Czasopismo
Tytuł artykułu
Autorzy
Warianty tytułu
Języki publikacji
Abstrakty
In this study we investigate how bankruptcy affects the market behaviour of prices of stocks on Warsaw's Stock Exchange. As the behaviour of prices can be seen in a myriad of ways, we investigate a particular aspect of this behaviour, namely the predictability of these price formation processes. We approximate their predictability as the structural complexity of logarithmic returns. This method of analysing predictability of price formation processes using information theory follows closely the mathematical definition of predictability, and is equal to the degree to which redundancy is present in the time series describing stock returns. We use Shannon's entropy rate (approximating Kolmogorov-Sinai entropy) to measure this redundancy, and estimate it using the Lempel-Ziv algorithm, computing it with a running window approach over the entire price history of 50 companies listed on the Warsaw market which have gone bankrupt in the last few years. This enables us not only to compare the differences between predictability of price formation processes before and after their filing for bankruptcy, but also to compare the changes in predictability over time, as well as divided into different categories of companies and bankruptcies. There exists a large body of research analysing the efficiency of the whole market and the predictability of price changes en large, but only a few detailed studies analysing the influence of external stimuli on the efficiency of price formation processes. This study fills this gap in the knowledge of financial markets, and their response to extreme external events. (original abstract)
Twórcy
Bibliografia
- Capasso, V., Bakstein, D. (2012). An Introduction to Continuous-Time Stochastic Processes. Boston: Birkhäuser Boston.
- Cover, T., Thomas, J. (1991). Elements of Information Theory. New York: John Wiley & Sons.
- Fiedor, P. (2014a). Frequency Effects on Predictability of Stock Returns. In Proceedings of the IEEE Computational Intelligence for Financial Engineering & Economics (pp. 247-254). London: IEEE.
- Fiedor, P. (2014b). Maximum Entropy Production Principle for Stock Returns. arXiv, 1408.3728.
- Fiedor, P. (2014c). Sector Strength and Efficiency on Developed and Emerging Financial Markets. Physica A, 413, 180-188.
- Fiedor, P., Hołda, A. (2014). Wpływ ogłoszenia upadłości na złożoność strukturalną zmian cen na GPW. Manuscript in review.
- Garland, J., James, R., Bradley E. (2014). Model-free Quantification of Time-series Predictability. arXiv, 1404.6823.
- Gao, Y., Kontoyiannis, I., Bienenstock, E. (2006). From the Entropy to the Statistical Structure of Spike Trains. In IEEE International Symposium on Information Theory (pp. 645-649).
- Kontoyiannis, I. (1998). Asymptotically Optimal Lossy Lempel-Ziv Coding. In IEEE International Symposium on Information Theory. Cambridge: MIT (p. 273).
- Mantegna, R.N., Stanley, H.E. (2000). Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge: Cambridge University Press.
- Martyushev, L., Seleznev, V. (2006). Maximum Entropy Production Principle in Physics, Chemistry and Biology. Physical Reports, 426, 1-45.
- Rosser, B. (2008). Econophysics and Economic Complexity. Advances in Complex Systems, 11(5), 745-760.
- Shannon, C.E. (1948). A Mathematical Theory of Communication. The Bell System Technical Journal, 27, 379-423, 623-656.
- Sinai, Y. (1959). On the Notion of Entropy of a Dynamical System. Doklady of Russian Academy of Sciences, 124, 768-771.
- Song, C., Qu, Z., Blumm, N., Barabási, A.-L. (2010). Limits of Predictability in Human Mobility. Science, 327(5968), 1018-1021.
- Willems, F., Shtarkov, Y., Tjalkens, T. (1995). The Context-Tree Weighting Method: Basic Properties. IEEE Transactions on Information Theory, 41(3), 653-664.
- Ziv, J., Lempel, A. (1977). A Universal Algorithm for Sequential Data Compression. IEEE Transactions on Information Theory, 23(3), 337-343.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171440090