Similarities to the dot-com bust?

Sharing is Caring!


The stock market tanked today on more trade war news. It currently sits at a decent support/resistance level.

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.

Is this decline just like the dot-com bust?

A few weeks ago we said that there is some FOMO in the stock market, and that the last time this happened was at the 2000 bull market peak.

Here are some continued similarities between today and the 2000 bull market peak.

“Sell in May and go away” doesn’t always work. But when it does work, everyone starts to pay attention to this catchy phrase again.

This is one of the worst starts to May, with the NASDAQ down more than -5%. Throughout the NASDAQ’s entire history, such a terrible start to May has only happened 1 other time: May 2000

While this may look scary, it’s important to remember that n=1 isn’t useful for trading.

Let’s increase the sample size by relaxing the parameters.

Let’s increase the sample size again…

…And again

So while there are some bad short term drawdowns in there, this is not a consistently long term bearish sign. (Anytime you get a -5% rapid decline in 9 days, there will be big short term drawdowns. The stock market chops up and down with high volatility).

What about the S&P? Here’s what happens next when the S&P falls more than -4% in the first 9 days of May.

If we relax the study’s parameters (-4% to -3%), we can see that the short term still has a bearish lean.


The stock market has had a clear risk-on / risk-off mentality over the past few weeks.

  1. When stocks performed well, defensives performed poorly
  2. When stocks performed poorly, defensives performed well.

While the S&P 500 tanked today, XLU (utilities – defensive sector) rallied.

This big of a divergence between the S&P and XLU is rare, and typically only happens in big crashes.

Let’s relax the study’s parameters to increase the sample size. Here’s what happens next to the S&P when it falls more than -2% in 1 day, while XLU rallies more than 1%.

Let’s increase the sample size again. Here’s what happens next to the S&P when it falls more than -1.5% in 1 day, while XLU rallies more than 1%.

You can see that the S&P tends to do well over the next few weeks…

…While XLU performs poorly. Risk-off

The persistency of this decline…

The S&P has very quickly made a -5% decline after being at an all-time high.

This alone is not uncommon or consistently bullish/bearish.

But what is rare is that the S&P has sold off almost every single day over the past 6 days, with lower LOWS and lower HIGHS almost every day.

On an intraday chart, this looks like a non-stop slide

Historically, these kind instant and non-stop -5% declines from an all-time high were not great for stocks 2 months later

Index Put/Call

The Put/Call ratio spiked on Friday, when stocks were decent. The Put/Call ratio tanked today after stocks crashed. Looks like someone bet on a Monday crash, and took some profits.

Here’s the Index Put/Call ratio, which crashed today. This is uncommon considering that the S&P tanked today as well.

Here’s what happens next to the S&P when it falls more than -2% while the Index Put/Call ratio falls more than -0.4 in one day


Let’s relax the parameters. Here’s what happens next to the S&P when it falls more than -2% while the Index Put/Call ratio falls more than -0.3 in one day

There is a bullish lean over the next 1 week, even during the 2008 crash.


The NASDAQ:S&P ratio tends to go up during bull markets and go down during bear markets. This is because the NASDAQ is more volatile than the S&P.

The NASDAQ:S&P ratio has fallen very quickly over the past few days, which demonstrates the sudden decline in stocks. In fact, the NASDAQ:S&P ratio is now more than -3 standard deviations below its 20 day moving average.

Historically, this was slightly bullish over the next 2 months for the S&P.


Volume was very low in April. And now that the stock market is falling, volume is rising. Volume tends to move inversely to the S&P.

The 10 day moving average in SPY’s volume has increased more than 75% from 10 days ago. Is this a bullish sign for stocks?

Not quite. A 75% increase in volume is uncommon, but a more bullish sign would be if volume increased more than +100%.


The % of stocks above their 200 dma has fallen below this figure’s own 50 dma, for the first time in 3 months.

Sample size is small, but this is mostly bullish for stocks 6-12 months later.

There’s always a bull market somewhere.

And lastly, I would like to draw your attention to Bitcoin. Crypto is on fire right now after 2018’s massive bear market.

Bitcoin’s 14 week RSI is now above 75. Think this is overbought?

*Would I trade Bitcoin for +2316% in 1 year? No. I don’t trade crypto.

Read Is this a bull trap, just like October 2018 all over again?

We don’t use our discretionary outlook for trading. We use our quantitative trading models because they are end-to-end systems that tell you how to trade ALL THE TIME, even when our discretionary outlook is mixed. When our discretionary outlook conflicts with our models, we always follow our models.


Here is our discretionary market outlook:

  1. 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.
  2. The medium term direction (e.g. next 6-12 months) leans bullish
  3. The short term is very noisy right now. There is no clear risk:reward edge in either direction (bullish or bearish). Some short term market studies are bullish, and others are bearish. And with trade war news flying left and right, we have even less conviction for the short term than usual.

Goldman Sachs’ Bull/Bear Indicator demonstrates that risk:reward does favor long term bears.



Leave a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.