In a previous post we analyzed the performance of US Sectors using SPDR Sector ETFs. Now, let’s dive into the analysis of sectors using S&P 500 components and some measures of its performance.
Before going any further, it is important to note that there are some differences between the Sector SPDR and the figures that we are going to see. In this analysis, we weight each company equally but SPDR Sector ETFs are not equally weighted. We start with S&P 500 companies year to date returns by sector
Year to Date Returns
From the previous figure we can infer the YTD Sector performance. If we look at the boxplots, we will see median, maximum, minimum, IQR, outliers… We can also know the returns distribution across the sector. For example, the distribution of returns in Utilities sector is very narrow, with no outliers. Information Technology has a much wider distribution with the presence of outliers.
Also you can wonder about the stocks returns from the top and bottom to detect retracements or run-ups:
Returns from YTD Highs & Lows
Despite the overall positive returns, we can see that more than 50% of Health Care and Communications Services have a retracement greater than 10%.
Although the charts above give us a lot of information, YTD Lows and Highs do not occur at the same time for all companies (of course). In the current environment, with S&P 500 index very close to ATH, it can be interesting to compare the recent behaviour using the 50 days moving average of every stock. It offers complementary point of view from previous plots:
Returns from 50 day Moving Average
We observe sectors with a very heterogeneous relative performance to 50 days moving average: Information Technology, Consumer Discretionary or Industrials. Other like Utilities, Financials or Real Estate have positive and narrow distributions. Meanwhile Communication Services has a negative bias.
Finally, we may also be interested in looking all the previous plots at the same time and comparing only some sectors across the four plots. This can be done by clicking on the legend names.