PREDICTING INTRADAY STOCK RETURNS BY INTEGRATING MARKET DATA AND FINANCIAL NEWS REPORTS

Forecasting in the financial domain is undoubtedly a challenging undertaking in data mining. While the majority of previous studies in this field utilize historical market data to predict future stock returns, we explore whether there is benefit in augmenting the prediction model with supplementary domain knowledge obtained from financial news reports. To this end, we empirically evaluate how the integration of these data sources helps to predict intraday stocks returns. We consider several types of integration methods: variable-based as well as bundling methods. To discern whether the integration methods are sensitive to the type of forecasting algorithm, we have implemented each integration method using three different data mining algorithms. The results show several scenarios in which appending market-based data with textual news-based data helps to improve forecasting performance. The successful integration strongly depends on which forecasting algorithm and variable representation method is utilized. The findings are promising enough to warrant further studies in this direction

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Evaluating Energy Options for Israel: A Case Study

More than 98 percent of Israel's primary energy resources are imported, most of it as crude oil, the rest of it as coal, placing the country in a most vulnerable and awkward position. The sharp increases in crude oil prices in 1973 following the Yom Kippur War and in 1979 has increased the country's economic burden, contributing to its increasing deficit in the balance of payments and staggering inflation rate. Perhaps here more than anywhere else, a balanced energy policy is most crucial for security and well-being. Such policy would allow diversification of primary energy resources by using more alternative and renewable resources supplemented by a variety of ways of managing demand and controlling peak-load growth.

Capacity Expansion of Power Generation Systems with Uncertainty in the Prices of Primary Energy Resources

In capacity expansion studies of power generation systems, the uncertainty in the prices of the primary energy resources is a major concern. The approach presented in this paper accounts for this uncertainty by mapping the probability distribution of the installed capacity for any given distribution of the fuel prices. Given the probability density function and the cumulative distribution of the installed capacity, a variety of performance measures is derived, including the expected value, the mode, and the variance of the installed capacity, and the expected total costs. Results are obtained analytically for a 2-unit system using a breakeven point analysis approach to find the optimal mix for any given set of fuel prices under the assumption of normally distributed primary energy prices.capacity expansion, industries: electric, planning: corporate