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The Basel II Accord requires that banks and other authorized deposit‐taking institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure value‐at‐risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realized losses exceed the estimated VaR. The purpose of this paper is to address the question of risk management of risk, namely VaR of VIX futures prices.

The authors examine how different risk management strategies performed before, during and after the 2008‐2009 global financial crisis (GFC).

The authors find that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

The paper examines how different risk management strategies performed before, during and after the 2008‐2009 GFC, and finds that an aggressive strategy of choosing the supremum of the univariate model forecasts is preferred to the other alternatives, and is robust during the GFC.

Both journal self-citations and exchanged citations have the effect of increasing a journal’s impact factor, which may be deceptive. The purpose of this paper is to analyse academic journal quality and research impact using quality-weighted citations vs total citations, based on the widely used Thomson Reuters ISI Web of Science citations database (ISI). A new Index of Citations Quality (ICQ) is presented, based on quality-weighted citations.

The new index is used to analyse the leading 500 journals in both the sciences and social sciences, as well as finance and accounting, using quantifiable Research Assessment Measures (RAMs) that are based on alternative transformations of citations.

It is shown that ICQ is a useful additional measure to 2-year impact factor (2YIF) and other well-known RAMs for the purpose of evaluating the impact and quality, as well as ranking, of journals as it contains information that has very low correlations with the information contained in the well-known RAMs for both the sciences and social sciences, and finance and accounting.

Journals can, and do, inflate the number of citations through self-citation practices, which may be coercive. Another method for distorting journal impact is through a set of journals agreeing to cite each other, that is, by exchanging citations. This may be less coercive than self-citations, but is nonetheless unprofessional and distortionary.

The premise underlying the use of citations data is that higher quality journals generally have a higher number of citations. The impact of citations can be distorted in a number of ways, both consciously and unconsciously.

Regardless of whether self-citations arise through collusive practices, the increase in citations will affect both 2YIF and 5-year impact factor (5YIF), though not Eigenfactor and Article Influence. This leads to an ICQ, where a higher ICQ would generally be preferred to lower. Unlike 5YIF, which is increased by journal self-citations and exchanged citations, and Eigenfactor and Article Influence, both of which are affected by quality-weighted exchanged citations, ICQ will be less affected by exchanged citations. In the absence of any empirical evidence to the contrary, 5YIF and AI are assumed to be affected similarly by exchanged citations.

The purpose of this paper is to propose a new method for estimating continuous‐time stochastic volatility (SV) models for the S&P 500 stock index process using intraday high‐frequency observations of both the S&P 500 index and the Chicago Board Options Exchange (CBOE) implied (or expected) volatility index (VIX).

A primary purpose of the paper is to provide a framework for using intraday high‐frequency data of both the indices' estimates, in particular, for improving the estimation accuracy of the leverage parameter, that is, the correlation between the two Brownian motions driving the diffusive components of the price process and its spot variance process, respectively.

Finite sample simulation results show that the proposed estimator delivers more accurate estimates of the leverage parameter than do existing methods.

The focus of the paper is on the Heston and non‐Heston leverage parameters.

Finite sample simulation results show that the proposed estimator delivers more accurate estimates of the leverage parameter than do existing methods.

The research findings are important for the analysis of ultra high‐frequency financial data.

The paper provides a framework for using intraday high‐frequency data of both indices' estimates, in particular, for improving the estimation accuracy of the leverage parameter, that is, the correlation between the two Brownian motions driving the diffusive components of the price process and its spot variance process, respectively.

