In my last post, I mentioned two forecasts from my model on stocks going into earnings, and discussed the implications of a model's performance during this critical time period.
GS and JNJ earnings have been reported, and our model's insight was correct in both cases. In the case of JNJ, analysts' predictions gave an average of $1.15 per share, with a low of $1.10 and a high of $1.17. In reality, JNJ reported $1.23 per share, despite a minor slip in revenue, and raised their EPS forecasts for year-end. As for GS, America's perennial investment bank, analysts averaged a forecast of $2.29, with a low of $1.81 and a high of $3.00. They came in at $2.98, just shy of the maximum forecast.
It is 9:15 right now and both stocks are down in pre-market trading, so only time will tell how the market will react. What is interesting, though, is the fact that our model's predictions were in line with true changes in the company's fair value. Whether the perceived value will change with it, of course, remains to be seen.
Tuesday, October 19, 2010
Monday, October 18, 2010
GS and JNJ Earnings Tomorrow
I've been working on an options trading strategy recently, which would loosely be classified as "volatility arbitrage." As an experiment, I took some of the trades it implied on two stocks entering earnings announcements: GS and JNJ. Both were long, coupled with a short position in PG. The short position is less important to the experiment, but is necessary for reasons unimportant.
The reason I find this particular moment so fascinating is because, in my opinion, it is the truest test of a strategy. When earnings are reported, equities experience a rare moment in which the full information set that determines their value is available. There is something of a "reset" to the perceived fair value, in which all market participants have the same information.
The question is, will the earnings announcement disrupt my strategy, or actually bolster it? If a model works by correctly identifying the genuine value of a security, the earnings announcement should force a convergence to fair value, which would be beneficial to the strategy. If, on the other hand, it works by predicting the changes in investors' whims, and in fact does little to determine true value, the earnings announcement should disrupt the strategy.
Naturally, the optimal strategy would fare well in both scenarios. But how could that be? We must construct portfolios that are sensitive to a likely outcome (such as convergence to fair value) but still robust and immune to other possible scenarios in which investors misread the evidence.
The reason I find this particular moment so fascinating is because, in my opinion, it is the truest test of a strategy. When earnings are reported, equities experience a rare moment in which the full information set that determines their value is available. There is something of a "reset" to the perceived fair value, in which all market participants have the same information.
The question is, will the earnings announcement disrupt my strategy, or actually bolster it? If a model works by correctly identifying the genuine value of a security, the earnings announcement should force a convergence to fair value, which would be beneficial to the strategy. If, on the other hand, it works by predicting the changes in investors' whims, and in fact does little to determine true value, the earnings announcement should disrupt the strategy.
Naturally, the optimal strategy would fare well in both scenarios. But how could that be? We must construct portfolios that are sensitive to a likely outcome (such as convergence to fair value) but still robust and immune to other possible scenarios in which investors misread the evidence.
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