PRESIDENTIAL ELECTION UNCERTAINTY AND COMMON STOCK RETURNS IN THE UNITED STATES

There is substantial evidence on the influence of political outcomes on the business cycle and stock market. We further hypothesize that uncertainty about the outcome of a U.S. presidential election should be reflected in pre‐election common stock returns. Prior research pools returns based on the party of the winning candidate, assuming that the outcome of the election is known a priori. We use candidate preference (i.e., polling) data to construct a measure of election uncertainty. We find that if the election does not have a candidate with a dominant lead, stock market volatility (risk) and average returns rise.     

WHEN ELECTIONS FAIL TO RESOLVE UNCERTAINTY: THE CASE OF THE 2016 U.S. PRESIDENTIAL ELECTION

In this article, we examine whether certain political election outcomes create, rather than resolve, uncertainty in financial markets. We posit that the market uncertainty associated with unanticipated election outcomes is not resolved before or on the election dates. To test this claim, we use the surprise outcome of the 2016 U.S. presidential election and two previous U.S. presidential elections as benchmarks. In contrast to prior elections, we find that the 2016 U.S. presidential election outcome did not resolve market uncertainty. Specifically, we show significant increases in transactions costs, adverse selection costs, and volatility in the days following the election date. We contribute to the literature by suggesting that unexpected elections can engender, rather than resolve, market uncertainty.     

Volatility spillovers and the effect of news announcements

We examine the effect of US and European news announcements on the spillover of volatility across US and European stock markets. Using synchronously observed international implied volatility indices at a daily frequency, we find significant spillovers of implied volatility between US and European markets as well as within European markets. We observe a stark contrast in the effect of scheduled versus unscheduled news releases. Scheduled (unscheduled) news releases resolve (create) information uncertainty, leading to a decrease (increase) in implied volatility. Nevertheless, news announcements do not fully explain the volatility spillovers, although they do affect the magnitude of volatility spillovers. Our results are robust to extreme market events such as the recent financial crisis and provide evidence of volatility contagion across markets.     

Stock market volatility around national elections

This paper investigates a sample of 27 OECD countries to test whether national elections induce higher stock market volatility. It is found that the country-specific component of index return variance can easily double during the week around an election, which shows that investors are surprised by the election outcome. Several factors, such as a narrow margin of victory, lack of compulsory voting laws, change in the political orientation of the government, or the failure to form a government with parliamentary majority significantly contribute to the magnitude of the election shock. Furthermore, some evidence is found that markets with short trading history exhibit stronger reaction. Our findings have important implications for the optimal strategies of institutional and individual investors who have direct or indirect exposure to volatility risk.     

Better the devil you know: The influence of political incumbency on Australian financial market uncertainty

The Australian federal election cycle, which occurs approximately every 3 years, causes much media attention and invokes indecision regarding investment decisions in both the real economy and financial markets. This paper constructs measures of political uncertainty and formally explores their relationship with market uncertainty, as measured by implied volatility. The empirical evidence suggests that increasing (decreasing) levels of uncertainty around the election result induce higher (lower) levels of market uncertainty. In a case of the market preferring the devil it knows, an increasing (decreasing) likelihood of the incumbent party, whose economic policies are well-known, winning the election, reduces market uncertainty. The results remain significant even after controlling for a number of macroeconomic variables, and when an alternative GARCH framework is considered.     

News implied volatility and disaster concerns

We construct a text-based measure of uncertainty starting in 1890 using front-page articles of the Wall Street Journal. News implied volatility (NVIX) peaks during stock market crashes, times of policy-related uncertainty, world wars, and financial crises. In US postwar data, periods when NVIX is high are followed by periods of above average stock returns, even after controlling for contemporaneous and forward-looking measures of stock market volatility. News coverage related to wars and government policy explains most of the time variation in risk premia our measure identifies. Over the longer 1890–2009 sample that includes the Great Depression and two world wars, high NVIX predicts high future returns in normal times and rises just before transitions into economic disasters. The evidence is consistent with recent theories emphasizing time variation in rare disaster risk as a source of aggregate asset prices fluctuations.     

Cross-section of option returns and volatility

We study the cross-section of stock option returns by sorting stocks on the difference between historical realized volatility and at-the-money implied volatility. We find that a zero-cost trading strategy that is long (short) in the portfolio with a large positive (negative) difference between these two volatility measures produces an economically and statistically significant average monthly return. The results are robust to different market conditions, to stock risks-characteristics, to various industry groupings, to option liquidity characteristics, and are not explained by usual risk factor models.     

