Glycemic Index, glycemic control and beyond

It is currently estimated that over 370 million individuals have diabetes, making diabetes a major public health issue contributing significantly to global morbidity and mortality. The steep rise in diabetes prevalence over the past decades is attributable, in a large part, to lifestyle changes, with dietary habits and behaviour significant contributors. Despite the relatively wide availability of anti-diabetic medicine, it is lifestyle approaches that still remain the cornerstone of diabetes prevention and treatment. Glycemic index (GI) is a nutritional tool, which represents the glycemic response to carbohydrate ingestion. In light of the major impact of nutrition on diabetes pathophysiology, with the rising need to combat the escalating diabetes epidemic, this review will focus on the role of GI in glycemic control, the primary target of diabetic treatment and beyond. The review will present the evidence relating GI and diabetes treatment and prevention, as well as weight loss, weight maintenance and CVD risk factors.

A trading strategy based on the lead–lag relationship between the spot index and futures contract for the FTSE 100

This paper examines the lead–lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996–1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.

An alternative approach to investigating lead-lag relationships between stock and stock index futures markets

In the absence of market frictions, the cost-of-carry model of stock index futures pricing predicts that returns on the underlying stock index and the associated stock index futures contract will be perfectly contemporaneously correlated. Evidence suggests, however, that this prediction is violated with clear evidence that the stock index futures market leads the stock market. It is argued that traditional tests, which assume that the underlying data generating process is constant, might be prone to overstate the lead-lag relationship. Using a new test for lead-lag relationships based on cross correlations and cross bicorrelations it is found that, contrary to results from using the traditional methodology, periods where the futures market leads the cash market are few and far between and when any lead-lag relationship is detected, it does not last long. Overall, the results are consistent with the prediction of the standard cost-of-carry model and market efficiency.

Predicting stock index volatility: can market volume help?

This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the NYSE. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than the other way around. The out-of-sample forecasting performance of various linear, GARCH, EGARCH, GJR and neural network models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to very modest improvements, if any, in forecasting performance.

The Corporate Gini Index (CGI) determinants and advantages: lessons from a multinational retail company case study

This article identifies and compares the determinants of CEO compensation to median employee earnings with those of the Corporate Gini Index (CGI). Using a multinational retail company, the article posits that the CGI is an advantageous corporate alternative pay inequality measure that concerns CEO pay multiples to median employee earnings, which regulators should consider using and disclosing in proxy statements. Although CGI and the official measure of multiples of CEO pay to median employee earnings share some of the challenges, the advantages of CGI as an alternative measure are greater. Our findings suggest that the CGI is a much better measure of corporate income inequality bringing clear benefits at both micro and macro levels of intervention.

Evidence for a second meal cognitive effect: glycaemic responses to high and low glycaemic index evening meals are associated with cognition the following morning

Low glycaemic index (GI) foods consumed at breakfast can enhance memory in comparison to high-GI foods; however, the impact of evening meal GI manipulations on cognition the following morning remains unexplored. Fourteen healthy males consumed a high-GI evening meal or a low-GI evening meal in a counterbalanced order on two separate evenings. Memory and attention were assessed before and after a high-GI breakfast the following morning. The high-GI evening meal elicited significantly higher evening glycaemic responses than the low-GI evening meal. Verbal recall was better the morning following the high-GI evening meal compared to after the low-GI evening meal. In summary, the GI of the evening meal was associated with memory performance the next day, suggesting a second meal cognitive effect. The present findings imply that an overnight fast may not be sufficient to control for previous nutritional consumption.