16 février 2017

Financial and Political Uncertainty in Perspective

February 16, 2017, by Dr. Christian Witt (YCAP Asset Management)

The world seems to be flooded with political uncertainty. From Brexit worries to Trump (Goldman’s worries, Weird Conduct, Reichstag Moment), the rise of populism in Europe (Bershidsky, Walesa) or the upcoming Chinese Communist Party’s National Congress. Yet, financial markets do not seem to bother. How so?

To provide some context, we first look at economic policy uncertainty (EPU) as measured by a news-based index developed by Baker, Bloom and Davis (in fact, we compute the average of a PPP and FX-weighted global index). As Figure 1 shows, global EPU has typically oscillated around zero up until the Great Recession. Ever since, there has been an unmistakable drift towards higher EPU. Most notably, in the wake of Brexit and the US election, global EPU has risen to the highest level since the index started in 1997.

Technical Disclaimer: A description of the Economic Policy Indicator (EPU) as well as all statistical metrics are presented in detail at the end of this article.

However, the global index obliterates a startling dispersion across regions (see Figure 2). To see this, we compute the excess EPU by subtracting the global EPU from the country-specific EPU. The results yield a big surprise. In the US, excess EPU is at all-time lows, whereas in China the measure stands at historical highs. European excess EPU wildly fluctuates. What puzzles us the most, is the obvious decoupling between the global EPU trend (+4 standard deviations) and the US excess EPU (-2 standard deviations) just around the time of the US elections. If at all, there is a negative Trump effect in the US. How is that possible? An explanation reconciling these opposites may be that Trump stands for a ‘rebalancing’ of the world order, both in diplomatic/military and economic terms. As a result, his election may be much more felt outside than inside the US. Countries that heavily depend on US exports (e.g. China, Japan, Germany/EU, Mexico), on US military protection (Europe, Japan) or potential rivals (China) would therefore be affected the most. The lesson to be learned here is one needs to study both the absolute level of global EPU as well as its regional dispersion.

Another finding is that EPU seems to have shifted from the US towards Europe (see Figure 3). For prior to the Euro Sovereign Debt Crisis, peaks in global uncertainty (see Figure 3) typically coincided with a higher EPU reading in the US (red) than in Europe (blue). But the relation has inverted in the aftermath of the crisis. In our eyes this structural break could be interpreted as evidence that Europe remains much more fragile under the surface than widely recognized. For instance, new episode of ‘European theatre’ emerge every now and then. Last year, such episodes included the Spanish re-re-election boogie or the Italian constitutional referendum. This year starts off with contested European elections in the Netherlands, France and Germany and a revival of the Grexit debate.

At last, we compare several financial measures to the global EPU. It turns out the co-movement of global EPU has shifted from equity risk to sovereign risk over time. Let’s look at equities first. As Figure 4 demonstrates an average of implied stock market volatility indices (VIX, VSTOXX, VNIKKEI) was strongly correlated with peaks in EPU up until the European Sovereign Debt Crisis. The relation subsequently broke down. Thus, precisely when the European EPU gained influence on global EPU as shown before, equity risk decoupled from global EPU. Figure 5 indicates that sovereign risk filled the void. In fact, starting with the Great Depression the average spread of French and Italian 10Yr yields over their German peers has been meaningfully correlated with global EPU. However, different from equity risk, the sovereign risk relation has remained intact ever since. Moreover, following a similar pattern, the EUR/USD exchange rate has started to move in lockstep with global EPU since the Great Recession, too (see Figure 6). Taken together, the evidence suggests global EPU became more (less) integrated with sovereign risk (equity markets) at about the same time when European EPU started to dominate its US equivalent.

