S&P 500, VIX Index, Stock Sector Diversification, Macro – Talking Points
- The S&P 500 has 11 sectors to choose from to diversify your stock portfolio
- Expanding exposure is not always ideal to avoid market volatility
- What levels of VIX undermine this strategy and what can traders do?
What is stock sector diversification?
If an investor wants to diversify exposure in the US stock market, there are plenty of sectors to choose from in the S&P 500. On the pie chart below, there are 11 to choose from from growth-oriented IT to industry-focused value-focused companies. To hedge sector-specific risks, a trader can allocate his portfolio among a combination of these.
In such a situation, if the S&P 500 hits a bump, losses in one corner of the market may be offset or reduced by gains in another. This may work if not all sectors of the market are in perfect harmony. However, when nearly every corner of the index falls in a binary movement, the stock diversification strategy becomes increasingly unreliable.
This is not a case against a stock diversification strategy. Instead, this is an analysis of conditions in the market that affect the sectors moving together in the S&P 500. This is performed using the CBOE Volatility Index (VIX), also known as the market’s preferred “fear gauge.” With that in mind, what levels of VIX should traders and investors watch that risk undermining a stock diversification strategy?
The collapse of the S&P 500 sector
What is VIX and why should traders watch it?
VIX was created in 1990 to be used as a standard for analyzing expectations of volatility in the US stock market. They are traded in real time, reflecting expectations of price action over the next 30 days. As such, it tends to have a very close inverse relationship to the S&P 500. In other words, as stocks go down, the VIX goes up and vice versa. To dig deeper into VIX, Check out the full guide here.
This inverse relationship can be seen in the following chart, which shows the average performance of the S&P 500 compared to equivalent VIX levels since 2002. For the study, average weekly data is used to calculate monthly results. This is done so that it helps to avoid the ‘volatility swing’ being cut off, while the monthly reading can bump into data that fails to capture the broader trend.
Looking at the data, April tended to see the most optimistic performance of the S&P 500, averaging 2.06%. After that, that performance faltered before hitting a bottom in October, when the benchmark stock index returned about -0.1%. During this period, we saw the VIX rise, starting at 18.30 in April, and then rising to 21.23 in October. Knowing this, we can now take a look at what’s happening inside the S&P 500.
VIX vs. S&P 500
S&P 500 Relationships Across Sectors with VIX
To see when a stock sector diversification strategy could fail, we will need custom price indices for the 11 sectors in the S&P 500. The data used for the latter only goes back to 2002. We can then find correlation levels between VIX and each sector using a one-month rolling basis One. Correlations range from -1 to 1. Reading A -1 means perfect inverse movements between two variables, while 1 is perfect harmony.
Calculating the average of all 11 outcomes in each reading period provides cross-sector correlation with VIX. Then, the correlations are separated into groups ranging from strong (-1 to -0.75), medium (-0.75 and -0.50), and weak (all values greater than -0.5). The strong reverse reading reflects the VIX up/down as the sectors together fell/rise with the most consistency. Weak sectors represent sectors that move more freely.
At 7 out of 12 months, higher levels of VIX were associated with stronger inverse associations across sectors with the ‘fear scale’. For example, VIX’s average weekly price in March was 26.55 when the S&P sectors moved the most in unison. The price fell to 15.28 when we saw the sectors moving more freely. Knowing this, what levels of VIX could undermine the diversification strategy across sectors?
VIX price against different levels of cross-segment inverse correlations in S&P
When can a stock sector diversification strategy fail?
We can now average VIX prices for all months and years since 2002 based on the three correlation groups. At the same time, we will average and align the weekly performance of all S&P segments based on the same categories. On the chart below, we can see that the result was somewhat predictable. Strong inverse correlations with VIX are in line with increasingly poor performance across sectors.
When we saw all sectors moving against the direction of VIX, the average price of the “Fear Scale” was 22.85. When this occurred, the average return per sector was -0.47%. On the contrary, when the sectors moved more freely relative to VIX, the price of the latter was 16.72. At this price, the average return between each segment was +1.08%.
It should be noted that correlation does not imply causation. Just because VIX is at an arbitrary price does not mean that it is the only reason for the trading dynamics between sectors. Instead, it is used here as a frame of reference. What actually causes markets to drop in binary moves is a combination of fundamental factors: monetary policy, fiscal spending, company direction, and more.
What can traders do about volatility?
Knowing this information, what can traders do when they expect high volatility and strong correlations across market segments? High volatility surges are often short-lived and temporary. During these times, haven-oriented assets tend to outperform. This includes the US dollar, Which often rises in times of global market stress. Short selling of shares is something else. Reducing exposure to existing and new tasks also helps. Combining these can help prepare dealers for some off-roading.
VIX price vs. S&P 500 segments performance based on correlation groups
– By Daniel Dobrovsky, strategic for DailyFX.com
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