253 research outputs found

    The Financial Indicators Leading Real Economic Activity - the Case of Poland

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    In many research studies it is argued that it is possible to extract useful information about future real economic activity from the performance of financial markets. However, this study goes further and shows that it is not only possible to use expectations derived from financial markets to forecast future economic activity, but that data about the financial system can be used for this purpose as well. This paper sheds light on the ability to forecast real economic activity, based on additional and different financial variables than what have been presented so far. The research is conducted for the Polish emerging economy on the basis of monthly data. The results suggest that, based purely on the data from the financial system, it is possible to construct reasonable measures that can, even for an emerging economy, effectively forecast future real economic activity. The outcomes are proved by two different econometric methods, namely, by a time series analysis and by a probit model. All presented models are tested in-sample and out-of-sample.forecasting, rational expectations, financial system, term spreads, real economic activity

    Tight and simple Web graph compression

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    Analysing Web graphs has applications in determining page ranks, fighting Web spam, detecting communities and mirror sites, and more. This study is however hampered by the necessity of storing a major part of huge graphs in the external memory, which prevents efficient random access to edge (hyperlink) lists. A number of algorithms involving compression techniques have thus been presented, to represent Web graphs succinctly but also providing random access. Those techniques are usually based on differential encodings of the adjacency lists, finding repeating nodes or node regions in the successive lists, more general grammar-based transformations or 2-dimensional representations of the binary matrix of the graph. In this paper we present two Web graph compression algorithms. The first can be seen as engineering of the Boldi and Vigna (2004) method. We extend the notion of similarity between link lists, and use a more compact encoding of residuals. The algorithm works on blocks of varying size (in the number of input lines) and sacrifices access time for better compression ratio, achieving more succinct graph representation than other algorithms reported in the literature. The second algorithm works on blocks of the same size, in the number of input lines, and its key mechanism is merging the block into a single ordered list. This method achieves much more attractive space-time tradeoffs.Comment: 15 page
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