I updated our closed trade log below. We took small loses on QQQ, TXN and CLOU as the tech sector pulled back into an intermediate terms consolidation. On a percentage basis, the loss on the cloud computing and QQQ ETFs look huge, but, we sized both option trades for max allowable % trade oss, and set our exit as 50% trailing loss of the value of the underlying option contract. The contracts actually grew before rolling over, so our traling 50% loss reduced the size of our net actual loss when we closed the trade. So, in reality, these losses were actually smaller that the Texas Instruments loss of .65%.
I know, this sounds like a whole bunch of mumbo jumbo distracting from the fact that these trades were losers. I got news for you, even with a powerful system like Chaikin putting the directional wind at your back, actually winning more times that losing on directional trades is hard to do. And it's actually not necessary, as long as stocks like GM are part of the equation. GM, at nearly $7.50 in appreciation in less than a month, more than paid for all of our losers, if everything in a corresponding properly position-sized portfolio were running. At twelve percent net gain, GM pays losers of .5% to .7%.
Moving forward, I'm only going to report trades as one lots. So, we'll be focused on the win/loss percentage and the % gain or lost on each trade. Once the sample size is big enough, I can break out stock and option trading performance separately. The goal of this test isn't about how much money gets made or lost. It's about the efficacy of swing trading using Chaikin Analytics core metrics.
Finally, CA is a trend following quantitative-funamentals-driven investment decision aid at its core. But, diversifying the types of trades taken can positively impact results. Sometimes markets just aren't favorable to trend followers. Sometimes, it's painfully obvious that GM has a lot more room to run after breaking out. Why would we exit? Because that's how we planned the trade.