Market volatility measures the size of variations of asset returns. Macroeconomic uncertainty measures the size of unpredictable disturbances in economic activity. Large moves in macroeconomic uncertainty are less frequent and more persistent than shifts in market volatility. However, macroeconomic uncertainty is an important driver of market volatility because it is related to future earnings and dividend discount rates. One proxy of macro uncertainty is a weighted average of forecasting errors over a wide set of macroeconomic indicators. Empirical evidence suggests that this proxy of latent macro uncertainty is a significant predictor of volatility and volatility jumps.
The below is a summary based on:
Megaritisa, Anastasios, Nikolaos Vlastakisa and Athanasios Triantafylloua (2020) Stock market volatility and jumps in times of uncertainty.
Jurado, Kyle, Ludvigson, Sydney., and Serena Ng (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216.
Macrodesiac post “Your Volatility Handbook”.
The post ties up with this site’s summary on macro trends.
The difference between market volatility and macro uncertainty
“Asset volatility is the standard deviation of logarithmic returns…[typically] between daily closing prices…This is simply known as close-close volatility…When dealing with volatility, it is a convention for it to be quoted as an annualised figure…The sampled realised volatility that a trader receives is not necessarily the same as the population volatility. Volatility is time-variant. Assets go through different ‘regimes’ of volatility.” [Macrodesiac]
“The extant empirical literature suggests that short-term volatility and jumps in the equity market are predictable to a degree using variables such as lagged realized volatility and implied volatility…Moreover…a large part of the time variation of equity market volatility can be explained by a single common factor.” [Megaritisa, Vlastakisa and Triantafylloua]
“Stock market volatility can change over time even if there is no change in uncertainty about economic fundamentals, [for example] if leverage changes, or if movements in risk aversion or sentiment are important drivers of asset market fluctuations…Most movements in common uncertainty proxies, such as stock market volatility (the most common), and measures of cross-sectional dispersion, are not associated with a broad-based movement in economic uncertainty.” [Jurado, Ludvigson, and Ng]
“Macroeconomic uncertainty…may be observed in many economic indicators at the same time, across firms, sectors, markets, and geographic regions….[It] is typically defined as the conditional volatility of a disturbance that is unforecastable from the perspective of economic agents…Increases in uncertainty can depress hiring, investment, or consumption if agents are subject to fixed costs or partial irreversibilities, if agents are risk averse, or if financial constraints tighten in response to higher uncertainty.” [Jurado, Ludvigson, and Ng]
“Quantitatively important [macroeconomic] uncertainty episodes appear far more infrequently than indicated by popular uncertainty proxies [such as market volatility], but when they do occur, they are larger, more persistent, and are more correlated with real activity.” [Jurado, Ludvigson, and Ng]
An introductory post on measures of market risk and uncertainty can be found here.
Measuring macro uncertainty
“Unobservable (latent) macroeconomic uncertainty…captures the unforecastable variations in key macroeconomic indicators. As a proxy for macroeconomic uncertainty, we use the unobservable Macroeconomic Uncertainty measure of Jurado et al. (2015), which captures the time variation in the degree of unpredictability of US macroeconomic fluctuations. [It] is defined as the squared forecast error of a multivariate factor model used for forecasting US business cycles.” [Megaritisa, Vlastakisa and Triantafylloua]
“Our goal is to provide superior econometric estimates of [macroeconomic] uncertainty…We start from the premise that what matters for economic decision making is not whether particular economic indicators have become more or less variable or disperse per se, but rather whether the economy has become more or less predictable; that is, less or more uncertain…If the expectation today (conditional on all available information) of the squared error in forecasting [future economic activity] rises, uncertainty in the variable increases. A measure…of macroeconomic uncertainty can then be constructed by aggregating individual uncertainty at each date using aggregation weights.” [Jurado, Ludvigson, and Ng]
“We emphasize two features of these definitions.
- First, we distinguish between uncertainty in a series [of economic activity] and its conditional volatility. The proper measurement of uncertainty requires removing the forecastable component.
