Declining output growth volatility: A sectoral decomposition

A decomposition of the U.S. aggregate output growth volatility using two-digit industry-level data shows that more than 60% of the post-1983 reduction in aggregate output growth volatility is attributed to the lowered comovement in total factor productivity (TFP) growth between industries. In contrast, stabilized input and TFP growths within an industry contribute little.     

Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

A recent strand in the literature emphasizes the role of news-based economic policy uncertainty (EPU) and equity market uncertainty (EMU) as drivers of oil price movements. Against this backdrop, this paper uses a kth-order nonparametric quantile causality test, to analyse whether EPU and EMU predict stock returns and volatility. Based on daily data covering the period of 2 January 1986 to 8 December 2014, we find that, for oil returns, EPU and EMU have strong predictive power over the entire distribution barring regions around the median, but for volatility, the predictability virtually covers the entire distribution, with some exceptions in the tails. In other words, predictability based on measures of uncertainty is asymmetric over the distribution of oil returns and its volatility.     

Exchange-rate variability and U.S.-French trade flows: evidence from industry data

Recent studies have greatly expanded the literature on the effects of exchange-rate volatility on industry-level bilateral trade flows. In this study, we examine the case of the United States and France, applying cointegration analysis to a set of 146 U.S. export and 115 U.S. import industries. We find that the majority of industries show little or no relationship between risk and trade volumes, but that small industries—particularly for exports—show more sensitivity than do large ones. A disproportionate share of industries respond positively to increased volatility, particularly among U.S. importers, suggesting the presence of “risk loving” behavior.     

On the robustness of alternative rankings methodologies: Australian and New Zealand economics departments, 1988 to 2002

Theoretical considerations appear to support the conjecture that stock returns are positively related to growth in the long run. However, the empirical literature does not give unanimous support to the theory. Based on a stochastic general equilibrium model it is argued that the long-run relationship between stock returns and per capita income growth is ambiguous and depends on output volatility. Using a century of data for 20 Organization for Economic Co-operation and Development (OECD) countries it is shown that the relationship between stock returns and growth is positive over the period 1916–1951, in which output volatility was persistent. Outside this period no relationship between stock returns and growth is found. These findings are consistent with the predictions of the theoretical model.     

Politics, stock markets, and model uncertainty

The available evidence on the effects of political variables on both returns and volatility of aggregate stock indices is scant and mixed. Applying Bayesian Model Averaging to a panel dataset of 17 parliamentary democracies spanning the post-war period until 1995, we test the robustness of political variables in explaining stock returns and stock return volatility. While we find that the influence of political variables on excess returns is weak, there is evidence of some political variables explaining return volatility.     

Intraday return and volatility relationships between the Ibex 35 spot and futures markets

This paper analyses the intraday lead-lag relationships between returns and volatilities in the Ibex 35 spot and futures markets. Using hourly data, we jointly analyze the interactions between markets, estimating a bivariate error correction model with GARCH perturbations which captures stochastically the presence of an intraday U-shaped curve for both spot and futures market volatility. Our findings show a bidirectional causal relationship between market volatilities, with a positive feedback. This two-way transmission of volatility is consistent with market prices evolving according to a long-run equilibrium relationship, and shocks affecting both markets in the same direction. Our empirical results also support a unidirectional cross interaction from futures to spot market returns. This pattern suggests that the futures market leads the spot market in order to incorporate the arrival of new information.     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.     

Predicting Equity Markets with Digital Online Media Sentiment: Evidence from Markov-switching Models

The authors examine the predictive capabilities of online investor sentiment for the returns and volatility of MSCI U.S. Equity Sector Indices by including exogenous variables in the mean and volatility specifications of a Markov-switching model. As predicted by the semistrong efficient market hypothesis, they find that the Thomson Reuters Marketpsych Indices (TRMI) predict volatility to a greater extent than they do returns. The TRMI derived from equity specific digital news are better predictors than similar sentiment from social media. In the two-regime setting, there is evidence supporting the hypothesis of emotions playing a more important role during stressed markets compared to calm periods. The authors also find differences in sentiment sensitivity between different industries: it is greatest for financials, whereas the energy and information technology sectors are scarcely affected by sentiment. Results are obtained with the R programming language. Code is available from the authors upon request.     

Exchange rate volatility and its impact on domestic investment

The relationship between exchange rate uncertainty and domestic investment has attracted some attention in macro literature. Previous studies that investigated the relation concentrated on firm level data with mixed results. In this paper we argue that the relationship applies equally at the aggregate. We assess the short-run and long-run effects of exchange rate volatility on domestic investment in each of the 36 countries in our sample using time-series data. The application of the bounds testing approach indicates that exchange rate volatility has significant short-run effects on domestic investment in 27 countries. The short-run effects are translated into the long-run only in 12 countries.     

The impact of exchange rate volatility on commodity trade between the US and Thailand

The impact of exchange rate volatility on trade flows continues to occupy the international finance literature. More recent studies have deviated from the traditional approach of using aggregate trade flows and have employed trade data at commodity level. This study investigates the impact of exchange rate uncertainty on the trade flows of 118 US exporting industries to Thailand and 41 US importing industries from Thailand. We find that exchange rate uncertainty has short-run effects on the trade flows of most industries. In the long-run, the main determinants of the trade flows are the level of economic activity in both countries.     

