Google Trends and the forecasting performance of exchange rate models

In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data.     

Granularity as a determinant of system architecture

The size of unit components in general systems is claimed to be the major determinant of architecture. Three generations of systems are characterized in terms of their component size. Architectural issues in information systems, production management, and organizational structure are identified and related to the size of their unit components. Historical debates on classification of information systems, production systems, and organizational structures are reviewed, analyzed, and explained in terms of three general architectural classes based on a selection of a unit component and the size of that unit component.     

Volatile content of lunar volcanic glasses and the presence of water in the Moon's interior

The Moon is generally thought to have formed and evolved through a single or a series of catastrophic heating events, during which most of the highly volatile elements were lost. Hydrogen, being the lightest element, is believed to have been completely lost during this period. Here we make use of considerable advances in secondary ion mass spectrometry to obtain improved limits on the indigenous volatile (CO(2), H(2)O, F, S and Cl) contents of the most primitive basalts in the Moon-the lunar volcanic glasses. Although the pre-eruptive water content of the lunar volcanic glasses cannot be precisely constrained, numerical modelling of diffusive degassing of the very-low-Ti glasses provides a best estimate of 745 p.p.m. water, with a minimum of 260 p.p.m. at the 95 per cent confidence level. Our results indicate that, contrary to prevailing ideas, the bulk Moon might not be entirely depleted in highly volatile elements, including water. Thus, the presence of water must be considered in models constraining the Moon's formation and its thermal and chemical evolution.