To sum up, the level and drivers of global EPU as well as the co-movement with financial risk indicators have undergone dramatic changes during the Great Recession and European Sovereign Debt Crisis. Since 2007, European EPU has gradually emerged as one of the most important contributors to global EPU, eventually superseding its US counterpart. Historically low US excess EPU is a case in point. Whether coincidence or not, about the same time stock market volatility decoupled from global EPU; (European) sovereign yield spreads took its place. In our assessment, the implications for financial markets are severe:

  • The currently strong relation between global EPU and European EPU may reverse again. Then, stock market volatility should re-emerge as a financial proxy of political uncertainty.
  • Historically high divergence of US excess EPU needs to mean-revert at some point. Either historically high global EPU will return to its normal range, or the US EPU will catch up with its global equivalent. In the former case (EPU normalization), receding political uncertainty should support financial markets. In the latter case (US EPU surge), financial markets might abruptly converge towards much higher political uncertainty; either in the form of a jump in equity market volatility or suddenly soaring yields.

Whatever scenario materializes, investors should be wary of their downside. Stock market volatility is already low and sovereign spreads still manageable. But should implied volatilities (sovereign spreads) play catch up with global EPU, they could easily hit 2008 (2012) levels (compare Figures 4 and 5). No pleasant picture.

 

Figure 1: Global Economic Policy Uncertainty (Z-Score, 3m-MAV)


Figure 2: Excess Economic Policy Uncertainty by Region (Z-Score, 3m-MAV)


Figure 3: Economic Policy Uncertainty: Global and Europe vs. USA (Z-Score)


Figure 4: Economic Policy Uncertainty and Implied Volatility (Z-Score)


Figure 5: Economic Policy Uncertainty and the Sovereign Spreads (Z-Score)

Figure 6: Economic Policy Uncertainty and the EUR/USD Exchange Rate (Z-Score)

 

Technical Annex:

  1. Economic Policy Uncertainty (EPU) index: The EPU index is a news-based indicator developed by the Scott Baker (Northwestern University), Nick Bloom (Stanford University), and Steven Davis (University of Chicago). In fact, to detect economic policy uncertainty, an algorithm screens newspaper articles for a certain combination of words related to the topic. If the algorithm frequently (rarely) detects the defined search terms in newspaper articles, the resulting EPU index is high (low). The relative frequency is also scaled by the number of published articles in a given month to account for activity clustering. For the US, the search terms are (E) « economy, economic, commercial » (P) « regulation, deficit, legislation, congress, white house, Federal Reserve, the Fed, regulations, regulatory, deficits, congressional, legislative, and legislature », and (U) « uncertainty, uncertain ». The following newspapers are considered: LA Times, USA Today, Chicago Tribune, Washington Post, Boston Globe, Wall Street Journal, Miami Herald, Dallas Morning News, Houston Chronicle, San Francisco Chronicle, New York Times. The proposed technique can be potentially applied to both other countries and topics. A comprehensive description of the methodology and the scientific background can be found on this website. The newest version of their scientific paper is available free of charge on their website (including a study going back to 1900): http://www.policyuncertainty.com/media/EPU_BBD_Mar2016.pdf.
  2. Z-Score: All EPUs reported in this article have been transformed into z-scores to make them comparable across time and countries. The respective z-score for country and month is computed as , where denotes the typical monthly country-specific EPU index value, the historical mean, and the historical standard deviation. Only after being transformed into z-scores are the different EPUs comparable across countries/regions.
  3. Excess EPU (see Figure 2): The excess EPU is the difference between a country-specific EPU and the global EPU: . Thus, if the excess EPU is positive (negative) the country-specific EPU is above (below) the global EPU. This technique is used to compute the series shown in Figure 2. The computation is based on the respective z-scores as defined in (2).
  4. Excess EPU Europe/USA (see Figure 3): In a minor variation of the excess EPU, we also compute the difference between the European and US EPU: . Thus, if the excess EPU Europe/USA is positive (negative) the European EPU is above (below) its US equivalent. This technique is used to compute the series shown in Figure 3. The computation is based on the respective z-scores as defined in (2).