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.     

Exchange rate volatility and international trade: A general-equilibrium analysis

We analyze the relation between exchange-rate volatility and the volume of international trade, in a general-equilibrium stochastic-endowment economy with imperfect international commodity markets, and treating both variables as endogenous. Even in the simplest model, the sign of the relation depends on the source for the change in volatility. For instance, more volatility of the endowments and higher costs to international trade both boost exchange risk (and lower welfare); but the first increases the expected volume of trade, while the second decreases trade. Note that even the (inter-equilibria) relation between trade and welfare is ambiguous.     

Return spillovers around the globe: A network approach

We study the connectedness of a sample of 40 stock markets across five continents using daily closing prices and return spillovers based on Granger causality. All possible 1560 return spillovers between 40 markets create a complex network of relationships between equity markets around the world. Apart from analyzing the topological and time-varying properties of the created networks, we also identify the determinants of the connectedness of equity markets over time. Adjusting for non-synchronous trading, our modelling approach leads to evidence that the probability of return spillover from a given stock market to other markets increases with market volatility and market size and decreases with higher foreign exchange volatility. We empirically show that the temporal proximity between closing hours is important for information propagation; therefore, choosing markets that trade during similar hours bears an additional risk to investors because the probability of return spillovers increases.     

Government size, composition, volatility and economic growth

This paper analyses the effects in terms of size and volatility of government revenue and spending on growth in OECD and EU countries. The results of the paper suggest that both variables are detrimental to growth. In particular, looking more closely at the effect of each component of government revenue and spending, the results point out that i) indirect taxes (size and volatility); ii) social contributions (size and volatility); iii) government consumption (size and volatility); iv) subsidies (size); and v) government investment (volatility) have a sizeable, negative and statistically significant effect on growth.     

An information theoretic analysis of stock returns,volatility and trading volumes

Information theory is used to examine the dynamic relationships between stock returns, volatility and trading volumes for S&P500 stocks. This provides an alternative approach to traditional Granger causality tests when dealing with nonlinear relationships. The article highlights the dominant role played by trading volumes in all of these relationships – even in the return–volatility relation – and finds evidence of a market level feedback effect from index returns to the return–volatility relation at the stock level. The article also produces a number of stylized facts from an information theoretic perspective.     

Volatility risk premium implications of GARCH option pricing models

In this paper we explore important implications of capturing volatility risk premium (VRP) within a parametric GARCH setting. We study the transmission mechanism of shocks from returns to risk-neutral volatility by providing an examination of the news-impact curves and impulse–response functions of risk-neutral volatility, in order to better understand how option prices respond to return innovations. We report a value of − 3% for the magnitude of the average VRP and we recover the empirical densities under physical and risk-neutral measures. Allowing for VRP is crucial for adding flexibility to the shape of the two distributions. In our estimation procedure, we adopt a MLE approach that incorporates both physical return and risk-neutral VIX dynamics. By introducing volatility - instead of variance - innovations in the joint likelihood function and by allowing for contemporaneous correlation between innovations in returns and the VIX we show that we may critically reduce the bias and improve the efficiency of the joint maximum likelihood estimator, especially for the parameters of the volatility process. Modeling returns and the VIX as a bi-variate normal permits identification of a contemporaneous correlation coefficient of approximately − 30% between returns and risk-neutral volatility.     

Terms of trade volatility,government spending cyclicality,and economic growth

This paper presents estimates of the effects that terms of trade volatility has on real gross domestic product (GDP) per capita growth. Based on 5‐year nonoverlapping panel data comprising 175 countries during 1980 to 2010, the paper finds that terms of trade volatility has significant negative effects on economic growth in countries with procyclical government spending. In countries where government spending is countercyclical, terms of trade volatility has no significant effect on growth. Conditional on the mediating role of government spending cyclicality, the GDP share of domestic credit to the private sector has no significant effect on the relationship between growth and terms of trade volatility.     

Trade openness and the informational efficiency of emerging stock markets

This paper examines the empirical link between trade openness and the informational efficiency of stock markets in 23 developing countries. Our fixed effects panel regression results document a significant negative relation between trade openness and stock return autocorrelations only when the de facto measure is used. On this basis, we argue that a greater level of de facto trade openness is associated with a higher degree of informational efficiency in these emerging stock markets because the former signals higher future firm profitability, and investors tend to react faster to information when there is less uncertainty about a firm's future earnings or cash flows. Further analyses find no significant association between the extent of financial openness and the degree of informational efficiency.     

