2019 has been treating the markets well so far. The S&P500 has had one of its best starts in history (up 11.1% through January and February) according to SeekingAlpha, and the Dow Jones has performed similarly well with an 11.4% YTD gain. This growth hasn’t been confined to the U.S, as nearly all major indexes across the world have been positive for the year. Chinese ETFs have posted exceptionally large returns so far, with the Shanghai Composite and Dow Jones China both up more than 20% on the year. Alongside these numbers, we’ve seen GDP growth estimates reflect more positive sentiment than the pessimistic outlooks from those at the end of 2018, with the Atlanta Fed reporting that real GDP growth in the first quarter of 2019 is currently around +0.4% and with most experts projecting +2.1% to +2.4% for the year.
Who could’ve predicted that all of this growth would happen just two months after volatile and unpredictable shifts in the markets which nearly caused a flash crash, and raising of Federal Funds Rates in December? Also, what’s next? Is this steady growth a sign that we have successfully avoided the recession which experts predicted would stain 2019?
To address the first question, I offered a calculated guess in my “End of 2018” post. Here, I predicted that the raising of Federal Funds Rates at the end of 2018 (along with the Fed’s report that they would continue raising rates through 2019) coupled with slowing GDP growth and instability in the markets (as evidenced by the market crash/rebound in late December) foreshadows greater market recession in April/May of 2019. In other words, I predicted that the market would see notably large returns for the first few months of 2019, then the train would hit a grinding halt somewhere around April or May (right now, it’s looking more like May). This will not be a full-blown crash, but rather a large dip in prices followed by a stagnant period of price readjustments and returns from inflated highs.
Here’s some what I wrote specifically:
“Whatever the true root of the cause may be, this rebound also seems to have effectively calmed stocks down, as the market has behaved pretty normally for the first trading days of 2019. What’s more, essentially the entire market was up yesterday, with Dow Jones up 3.3%.
It’s still very early to jump to conclusions (or, if you held AAPL, drop 9% to conclusions), but it may feel as if we just dodged a huge bullet, as a decline in the final week of 2018 would certainly have negatively impacted projections for 2019. But, considering what this massive market rebound has taught us, my overarching hypothesis is that this stock decline was not avoided, nor was it postponed. It still exists, and should be arriving on time somewhere around April or May.”
Later on, I mention how the times directly preceding market crashes are always times of extraordinary sudden growth. This gets more and more true as you get closer to the event horizon (the crash), and the extreme volatility days/minutes/seconds (or microseconds for all you high frequency traders) right before the crash are the precise moments where most profit can be made.
As for the other two questions, no one knows for certain what will happen next (except, hopefully, the embedding-based trading algorithm I’m writing…). There’s no way to tell if the market is actually going to reach a plateau in April/May other than waiting until April/May, but we can look at some of the indicators manually:
- GDP Growth: This one is essential for projecting macro-scale movements in the markets. It kind of makes sense too; GDP measures a country’s economic influence, so if this influence is growing, that should mean the stock market will grow as well. This is clearly not always true, as U.S GDP grew 2.9% last year while that same year was the worst year for stocks since 2008. This year, GDP growth estimates are much smaller than the numbers we saw in 2018, with growth estimates hanging around +2.5% for 2019 according to Kiplinger (the Fed’s estimates got cut in late 2018 as well). This may seem like a small dip (and it is), so this slowing GDP growth is nothing catastrophic on its own. The trouble emerges if the market is very unstable and volatile, or in other words, more receptive to these small signs of stagnation. The period of instability at the end of 2018 might be an indicator for how sporadic the market currently is, but this is countered by the fact that growth has been rather steady and consistent in the past two months.
- Market Performance: According to Seeking Alpha, whenever major ETFs like the S&P and Dow Jones are positive through the first two months of the year, the rest of the year will be positive as well. In fact, out of the 30 years when both January and February returned positive, only 1 year finished in the red (29 out of 30 times means this is true 97% of the time, and there aren’t many indicators on Wall Street which are right 97% of the time). So, going off of this one data point, one could confidently claim that the market will continue growing in 2019.