Over the past two years, senior managers at several automotive companies have begun to implement a new business model called a digital loyalty network (DLN). The model enables companies in any industry to continuously collect and monitor their customer, product and supply chain data and more precisely adjust engineering, production, distribution and sales/marketing activities to meet current and future demand. Moreover, they can use the same data to enhance their partnership with suppliers. For example, GM has put in place a number of components of a digital loyalty network, including the implementation of an integrated network connecting the company with suppliers, alliance partners, dealers and customers. GM has also adopted a new formula for managing the order‐to‐delivery process, has launched Web‐portals for customers and suppliers and continues to enhance and support its OnStar system, which allows drivers to communicate on the road with GM customer service representatives and vendors. Digital loyalty networks have three components: (1) Digital – the companies use sophisticated information technologies to manage information more effectively; (2) Loyalty – the system is designed to target, satisfy, and retain the most profitable customers and, in turn, use customer information and loyalty data to make the supply chain more efficient; (3) Networks – the information system links suppliers, producers and customers and is continuously updated. DLN companies use information technology resourcefully to increase the effectiveness of supply chain and customer relationship management initiatives. They develop a solid network of digitized information that ties together the value chain and creates loyalty and on both the front and back end of business operations. On the supply side, DLN companies continuously monitor customer value based on feedback about customer requirements, purchase history, and potential purchases and rely on digital technology to make certain their most valuable customers are kept satisfied. They do this by managing inventory through the supply chain so that the best customers are served first, and making certain short and long‐term capacity planning responds to these customer priorities. In addition to General Motors, Deloitte Research identified three other innovators in the automotive industry – Porsche, DaimlerChrysler and Renault/Nissan – that are developing certain aspects of a DLN.

The authors explore the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic.

The authors employ a non-linear autoregressive distributed lag (NARDL) methodology using daily data of the Indonesian economy over the period 2012–2021.

Whilst, over the full sample period, the authors find no cointegration between the exchange rate, the 10-year bond yield and stock market, for the COVID-19 period, evidence of cointegration is present. Furthermore, the results suggest that asymmetric effects are evident both in the short as well as the long run.

To the best of the authors’ knowledge, this is the first time that the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic has been explored in the case of the Indonesian economy.

This paper focuses on execution costs as liquidity measure. Execution costs are related to volatility and are an important component of a firm’s cost of capital. The purpose of this paper is to examine whether emerging market firms have lower execution costs when they face less restrictions on foreign investment and when they have more foreign shareholders.

The authors begin by documenting the cross-sectional behavior of execution costs. The authors then obtain preliminary evidence on the interaction between execution costs, the investability index and actual foreign investment. These results foreshadow those the authors obtain with the regression analysis. The ordinary least square results show that more investable firms have lower execution costs after the authors control for firm size, stock price, return volatility, industry effects and country effects. This evidence is very robust and highly significant. Direct foreign ownership (FO) in emerging market firms also appear to be associated with lower execution costs. The economic benefit from lowering the investability index on trade execution costs is highly significant.

Using a large cross-sectional sample from 23 emerging markets, the authors show that firms with more ex ante restrictions on FO, measured by the investability index, have lower execution costs, such as quoted spreads (QS) and effective spreads (ES), after the authors control for firm size, stock price, return volatility, industry factors and country effects. In addition, direct FO in emerging market firms appears to be associated with lower execution costs. However, ex ante restrictions on FO dominate the influence of direct FO. For a 0.5 increase in the investability index in the range of 0–1, the QS will be reduced by 17 percent of the mean QS, and the ES will be reduced by 12 percent of the mean ES from the sample stocks.

There are important differences between the approach and most of the financial liberalization studies. First, whereas most of the earlier studies are conducted at the level of country or market analysis, the investigation is at the level of individual stocks. Second, the authors focus on a cross-sectional association that avoids a criticism leveled at time series analyses. Over-time studies often use specific time points to represent financial liberalization watersheds. This approach can be misleading when financial liberalizations are viewed as processes that unfold over time. Third, the proxies for financial openness are available not only for individual firms across markets, but the authors also make a distinction between potential and actual foreign investment. The authors further categorize actual foreign investment into direct and indirect FO.

