892 resultados para Financial market data


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This article proposes that a complementary relationship exists between the formalised nature of digital loyalty card data, and the informal nature of small business market orientation. A longitudinal, case-based research approach analysed this relationship in small firms given access to Tesco Clubcard data. The findings reveal a new-found structure and precision in small firm marketing planning from data exposure; this complemented rather than conflicted with an intuitive feel for markets. In addition, small firm owners were encouraged to include employees in marketing planning.

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Why do firms pay dividends? To answer this question, we use a hand-collected data set of companies traded on the London stock market between 1825 and 1870. As tax rates were effectively zero, the capital market was unregulated, and there were no institutional stockholders, we can rule out these potential determinants ex ante. We find that, even though they were legal, share repurchases were not used by firms to return cash to shareholders. Instead, our evidence provides support for the information–communication explanation for dividends, while providing little support for agency, illiquidity, catering, or behavioral explanations. © The Authors 2013. Published by Oxford University Press [on behalf of the European Finance Association]. All rights reserved.

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This paper analyses some of the factors that impact multinational companies' (MNCs) reaction to the global financial crisis. This paper reports the results from a large-scale study of its impact on MNCs in Australia, considering occurrences of site closures, offshoring, outsourcing, labour force reductions, reductions in working hours, salary reductions, and reductions in training and travel. Evidence showed that MNC reactions varied according to certain institutional and organizational effects. For example, MNCs originating from liberal-market economies are more likely to have offshored and outsourced production and reduced employment. The implications for understanding of MNC behaviour are discussed. © 2013 Copyright Taylor and Francis Group, LLC.

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The crisis that spread worldwide since 2007 started from the financial sector and ended to affect also real economy. This process has attracted the attention of many scholars seeking to study its causes and impacts. Notwithstanding many works on this topic, the impact of the crisis on specific industries is still rather unexplored. The present work seeks to address this issue by analyzing the confectionery industry, with particular emphasis for Italian market leaders, Ferrero S.p.A. and Perfetti Van Melle S.r.l.. The aim of the study is to assess if they have been successful in tackling the crisis, keeping a satisfactory level of profitability associated to a good financial health notwithstanding ongoing difficulties. Moreover, we seek to analyze the strategies the companies employed to survive the crisis. The concern of the paper is both quantitative and qualitative. Thus, we calculated a complete set of indicators using a specific methodology for financial statement analysis which has been conceived especially for studying Italian firms; these data have been integrated with other information retrieved from the annual reports of the companies (especially the notes to the accounts and the directors’ report). The analysis highlights that both the firms benefit from a good financial health, with Perfetti Van Melle presenting a large amount of liquidity. On the contrary, liquidity should be the main concern of Ferrero because of an excessive reliance on current liabilities. Both the firms have a good level of profitability, even if Perfetti Van Melle’s one is decreasing. The key-strategies for the success of these firms are ongoing investments in state-of-the-art plant and machinery, an increasing use of equity as the main source of funding, along with huge investments in research and advertising.

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Energy consumption and total cost of ownership are daunting challenges for Datacenters, because they scale disproportionately with performance. Datacenters running financial analytics may incur extremely high operational costs in order to meet performance and latency requirements of their hosted applications. Recently, ARM-based microservers have emerged as a viable alternative to high-end servers, promising scalable performance via scale-out approaches and low energy consumption. In this paper, we investigate the viability of ARM-based microservers for option pricing, using the Monte Carlo and Binomial Tree kernels. We compare an ARM-based microserver against a state-of-the-art x86 server. We define application-related but platform-independent energy and performance metrics to compare those platforms fairly in the context of datacenters for financial analytics and give insight on the particular requirements of option pricing. Our experiments show that through scaling out energyefficient compute nodes within a 2U rack-mounted unit, an ARM-based microserver consumes as little as about 60% of the energy per option pricing compared to an x86 server, despite having significantly slower cores. We also find that the ARM microserver scales enough to meet a high fraction of market throughput demand, while consuming up to 30% less energy than an Intel server

