I just couldn't refrain from thinking of the possibilities in exploiting the above edge using options. Like someone has mentioned, it is unrealistic to have that type of edge for short durations like intra-day trades. I find that on the average intra-day trade the underlying stock moves in my favour by, say 0.4%. While this is more than sufficient to make a profit in stocks, it will usually result in a loss for options because of the bid/ask spread (in addition to commissions). I find that this is the primary reason for my option trades being a net loss prior to the start of this thread. For instance, on tuesday I saw NTY trading at 40.86, down 6%. I looked at the possibility of buying the JULY 40 CALL for an overnight trade, but find the quotes bid 2.40, ask 2.80. What does this mean? If I should buy the option(at 2.80) and sell immediately (2.40), I would have incurred an immediate loss of 14% (in addition to commissions) even though the stock price has not changed. To break even on this position the stock price will have to appreciate by approximately 1.8%. That is too high an average expectation for an intra-day trade. On the other hand, if it were a one-week or two-week set-up with an average expectation of say 5%, it makes sense to go ahead in spite of the spread. I am ready to reverse this trend by taking more longer term view to optionable set-ups. The quiz earlier given implied an average of 5% per trade (on a one-week duration). That is certainly great for exploitation through options. Let's assume we are doing weekly options, with a premium at-the-money of 5% (pretty high for a one-week expiration, but goes to illustrate my point nevertheless). Let's also assume we are buying the options whose strike prices are the current stock price. So for the successful trades (up 20% in one week), this translates to a gain of 300% on the exposed amount (example strike 100 and current stock price 100, premium $5, at end of week premium rises to $20 from an initial $5, which is a 300% gain). For the losing trades (down 10% at the end of the week): this translates to a loss of 100%. So what is the optimum leverage to maximize our total returns (ignore commissions and slippage). This reduces to maximizing (1+3r)(1-r). This solves to r = 0.33 (1/3). Now let's see what our initial 10K would grow to using this leverage, as well as using some other leverage. The table below summarizes them (using the random distribution used earlier): Code: Leverage Total Returns Max Drawdown 1.00 -100% 100% (This leverage would obviously be insane! You are bound to lose all) 0.60 1904% 100% almost 0.33 177062% 96% (This return is mouth-watering!!! Note the drawdown however!) 0.10 5927% 44% 0.05 998% 22% The most frightening thing about this is that the returns decline precipitously once you exceed the optimum leverage (0.33). That is why it is so important to err on the safe side and use a leverage that is much less than estimated optimum. The real-life costs (bid/ask spread and commissions) will obviously eat into these returns. I have been developing and refining a strategy for options that imply holding for a period of about 2 weeks. I am even being spurred more after seeing a position that my strategy would have caught two weeks ago shoot up nearly 20% since then. However once beaten twice shy: I am not in a rush to get this thing going. Of course the key to making it work would be the discipline to wait for the set-up and using consistent money management.
I do my own programming using native programming languages like Java and VB, and use the APIs to link to the brokers (TWS API for IB and QuoteTracker API for Ameritrade). My back-testing (for strategies that can be back-tested) is done by gathering the requisite data in my Oracle database and doing the analysis.
A few comments: - the Kelly ratio gives the optimum bet for a given set of: average_Win, average_Loss, probability_of_Win, probability_of_Loss -in this case: K=pW-pL*avgL/avgW=.5-.5*r/(3*r)=33% -using a 20% Kelly for a reasonable low probability of ruin, the optimum bet size is 6.6% of your account -in February a CBOE - Hybrid, Penny Pilot Program was initiated; this dramatically reduced slippage, e.g. INTC options' slippage is 1-2 pennies, which allows for intraday trading almost as futures trading -high liquidity options have small slippage: QQQQ, SPX, IWM, etc. -selling front or back month options, instead of buying them, allows for the time decay to exceed the slippage after a few days -it is true that selling limits the upside -as a general rule I'd suggest selling near out-the-money (as well as I'd suggest near in-the-money when buying) for a better profit graph, but this may be overridden by other considerations like the current and forecasted implied volatility, the event calendar, etc.
Neke, perhaps plotting your equity curve over time would help. You know, there are times when it spikes and times when you can *sense* withing reason a drawdown. Checking thyself and backing down size or sit on your hands and not trade is a strategy too. Just food for thought...
Weekly Update for week 17 ended 06/22/2007 Another slow week. Glad I made some gains. Lost 4K in my automated method (AUTOTRADE1), while the discretionary trades made up for the loss and got another 5K. The new automated strategies AUTOTRADE2, AUTOTRADE3 are yet to pick a trade! Still susceptible to revenge whipsaw trading, as the bottom two trades for the discretionary trades show. Code: Balance B/F: 99,237 Gain for the week 4,880 ------------------------------------------------ Balance C/F: 104,117 Number of Trades 22 Number of Profitable Trades 11 Since Inception of Thread 2/25/2007 - 06/22/2007 Balance B/F: 76,636 Net Gain (Less Margin Interest) 52,481 Cash Withdrawal -25,000 ------------------------------------------------ Balance C/F: 104,117 (Without withdrawals should have been 129117, up 68% ) Number of Trades 426 Number of Profitable Trades 257 Expected Balance at this time to be on track for Year-End Target : 158,177 Status: Behind Target Top/Bottom Discretionary Trades for the week TICKER ENTRY DATE/TIME EXIT DATE/TIME QTY PURCHASE AMT SOLD AMT GAINS TYPE ZGEN 2007-06-19-08-25-34 2007-06-19-14-53-40 6500 100272 104955 4631 SHORT CVTX 2007-06-18-08-24-45 2007-06-18-09-31-46 8000 94400 97200 2779 SHORT JBL 2007-06-22-09-45-18 2007-06-22-10-31-18 4000 94520 92628 -1913 SHORT JBL 2007-06-22-10-33-22 2007-06-22-15-35-45 4000 95000 93044 -1978 LONG