US Stock Sectors: 2022’s losers are 2023’s YTD winners

US stocks have experienced a significant surge of +13% in the first half of 2023 on the back of a US$5 TRILLION bounce due to the excitement in Artificial Intelligence (AI). Two key insights have emerged in this period:

1️. The ongoing rally is broadening which may suggest there is more room for US stocks to run ahead.

I'm personally quite cautious given current elevated valuation levels that we are ripe for a pullback but let's look at the market data objectively.

A big topic in the past 1-2 months has been that 80%+ of the US stock market rally so far is pretty much driven by just 7 stocks (FAAMG + Tesla + Nvidia). Nvidia has been the runaway winner up +189% while Meta is a close 2nd at +140%. But also non tech or AI names are delivering as well in 2023. Take for example cruise (ship) line stocks like Royal Caribbean (+98%) and Carnival (+96%).

We can also measure the how wide or narrow the market breadth via the A/D line index. The "Advance-Decline Index" also known as the A/D line, calculates a running total of the difference between the number of advancing and declining stocks. When this number is high (while stocks rally) it means more stocks are rallying together. On the sector level we are starting to see both industrial and materials sector also start to rally alongside the tech names which would confirm that the breadth is improving.

Saxo Markets Hong Kong Technical Analyst Kim Cramer Larsson highlights when he is looking at the US technical indications he believes a short-term correction may be in the cards but the bullish picture for US stocks will likely to continue next 2-3 months.

2️. A strong first half historically leads to a strong performance in the 2nd half.

Let's crunch the US stock data for the past 95 years. When looking at the past 95 years there has been 28 times US stocks have been up +10% or more in the first 6 months of the year. Of those 28 years, 22 years resulted in positive returns, with a 2nd half return of ~6%.

Clearly I'm not suggesting we use this past data to 'predict' the future but I've always found that the past does serve as a helpful reminder to investors.