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Hi everyone,
As emphasised in CasP research, understanding capitalists’ fear allows to better grasp capitalist crises and limits to capitalist power. In that context Jonathan Nitzan and Shimshon Bichler propose the stimulating concept of systemic fear:
“Under normal circumstances, the performance of this ritual quantifies the way capitalists expect their power to unfold: the earnings they hope to redistribute, the risk they try to minimize and the normal rate of return that secures their rule as natural and their command as eternal. But during times of systemic fear, when the very future of their power is put into question, discounting cannot be properly performed, and the capitalization ritual, which otherwise embodies their confidence in obedience, breaks down” (Bichler & Nitzan, 2010, p. 38)
On the other hand, it seems common to assert in the financial world that price volatility is a manifestation of fear. For instance, it seems that VIX (a volatility index based on S&P 500 index options) is often called the fear index or fear gauge. Furthermore, many studies identify possible connections between volatility and political uncertainty, which could be a reason for fear.
Below I copy paste the evolution of the systemic fear index in the US from McMahon (2021):
and VIX between 1985 and 2012 from Wikipedia:
A proper comparison would be useful, but we can already see from these two figures that they do not necessarily peak at the same time.
However, don’t they both reflect a lack of certainty about the future?
Then, my questions are: how do you think systemic fear and volatility may relate to each other? Are they two manifestations of a same sentiment or do they point out to different kinds of fear? Could volatility be a more sudden manifestation of fear, such as a panic due to rapid (and uncontrolled) changes in the nomos, when discounters can’t easily reach an agreement on prices? While systemic fear would reflect a more profound outlook? Finally, can we think both as revealing periods of indeterminacy (and possible social changes), i.e. when the future is more open than usual?
Best,
Julien
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Thank you Julien.
1. Our Systemic Fear Index measures the short-term correlation between stock prices and current EPS. We argue that this measure indicates the extent to which asset pricing deviates from the key ritual of capitalizing expected future profits, and that this deviation indicates systemic fear because it shows the extent to which investors doubt their own central compass (A CasP Model of the Stock Market, 2016).
2. The VIX index is a short-term approximation of expected stock-price volatility (30 days to 1 year, depending on the measure).
Although both measures are related to fear, the nature of their respective fear seems different. The first measure is long term, focusing on very limits of capitalization, the second short term, focusing on stock price volatility in the near future.
Perhaps there is reason for them to correlate, though that reason doesn’t seem obvious on the surface.
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The CBOE volatility index measures the (expected) magnitude of price changes, whereas the systemic fear index measures the correlation between price and earnings-per-share. This means that the fear index is affected by both the volatility of prices and earnings. In other words, prima facie, an increase in volatility of prices could either undermine the correlation between price and earnings-per-share or reinforce it, depending on what is happening with earnings.
Nitzan and Bichler argue that the systemic fear index is positively associated (both empirically and theoretically) with the power index, which tracks stock prices relative to the wage rate (McMahon 2021 adds two further ways of measuring the power index). This means that as stock prices rise relative to the income of the general population, the power index (and by association, the systemic fear index) goes up.
Volatility appears to follow a different dynamic. Investopedia notes: “The [volatility index] generally rises when stocks fall, and declines when stocks rise.” This seems like common sense: when stocks go up, people are more likely to hold onto them then to sell. It also makes quantitative sense. If the magnitude of change is measured as a percentage, then when stock prices are higher, the same absolute change will register as a smaller rate of change, and therefore less volatile. I may be misinterpreting Investopedia’s claim, but its possible that the volatility index may simply be measuring a statistical regularity, and may have only a tenuous claim to measure ‘systemic’ phenomena.
Another thing to note is that larger firms tend to have less volatile prices than smaller firms, likely for the same reasons. People tend to trust, and therefore hold onto higher value stocks and the same absolute change in price registers as a smaller percent rate of change for the larger firm. The CBOE volatility index is based on the S&P500, which represents some of the largest firms, but there is a question of to what extent the S&P500 (or any group of firms) is representative of the ‘system’ as a whole.
That being said, I have found evidence that the volatility of the capitalization of some firms is linked to power dynamics. In my master’s research project, I found that the volatility of the capitalization of dominant semiconductor manufacturing firms was correlated with the total number of listed semiconductor manufacturing firms on the Compustat financial database. I argued in that paper that this was evidence that the growth of new firms caused greater uncertainty in the future earning-capacity of the large established firms.
A rise in new firms, however, says very little about systemic fear. If anything, proponents of the capitalist system point to such growth as proof of capitalism’s essential dynamism and a significant reason for its long term stability, and new firm growth is cause for optimism (among capitalists at large). -
The first measure is long term, focusing on very limits of capitalization, the second short term, focusing on stock price volatility in the near future. Perhaps there is reason for them to correlate, though that reason doesn’t seem obvious on the surface.
Thank you Jonathan for this clarification.
Volatility appears to follow a different dynamic. Investopedia notes: “The [volatility index] generally rises when stocks fall, and declines when stocks rise.” This seems like common sense: when stocks go up, people are more likely to hold onto them then to sell. It also makes quantitative sense. If the magnitude of change is measured as a percentage, then when stock prices are higher, the same absolute change will register as a smaller rate of change, and therefore less volatile. I may be misinterpreting Investopedia’s claim, but its possible that the volatility index may simply be measuring a statistical regularity, and may have only a tenuous claim to measure ‘systemic’ phenomena. Another thing to note is that larger firms tend to have less volatile prices than smaller firms, likely for the same reasons. People tend to trust, and therefore hold onto higher value stocks and the same absolute change in price registers as a smaller percent rate of change for the larger firm.).
Thank you for your input, James.
I think you are right that volatility cannot be always related to systemic phenomena (and as your Master thesis’ findings illustrate). Furthermore, traders can purposively provoke volatility to increase their share of the cake.
However, in the other way around, the relation could be true (systemic phenomena threatening power -> increased volatility), I think. I’ve found different papers suggesting at least that major political events create volatility. For example, this one on “political shocks and asset prices” finds that:
With respect to the size of these effects, the most significant increase in post-event volatility is associated with irregular government turnovers (coup d’états, presidential death, and resignations). […]. National elections are also a source of considerable financial volatility. In the case of nominal returns, the arrival of post-electoral news is associated with a 40 percent increase in volatility. The effect of electoral outcomes on asset prices is comparable to how the market reacts to changes in the country’s economic stewardship. Whenever the person in charge of the economy changes, regardless of whether the country’s administration changes or not, the post-event volatility ratios are also positive and statistically significant.
But I agree that it is definitely something different than N&B’s “systemic fear”. In this case the capitalization ritual does not seem broken.
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However, in the other way around, the relation could be true (systemic phenomena threatening power -> increased volatility), I think.
Thanks, Julien.
On the one hand, I agree that it is at least plausible that when systemic fear is high, volatility would also be high. It would be interesting to see if there is indeed an empirical correlation. I also think looking at how volatility, or changes in volatility are distributed (for instance, between large and small firms) in the context of the systemic fear index (and power index, for that matter) would be interesting.
On the other, as we’ve both noted, volatility is associated with a whole range of phenomena, meaning that its causes are to a certain extent over-determined. This makes it tricky as an analytical tool, especially with large aggregate measures like the CBOE VIX.
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