The source of global stock market risk: A viewpoint of economic policy uncertainty

This study explores the effect of economic policy uncertainty (EPU) in four countries or regions (China, Japan, Europe, and the United States) on the contagion risk of investments in the global stock market. The stock returns of 22 stock markets worldwide are analyzed to determine which region’s EPU exhibits the greatest effect on regional systematic risk in the global stock market and on volatility risk in individual stock markets. First, all of the samples, the markets of different continents and the spillover indices of the developed and emerging markets, are calculated to observe the dynamic correlation among these markets with the aim of quantifying regional systematic risk and further examining the contagion risk effect of EPU. The results indicate the following: EPU in China is the most influential, and its contagion risk spreads to different regional markets, except for Europe; the effect of EPU in the United States is inferior to that in China; EPU in Japan merely influences contagion risk in emerging markets; contagion risk in European markets is not influenced by the four EPU indices; and EPU in Europe is not influenced by contagion risk in the global stock market. However, according to the volatility risk in each market, the EPU in Europe and China respectively influence Asian countries and European countries the most. These results may be attributable to the extremely high trade dependence among these countries because the performance of international enterprises is mainly determined by the economic policies of their trading partners.     

Growth-business cycle interaction: A look at the OECD

This paper examines the relationship between long-run growth and business cycles in the Organization for Economic Co-operation and Development (OECD). The model in the paper specifically assumes that the business cycle influences growth through total factor productivity. Using unconditional volatility to measure the business cycle, this paper finds a negative relationship between the business cycle and long-run growth even after controlling for endogeneity. The result is robust to the inclusion of either period or country dummy variables, but not both. Therefore, the result is somewhat fragile. Finally, the assumption of constant returns to scale is consistent with the data.     

Impact of exchange rate uncertainty on commodity trade between US and Sweden

Previous studies that investigated the effects of exchange rate uncertainty on the trade flows of Sweden employed aggregate trade data either between Sweden and the rest of the world or at bilateral level between Sweden and her major trading partners. In this article, we disaggregate the trade data and employ the import and export data from 87 industries that trade between Sweden and the US. We find that exchange rate volatility has significant short-run effects on the trade flows between the two countries in almost two-third of the industries. However, the short-run effects are translated into the long-run effects in one-third of the cases. Furthermore, the real depreciation of krona against the dollar was found to have favourable effects on the overall trade balance between the two countries.     

Substitute or complement? Assessing renewable and nonrenewable energy in OECD countries

The elasticity of interfuel substitution between renewable and nonrenewable energy is key to establishing effective climate change policy. This is the first study to estimate the elasticity of substitution between different fossil fuels and renewable resources. We used 12 manufacturing industry-level datasets for the OECD countries from 1995 to 2009. We found a complementary relationship from nonrenewable energy to renewable energy in eight industries, whereas a substitute relationship was maintained for four industries. In particular, the food and pulp industries had a strong complementary relationship.     

Time-varying relationship of news sentiment,implied volatility and stock returns

I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.     

Profit persistence and stock returns

This article attempts to assemble further empirical evidence on the relationship between the product and the financial market. Drawing back on work in industrial organization, we analyse the relationship between profit persistence and factor-adjusted stock returns looking at about 2000 listed US firms over the last 34 years. While the relationship between (current, lagged and unexpected) profits/earnings and returns has been extensively analysed before, to our knowledge this is the first study to look at the relationship between stock returns and profit persistence. We interpret profit persistence as a result of market competition and innovation of the firm. It is shown that firm-specific long-run profit persistence after correction for other additional economic fundamentals of the firm has a positive impact on four-factor adjusted returns and a negative impact on their volatility.     

Long-run growth and volatility: which source really matters?

The aim of the article is to analyse the relationship between long-run growth and business cycle volatility. In particular, the main purpose of this article is to identify which source of volatility is most detrimental to growth. Using cross-country data from 1970 to 2000, and several indicators of volatility (such as inflation, exchange rate, government expenditure, output and investment volatility) this article shows that although, all these measures of volatility are remarkably harmful for growth, business cycle investment volatility is the main source that hampers long-run growth. This relation is robust to different measures of business cycle, and to different sub-samples of countries.     

Impact of oil prices on firm stock return: industry-wise analysis

The study investigates the impact of oil prices on firm-level stock returns in case of Pakistan over the period 1998–2014, as this relationship is neglected by the previous literature. By using the panel data estimation, the results of full sample indicate significant positive effect of oil price changes on firm stock returns in the same period, whereas the lagged oil price changes have significant negative effect on firms’ stock return. Moreover, the industry-level analysis also confirms the similar findings; results indicate significant positive impact of oil price on firms’ stock return in full sample, textile, chemical and miscellaneous industry, while the lagged oil price changes negatively affect the stock returns of full sample and all the industries except tobacco, jute and vanaspati industries. The study confirms that rise in oil price transfers a positive signal in the stock market that boosts the firm-level stock returns in Pakistan. In contrast to the negative shocks, the stock returns are significantly affected by the positive oil price shocks.     

Predictability of sustainable investments and the role of uncertainty: evidence from a non-parametric causality-in-quantiles test

In this article, we examine sustainable investments returns predictability based on the U.S. Dow Jones Sustainability Index (DJSI) and a wide set of uncertainty and financial distress indicators for the period 2002:01–2014:12. To this end, we employ a novel non-parametric causality-in-quantile approach that captures non-linearities in returns distribution. Based on our findings we conclude that the aggregate economic policy uncertainty (EPU) indicator and some components have predictive ability for real returns of the U.S. sustainable investments index. Moreover, if we split our sample to before and after the global financial crisis our results suggest that predictors carry causal information for real returns only in the after-crisis period. Finally, some marginal evidence of predictability from sovereign debt is also observed at the lower and upper ends of the conditional distribution of the real returns of sustainable investments. Our results might entail policy implications for investors and market authorities.