Application of the Divisia Index with Interconnected Factors in the Warsaw Stock Exchange Index (WIG) fluctuation analysis

• Authors: Jacek Białek , Radosław Pietrzyk

Title variants

Zastosowanie indeksu Divisia z powiązanymi czynnikami do analizy fluktuacji indeksu WIG

• Languages of publication: EN

Abstracts

EN

This paper presents a method of economic factorial analysis based on the Divisia index extended to interconnected factors. We verify the applicability of the presented method to financial market research by examining fluctuations of the Warsaw Stock Exchange WIG Index (WIG). We consider four main factors of WIG changes: the GDP growth, the PLN/EUR rate, the S&P500 and the unemployment rate. Due to computational reasons we apply the transformation that produces variables in the bigger the better form. We use quarterly data from the time interval between 2003 and 2014 divided into periods of bull and bear market. All considered variables are assumed to change linearly between quarters. The main conclusion is that during market prosperity, GDP and S&P500 changes exhibit the strongest influence on WIG changes.

PL

W artykule zaprezentowano metodę analizy ekonomicznej opartej na indeksie Divisia z powiązanymi czynnikami. Zweryfikowano możliwości aplikacyjne wymienionej metody do badania zmienności indeksu WIG. W analizie uwzględniono cztery główne zmienne wpływające na indeks warszawski: GDP, kurs PLN/EUR, indeks S&P500 oraz stopę bezrobocia, przy czym dokonano (w razie konieczności) transformacji zmiennych na stymulanty. Analizą objęto lata 2003–2014 i uwzględniono dane kwartalne, przy czym interwał czasowy podzielono na podokresy związane z hossą i bessą na giełdzie warszawskiej. Przyjęto również model czasu ciągłego z założeniem, że między kwartałami wartości zmiennych zmieniają się liniowo. Głównym wnioskiem z przeprowadzonego badania jest wyodrębnienie najbardziej wpływowych zmiennych objaśniających w postaci GDP i indeksu S&P500.

Keywords

EN

Factorial analysis; Divisia index; interconnected factors; Warsaw Stock Exchange Index analysis

PL

analiza czynnikowa; indeks Divisia; czynniki powiązane; indeks WIG; analiza czynnikowa; indeks Divisia; czynniki powiązane; indeks WIG

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2017
• Volume: 4
• Issue: 330

Dates

published

2017-11-15

Contributors

author

Jacek Białek

• University of Lodz, Faculty of Economics and Sociology, Department of Statistical Methods

author

Radosław Pietrzyk

• Wrocław University of Economics, Faculty of Management, Information Systems and Finance, Department of Financial Investment and Risk Management

• https://orcid.org/0000-0002-6583-8424

References

• Ang B.W. (2004), Decomposition analysis for policymaking in energy: which is the preferred method?, “Energy Policy”, vol. 32, pp. 1131–1139.
• Ang B.W., Liu F.L., Chew E.P. (2003), Perfect decomposition techniques in energy and environmental analysis, “Energy Policy”, vol. 31, pp. 1561–1566.
• Białek J. (2015), Generalization of the Divisia price and quantity indices in a stochastic model with continuous time, “Communications in Statistics: Theory and Methods”, vol. 44, no. 2, pp. 309–328.
• Chen N.F., Roll R., Ross S.A. (1986), Economic Forces and the Stock Market, “The Journal of Business”, vol. 59, no. 3, pp. 383–403.
• Choi K.H., Oh W. (2014), Extended Divisia index decomposition of changes in energy intensity: A case of Korean manufacturing industry, “Energy Policy”, vol. 65, pp. 275–283.
• Dadgostar B., Moazzami B. (2003), Dynamic Relationship Between Macroeconomic Variables and the Canadian Stock Market, “Journal of Applied Business and Economics”, vol. 2, no. 1, pp. 7–14.
• Divisia F. (1925), L’indice Monetaire et la Theorie de la Monnaie, “Revue d’Economic Politique”, vol. 39, no. 5, pp. 980–1020.
• Fama E.F. (1981), Stock Returns, Real Activity, Inflation, and Money, “The American Economic Review”, vol. 71, no. 4, pp. 545–565.
• Fernández González P., Presno M.J., Landajo M. (2015), Regional and sectoral attribution to percentage changes in the European Divisia carbonization index, “Renewable and Sustainable Energy Reviews”, vol. 52, pp. 1437–1452.
• Humpe A., Macmillan P. (2009), Can macroeconomic variables explain long‑term stock market movements? A comparison of the US and Japan, “Applied Financial Economics”, vol. 19, no. 2, pp. 111–119.
• Lippe P. von der (2007), Index Theory and Price Statistics, Peter Lang Publishing, Frankfurt.
• McMillan D.G. (2010), Stock Market Fundamentals and Bubbles: Implications for Prices, GDP and Consumption, “SSRN Electronic Journal”, http://www.ssrn.com/abstract=1695443 [ac­cessed: 18.12.2016].
• Mukherjee T.K., Naka A. (1995), Dynamic Relations between Macroeconomic Variables and Japanese Stock Market: An Application Of A Vector Error‑Correction Model, “The Journal of Financial Research”, vol. 18, no. 2, pp. 223–237.
• Nelson C.R. (1976), Inflation and Rates of Return on Common Stocks, “The Journal of Finance”, vol. 31, no. 2, pp. 471–483.
• Sheremet A., Dei G., Shapovalov V. (1971), Method of the chain substitutions and development of the factorial analysis of the economic indicators, “Vestnik Moskovskogo Universiteta, Ser. Ekonomika”, vol. 4, pp. 62–69.
• Vaninsky A.Y. (1986), Analysis of production efficiency based on the generalized integral method, [in:] A. Aksenenko (ed.), Accounting and analysis of production efficiency (Uchet i analiz effectivnosti proizvodstva), Financy i Statistika, Moscow.
• Vaninsky A.Y. (1987), Factorial Analysis of Economic Activity (Factornyi Analiz Khozyaistbennoi Deyatel’nosti), Financy i Statistika, Moscow.
• Vaninsky A.Y. (2013), Economic Factorial Analysis of CO2 Emissions: The Divisia Index with Interconnected Factors Approach, “International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering”, vol. 7, no. 10, pp. 2772–2777.
• Vaninsky A.Y., Meerovich V. (1978), Problems of the methodology of analysis of the impact of structural change on the indicators of production efficiency (Voprosy metodologii analiza vliyaniya strukturnykh sdvigov na pokazateli effectivnosti proizvodstva), “Proceedings of the National Scientific Conference ‘Economic Leverages of the Efficiency of Using Material, Labor, Financial, and Natural Resourses’”, Central Economic‑Mathematical Institute, Moscow.
• Wiśniewski H. (2014), Wpływ zmiennych makroekonomicznych na indeksy giełdowe, Uniwersytet Warszawski, Warszawa.

Identifiers

DOI

10.18778/0208-6018.330.09