I’m starting out with my customary warning that my temperament is such that I’ve gotten more than all my outperformance as an investor in up-trending and flattish markets. My idea of success in a down market is not entirely losing my shirt. The main issue is that in sizing up the market in general I look much harder for what can go right than for what can go wrong. I do more or less the right things in a bad market–rotate into larger-cap stocks vs. smaller, low-PE vs. high, stable vs. cyclical, less concentration in a few names–just not enough of each to keep up with the market.

This is presumably not news to regular readers, so this “disclaimer” is as much to remind myself as you that most of what I think is tinged with optimism. While on average this may be the most useful frame of mind to be in, it’s not the way to go in a market downturn.

Yesterday, I wrote that the typical cyclical bear market lasts anywhere from 8-12 months. By that yardstick, and assuming the down market began last November, we shouldn’t expect a market pickup until the fall. The big issue with this train of thought is that the overriding economic factor isn’t the business cycle but the multi-year bolt from the blue of the pandemic, together with the much lesser negative of the invasion of Ukraine, which shows up in the stock market mostly through rising commodities prices.

Another complication, with another disclaimer: at one time I had a seat for the stock market game at field level, right behind the catcher; I’m now high in the bleachers. From where I now sit, however, a lot of current trading seems to be handled by AI that react to news stories, corporate announcements and recent stock price action. Are these trained on data from periods of external shock, like the runaway inflation of the late 1970s-early 1980s? …or are they trained on 2007-09, when world trade ground to a halt on worries about the solvency of the global banking system? …or do they mostly respond to the financial media, which I see (the Economist, Nikkei News and the FT excepted) as an echo chamber of cluelessness.

My point is: to what degree can we depend on reading stock prices as an indicator of market sentiment? I’m not sure. On the other hand, it may be all we’ve got.

AAPL, for example, reported after yesterday’s close. The results were fine. The company warned, however, that revenues (i.e., not profits) for the coming quarter would be lower by maybe 5% than they would have been had China not been having covid-induced factory lockdowns. The immediate press reaction was negative. As I’m writing this about an hour before the open, AAPL shares are down by less than a percent, with NASDAQ futures off by more than a percent.

I read this as a bullish-ish sign. An important step in the market recovering its equilibrium after a decline has always been that it stops discounting bad news over and over. Although I’m not an AAPL fan and I don’t know much about the stock, it seems to me that the Chinese factory shutdowns should have already been well-known (and already factored into the AAPL stock price) before last night’s earnings call. The “news,” if there was any, is that production is already up and running in non-covid areas. Two more nuanced takes: revenues will be down by mid-single digits, but this doesn’t imply that profits will fall this much; and revenues will be down from what they would have been otherwise, not down in the absolute–maybe they will be up by 30% vs. AAPL’s former internal forecast of +35%.

In any event, AAPL gave the overnight market an excuse (not a reason) to sell off it wanted. So far at least, that hasn’t happened. Like the reaction to recent MSFT and FB reports, this is an encouraging sign.