- Gold Prices: Traditionally, the price of gold is interpreted as a measure of confidence in modern financial systems. Gold has held its value throughout history, so people tend to think of gold as the safest form of currency which can always be exchanged for goods, unlike paper (fiat) currencies which can be devalued, replaced, or made irrelevant through inflation. Also, no one can track gold transactions like they can with credit cards or SWIFT, which adds to its allure. Whenever people start losing faith in modern financial systems like banks or Wall Street, or when people anticipate an economic crash, gold prices go up since more people want to be prepared. As you can see in the chart below, gold prices rose pretty starkly from September 2018 to early January 2019, and this was followed by a huge, sudden jump in February. However, gold prices have returned to their end-of-2018 levels, and it looks like they’re continuing to drop significantly.
- Investor Sentiment: This one is a bit harder to measure because it’s much more qualitative than quantitative, but there are several indexes which use tools like NLP A.I to gauge if investors are optimistic or pessimistic. One such metric is CNN’s Fear-and-Greed index, which measures how greedy or fearful investors are on a given day. I don’t recommend taking out a second mortgage on your house to invest based off of this index because it never tells the full story, but it is a very interesting concept to consider, as more greediness should always correlate with increases in market prices. Over the past few months, things have been rather greedy, but we’re getting closer to fearful territory. The 0-50 range is fearful and the 50-100 range is greedy, and we’ve been hovering around the mid-60s for the past month. This is nice, but it’s too close to fearful to draw any confident or meaningful conclusions.
So, with all of this in mind, the outlook is looking much more positive overall than it was in December 2018. Don’t forget that this early growth in the year was heavily influenced by the Federal Reserve’s decision to be more lenient and incremental with increasing Federal Fund Rates. The Fed’s announcement came early this year, clearly as an early attempt to abate qualms about the markets in response to what happened at the end of 2018. But the Fed can only pull this trick so many times, and if the recession bias (this is a really cool article which explains how when the majority starts to believe a recession is coming, it will most likely happen because people and businesses start hedging more rather than spending freely) hits again, there’s little room elsewhere to run (aside from maybe lowering rates). With that said, it should be easier to paint a picture of what the markets might look like going into summer 2019.
Or, rather than writing this entire post and spending time trying figure out what might happen based off economic indicators, we could use an embedding-based market analysis tool like the one I’m currently building. The usefulness of an embedding-based trading algorithm is that we can look up which periods in stock market history are contextually similar to the period we are observing right now. This is done through the power of dynamic NLP, which does not look at fundamental market data like cash flow or PE ratios, but rather looks at what contexts certain events appear in. So, if two historical series of price changes in the markets are similar, we can assume that their outcomes will be similar as well. With this knowledge, we can make predictions for what will likely happen in the market during a certain time window.
This may sound far-fetched, but think about how humans naturally go about making predictions: We observe what’s going on right now, we try to relate this to previous knowledge, and we use this previous knowledge to think of what will happen in the future. Think of a cup slowly sliding toward the edge of a table. You know this cup will fall, because you’ve seen what happens when an object above the ground loses support before through your personal experiences and the memories stemming from these experiences. These memories are really just embeddings themselves.
So think of this post as my independent projection for what will happen with the markets in the next few months which is not influenced by my algorithm, because if I was using my algorithm, then I wouldn’t have to write this. If my overarching projection continues to prove correct, then this will be a testament to my trading aptitude. But if I am completely wrong and the market continues to grow 10% every two months for the year, then at least I will have my algorithm to fall back on.
Finally, on an unrelated note, I’ve been reading Q is for Quantum by Terry Rudolph, which is supposed to be an accessible intro to the concept of quantum computing. I’m reading this because as I mentioned in my last post, there’s a lot of discussion around the topic of quantum computers being the logical next step in computing speed and power. Since most of trading nowadays focuses on beating competitors through efficiency, you could imagine that Wall Street is very interested in getting their hands on quantum computers. I’m reading this book to get on this wave before it’s too late, and I will share some findings if any of them are pertinent to my work on trading algorithms.