Non-Fundamental Factors

Non-Fundamental Factors

I generally try to stay away from getting into the weeds of what happens in the market, as it’s fairly wonky and hard to explain. Lord knows the media doesn’t bother. They just go with first-order effects and call it a day. Why are big tech stocks up so much versus everything else? Uhh…. AI? Sure. Just be sure not to look at any actual numbers, as there’s not much steak behind the sizzle.

The fact of the matter is that over time, the market has grown more complex and financialized. The options market gets bigger, futures get bigger, structured products get bigger. This is especially true when nothing too bad has happened for a while. Taking risks keeps working.

I bring this up because I’m very fundamentally oriented. I pay a lot of attention to macro and fundamentals. As all of the above has become bigger, non-fundamental influences have become bigger. Over the long term, that doesn’t really matter. Stocks get pushed up for temporary non-fundamental reasons, then that fades.

Really, I’m just facing the same basic issues that Commodity Trading Advisors (CTAs) face. They historically have great risk-adjusted returns over the long term that are especially great because they’re fairly uncorrelated with other markets. The problem is that when other systems, like the stock market, look good for a while, suddenly, they get pressure for why they aren’t doing so well. Some of them try to make adjustments, and some just say the trend works over time, so don’t worry about noise.

Similarly, macro and fundamentals work over time. You look like an idiot in 2020 and make it back in 2022. I could just lay back and let it all play out or, like some CTAs, I can try to do something about it. For my part, currently it seems like non-fundamental factors keep growing in importance, so it seems like a no-brainer to do something about it.

To get back to right now, we had this explosion in a few huge tech stocks that has nothing to do with fundamentals. As I’ve said before, a far more reasonable answer for what’s going on comes from Cem Karsan of Kai Volatility. He says that higher rates have led to a proliferation of structured products. which more or less do well if the stock market doesn’t move too much. This is most easily managed by dealing with liquid volatility centers, and big tech fits that perfectly.

Since life goes on in the market, earnings warnings happen, CEOs get fired, and all that, the counterbalance to that is to sell volatility in big tech, which helps them to levitate. If that sounds crazy, we saw the same basic idea in 2017 and 2020, though this seems like the most dramatic example. Yes, eventually this should break down, whether through time or price. Could it be bad? Perhaps, but I’m not going to pound the table on that.

Whether or not structured products are the primary driver of the incredible dispersion in the market, this year, the fact of the matter is if you invested in the seven biggest tech stocks, you’ve done fine. If you didn’t you look lousy. Wouldn’t it be nice to see that coming?

As I’ve said before, I focus on earnings and fundamentals. In the past, I’ve spent a reasonable chunk of time to make sure that works pretty well. Like CTAs, it doesn’t work every quarter, but it’s a tailwind over time. That data comes from a top-down perspective. What are growth, inflation, and liquidity doing?

To deal with the non-fundamental moves, I built a model that instead asks what the market thinks. For instance, the big-picture macro data has been saying for a while that economic growth is slowing, as is inflation. According to my market model, though, the peak fear was around November of last year. The market got scared again in March, but in general has been very constructive on future prospects.

What would we do with this? Ultimately, I think it’s important to accurately model the market. The market has been constructive. Why? It gives me a better understanding of what’s going on, which hopefully aids decision making.

That said, it’s certainly not magic. We still have the CTA problem. We have a great model that does well over time, so is there a point investing in what seems like long-term noise? I can tell you I have stylized models for both systems going back to 1999, and the long-term model wins. It’s not very close.

What the bottom-up model does to is provide context to what’s going on, which can help decision making. Hopefully, we can use that to round off some of the dispersion in what we do. When the market starts saying something is starting to get priced in or out, we can see it and potentially take action. The market has become more complex over time, and we should take the time and energy to deal with that.

I would also say that in the short-term, with the data I have, I wouldn’t do anything differently. Going back to the vol control issues of Cem Karsan, above, OpEx is when this system is most likely to break down. We have OpEx this week, along with earnings really hitting. Additionally, volatility is very low compared to history. Looking at volatility and correlations, this is a reasonable time to look for a correction, or perhaps more.

For now, we’ll see how the market acts into and out of OpEx, this week and next. This move has gone a long way. We’ll watch the data and go from there. As a final point, I’m not suddenly in a panic and making big changes. This is virtually identical to what happened in the summer of 2000. I’ve been here before. I do, however, believe that the more accurately you can model the market, the better prepared you can be for what comes.

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