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On formal credit markets, access to formal credit and reasonable credit terms of smallholder farmers
in rural sub-Saharan Africa is limited due to adverse selection. Financial institutions operating in
rural areas often cannot distinguish between borrowers (farmers) that are creditworthy and those that
are not, thus, allocate limited resource to agriculture to reduce credit risk. In the presence of limited business quality signaling by smallholder farmers, financial institutions shall demand for collateral and/or offer unfavorable contract terms. Moreover, agricultural productivity of rural sub-Saharan
Africa, dominated by subsistence or small-scale farmers, is also negatively impacted by the adverse
effect of climate change. A strategy that may make the farming practices of smallholder farmer’s
climate resilient and profitable may also improve smallholder farmer's access to formal credit. This
study investigates to what extent participating in ecosystem and extension services (EES) programs
signals business quality of smallholders, thus granting them credit accessibility. We collected data
on 210 smallholder farmers in 2013, comprising farmers that receive payments for ecosystem
services (PES) and farm management training from the International Small Group Tree Planting
Program (TIST) Kenya to test the aforementioned theory empirically. We use game theory,
particularly a screening and sorting model, to illustrate the prospects for farmers with EES to access
formal credit and to improve their credit terms given that they receive PES and banking services
training. Furthermore, the PES’ long term duration (10 – 30 years) generates stable cash-flow which
may be perceived as collateral substitute. Results suggest that smallholder farmers in the TIST
program were less likely to be credit constraint compared to non-TIST farmers. Distance to market,
education, livestock and farm income are factors that determine access to credit from microfinance
institutions in rural Kenya. Amongst farmers that have obtained loans, those keeping business records
enjoy more favorable formal credit conditions. These farmers were observed to pay ca. 5 percent less
interest rate in microfinance charges. For TIST farmers, this type of farm management practices may
be attributed to the banking services and other training they receive within the program. While the
availability of classical collateral (farmlands) and PES may reduce interest rate, the latter was found
to be statistically insignificant. This research underlines the importance of an effective extension
services in rural areas of developing countries and the need to improve gains from conservation
agriculture and ensuing PES. The benefits associated with EES and PES may encompass agricultural
financing.

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Expansion of the meat inspection process to incorporate animal-based welfare measurements could contribute towards significant improvements in pig (Sus scrofa domesticus) welfare and farm profitability. This study aimed to determine the prevalence of different welfare-related lesions on the carcase and their relationship with carcase condemnations (CC) and carcase weight (CW). The financial implications of losses associated with CC and CW reductions related to the welfare lesions were also estimated. Data on tail lesions, loin bruising and bursitis, CW and condemnation/trimming outcome (and associated weights) were collected for 3,537slaughter pigs (mean [± SEM] carcase weight: 79.2 [± 8.82] kg). Overall, 72.5% of pigs had detectable tail lesions, whilst 16.0 and 44.0% were affected by severe loin bruising and hind limb bursitis, respectively. There were 2.5% of study carcases condemned and a further 3.3% were trimmed. The primary cause of CC was abscessation. While tail lesion severity did not increase the risk of abscessation, it was significantly associated with CC. Male pigs had a higher risk of tail lesions and of CC. The financial loss to producers associated with CC and trimmings was estimated at €1.10 per study pig. CW was reduced by up to 12 kg in cases of severe tail lesions. However, even mild lesions were associated with a significant reduction in CW of 1.2 kg. The value of the loss in potential CW associated with tail lesions was €0.59 per study pig. Combined with losses attributable to CC and trimmings this represented a loss of 43% of the profit margin per pig, at the time of the study, attributable to tail biting. These findings illustrate the magnitude of the impact of tail biting on pig welfare and on profitability of the pig industry. They also emphasise the potential contribution that the inclusion of welfare parameters at meat inspection could make to pig producers in informing herd health and welfare management plans.

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Inter-dealer trading in US Treasury securities is almost equally divided between two electronic trading platforms that have only slight differences in terms of their relative liquidity and transparency. BrokerTec is more active in the trading of 2-, 5-, and 10-year T-notes while eSpeed has more active trading in the 30-year bond. Over the period studied, eSpeed provides a more pre-trade transparent platform than BrokerTec. We examine the contribution to ‘price discovery’ of activity in the two platforms using high frequency data. We find that price discovery does not derive equally from the two platforms and that the shares vary across term to maturity. This can be traced to differential trading activities and transparency of the two platforms.

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The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.

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Background: We examined whether higher effort-reward imbalance (ERI) and lower job control are associated with exit from the labour market

Methods: There were 1263 participants aged 50-74 years from the English Longitudinal Study on Ageing with data on working status and work-related psychosocial factors at baseline (wave 2; 2004-2005), and working status at follow-up (wave 5; 2010-2011). Psychosocial factors at work were assessed using a short validated version of ERI and job control. An allostatic load index was formed using 13 biological parameters. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale. Exit from the labour market was defined as not working in the labour market when 61 years old or younger in 2010-2011. 

Results: Higher ERI OR=1.62 (95% CI 1.01 to 2.61, p=0.048) predicted exit from the labour market independent of age, sex, education, occupational class, allostatic load and depression. Job control OR=0.60 (95% CI 0.42 to 0.85, p=0.004) was associated with exit from the labour market independent of age, sex, education, occupation and depression. The association of higher effort OR=1.32 (95% CI 1.01 to 1.73, p=0.045) with exit from the labour market was independent of age, sex and depression but attenuated to non-significance when additionally controlling for socioeconomic measures. Reward was not related to exit from the labour market

Conclusions: Stressful work conditions can be a risk for exiting the labour market before the age of 61 years. Neither socioeconomic position nor allostatic load and depressive symptoms seem to explain this association.