A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence,modeling and forecasting

In existing researches, the investigations of oil price volatility are always performed based on daily data and squared daily return is always taken as the proxy of actual volatility. However, it is widely accepted that the popular realized volatility (RV) based on high frequency data is a more robust measure of actual volatility than squared return. Due to this motivation, we investigate dynamics of daily volatility of Shanghai fuel oil futures prices employing 5-minute high frequency data. First, using a nonparametric method, we find that RV displays strong long-range dependence and recent financial crisis can cause a lower degree of long-range dependence. Second, we model daily volatility using RV models and GARCH-class models. Our results indicate that RV models for intraday data overwhelmingly outperform GARCH-class models for daily data in forecasting fuel oil price volatility, regardless the proxy of actual volatility. Finally, we investigate the major source of such volatile prices and found that trader activity has major contribution to fierce variations of fuel oil prices.     

Globalization,Wage Volatility,and the Welfare of Workers*

This paper analyzes the effects of trade liberalization on the level and volatility of factor returns, in a model with identical technologies across industries and industry‐specific uncertainty. The results show an increase in the return to capital and, under certain conditions, a decline in the real wages and welfare of workers, along with an expansion of wage dispersion and volatility. Unlike the Solper–Samuelson mechanism, our results do not depend on the factor intensity of imports and exports and are borne out by all patterns of trade, including among industrialized countries, suggesting that the traditional analysis has missed some important linkages between trade and wages.     

The disappearing size effect

In this paper, we use average monthly returns and monthly cross-sectional regressions to investigate the relation between returns and firm size. During the period 1963–1981, we find an annualized return difference between small and large firms over 13% compared to a negative 2% return differential since 1982. Removal of the smallest firms (less than $5 million market value) eliminates any statistically significant size effect during the sample period using a regression framework. Several explanations are proposed for the disappearance of the size effect. Our results imply that size should not be considered as a systematic proxy for risk.     

On the asymmetric effects of exchange-rate volatility on trade flows: Evidence from US–UK Commodity Trade

We consider the response of each of the 67 industries that trade between the United States and United Kingdom to the volatility of the real dollar–pound exchange rate. When we follow previous research and estimate a linear ARDL model for each industry, we find short-run effects of volatility in 22 US exporting industries to the United Kingdom that last into the long run only in nine industries. As for the UK exports to the United States, we find short-run effects in 18 industries that last into the long run in 15 industries. However, when we estimate a nonlinear model for each industry, we find short-run effects of volatility on 41 US exporting industries and on 43 UK exporting industries, all in an asymmetric manner. Short-run asymmetric effects lasted into long-run asymmetric effects in 24 US exporting industries to the United Kingdom and in 33 UK exporting industries to the United States. While total trade shares of industries from the linear models were negligible, those of the industries from the nonlinear models were significant in size, in the tune of one-third of the trade.     

The relation between the informational content of implied volatility and arbitrage costs: Evidence from the Oslo Stock Exchange

This study investigates the proposition that volatility of stock returns can be predicted from the volatility implied by options on the Oslo Stock Exchange (OSE), conditional on the ability to perform arbitrage. Insights into the relation between the informational content of implied volatility and arbitrage cost can be distilled from Oslo Stock Exchange data. For Norwegian firms, options and their underlying stock trade on the Oslo Stock Exchange and have an overlapping set of market makers thereby lowering the cost of arbitrage. Other components of arbitrage trading costs, liquidity and dispersion of stock return volatility, vary widely across Norwegian firms. Moreover, restriction on the short selling of stock in Oslo allows further insight into the role of arbitrage costs in determining the informational content of implied volatility. The results yield support for the arbitrage cost hypothesis: the lower the arbitrage cost between the stock and the option, the greater the informational content of implied volatility.     

Where does return and volatility come from? The case of Asian ETFs

We analyze return and volatility of Asian iShares traded in the U.S. The difference in trading schedules between the U.S. and Asia offers a unique market setting that allows us to distinguish various return and volatility sources. We find Asian ETFs have higher overnight volatility than daytime volatility, explained by public information released during each local market's trading session. Local Asian markets also play an important role in determining each Asian ETF return. Nonetheless, returns for these funds are highly correlated with U.S. markets, indicative of the effects of investor sentiment and location of trade. Finally, returns in the U.S. market Granger-cause returns in all six Asian markets are analyzed.     

