X Международная научная конференция по проблемам развития экономики и общества: В 3 кн.
This paper addresses state participation in the financial sector. We take the example of the Russian banking industry to suggest criteria for a more accurate definition of public sector boundaries and an assessment of the actual scale of state presence in the national banking market.
The phenomenon of positive autocorrelation in daily stock index returns is often viewed as a consequence of stable behavioral patterns of certain investor groups (e.g., [Sentana, Wadhwani, 1992; Koutmos, 1997]). However, such patterns may change due to extreme events, i.e. currency and financial crises, and affect the autocorrelation of returns. Emerging markets have experienced severe crises in a recent decade and are therefore a suitable object to study.
Thus the focus of the current paper is to identify substantial changes in autocorrelation of BRICs’ stock markets index returns after experiencing these failures of financial system (the Asian crisis of 1997–1998, the crises in Russia, Brazil in 1998–1999 and the revaluation of the Chinese yen in 2005). Since all countries considered belong to the group of emerging markets and crises might have contagious effects we expect to reveal the influence of events in one country from the group on the markets in other countries. Studying stock market crises in BRICs and Thailand as possible causes of structural changes on stock markets is contribution of this paper to the existing literature. For this purpose we test for structural breaks in an ARMA-GARCH-model on the commonly known crisis dates.
The paper is organized as follows. Section 2 discusses the properties of long memory processes and their application in finance, section 3 focuses on the dichotomy between long-range dependence and structural breaks. Section 4 describes the used methodology, section 5 provides the data description. Finally, section 6 presents the results of the estimation, and section 7 concludes, summarizing findings and outlining directions for future research.
In this paper we will lean on the behavioral explanation of return dynamics. The most popular behavioral origin of autocorrelation is gradual information diffusion between equity securities [Badrinath et al., 1995] and different groups of investors [Hong, Stein, 1999]. The first point out, that some piece of information is instantaneously considered to be price-relevant for a certain industry or individual company, but after a while the investors realize, that the information revealed has an effect on valuation of further assets, what induces the prices of these further stocks to follow and thus generate autocorrelation of index returns. The latter argue, that investors perceive different bits of news (even on the same company) and gradually exchange the information they got, until each of them can get together a whole picture from the different parts, similar to children putting a puzzle together. Since each investor gets the same bit of information from a previous investor, he acts on it in the same way (assuming he draws the same conclusions) with a lag, thus inducing serial correlation on single equity and index returns as well.