The aim of the article to assess the functioning of the NewConnect market over 10 years from the organizer’s and participants’ perspective. This helps to diagnose the most important organizational advantages and problems of the Polish MTF, determine further development prospects and propose potential changes to neutralize the negative factors. To illustrate the problem, a comprehensive analysis will be made of aggregated statistical data from 2007–2017, which show the changes and trends on this market, and additionally include the data comparing the current state of the NewConnect market with other alternative markets organized by European stock exchanges. The conducted research does not allow to view the NewConnect market as an organizational success. The analysis identified a number of problems in the functioning of the Polish MTF, ranging from the inappropriate organization of the primary market, resulting in the admittance of too high a number of issuers of dubious credibility, to the consequences appearing on the secondary shares market. It does not give unambiguous grounds to expect positive prospects for the market development in the future. In order to stop unfavorable trends and to improve the issuers’ quality, a discussion on the regulations regarding issuers’ admission, i.e. the size of the minimum equity, IPO, capitalization and the issue price of the debuting company, should be initiated.
In 1989–2017 women’s magazines were an important segment of Poland’s media market dominated by international publishing houses like Bauer Media, Edipresse Polska and Burda International. Each year they launched new leads (a total of about one hundred in that period). Most of them were successful in terms of sales and ad revenue. This article tries to chart the quantitative changes and major trends in the women’s magazines market as well as analyze the role of foreign capital in its development.
This paper develops a new model of market abuse detection in real time. Market abuse is detected, as Minenna (2003) proposed, on the basis of prediction intervals. The model structure is based on the discrete-time, extended market model introduced by Monteiro, Zaman, Leitterstorf (2007) to analyze the market cleanliness. Parameters of the expected return equation are assumed, however, to be time-varying and estimated under the state-space framework using the extended Kalman filter postulated by Chou, Engle, Kane (1992) to capture the GARCH effect in returns. QML estimation is performed on intraday data; its utilization is proposed as an alternative to the continuous time modeling by Minenna (2003). This framework is generalized to the bivariate case which enables the analysis of daily open/close data. The paper also extends procedures of the statistical verification of the estimated state-space model to include the uncertainty arising from time-invariant parameters.