89)

     Post-August Profit/(Loss):                       86.61

 -3 DD 20OCT12 40.0 P             0.00     0.00        0.00
     Basis 02/29/2012:                              (288.55)
     Profit/(Loss):                                  288.55

     Value 08/31/2012:                               (20.29)
     Post-August Profit/(Loss):                       20.29

 -5 INTC 20OCT12 25.0 P           3.735    0.00    1,867.50
     Basis 08/17/2012:                              (242.70)
     Profit/(Loss):                               (1,624.80) 

     Value 08/31/2012:                              (494.90)
     Post-August Profit/(Loss):                     (494.90)

 -3 SNDK 20OCT12 35.0 P           0.00     0.00        0.00
     Basis 02/21/2012:                              (554.08)
     Profit/(Loss):                                  554.08

     Value 08/31/2012:                              (164.04)
     Post-August Profit/(Loss):                      164.04

 -4 STX 20OCT12 28.0 P            0.10     0.00       40.00
     Basis 08/21/2012:                              (208.96)
     Profit/(Loss):                                  168.96

 -2 TM 20OCT12 55.0 P             0.00     0.00        0.00
     Basis 02/29/2012:                              (109.39)
     Profit/(Loss):                                  109.39

     Value 08/31/2012:                                (2.47)
     Post-August Profit/(Loss):                        2.47

 -3 UPS 20OCT12 33.0 P            0.00     0.00        0.00
          Basis 02/23/2012:                              (249.39)
     Profit/(Loss):                                  249.39

     Value 08/31/2012:                               (12.47)

     Post-August Profit/(Loss):                       12.47


Opened:
 Pos    Symbol                   Price     Comm       Net
 500 INTC INTEL CORPORATION      21.265    0.00   10,632.50

 400 STX SEAGATE TECH PLC        27.90     0.00   11,160.00

 -4 BBBY 20OCT12 40.0 P           0.50     1.14     (148.86)

Also, on October 3 I withdrew $2,500.00 from the account and a dividend of $136.00 became payable November 1 on 400 shares of BMY; on October 5 a dividend of $206.00 became payable November 1 on 400 shares of VZ; and on October 17 a dividend of $112.40 became payable November 15 on 200 shares of PG.