Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

Results found: 2

first rewind previous Page / 1 next fast forward last

Search results

help Sort By:

help Limit search:
first rewind previous Page / 1 next fast forward last
1
100%
EN
This article presents one of the most promising methods to predict the sudden changes in the stock market, namely the theory of log-periodic oscillations. The authors, in addition to the above theoretical basis method referring to the theory of complex systems and critical phenomena, show empirical evidence of the effectiveness of this approach in predicting both the bust in the stock market, as well as in the resources market. The examples (based on the analysis and forecasts) shown in the research confirm that self-similar log-periodicity with a parameter contraction lambda approx. 2 is able to properly describe the dynamics of the stock exchange on different time scales. What is more, the prediction, indicating a reversal of the uptrend in the stock market in September and October in 2009, was shown.
EN
The study will examine the probability distributions of returns for the WIG20 index and the portfolio for the period from 17.11.2000 to 30.06.2005. These are the highest frequency (1 min) and the so-called tick by tick data (quotes at the time of the transaction). Except the data from the Polish stock market, the data from so-called mature markets (such as trading for the 1000 largest companies from the NYSE and NASDAQ index) will be analyzed. The analytical form of distributions (called q-Gaussian) will also be proposed. Nowadays it is one of the best representations describing the actual distributions.
first rewind previous Page / 1 next fast forward last
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.