Can the Recent Market Rally be Sustained?

Originally published via our newsletter previously. Subscribe for early access!

Support and Resistance from a technical charting view are powerful.

They are places that represent not just the prices of a security, but what investors and trader alike think about that price.

Support: The price in which a securities price is ’supported’ from trading any lower at that point in time.

Resistance: The price in which a securities price ‘resists’ going any higher at that point in time.

The markets – and I am talking about the big three US Indices, Dow, NASDAQ, and S&P 500, have all ramped higher post the Fed decision to NOT hike rates last week.

All three have run up to a prior peak they all traded down from.

They have all made their way back up to that prior peak, which can be considered resistance.  Resistance is a place that can end up being a price point investors stop adding money to the purchase of that security.

That would result in the security ‘resisting’ trading above that price.  It could then roll over and trade down from that resistance level.

OR… it could break out.  That indicates the strength of buyers.  It represents a conviction of buyers in that security at a higher price than that resistance and that at times brings in more buyers who don’t want to miss out on a potential higher move on what is called that ‘break out’ above Resistance.

Look at three charts at least 90-trading days on DIA, QQQ and SPY and you can see a bit of potential strength in that they are slightly breaking out above their prior resistance.

Markets in Focus: DIA, QQQ, and SPY

Here are those 3 Indices with breakout of resistance highlighted:

From the Desk of a CMT – Sector Correlations

When diversifying a portfolio, you seek instruments that are not highly correlated over time. This article assesses:

• The performance of two uncorrelated ETFs in the Sector SPDR list, 
• Their performance relative to SPY over the last 3 weeks, and 
• The performance of two call options with similar moneyness for the two ETFs performed.

Figure 1 provides the results from a 60-day correlation test on the Select SPDR list using daily percent change (10/17/2023).

The two ETFs selected for review were XLE (0.243 correlation to SPY) and XLV (0.675 correlation to SPY). The correlation between the two was 0.199, so no correlation.

To access the correlation analyzer, select: Stocks > Stock Analysis > Correlations. You may want to consider varying the Correlation Days Length (6 – 249 days). Although it’s not something I would do as an initial assessment because it’s too short, let’s see where correlations were for the 15-day period since the first scan (Figure 2).

The correlation value for the two stocks increased over the shorter period but stayed within a no, to low correlation value (0.654).

You do want to be more thoughtful about the correlation period you’re reviewing and current market conditions. 

As a quick reminder, correlations across and within asset classes can move towards +1.00 during severe declines so diversification across ETFs alone may offer limited protection in strong bearish moves. Although we’ve certainly experienced a few of those moves in the last couple of decades, it hasn’t been the norm.

To get a different view of how the two ETFs over the period, Figure 3 displays an 80-day price chart for the two ETFs with a vertical line to approximate 10/17/2023. This captures the original 60-day test and the 15 market days since, with 5 market days to spare.

Since 10/17/2023, both ETFs experienced an initial decline and a bounce; however, XLE’s bounce was not sustained. With that background, a recap follows for the call option selection after running a bullish scan on 10/17/2023. 

• The scan covered a one-month period, so November expirations were selected for both ETFs.
• The short-term trend was bullish for each using short-term EMAs as objective qualifiers.
• 3% ITM for each, which translated to 88 for XLE (91.13) and 127 for XLV (130.99)

One note will be explored in the future because it’s important, “Consider using realized volatility data to set a different moneyness value for two.” Volatility matters! 

Figures 4 and 5 provide the risk graphs for the two bullish case studies with a primary stated goal of monitoring how two relatively stronger (bullish), uncorrelated (0.199) sectors behave over the next month.

Despite the similar premium, note the spread for the XLV call is much larger after the close on 10/17/2023. It’s helpful with these case studies to have the midpoint built in and there was likely a better market for the monthly option at the close.

Each single call is under the $500 max loss and will be held until Nov 16th, the day before expiration. If this was a true set-up rather than observation, prices for an expected gain and loss would be provided for each underlying. 

The next few charts display the current data for each call option. A continued decline in XLE led to a larger loss for the option which is no longer in-the-money (ITM).

The back test data appears next with the right portion of the table cut so the information on the two call options could be shown side by side:

Here are a few questions to consider before we dig deeper next week:

• The charts were both trending downwards early during the period and it appears XLE is more volatile, but does the scaling come into play? 
• What can we assess to help explain the differences in performance when both stocks were trending downward?
• How different are the back test results between XLE and XLV?

Clearly XLE being out of the money with a short time to expiration is the key driver here, but let’s determine if there is more to uncover from this performance.

Regards,
Clare White, CMT

Appreciate you, Clare!