佳作分享|用溢出指数法研究证券市场的风险关联性
Risk connectedness of selected CESEE stock markets: a spillover index approach
用溢出指数法研究证券市场的风险关联性
· 文章作者 ·
Tihana Škrinjarić
Department of Mathematics, Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia,and
Boško Šego
Department of Mathematics, Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia
Citation
Škrinjarić, T. and Šego, B. (2019), "Risk connectedness of selected CESEE stock markets: a spillover index approach", China Finance Review International, Vol. 10 No. 4, pp. 447-472. https://doi.org/10.1108/CFRI-07-2019-0124
· 摘要 ·
Purpose
The purpose of this paper is to empirically evaluate risk spillovers between selected CESEE (Central, Eastern and South-Eastern Europe) stock markets in order to evaluate the possibilities of an international diversification of a portfolio.
Design/methodology/approach
The VAR model and the Diebold and Yilmaz (2009, 2012) spillover index are used, with rolling indices estimation over time in order to observe dynamics, which is important for investment strategies. Data are monthly and include selected CESEE stock market indices which were available to the researcher.
Findings
The empirical analysis for the period of January 2012–June 2019 indicates that some country risks were the net emitter of shocks in the system (Slovenia and Czech Republic), whereas some were net receivers (Croatia and Ukraine). The results are robust with respect to changing the length of the rolling window analysis, which means that investors could utilize such an approach in a dynamic portfolio selection.
Research limitations/implications
Observing only selected markets due to data (un)availability.
Practical implications
The paper shows how international investors can utilize the aforementioned methodology in order to make a more detailed analysis of the dynamics of stock markets connectedness so that international portfolios can be rebalanced according to the results and investors’ preferences.
Originality/value
This is the first such research which focuses on CESEE countries, since existing research is focused on more developed stock markets. Moreover, the empirical analysis extends to commenting the pairwise net indices over time, which is important for the dynamic portfolio rebalancing over time.
· 文章结构 ·
Introduction
Literature review
Methodology
Results of empirical analysis
4.1 Data description
4.2 Initial results
4.3 Spillover indices results
4.4 Robustness checking
Discussion and conclusion
研究成果
· 1 · Descriptive statistics for SDs, all countries in the analysis.
· 2 · Unit root test results, constant as deterministic regressor included.
· 3 · Lag length criteria testing and diagnostics of VAR(2) model.
· 4 · Granger causality test results for VAR(2) model.
· 5 · Spillover table for the VAR(2) model, total sample.
· 6 · Rolling net spillover indices for all countries in the analysis.
· 7 · Rolling pairwise spillover indices for all countries in the analysis.
· 8 · Rolling pairwise spillover indices for all countries in the analysis.
· 9 · Rolling pairwise spillover indices for all countries in the analysis.
· 10 · Rolling pairwise spillover indices for all countries in the analysis.
· 11 · Rolling total spillover indices, different window lengths.
· 12· p-values of the rolling Granger causality tests.
· 13 · Spillover table for VAR(40) model on daily data, total sample, h=252 days.
· 14 · Monthly correlations (grey lines, left axis) compared to pairwise spillover indices (black lines, right axis).
· 结论·
For the purpose of optimal portfolio selection and rebalancing over time, a lot of different knowledge is necessary so that the investor’s goals can be achieved in the best way possible. Those investors, who are focused on risk mitigation, aim to achieve the best portfolio diversification. Since previous research has shown that the connectedness of many stock markets has increased over the last couple of decades, this means that the diversification possibilities have diminished over time. However, some still exist, and investors should aim to utilize them if possible.
This research focused on the shock spillovers between risks of selected CESEE stock markets, due to them being under-analyzed in the existing literature. Up until writing this research, the authors did not find any similar research focusing on the aforementioned countries, just the more developed ones. Thus, there exists a gap in the literature which was endeavoured to be filled here. That is why this research focused on utilizing the methodology of spillover indices, to give detailed insights into spillovers of shocks in risks between the selected stock markets. It was shown how the investor can depict the results to observe when a country SD is the receiver and when the emitter of shocks. This knowledge is important so that the portfolio can be rebalanced accordingly. In the particular case of findings in this research, greatest spillovers were found between the Slovenian and Bulgarian SDs ( from Slo to Bulg); Polish and Czech (from Pol to Cz); Czech and Polish and Hungarian ( from Cz to Pol and Hun); and Polish and Hungarian SDs ( from Pol to Hun). Thus, it is not advised to have a combination of the mentioned markets in the portfolio at the same time in order to reduce portfolio risk. Since the shock spillovers between the risks of the mentioned countries were the greatest in the observed period, the investor should be careful and monitor their comovements when having them in the portfolio. Next, for better diversification possibilities, investors should look into the next combinations. Least amount of spillovers was found for the Czech and Slovakian and Ukrainian SDs; Slovenian and Slovakian; Ukrainian and Czech and Polish; and Bulgarian and Hungarian. Alongside mentioned research which tries to explain the causes of spillovers between the observed stock markets, these results are in line with findings in Škrinjarić (2019), where results indicate that several stock markets absorb more shocks from the CEE neighbourhood indices (those that geographically belong to CEE), whilst others absorb more from the SEE neighbourhood. This additionally increases the mutual spillovers between pairs of countries within each sub region.
Of course, it is not easy to monitor all of the pairwise spillovers in parallel, due to there being a lot of pairs to compare over time. However, this detailed approach enables the investor to obtain full information on the risk spillovers, compared to some other approaches in which only the conclusion of existence or nonexistence of a relationship can be confirmed. Some of the shortfalls of this study were noticed while conducting it. First, a short period was observed, due to unavailability of data. Thus, future work should focus on extending the time period, as well as the number of countries in the analysis.
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作者简介
Tihana Škrinjarić, PhD, Assistant Professor, Department of Mathematics, Faculty of Economics and Business, University of Zagreb.
Interests: financial econometrics; portfolio analysis; stock market; developing markets; applied econometrics; performance measurement; quantitative techniques; risk analaysis
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