When the United States and Mexico reached a new understanding about trade matters this past summer, renegotiating parts of the North American Free Trade Agreement, President Donald Trump cheered. Others had questions: How would the deal affect the US auto industry? How would it affect consumers? What would it mean for recent tariff hikes on steel and aluminum imports? You could almost hear executives across the continent reaching for antacids.
Moments such as this carry significant risk for business, and there have been many such moments of late. “Political uncertainties abound,” observes Chicago Booth’s Steven J. Davis: “Brexit, Trump, trade wars, eurozone perils, autocracy in Turkey, war in the Middle East, clampdowns in China, corruption scandals in Brazil, crisis in Argentina, and more.”
But the tools that exist to help investors and businesses navigate through uncertainties are surprisingly limited. The CBOE Volatility Index (the VIX, popularly known as “Wall Street’s fear gauge”) and other derivatives contracts including futures and swaps can indicate traders’ worry levels and serve as financial insurance. But derivative contracts can also be imperfect tools, amplifying risks rather than containing them. And these markets, more popular in finance than with mainstream investors, can be narrow—revealing traders’ thoughts about what’s happening in large-cap stocks, for example, as opposed to the economy at large.
Research, however, is producing new ways to assess economic uncertainty and tracking how some of that uncertainty manifests itself in stock and bond markets. While risk is ever present, new methods of measurement could help investors better navigate the current moment.
An index of uncertainty
Making sense of uncertain times can stump the most educated and informed people. Justin Wolfers of the University of Michigan and Eric Zitzewitz of Dartmouth College estimated that US President Donald Trump’s election would cause stock prices to fall by 10–15 percent. Bridgewater Associates, the world’s largest hedge fund, told clients it expected a similar decline if Trump won. Simon Johnson of MIT predicted Trump’s election “would likely cause the stock market to crash and plunge the world into recession,” and billionaire Dallas Mavericks co-owner and Shark Tank star Mark Cuban said, “There is a really good chance we could see a huge, huge correction” of 20 percent or more.
Instead, the Wilshire 5000 Total Market Index, which covers a broad swath of US equities, soared 38 percent from just before the election until late January. And the VIX, the most widely used barometer of stock market volatility, hit an all-time low in November 2017. Volatility dominates risk-management models in finance, and many interpreted a low VIX as a sign that investors were feeling calm and confident.
But the VIX does not capture all economic risk, Davis observes, so much as it measures risk on Wall Street. The index charts market participants’ expectations of volatility, as implied by options trading on the S&P 500, reflecting uncertainty specifically about the short-term volatility of the 500 large, publicly traded stocks that make up that index. These give an important yet incomplete view of the economy, considering that all publicly listed companies account for less than a third of private-sector employment, and the stocks in the S&P 500 skew toward bigger, older, capital-intensive, skill-intensive, and multinational companies.
This dive into uncertainty is helping to illuminate and explain what had previously been unseen, like dark matter of the economic universe.
Is there a way to measure a broader set of economic risks? Davis started pondering this as the dust was clearing from the 2008–09 financial crisis, when there was a lot of uncertainty, particularly in developed economies, about how policy makers would react. “Back in 2010, [Nicholas Bloom of Stanford] and I, and others as well, had the sense that we were living through an unusual historical epoch, in terms of how much policy-related economic uncertainty there was,” Davis says. “We had just come through a global financial crisis that presented policy makers with unusual and extraordinarily complex policy challenges.”
Economists had thought about such uncertainty before, but no one had measured it. Outside of financial markets, the research into economic uncertainty was mostly theoretical. Bloom, Davis, and Northwestern’s Scott R. Baker set about to make the concept less “squishy” by quantifying it. To do this, they wrote a list of terms generally associated with uncertainty, business, and government. They then analyzed the content of 10 major US newspapers, directing a team of students to flag articles in which those terms appeared. Using the flagged articles to refine their term list, the researchers arrived at a list of keywords that they used to classify articles as reports of policy-based economic uncertainty. Finally, they automated the process and had a computer count articles that met their term-set criteria (see graphic). They used the process to produce the Economic Policy Uncertainty Index, which debuted in 2013.
The index highlights that policy uncertainty has risen significantly since the 1960s. Exploring the reasons with Princeton’s Brandice Canes-Wrone and Stanford’s Jonathan A. Rodden, the researchers argue that the rise closely tracks two trends: the growing reach of government, and an increase in political polarization.
