Thank goodness that's over! There's no other way to sugar-coat it, unless you were short, October was rubbish! But, was October 2023's performance par for the course, or something else? And what can we expect in November?
Seasonal analysis is the study of how a particular security or index moves at various times of the year. Seasonal trends occur due to regularly occurring events which impact a particular market, for example, harvesting for a commodity security, or the payment of dividends for a stock.
Seasonal patterns should never be considered as a schedule of future price action, rather they are an overview of what has regularly occurred in the past, and therefore what may happen in the future. Remember! The future is unwritten and there's no guarantee even the most reliable seasonal pattern will ever occur again.
Having read you the usual seasonal pattern disclaimer, there are a couple of important seasonal patterns in the stock market all investors should be aware of. You've probably heard of the first one: "Sell in May and go away". This describes the tendency for stocks to struggle in May and sometimes June as (in theory) many US fund managers settle up before their summer holidays. The other potential reason for May's malaise is the fact the months from November to April tend to be so good. Perhaps May is just too good an opportunity to take profits.
You've probably also heard about the "Santa Claus Rally" which describes the tendency for the stocks to rally over the Christmas and Holiday period. As we'll see when we look at the hard data below, there are clearly observable trends over many years which confirm the existence of both of these phenomena.
It's worth also considering that sometimes seasonal trends occur because people are aware of seasonal trends, that is, they become self-fulfilling. Hey - if you know May's usually a dud month for stocks, you'll probably be selling. Similarly, you'll probably be buying in the lead up to Christmas. But then there's the theory that some fund managers will take this into account and try to beat you to the punch. So, you can see how many of these theories are quite fluid, and this probably explains the variances in seasonal trends from year to year.
The other key aspect of seasonal analysis when it comes to stocks specifically, is the importance of accounting for dividends. Too many supposed seasonal analysis data is bandied around using only raw prices from the major benchmark indices. These indices reflect the prices of stocks after dividends have regularly been paid throughout the year. Each time a dividend is paid, the price of the stock paying the dividend fall by around the dividend amount as new shareholders won't get the benefit of receiving that dividend.
Accounting for dividends in seasonal analysis is not such a big deal for some markets where dividends are typically a small component of stocks' total returns. For example, in the USA, the dividend yield of the benchmark S&P500 varies from around 1-2% over the long term. Compare this to the Aussie market, where the benchmark S&P/ASX 200 typically yields upwards of 4%, and you can see why you'd definitely want to account for dividends when considering seasonal trends. If you didn't, you'd get completely the wrong idea of seasonal performance for the Aussie market in the customary dividend paying months of February-March and August-September.
All of the data I will show you here has added back the impact of dividends. So you are seeing the true performance of the Aussie and US markets from a seasonal perspective.
One final point on seasonal analysis. It's worth considering seasonal trends over different timeframes. Seasonal patterns and trends do evolve over time as markets respond to similarly evolving challenges and economic trends. So, when looking at seasonal charts, try to also obtain data over varying time periods, e.g. 5, 10, 20, and 30 years. You can also go back too far. A seasonal pattern which existed between 1960 and 1970 probably has very little relevance today, so don't automatically assume larger seasonal analysis data samples are better.
Ok, that's the intro spiel, let's get to the data. What do seasonal patterns tell us to expect from this November (and potentially for the rest of 2023)?
Note, when conducting seasonal analysis for the Aussie market, I prefer to use the All Ordinaries Index instead of the usual benchmark S&P/ASX 200. This is because the All Ord's contains around 500 ASX-listed companies making it a far broader barometer of local market strength than the S&P/ASX 200.
Firstly it's worth noting October 2023 was a poor month for the All Ord's, returning -3.35% compared to the 30 year average of +1.14%. You can't really say -3.35% is much of an outlier though, considering October 1987's 42.1% plunge (the "Big One"), October 1997's South-East Asian Crisis inspired 10.4% drop, and October 2008's GFC induced 13.9% rout. Indeed, the standard deviation over the last 40 years of All Ord's data I have for October is a whopping 8.4%.
Despite October's bruising encounter, investors have reason to be more optimistic for November. The data shows positive returns for November over all the data samples: 0.8% over 30 years, 0.7% over 20 years, 1.6% over 10 years, and 3.3% over 5 years (that 5 year trend sounds pretty good to me!).
It's also worth noting November is part of a prolonged period of market strength, usually running all the way to April. There are some blips here, particularly in the recent data for February and March, but at least the trend into the end of the year appears to be reliable.
Let's take a quick look of the corresponding data for the US. Not surprisingly, it's very similar. My data set only goes back 30 years here, and so doesn’t include the 1987 Stock Market Crash. October is usually a positive month, showing a 1.88% average return over the last 30 years. This October's -2.1% return was below par, but not an outlier given October is usually a volatile month, running at a standard deviation of 5.4% over the last 30 years (FYI, October is the most volatile month of the year, whereas May is the least volatile with a standard deviation of 3.4%).
So with typically the most volatile month of the year behind US markets, what can we expect in November? Like Australia, November usually delivers a positive return, around 2.2% based upon the last 30 years, 2% over the last 20 years, an impressive 3.4% over the last 10 years, and a whopping 4.3% over the last 5 years. November is actually the best month of the year for US stocks over the last 10 years, and it is the second best over the last 5 years.
Conclusions from this data? Again, seasonality disclaimers aside, in many instances during the various sample periods markets were dealing with just as much "bad stuff" in October as they're dealing with right now. October is clearly the most volatile month for both markets, and volatility tends to fall substantially in both markets during November and December while returns tend to increase.
So, as bad as some of the "current stuff" is facing markets, I feel we do have reason to be optimistic this November. Further, I am a true believer in the Santa Rally - I've just seen it too many times!
But, I am a trend follower first and foremost. I concede there aren't many great uptrends out there given current circumstances. Still, I will be watching closely for turnaround plays over the next few weeks and allocating some strategic capital if the situation warrants.
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