Regional origins of employment volatility: evidence from German states

Greater openness for trade can have positive welfare effects in terms of higher growth. But increased openness may also increase uncertainty through a higher volatility of employment. We use regional data from Germany to test whether openness for trade has an impact on volatility. We find a downward trend in the unconditional volatility of employment, paralleling patterns for output volatility. The conditional volatility of employment, measuring idiosyncratic developments across states, in contrast, has remained fairly unchanged. In contrast to evidence for the US, we do not find a significant link between employment volatility and trade openness.     

Output volatility,composition of trade,and transmission of economic shocks across countries

In this paper we investigate how supply and demand shocks in one country affect output volatility in other countries. While the evidence for cross‐country transmission of demand shocks is mixed, we find that volatile supply in one country leads to larger imports and output volatility in other countries. As a result, the effect of trade openness on output volatility is highly heterogeneous across countries and depends on the composition of their trade. Those countries whose imports originate in economies with volatile supply experience a greater impact of trade on output volatility.     

Oil prices and the macroeconomy reconsideration for Germany: Using continuous wavelet

The cross wavelet analysis is used in the study to decompose the time–frequency effects of oil price changes on the German macroeconomy. We argue that the relationship between oil prices and industrial production is ambiguous. Our results show that there are both phase and anti-phase relationships between oil price returns and inflation and in most of the cases inflation is the leading variable. Additional evidence shows that there is a huge inconsistency between the phase-difference of the return series of oil price and industrial production at the 12–16 month frequency bands but at the 16–24 month frequency bands, we find that oil price changes that have occurred during 1982–2009 were demand-driven. In a nutshell our results suggest that oil price changes that have occurred after 1994 were demand-driven and the volatility of the inflation rate started to decrease after the 1990s but the volatility of the industrial output growth rate started to decrease after the 2000s.     

Investment under Trade Policy Uncertainty: an Empirical Investigation*

The link between trade policy uncertainty and the share of investment in GDP per capita is investigated using panel data drawn from over a hundred countries for the period 1960–2000. Five indicators of trade policy are used. Two specifications of volatility for each of the trade policy indicators are constructed as measures of trade policy uncertainty. Panel regression results suggest a robust correlation between the volatility of trade policy indicators and the investment share. A significant negative impact of trade policy volatility on the investment share is found in most trade policy indicators with an exception—the volatility of the trade share indicator more closely associated with volatility in quantity than in prices has a significant positive impact on the investment share.     

Forecasting volatility in the Indian equity market using return and range-based models

In this article, we assess the time-varying volatility of the National Stock Exchange in the Indian equity market using unconditional estimators and asymmetric conditional econometric models. The volatility estimate and forecast is computed from the interday return and intraday range-based data of the exchange’s flagship index, CNX NIFTY, for the time period spanning 1 January 2009 through 31 December 2013. These are our findings: First, we determine that the time-varying volatility of the index is asymmetric with qualities of stationarity and leptokurtic distribution. Second, the one-step-ahead volatility forecast derived from the univariate time series parameters through the GJR-GARCH ?????process indicates that the model evaluation criteria of the autoregressive process tends towards range-based models vis-à-vis a return-based model. The validity of this methodology is further analysed with the superior predictive ability test, the outcome of which supports the use of range-based conditional models. Finally, among the evaluated range-based model variants, the model confidence set procedure favours the Yang–Zhang estimator as being better suited to forecast the exchange’s volatility than the ones by Parkinson, Garman–Klass and Rogers–Satchell.     

Pecking order and core‐periphery in international trade

This paper analyzes the impact of market size and trade costs on bilateral trade flows. A multi‐country trade model with firm‐level heterogeneity in productivities and countries’ market potential provides a simple micro foundation for the link between these variables. In the model, market size and trade costs jointly determine a country‐specific pecking order of exporters serving their destination countries. In a counterfactual setting where bilateral trade costs are homogeneous across country pairs, market size predicts a common ranking of exporters among destination countries. This leads to a unique core‐periphery structure of the world trade network. With heterogeneous trade costs, we illustrate the impact of market size and trade costs on bilateral trade flows and its margins in a simple gravity‐like setting. Using an instrumental variables approach, we find that both market size and trade costs (measured through the network position of countries) have a significant impact on bilateral exports: countries in the core bilaterally trade more with other countries in the core than with peripheral countries, conditional on typical observables.