An explosion of indices
The US EPU represented a new take on risk, although the researchers noted “a strong relationship” between the US EPU and the VIX, which moved in the same direction as the EPU more than half the time. Davis notes that the EPU tends to be countercyclical, high in weak economies and low in strong ones. In this sense, it’s a lot like the VIX—reflecting investors’ anxiety and complacency.
But when the VIX drifted down in January 2017, the US EPU index remained elevated through April of that year. Chicago Booth’s Lubos Pastor and Pietro Veronesi argue in a VoxEu column that the divergence indicated investors didn’t know how to interpret unreliable and inconsistent political news. “Political news is noisier than it used to be,” they write. “Investors are becoming skeptical that politicians’ pronouncements have much to do with their future policy actions.”
When the US EPU was high, some companies appeared particularly affected, demonstrating higher stock-price volatility and reduced investment and employment. The researchers find that these companies were in industries that relied heavily on government spending, including defense and health care. This finding, they conclude, “points to a policy uncertainty channel at work rather than a broader uncertainty effect.”
Economic risk beyond Wall Street
Complementing the widely used VIX, the researchers’ index provides a measurement of uncertainty about economic policy.
Due to the complicated nature of the VIX, investors and traders have misused some ETFs and ETNs that go long or short on the VIX. In early February, three small exchange-traded products that went short on volatility plunged more than 90 percent in a single day when the VIX itself spiked to 37 amid a big sell-off in stocks. This caused those funds to shut down and wiped out the holdings of many unsophisticated individuals who did not fully understand these short-VIX vehicles, an event traders dubbed Vol-mageddon.
This led Xiu to track the real risk of any exchange-traded asset, tapping into the trove of high-frequency-trading data he has long studied, to estimate daily annualized volatilities for US stocks, ETFs, and futures on many asset classes, using trades-and-quotes data collected at the highest frequency available—up to every millisecond for US stocks after 2007.
A sample of his data resides in beta form online, stored publicly in what he calls the Risk Lab. On his faculty website, he displayed a chart tracing the daily volatility of the SPDR S&P 500 ETF over periods ranging from one month to more than 20 years. Not surprisingly, its biggest spike in volatility, an astonishing 89 percent move, came in October 2008, in the heat of the financial crisis.
He also posts data on the daily volatility of several ETFs that track the nine major sectors of the S&P. During a week in mid-June, the Energy Select Sector SPDR ETF had the highest volatility—between 14 percent and 17 percent over the previous five trading days—while the Health Care Select Sector SPDR ETF had the lowest, ranging from about 7 to 10 percent during that time. Xiu plans to add international stocks to his Risk Lab as well.
Rui Da and Dacheng Xiu, “When Moving-Average Models Meet High-Frequency Data: Uniform Inference on Volatility,” Working paper, September 2017.
In strong economies, the announcements of politicians rarely shake markets because governments are unlikely to change their policy when things are going well. But during recessions, governments tend to take stimulative measures—with unknown outcomes. This is why political news affects markets especially when the economy is weak, according to Pastor and Veronesi.
When the financial system shook in fall 2008, the market was still volatile despite government actions. And in the aftermath, investors reacted strongly to political news. After share prices bottomed in March 2009 during the Great Recession, the economy remained weak, losing hundreds of thousands of jobs a month. Yet reacting to comments from Federal Reserve Chairman Ben Bernanke and the promise of an economic stimulus package from Congress, investors started buying stocks.
“Political uncertainty makes stocks more volatile because it makes political signals more potent,” Pastor and Veronesi write. “It also makes stocks more correlated because political signals affect all firms.” Thus, because uncertainty increases the correlations between individual stocks, it’s harder for investors to diversify it away.
To test these ideas, the researchers turned to options markets. A stock option can function like insurance that kicks in if a stock price falls, and contracts can be bought and sold for specific timeframes. At Booth, Bryan Kelly (now at Yale) and Pastor and Veronesi looked at elections and summits, which regularly produce policy shifts, to compare the price paid for options that expired just before, during, and just after an event.
Sure enough, investors put a dollar value on political risks associated with such events. And they put a higher value on them when the economy is weak and political uncertainty is high, because that is when lasting political change is more likely, say Pastor and Veronesi.
The three researchers analyzed stock options data from 20 countries dating back to 1990. They looked at what happened around key events, including the 2008 US presidential election and the 2012 Greek parliamentary elections, both of which occurred in the midst of financial crises. The researchers then looked at how options contracts performed around such events—and confirmed that options protection is more expensive before a major political event.