The predictive power of the implied volatility of options traded OTC and on exchanges

This paper investigates the efficiency of stock index options traded over-the-counter (OTC) and on the exchanges in Hong Kong and Japan. Our findings suggest that implied volatility is superior to either historical volatility or a GARCH-type volatility forecast in predicting future volatility in both the OTC and exchange markets. This paper is also one of the first to compare the predictive power of the implied volatility of stock index options traded OTC to that of exchange-traded stock index options. Our evidence suggests that the OTC market is more efficient than the exchanges in Japan, but that the opposite is true in Hong Kong.     

Spreading the fear: The central role of CBOE VIX in global stock market uncertainty

Construction of efficient portfolios is reliant on understanding the correlation between assets. If correlations change markedly during times of economic turmoil then investors are exposed to greater risk at the most inopportune time. We examine the linkages between global stock markets using measures of market uncertainty (implied volatility). Using a sample of daily changes in G7 and BRIC implied volatility measures, over a 20-year sample period, we demonstrate that uncertainty in U.S. markets plays a pivotal role in global stock market uncertainty. “Fear is spread” across markets, as heightened uncertainty in U.S. markets is transmitted across global markets. Conversely, changes in global market uncertainty do not explain changes in U.S. market uncertainty. While there is a clear increase in connectedness during crisis periods, we observe a disparity in the way that inter-dependencies change during the two major economic crises in our sample period; the GFC (2007–2009) and COVID-pandemic (2020). The additional importance of US news largely drives our results during the GFC, while the effect is spread among several countries (particularly within European markets) during COVID.     

Oil prices implied volatility or direction: Which matters more to financial markets?

We examine the impact of oil price uncertainty on US stock returns by industry using the US Oil Fund options implied volatility OVX index and a GJR-GARCH model. We test the effect of the implied volatility of oil on a wide array of domestic industries’ returns using daily data from 2007 to 2016, controlling for a variety of variables such as aggregate market returns, market volatility, exchange rates, interest rates, and inflation expectations. Our main finding is that the implied volatility of oil prices has a consistent and statistically significant negative impact on nine out of the ten industries defined in the Fama and French (J Financ Econ 43:153–193, 1997) 10-industry classification. Oil prices, on the other hand, yield mixed results, with only three industries showing a positive and significant effect, and two industries exhibiting a negative and significant effect. These findings are an indication that the volatility of oil has now surpassed oil prices themselves in terms of influence on financial markets. Furthermore, we show that both oil prices and their volatility have a positive and significant effect on corporate bond credit spreads. Overall, our results indicate that oil price uncertainty increases the risk of future cash flows for goods and services, resulting in negative stock market returns and higher corporate bond credit spreads.     

The determinants of the model-free positive and negative volatilities

In this paper we analyze the role of macroeconomic and financial determinants in explaining stock market volatilities in the U.S. market. Both implied and realized volatility are computed model-free and decomposed into positive and negative components, thereby allowing us to compute directional volatility risk premia. We capture the behaviour of each component of implied volatility and risk premium in relation to their different determinants. The negative implied volatility appears to be linked more towards financial conditions variables such as uncertainty and geopolitical risk indexes, whereas positive implied volatility is driven more by macro variables such as inflation and GDP. There is a clear shift in importance from macro towards financial determinants moving from the pre towards the post financial crisis. A mixed frequency Granger causality approach uncovers causality relationships between volatilities and risk premia and macro variables and vice versa, a finding which is not detected with a conventional low frequency VAR model.     

The volatility of consumption-based stochastic discount factors and economic cycles

This paper aims to assess the macroeconomic and financial impact of economic uncertainty using information contained in the second moments of financial risk factors employed in the asset pricing literature. Specifically, we propose the volatility of consumption-based stochastic discount factors (SDFs) as a predictor of future economic and stock market cycles. We employ both contemporaneous and ultimate consumption risk specifications with durable and non-durable consumption. Alternative empirical tests show that this volatility has significant forecasting ability from 1985 to 2006. The degree of predictability tends to dominate that shown by standard predictor variables. We argue that the significant predictability of the volatility of consumption-based SDFs reported in this paper relies mainly on the joint effect of their components.     

Political geography and stock returns: The value and risk implications of proximity to political power

We show that political geography has a pervasive effect on the cross-section of stock returns. We collect election results over a 40-year period and use a political alignment index (PAI) of each state's leading politicians with the ruling (presidential) party to proxy for local firms’ proximity to political power. Firms whose headquarters are located in high PAI states outperform those located in low PAI states, both in terms of raw returns, and on a risk-adjusted basis. Overall, although we cannot rule out indirect political connectedness advantages as an explanation of the PAI effect, our results are consistent with the notion that proximity to political power has stock return implications because it reflects firms’ exposure to policy risk.     

Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data

This paper provides strong evidence of time-varying return predictability of the Dow Jones Industrial Average index from 1900 to 2009. Return predictability is found to be driven by changing market conditions, consistent with the implication of the adaptive markets hypothesis. During market crashes, no statistically significant return predictability is observed, but return predictability is associated with a high degree of uncertainty. In times of economic or political crises, stock returns have been highly predictable with a moderate degree of uncertainty in predictability. We find that return predictability has been smaller during economic bubbles than in normal times. We also find evidence that return predictability is associated with stock market volatility and economic fundamentals.     

Time-varying rare disaster risk and stock returns

This study provides empirical support for theoretical models that allow for time-varying rare disaster risk. Using a database of 447 international political crises during the period 1918-2006, we create a crisis index that shows substantial variation over time. Changes in this crisis index, our proxy for changes in perceived disaster probability, have a large impact on both the mean and volatility of world stock market returns. Crisis risk is positively correlated with the earnings-price ratio and the dividend yield. Cross-sectional tests also show that crisis risk is priced: Industries that are more crisis risk sensitive yield higher returns.     

Intraday trading volume and international spillover effects

The objective of this paper is to explore whether lagged trading activity in one market contributes to the return and volatility process in other markets, using 5-min concurrent data from German and British equity market. Our results lend support to our initial premise that if international investors have access to the same information set as domestic traders, then after observing foreign trading activity, market makers adjust prices to reflect their expectation of the security value, conditional upon all available information, including prior trades. Our findings clearly indicate that intraday trading volume contains predictive power for cross-border return and volatility processes. Moreover, these volume effects are found to be asymmetric in the sense that the impact of positive volume changes upon foreign stock market volatility is greater than is the impact of negative changes.     

Interest rate expectations and uncertainty during ECB Governing Council days: Evidence from intraday implied densities of 3-month EURIBOR

This paper analyses changes in short-term interest rate expectations and uncertainty during ECB Governing Council days. For this purpose, it extends the estimation of risk-neutral probability density functions up to tick frequency. In particular, the non-parametric estimator of these densities, which is based on fitting implied volatility curves, is applied to estimate intraday expectations of 3-month EURIBOR 3 months ahead. Estimates of the noise impact on the statistical moments of the densities enhance the interpretation. In addition, the paper assesses the impact of the ECB communication during Governing Council days. The results show that the whole density may react to the communication and that such repositioning of market participants’ expectations will contain information beyond that of changes in the consensus view already observed in forward rates. The results also point out the relevance of the press conference in providing extra information and triggering an adjustment process for interest rate expectations.     

Forecasting global stock market volatilities in an uncertain world

We investigate the predictive relationship between uncertainty and global stock market volatilities from a high-frequency perspective. We show that uncertainty contains information beyond fundamentals (volatility) and strongly affects stock market volatility. Using several crucial uncertainty measures (i.e., uncertainty and implied volatility indices), we prove that the CBOE volatility index (VIX) performs best in point (density) forecasting; the financial stress index (FSI) in directional forecasting. Furthermore, VIX's predictive power improved dramatically after the COVID-19 outbreak, and the VIX-based portfolio strategy enables mean-variance investors to achieve higher returns. There are two empirical properties of VIX: (i) it helps reduce significantly forecast variance rather than bias; and (ii) its forecasts encompass other uncertainty forecasts well. Overall, we highlight the importance of considering uncertainty when exploring the expected stock market volatility.     

Political Uncertainty, Financial Crisis and Market Volatility

This paper examines the impact of political uncertainty on financial crises using a panel of 22 emerging markets. By examining political election cycles, we find that eight out of nine of the financial crises happened during the periods of political election and transition. Using a combination of probit and switching regression analysis, we find that there is a significant relationship between political election and financial crisis after controlling for differences in economic and financial conditions. We observe increased market volatility during political election and transition periods. Our results suggest that political uncertainty could be a major contributing factor to financial crisis. Thus, politics does matter in emerging markets. Since the odds of financial crisis tend to be much larger during the political election periods, institutional investors should take that into account when making emerging market investment during those time periods.     

The options market response to accounting earnings announcements

We examine the reaction of the equity options market to accounting earnings announcements over the period 1996–2008 using changes in implied volatility to measure the options market response to earnings news. We find that positive earnings surprises and positive profit announcements produce a larger uncertainty resolution than negative earnings surprises and loss announcements. We demonstrate an inverse relation between the change in implied volatility and earnings news in a three-day window immediately after an earnings announcement. We refer to the magnitude of this relation as the ‘options market earnings response coefficient’. This ‘options market earnings response coefficient’ is stronger for both bad news announcements and positive profit announcements. We do not find any significant relation between changes in implied volatility and earnings news in the pre- or post-announcement periods. We conclude that the options market efficiently absorbs earnings information.