Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Predicting the equity market with option-implied variables

We comprehensively analyze the predictive power of several option-implied variables for monthly S&P 500 excess returns and realized variance. The correlation risk premium (CRP) and the variance risk premium (VRP) emerge as strong predictors of both excess returns and realized variance. This is true both in- and out-of-sample. Our results also reveal that statistical evidence of predictability does not necessarily lead to economic gains. However, a timing strategy based on the CRP leads to utility gains of more than 5.03% per annum. Forecast combinations provide stable forecasts for both excess returns and realized variance, and add economic value.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Firm age and performance

Amid increasing interest in firm age and its effects on firm performance, this special issue offers an exhaustive review of the literature and a novel collection of evidence on the effects of firm age on performance, including a special focus of interest on innovation performance, financial performance, exports, survival and growth. This editorial positions the theme in the extant literature, and provides key definitions and challenges ahead in the field of evolutionary economics. It introduces the collection of articles composing the special issue. The papers offer a diversity of country contexts, as well as analytical approaches and methods. They include an exhaustive review of the literature on age and firms’ performance, and present original empirical studies focusing on the effects of age on firms’ economic outcomes on the one hand, and on innovation outcomes on the other hand. While most of the papers use econometric analysis, the level of analysis ranges from firm to individual.     

The Great Recession,Austerity and Inequality: Lessons from Ireland

The advent of the Great Recession and the widespread adoption of fiscal austerity policies have heightened concern about inequality and its effects. We examine how the distribution of income in Ireland—a country which experienced one of the most severe economic contractions—has evolved over the years 2008 to 2013. Standard cross‐sectional analysis of the income distribution shows broad stability in the Gini coefficient and in decile shares, with one main exception: the share of the bottom decile fell sharply, with the largest fall in average incomes being for that group. Longitudinal analysis shows that the falls in the average income for the bottom decile were not due to decreasing income for those remaining in the bottom decile, but to falls in income from those initially located in higher deciles. The extent of redistribution through taxes and transfers increased strongly, as measured by the Reynolds‐Smolensky index, which rose from 0.20 before the onset of the crisis to 0.27 in 2013. Analysis indicates that about three‐quarters of this increased redistribution is due to automatic stabilisers and one‐quarter to discretionary policy changes.     

Easing the assessment of emerging technologies in technology observatories. Findings about patterns of dissemination of emerging technologies on the internet

This paper considers the Web as a big data container that can be used by Technology Observatories and administrations to track emerging issues and more specifically emerging technologies. It considers information that is available on the Internet for free from different sources, and proposes a framework that can be useful to characterise them and to detect patterns of dissemination. This framework is made up of 30 metrics obtained from different kinds of sources (general web, patents, scholars?…). Some of them are obtained directly as the number of hits retrieved by queries on a search engine, and other ones calculated by means of ratios. This paper contains the development of a complete case that utilises this framework to characterise emerging technologies included in the well-known Hype Cycle for Emerging Technologies, in this case the 2015 release¹ and to analyze patterns of dissemination of these technologies on the Internet.     

Towards an operations strategy model of servitization: the role of sustainability pressure

Servitization requires an important strategic shift to drive changes in the operations of manufacturing firms. Using a large-scale survey, the purpose of this paper is (1) to build and validate an operations strategy model of servitization confirming previous case study findings on servitization as a strategic action and (2) to explore the role of sustainability pressures in, and the sustainability performance effects of, pursuing service-based operations strategies. To reach these objectives, a dataset including the responses of 735 manufacturing plants from 21 different countries is analyzed using the PLS-SEM method. The results indicate that the sustainability pressures of stakeholders can push manufacturers to adopt a service-based operations strategy, materializing in the provision of both basic (product-oriented) and advanced (customer-oriented) services (BAS and ADS). Our analysis further indicates that while offering BAS is a precondition for ADS provision, only ADS can offer a competitive edge for manufacturers, both in terms of service and sustainability-related operational performance.     

ICT Statistics at the New Millennium—Developing Official Statistics—Measuring the Diffusion of ICT and its Impact

The paper gives a short and very rough overview of the ongoing work in the field of statistics relating to the development of information and communication technology (ICT) and its impacts on the economies and on the society as a whole. It introduces three slightly different approaches with different emphasis on describing the emergence and diffusion of ICT and the respective economic and social change. These are termed the indicators approach, the new economy approach and the intellectual capital approach. The paper also discusses the basic requirements for the establishment of a new statistical system, as well as the present obstacles and problems of this work. Finally, some remarks are presented regarding further statistical co-operation in this field.     

Battles in the costing war: UK debates, 1950-75

In the UK, 1950-75 was a lively period in the long-running debates between proponents of absorption and marginal costing. In the nexus of competing interests, management accountants advocated and defended rival costing systems with much vigour and passion. Expressed in the language of the times, these debates were 'battles' in the costing 'war'. We focus on these battles, analysing the various forces that operated upon the combatants, and locate them in the wider costing war. We conclude that no final resolution of the conflict was achieved in the twentieth century, nor is one likely in the foreseeable future.     

Changes in food provision in Russian households experiencing perestroika

The purpose of this article is to describe how households in Novgorod the Great, Russia, deal with food provision in everyday life. The study focuses on changes experienced in food provision and consumption in Russian society, in order to illustrate how households respond to the transformation towards a market economy. The study reflects women's perspective on food provision. Students from Novgorod the Great visited 105 households and asked the women in the household to answer a questionnaire. Results from the study show that in order to cope with changes in society related to economic reforms, Russian households had changed both their food consumption and food production patterns. There was no big difference between urban and rural households. Nearly all of the households were self‐sufficient in the provision of vegetables and potatoes. Many households had a ‘dacha’ (plot), where they produced most of what they needed. Among the changes experienced during recent years (i.e. during the end of the 1990s), a decade after perestroika was initiated, households mentioned the rise in food prices and the decrease of income. Households reported that they consumed less fruit and/or meat. Some households also mentioned that the quality of nourishment had decreased, thereby indicating lower general quality, lower nutrition value, or less healthy foodstuffs.