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We present a rigorous methodology and new metrics for fair comparison of server and microserver platforms. Deploying our methodology and metrics, we compare a microserver with ARM cores against two servers with ×86 cores running the same real-time financial analytics workload. We define workload-specific but platform-independent performance metrics for platform comparison, targeting both datacenter operators and end users. Our methodology establishes that a server based on the Xeon Phi co-processor delivers the highest performance and energy efficiency. However, by scaling out energy-efficient microservers, we achieve competitive or better energy efficiency than a power-equivalent server with two Sandy Bridge sockets, despite the microserver's slower cores. Using a new iso-QoS metric, we find that the ARM microserver scales enough to meet market throughput demand, that is, a 100% QoS in terms of timely option pricing, with as little as 55% of the energy consumed by the Sandy Bridge server.

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Successful innovation depends on knowledge – technological, strategic and market related. In this paper we explore the role and interaction of firms’ existing knowledge stocks and current knowledge flows in shaping innovation success. The paper contributes to our understanding of the determinants of firms’ innovation outputs and provides new information on the relationship between knowledge stocks, as measured by patents, and innovation output indicators. Our analysis uses innovation panel data relating to plants’ internal knowledge creation, external knowledge search and innovation outputs. Firm-level patent data is matched with this plant-level innovation panel data to provide a measure of firms’ knowledge stock. Two substantive conclusions follow. First, existing knowledge stocks have weak negative rather than positive impacts on firms’ innovation outputs, reflecting potential core-rigidities or negative path dependencies rather than the accumulation of competitive advantages. Second, knowledge flows derived from internal investment and external search dominate the effect of existing knowledge stocks on innovation performance. Both results emphasize the importance of firms’ knowledge search strategies. Our results also re-emphasize the potential issues which arise when using patents as a measure of innovation.

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OBJECTIVES: Evaluate current data sharing activities of UK publicly funded Clinical Trial Units (CTUs) and identify good practices and barriers.

STUDY DESIGN AND SETTING: Web-based survey of Directors of 45 UK Clinical Research Collaboration (UKCRC)-registered CTUs.

RESULTS: Twenty-three (51%) CTUs responded: Five (22%) of these had an established data sharing policy and eight (35%) specifically requested consent to use patient data beyond the scope of the original trial. Fifteen (65%) CTUs had received requests for data, and seven (30%) had made external requests for data in the previous 12 months. CTUs supported the need for increased data sharing activities although concerns were raised about patient identification, misuse of data, and financial burden. Custodianship of clinical trial data and requirements for a CTU to align its policy to their parent institutes were also raised. No CTUs supported the use of an open access model for data sharing.

CONCLUSION: There is support within the publicly funded UKCRC-registered CTUs for data sharing, but many perceived barriers remain. CTUs are currently using a variety of approaches and procedures for sharing data. This survey has informed further work, including development of guidance for publicly funded CTUs, to promote good practice and facilitate data sharing.

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This article is a short introduction to a special section on economic ideas and the political construction of the financial crash. It begins by explaining why economic ideas and the politics of appeals to certain ideas are so integral to the historical significance of the crash of 2008 and the question of whether it can be considered a crash at all. The first section covers the literature on ideas and economic crisis. The second section highlights that the contribution of the special section is to engage in a stock taking exercise of the empirical and conceptual patterns concerning the politics of ideational change underway in the areas of: comparative fiscal policy; monetary policy and Euro zone debt management; capital controls; and financial and securities market regulation and standard setting. The final section outlines the structure of this special section and content of the individual articles.

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How can GPU acceleration be obtained as a service in a cluster? This question has become increasingly significant due to the inefficiency of installing GPUs on all nodes of a cluster. The research reported in this paper is motivated to address the above question by employing rCUDA (remote CUDA), a framework that facilitates Acceleration-as-a-Service (AaaS), such that the nodes of a cluster can request the acceleration of a set of remote GPUs on demand. The rCUDA framework exploits virtualisation and ensures that multiple nodes can share the same GPU. In this paper we test the feasibility of the rCUDA framework on a real-world application employed in the financial risk industry that can benefit from AaaS in the production setting. The results confirm the feasibility of rCUDA and highlight that rCUDA achieves similar performance compared to CUDA, provides consistent results, and more importantly, allows for a single application to benefit from all the GPUs available in the cluster without loosing efficiency.