Many industrial companies have expressed a growing concern over the quality of managers in manufacturing industry and their ability to adapt to rapid environmental and technological changes. In addition, it has been felt that in the UK, the traditional postgraduate management teaching mechanism tended to be out of date and excessively academic. To address these shortcomings, what seems to be needed is the development of postgraduate courses which place more weight on the industrial experience of the participants. At the same time, it is necessary to give postgraduate teaching a stronger orientation towards the actual needs of industry rather than the perceived needs as seen by the contemporary academic. As a result, companies are now beginning to investigate alternative approaches to developing the business and technical skills of their managers. One such approach has been adopted by a Northern Ireland subsidiary of a multinational corporation in the aerospace industry. As part of this process, the firm asked the University of Ulster, in conjunction with the Irish Management Institute, to provide a programme of developmental support in a comprehensive range of general management concepts, skills and techniques.

The ability of the Irish economy to continue growing depends not only on demand, but also on supply conditions. While these have remained favourable up to now, there are signs of increasing skill shortages and ongoing pressure on economic infrastructure. It has been established that human resources development (HRD) is vital to maintaining Ireland’s competitiveness internationally. This paper seeks to document the nature of HRD at organizational level in Ireland. Following a brief sketch of the Irish context, we draw on a nationally representative survey of HRD practices and present data on where responsibilities for HRD policy decisions lie, the extent of and the approaches to the identification of HRD needs, HRD coverage and delivery, and the nature of longer‐term developmental activities. Variations between firms of different size, between sectors, between firms of different origin, and between unionized and non‐union environments are, where appropriate, highlighted.

The aim of this paper is to engage with the translation and linking of the “scientific knowledge” of theory on local economic growth with the “practical knowledge” of, on the one hand, local economic policy formulation and, on the other hand, entrepreneurship and entrepreneurship education. The paper uses theoretically informed empirical modelling to identify and prioritise the drivers of local economic growth using data for Australia. The analyses demonstrate the significance of human capital and an enterprise culture in promoting local employment growth. From these results it is suggested that “bottom up” entrepreneurial education and related, but more “top down”, enterprise facilitation are practical mechanisms for achieving such local growth. These results suggest the great importance of translating “scientific knowledge” into “practical knowledge” to allow communities to engage with the knowledge economy.

The significant impact of innovation in stimulating economic growth cannot be overemphasized, more importantly from policy perspective. For this reason, the relationship between innovation and economic growth in developing economies such as the ones in Africa has remained topical. Yet, innovation as a concept is multi-dimensional and cannot be measured by just one single variable. With hindsight of the traditional measures of innovation in literature, we augment it with the number of scientific journals published in the region to enrich this discourse.

We focus on an approach that explores innovation policy qualitatively from various policy documents of selected countries in the region from three policy perspectives (i.e. institutional framework, financing and diffusion and interaction). We further investigate whether innovation as perceived differently is important for economic growth in 25 economies in sub-Saharan Africa over the period 1990–2016. Instrumental variable estimation of a threshold regression is used to capture the contributions of innovation as a multi-dimensional concept on economic growth, while dealing with endogeneity between the regressors and error term.

The results from both traditional panel regressions and IV panel threshold regressions show a positive relationship between innovation and economic growth, although the impact seems negligible. Institutional quality dampens innovation among low-regime economies, and the relation is persistent regardless of when the focus is on aggregate or decomposed institutional factors. The impact of innovation on economic growth in most regressions is robust to different dimensions of innovation. Yet, the coefficients of the innovation variables in the two regimes are quite dissimilar. While most countries in the region have offered financial support in the form of budgetary allocations to strengthen institutions, barriers to the design and implementation of innovation policies may be responsible for the sluggish contribution of innovation to the growth pattern of the region.

Segregating economies of Africa into two distinct regimes based on a threshold of investment in education as a share of GDP in order to understand the relationship between innovation and economic growth is quite novel. This lends credence to the fact that innovation as a multifaceted concept does not take place by chance – it is carefully planned. We have enriched the discourse of innovation and thus helped in deepening understanding on this contentious subject.