“Our results indeed suggest a sizable risk premium for political uncertainty, especially in a weak economy,” they write. This fact, that the risk premium for political uncertainty is higher in a weak economy, is something investors could use to better protect themselves—and profit from.
Risk in credit markets
Uncertainty, naturally, affects bond markets too. Veronesi wanted to quantify the impact of political uncertainty on bond markets, and again turned to options to do so.
Investors measure the risk of an individual bond by looking at the difference between its yield and that of the benchmark 10-year US Treasury note. In general, the riskier the bond, the wider its “spread” against Treasuries, as investors demand a higher yield to compensate them for the greater risk.
Measuring the impact of macroeconomic uncertainty on these spreads can be tricky, mostly because credit markets aren’t as transparent as equity markets, and because some corporate bonds aren’t particularly liquid. Also, since corporate bonds reflect the financial situations of individual companies, it’s tough to separate macro factors from the so-called idiosyncratic risk that individual companies may face, such as the impact of heavy borrowing or changes in their credit rating.
Many companies are reassessing spending plans.Trump’s Trade-Policy Uncertainty Deters Investment
Pseudo firms reveal that the primary element driving corporate credit spreads is a premium for tail and idiosyncratic asset risks.Are Investors Paying Too Much for ‘Black Swan’ Risk?
To strip away idiosyncratic risk, Johns Hopkins’s Christopher L. Culp, Yoshio Nozawa of the Federal Reserve Board, and Veronesi created a set of fictitious companies, called “pseudo firms,” that “have simple and empirically observable balance sheets,” they write. “Our pseudo firms have assets comprised of real traded securities and liabilities comprised of equity and zero-coupon bonds.” These pseudo firms issue pseudo bonds, whose properties are close to those of real corporate bonds, but without the quirky properties that make it harder to measure the true impact of uncertainty on credit spreads.
Culp, Nozawa, and Veronesi find that higher pseudo spread values predicted lower future economic growth, indicating that corporate bond and options markets move closely together and that investors demand a higher premium to take the risk of less likely events. The premium drives corporate spreads, so by using pseudo bonds, investors can get a better idea of how policy uncertainty, and other macroeconomic risks, affect real bond prices.
As Baker, Bloom, and Davis do with their policy uncertainty indices, Culp, Nozawa, and Veronesi track their universe of pseudo firms online, at the Credit Risk Laboratory website, where they regularly update data to reflect market conditions and introduce new pseudo firms and pseudo bonds. The more of these they add, the more investors and scholars can discover variations in the sensitivity to uncertainty among sectors and industries—and even individual companies.
Measuring all this uncertainty won’t make it go away, of course. The late physicist Werner Heisenberg established an uncertainty principle that says scientists can never be sure of the speed and position of microscopic particles at the subatomic level. “The most we can hope for is to calculate probabilities for where things are and how they will behave,” explained science journalist Alok Jha. In finance—a long way from quantum mechanics—researchers have similarly realized that uncertainty will always be a central part of markets. But the hope is that with a better ability to measure risk, investors can come closer to living with it.
- Scott R. Baker, Nicholas Bloom, Brandice Canes-Wrone, Steven J. Davis, and Jonathan A. Rodden, “Why Has US Policy Uncertainty Risen since 1960?” American Economic Review Papers and Proceedings, May 2014.
- Scott R. Baker, Nicholas Bloom, and Steven J. Davis, “Measuring Economic Policy Uncertainty,” Quarterly Journal of Economics, November 2016.
- Christopher L. Culp, Yoshio Nozawa, and Pietro Veronesi, “Option-Based Credit Spreads,”American Economic Review, February 2018.
- Steven J. Davis, “An Index of Global Economic Policy Uncertainty,” Macroeconomic Review, October 2016.
- Bryan Kelly, Lubos Pastor, and Pietro Veronesi, “The Price of Political Uncertainty: Theory and Evidence from the Option Market,” Journal of Finance, March 2016.
- Lubos Pastor and Pietro Veronesi, “Political Uncertainty and Risk Premia,” Journal of Financial Economics, December 2013.
- ———, “Explaining the Puzzle of High Policy Uncertainty and Low Market Volatility,” VoxEu.org, May 25, 2017.
- Pietro Veronesi, “Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model,” Review of Financial Studies, Winter 1999.
- Justin Wolfers and Eric Zitzewitz, “What Do Financial Markets Think of the 2016 Election?” Brookings Institution report, October 2016.
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