MasterAtWork: 1- I never mentioned delta as a probability, although the delta is usually very close to the calculated natural state probability. 2- There is a probability for every event and every non-event. Whether you wish to acknowledge it or not, that is your decision. And I suspect the probability odds of your admission of error are relatively small. 3- Determining the right or most accurate probability of an event is the crux of the problem. If you don't have some method of making that determination then you are simply making random, meaningless trades (no better than randomly choosing red or black on the roulette table). kinggyppo: My example is simply that, an example to illustrate the point. If you run the numbers you will find that all option positions have a natural state negative EV. My proof is providing you the formula that you can apply and see for yourself the truth of my claim. If that were not the case then one could simply devise a software formula to automatically trade all +EV option positions. Imagine the financial potential of that!!!
Options have a -EV even if there are no commissions and regardless of the B/A spread. Those factors only increase the amount of -EV.
Well let's go How do you derive it ? (I stated that you implicitly get your numbers from the deltas, because every public sofwares do the same just as TOS does.)
The statement above tells me that you really don't understand options. If there is no spread or commissions, then selecting buys and sells at random will on average produce breakeven results. Random buys and sells are -EV because of spreads and commissions. The "trick" is to find some method and/or data that puts the %'s in your favor by allowing you to collect more in total on your winning trades than you lose in total on your losing trades (just like sports gambling :eek: ). Joe.
Offhand, it looks like you are using the wrong probabilities. Assuming your 45.52% of max winnings is correct (which I'm not sure it is), the remaining 54.48% would not be max loss if you are creating an iron condor. In fact, some of it would be profit (below max) and then zero before you get to any loss, let alone the max loss. Just look at the structure: http://www.theoptionsguide.com/images/iron-condor.gif The way you're explaining it, the structure would be Long a digital and short a digital, not an iron condor using vanillas.
Thanks for asking the question magic. If you evaluate any product/asset class this way you are guaranteed to find a loser each time. If a specific strategy is a winner each time, the market will digest that information and then trade on it, and then make money on it, and then it will go away (called crowding out). This is also referred to as no-arbitrage which is the central piece to the "Fundamental Theory of Finance" which tells us how options (and other derivatives) are priced. If you find a strategy that always fails, then someone else always wins. In this case, you have identified that the market makers generally win to simple retail order flow. I agree with that finding. If you find a strategy that only wins b/c of commission, then you've found why brokerages exist (I also agree with that finding). In general, retail option investors lose their money (wealth destruction) and pass that wealth to market makers and brokers on some split percentage (wealth accumulation). This is also true for the stock market where retail wealth is passed to mutual funds, insurance companies, brokers and specialists (i.e. stock market makers).
An interesting post, and very thought-provoking...a couple of points/questions... In the example above, your probability is based on expected value of the underlying at expiration. What about strategies that don't rely on expiration though? Although butterflies/condors/etc rely on the trader holding them until expiration, there are other options trading strategies that can be legged out or closed prior to expiration. In evaluating the expectancy of such a position, you could not simply use the probability of the underlying's value at expiration being at (or in favor of) your position's breakeven point, because the underlying could rise (or fall) past your breakeven point at any time prior to expiration, which would afford you the chance to exit your trade at a profit. How does your "proof" account for the ability to adjust trades prior to expiration, when market conditions render them profitable?
The EV calculation is incorrect. magic423 has posted the same thread 3 times. Methinks the OP is a spammer/scammer. In another identical thread, he posted a "paper" signed Kevin Butler at the end. There is a Kevin Butler that scams naive targets into giving him money for his power spike trading system. Is this your site, magic 423?: http://www.powerspiketrading.com/. I wouldn't want to slander an innocent avatar.
Not to mention out thinking all the quants, options MM's and institutional traders, is EV the new holy grail, magic coin flipper?? get that paper to Wilmott stat. "Take for example the stock market crash of October 1987. Following the standard paradigm, assume that stock market returns are lognormally distributed with an annualized volatility of 20% (near their historical realization). On October 19, 1987, the two month S&P 500 futures price fell 29%.1 Under the lognormal hypothesis, this is a -27 standard deviation event with probability 10-160. Even if one were to have lived through the entire 20 billion year life of the universe and experienced this 20 billion times (20 billion big bangs), that such a decline could have happened even once in this period is a virtual impossibility. Nor is October 1987 a unique refutation of the lognormal hypothesis. Two years later, on October 13, 1989, the S&P 500 index fell about 6%, a -5 standard deviation event. Under the maintained hypothesis, this has a probability of .00000027 and should occur only once in 14,756 years. In addition to this episodic evidence, it is now well known that since the 1987 crash Black-Scholes implied volatilties for S&P 500 Index options have consistently exhibited pronounced smile effects -- a fact that can perhaps be best explained by extreme departures from lognormality. " http://www.haas.berkeley.edu/groups/finance/WP/RPF-250REV.pdf