It’s another slow day in the stock market, to the point where this price action will put you to sleep. The S&P remains near all-time highs.
Go here to understand our fundamentals-driven long term outlook.
Let’s determine the stock market’s most probable medium term direction by objectively quantifying technical analysis. For reference, here’s the random probability of the U.S. stock market going up on any given day.
*Probability ≠ certainty. Past performance ≠ future performance. But if you don’t use the past as a guide, you are blindly “guessing” the future.
The slow moving stock market
Volatility and volume in the stock market have been notably low in recent days.
For example, the 15 day average of SPY’s volume is now where it was in July-September 2018.
While this may seem scary (“the last time this happened was before the October 2018 stock market peak”), I urge readers to avoid recency bias and look at the data holistically.
Here’s the complete chart, from 1993 – present
It’s obvious that the upper and lower end of this range have shifted over time. To make this figure range-bound, we can look at the 15 day average’s distance from its 200 day average. Either way, volume is very low.
Here’s what happens next to the S&P when volume is this low.
Not consistently bullish nor bearish for the stock market.
It’s not just boring in the stock market…
- The stock market’s volatility is low
- Currency markets’ volatility is also low
Here’s a simpler way of looking at currency market volatility. This is the USD Index. You can see that it has swung in a very narrow range over the past 9+ months.
This is the 6 month High – Low % difference for the USD Index. Once again, very low USD volatility.
Here’s what happens next to the USD Index when this High – Low % range is less than 4%.
You can see that there is a short term bearish lean 2 months later.
Here’s what happens next to the S&P:
Not consistently bearish, particularly 9 months later.
In a low volatility environment, the low volatility ETF is outperforming the broad S&P index. Here’s SPLV.
As you can see, SPLV is rather overbought right now. If you only buy SPLV when its weekly RSI > 70, then your returns would be very poor. So if you are thinking about buying SPLV right now, it’s probably a good idea to wait a little for momentum to back off.
Here’s what happens next to SPLV when its 14 weekly RSI exceeds 70 (first case in 3 months).
While the 6-12 month forward returns look consistently bullish, I would like to remind investors that SPLV’s data is limited to 2011-present. If you only use bull market data, then of course your historical forward returns would always be bullish 6-12 months later.
The S&P remains approximately 1.9 standard deviations above its 50 day moving average. Standard deviations are used in Bollinger Bands.
From 1950 – present, the S&P has spent 10.57% of its time more than 1.9 standard deviations above its 50 dma.
This chart illustrates what would happen if you only buy and hold the S&P when it is more than 1.9 standard deviations above its 50 dma. As you can see, the short term returns are almost nonexistent.
Here’s what happens next to the S&P when it’s more than 1.9 standard deviations above its 50 day moving average.
Forward returns are mostly random, although there is a slight bullish lean 12 months later.
And lastly, a quick reminder of seasonality as we are just 2 weeks away from May.
There’s a popular saying in the investment community: “Sell in May and Go Away”. This is because the best 6 months occur from November – April, whereas the worst 6 months occur from May – October.
To illustrate this point, we’ve plotted what would happen if you only buy during the Best 6 Months vs. what would happen if you only buy during the Worst 6 Months.
Does this mean that the stock market can’t go up from May – October?
It can go up. But more often than not, it doesn’t.
I would also like to caution investors that seasonality factors are of tertiary importance. They change on a dime. Here’s the same chart, but on a log scale.
You can see that the “worst 6 months” (May – October) actually outperformed from the 1930s – 1950s. But since then, the “worst 6 months” has consistently underperformed.
If the S&P doesnt’ fall significantly throughout the reminaing 2 weeks of April, then it would have gone up more than 15% from January – April. Historically, the rest of the year’s returns were not as good as the first 4 months.
What if we use a rolling 4 month period instead of January – April?
Here’s what happens next to the S&P when it rallies more than 15%+ over the past 4 months, excluding overlaps.
*Data from 1950 – present
Quite bullish, isn’t it?
Let’s include pre-1950 data.
Not as bullish. Seasonality changes over time, and for no apparent reason.
*I generally don’t like to use pre-1950 data because it doesn’t include dividends. Dividend yields were much higher pre-1950s than post-1950s. But even after factoring in dividends, many of the pre-1950 historical cases in this table would have been bearish.
Read The S&P 500 Total Return Index has made new highs. What’s next
Here is our discretionary market outlook:
- The U.S. stock market’s long term risk:reward is no longer bullish. In a most optimistic scenario, the bull market probably has 1 year left. Long term risk:reward is more important than trying to predict exact tops and bottoms.
- The medium term direction (e.g. next 6-9 months) is mostly mixed, although there is a bullish lean.
- We don’t predict the short term because the short term is always extremely random. At the moment, the short term does seem to have a slight bearish lean.
- In summary, 12-24 months = bearish, 12 months = neutral, 6-9 months = slightly bullish.
Goldman Sachs’ Bull/Bear Indicator demonstrates that risk:reward does favor long term bears.
Our discretionary outlook does not reflect how we trade the markets right now. We trade based on our quantitative trading models. When our discretionary outlook conflicts with our models, we always follow our models.
Members can see exactly how we’re trading the U.S. stock market right now based on our trading models.
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