- Second, macroeconomic uncertainty is not equal to the uncertainty in any single series [of economic activity] . Instead, it is a measure of the common variation in uncertainty across many series. This is important because uncertainty-based theories of the business cycle typically require the existence of common (often countercyclical) variation in uncertainty across large numbers of series.” [Jurado, Ludvigson, and Ng]
“We find significant independent variation in our estimates of uncertainty as compared to commonly used proxies for uncertainty. An important finding is that our estimates imply far fewer large uncertainty episodes than what is inferred from all of the commonly used proxies [such as VIX]… Moreover, our estimate of macroeconomic uncertainty is far more persistent than stock market volatility: the response of macro uncertainty to its own innovation from an autoregression has a half-life of 53 months; the comparable figure for stock market volatility is four months.” [Jurado, Ludvigson, and Ng]
The uncertainty measures of Jurado et al. (2015) is not a real-time index but historic time series are available at https://www.sydneyludvigson.com/data-and-appendixes
The relation between macro uncertainty and market volatility
“The main channel through which economic uncertainty affects the volatility of stock prices is by increasing the uncertainty about future cash flows (dividends). The discounted cash flow model specifies that the fair value of a firm’s stock is equal to the sum of the discounted expected cash flows to its stockholders…Nevertheless, the majority of related studies show that stock price fluctuations are too high to be entirely attributed to fluctuations of their discounted dividend yields.” [Megaritisa, Vlastakisa and Triantafylloua]
“[Academic] literature shows…the significant impact of macroeconomic news releases and policy uncertainty on stock market volatility…[and] that equity market volatility is related to business cycle fluctuations…Macroeconomic news announcements explain more than three-fourths of the intra-day S&P500 index futures price jumps which occur during the morning hours when macroeconomic news are released…Excess returns in equity markets accrue around scheduled macro-news announcement hours.” [Megaritisa, Vlastakisa and Triantafylloua]
“When the forecast errors of investors regarding the future state of the macroeconomy are reduced, this results in decreasing stock market volatility. This reduction in stock market volatility comes not through less fluctuations in the real economy, but through less ambiguity (or uncertainty) about these cash flows. The rising macroeconomic uncertainty represents the component of stock market volatility which cannot be explained by fundamentals.” [Megaritisa, Vlastakisa and Triantafylloua]
The predictive power of macro uncertainty
“We estimate monthly realized variance and jump tail risk, using high-frequency (5-minute) price observations for the S&P 500 index for the period between 1st January 1990 and 31st December 2017.” [Megaritisa, Vlastakisa and Triantafylloua]
“Stock market volatility is significantly affected by the rising degree of unpredictability in the macroeconomy, while it is relatively immune to shocks in observable uncertainty proxies…We find that increasing macroeconomic uncertainty predicts a subsequent rise in volatility and price jumps in the US equity market. Our analysis shows that the latent macroeconomic uncertainty measure of Jurado has the most significant and long-lasting impact on US stock market volatility and jumps in the equity market when compared to the respective impact of the VIX and other popular observable uncertainty proxies.” [Megaritisa, Vlastakisa and Triantafylloua]
“Latent macroeconomic uncertainty has significant predictive power on US stock market volatility and contains information which is different to the predictive information content of the VIX and other uncertainty.” [Megaritisa, Vlastakisa and Triantafylloua]
“The fact that the macroeconomic uncertainty factor has incremental predictive power when included into a multivariate forecasting regression model which includes the VIX, US Industrial Production and the Baa corporate default spread, shows that the macroeconomic uncertainty factor indeed explains the part of stock market volatility which cannot be attributed to changes in fundamentals.” [Megaritisa, Vlastakisa and Triantafylloua]
“Moreover…a positive latent macroeconomic uncertainty shock has larger and more long-lasting positive effect on stock market volatility compared with the respective impact of VIX shocks and shocks to other popular observable economic uncertainty proxies. For example, the response of stock market volatility to macroeconomic uncertainty shocks is more than 3 times larger in magnitude and persistence when compared with the respective response of stock market volatility to VIX or Economic Policy Uncertainty shocks.” [Megaritisa, Vlastakisa and Triantafylloua]
“[However,] the macroeconomic uncertainty factor does not provide significant forecasts regarding the discontinuous (jump) component of stock market volatility…The VIX and the lagged [volatility jump] variables are the most significant predictors of [volatility jumps] in the US stock market.” [Megaritisa, Vlastakisa and Triantafylloua]
“The macroeconomic uncertainty factor produces significantly better out-of-sample realized volatility forecasts when compared with economic policy uncertainty and monetary policy uncertainty. More specifically, when using macroeconomic uncertainty as our only predictor of SP500 realized volatility for one-month horizon, we obtain out-of-sample adjusted R2 values of 17.8% as opposed to 0.5% and 2.6% when using EPU and MPU instead. These results show that the latent macroeconomic uncertainty factor has the highest predictive power on stock market volatility when compared to popular macroeconomic uncertainty proxies…[However,] the macroeconomic uncertainty factor cannot outperform the VIX in real-time out-of-sample stock market volatility forecasting, since the respective out-of-sample R2 value for our VIX bivariate model is 26.4%.” [Megaritisa, Vlastakisa and Triantafylloua]
“The impact of macroeconomic uncertainty shocks on US stock market volatility has exponentially increased during the post-2007 crisis period.” [Megaritisa, Vlastakisa and Triantafylloua]
