Econophysical bourse volatility – Global Evidence

1. A. Abhyankar, L. S. C. & W. W. (1995). Moment condition failure in high frequency financial data: evidence from the S&P 500. Applied Economics Letters, 2(8), 288–290. https://doi.org/DOI:10.1080/13504859535725810.1080/135048595357258Search in Google Scholar

2. Ajaz, T. (2019). Nonlinear Reaction functions: Evidence from India. Journal of Central Banking Theory and Practice, 8(1), 111–132. https://doi.org/10.2478/jcbtp-2019-000610.2478/jcbtp-2019-0006Search in Google Scholar

3. Arms, R. W. (1996). Trading without Fear (1st ed.). John Wiley and Sons.Search in Google Scholar

4. Australian Securities Exchange. (2013). Australian Share Ownership Study. Sydney. Retrieved from https://www.asx.com.au/documents/resources/australian-share-ownership-study-2014.pdfSearch in Google Scholar

5. Bentes, S. R., & Menezes, R. (2012). Entropy: A new measure of stock market volatility? Journal of Physics: Conference Series, 394(1). https://doi.org/10.1088/1742-6596/394/1/01203310.1088/1742-6596/394/1/012033Search in Google Scholar

6. Cotfas, L. A. (2013). A quantum mechanical model for the rate of return. Romanian Reports in Physics, 65(2), 327-333.Search in Google Scholar

7. Dhaene, J., Dony, J., Forys, M., Linders, D., & Schoutens, W. (2011). FIX - The fear index. Measuring market fear. FBE Research Report AFI_1155, (January), 1–17. https://doi.org/10.2139/ssrn.188833510.2139/ssrn.1888335Search in Google Scholar

8. Dorsey, D. (1993). Technical Analysis of Stocks and Commodities, New York.Search in Google Scholar

9. Dumičić, M. (2019). Linkages between Fiscal Policy and Financial (In) Stability. Journal of Central Banking Theory and Practice, 8(1), 97–109. https://doi.org/10.2478/jcbtp-2019-000510.2478/jcbtp-2019-0005Search in Google Scholar

10. Fabris, N. (2018). Challenges for modern monetary policy. Journal of Central Banking Theory and Practice, 7(2), 5–24. https://doi.org/10.2478/jcbtp-2018-001010.2478/jcbtp-2018-0010Search in Google Scholar

11. Ghosh, B., Krishna, M., Rao, S., Kozarević, E., & Pandey, R. K. (2018). Predictability and herding of bourse volatility: an econophysics analogue. Investment Management and Financial Innovations, 15(2), 317–326. https://doi.org/10.21511/imfi.15(2).2018.2810.21511/imfi.15(2).2018.28Search in Google Scholar

12. Ghosh, B., & Kozarevic, E. (2018). Identifying explosive behavioral trace in the CNX nifty index: A quantum finance approach. Investment Management and Financial Innovations, 15(1), 208–223. https://doi.org/10.21511/imfi.15(1).2018.1810.21511/imfi.15(1).2018.18Search in Google Scholar

13. Ghosh, B. & Kozarević, E. (2019). Multifractal analysis of volatility for detection of herding and bubble: evidence from CNX Nifty HFT. Investment Management and Financial Innovations, 16(3), 182-193. doi:10.21511/imfi.16(3).2019.1710.21511/imfi.16(3).2019.17Search in Google Scholar

14. Gopikrishnan, P., Meyer, M., Amaral, L. A. N., & Stanley, H. E. (1998). Inverse cubic law for the distribution of stock price variations. European Physical Journal B, 3(2), 139–140. https://doi.org/10.1007/s10051005029210.1007/s100510050292Search in Google Scholar

15. Haug, E., & Taleb, N. N. (2007). Why we have never used the Black-Scholes-Merton option pricing formula. Social Science Research Network, (January), 1–11. https://doi.org/10.2139/ssrn.1012075Search in Google Scholar

16. Jakimowicz, A., & Juzwiszyn, J. (2015). Balance in the turbulent world of economy. Acta Physica Polonica A, 127(3), A78–A85. https://doi.org/10.12693/APhysPolA.127.A-7810.12693/APhysPolA.127.A-78Search in Google Scholar

17. L. Bachelier. (1900). Th´eorie de la sp´ eculation. Ann. Sci. Ecole Norm. Sup, ISSN 0012-9593, 17, 21–86. Retrieved from http://eudml.org/doc/8114610.24033/asens.476Search in Google Scholar

18. Laloux, L., Potters, M., Cont, R., Aguilar, J. P., & Bouchaud, J. P. (1998). Are financial crashes predictable? Europhys. Lett., 45, 1-5.10.1209/epl/i1999-00122-9Search in Google Scholar

19. Leora Klapper, Annamaria Lusardi, & Peter van Oudheusden. (2014). Financial Literacy Around the World: Leora Klapper, World Bank Development Research Group Annamaria Lusardi, The George Washington University School of Business Peter van Oudheusden, World Bank Development Research Group INSIGHTS FROM THE STANDARD & POOR’. The Standard & Poor’S Ratings Services Global Financial Literacy Survey, 10(04), 509–525. Retrieved from https://www.mhfi.com/corporate-responsibility/global-financial-literacy-surveySearch in Google Scholar

20. Los, C. A. (2004). Measuring Financial Cash Flow and Term Structure Dynamics. SSRN Electronic Journal.Search in Google Scholar

21. Mandelbrot, B. and R. L. H. (2004). Misbehavior of markets. Basic Books.Search in Google Scholar

22. Mantegna, R. N., & Stanley, H. E. (1995). Scaling behaviour in the dynamics of an economic index. Nature. https://doi.org/10.1038/376046a010.1038/376046a0Search in Google Scholar

23. Ormos, M., & Timotity, D. (2016). Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading. Finance Research Letters, 1–15. https://doi.org/10.1016/j.frl.2016.06.00310.1016/j.frl.2016.06.003Search in Google Scholar

24. Pan, R. K., & Sinha, S. (2008). Inverse-cubic law of index fluctuation distribution in Indian markets. Physica A: Statistical Mechanics and Its Applications, 387(8–9), 2055–2065. https://doi.org/10.1016/j.physa.2007.11.03110.1016/j.physa.2007.11.031Search in Google Scholar

25. Samuelson, P. A. (1965). Rational Theory of Warrant Pricing. Industrial Management Review, 6(2), 13–39.Search in Google Scholar

26. Samuelson, P. A. (1969). Classical and Neoclassical Theory. In R. W. Clower (Ed.), Monetary Theory (pp. 170–190). London: Penguin.Search in Google Scholar

27. Sinha, S., Thess, M and Markose, T. (2013). How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations. In Econophysics of Systemic Risk and Network Dynamics, New Economic Windows (Vol. 13). Springer Verlag. https://doi.org/10.1007/978-88-470-2553-0_510.1007/978-88-470-2553-0_5Search in Google Scholar

28. Zhang, C., & Huang, L. (2010a). A quantum model for the stock market. Physica A: Statistical Mechanics and Its Applications, 389(24), 389(24), 5769–5775. https://doi.org/10.1016/j.physa.2010.09.00810.1016/j.physa.2010.09.008Search in Google Scholar

29. Zhang, C., & Huang, L. (2010b). A quantum model for the stock market. Physica A: Statistical Mechanics and Its Applications, 389(24), 5769–5775. https://doi.org/10.1016/J.PHYSA.2010.09.00810.1016/j.physa.2010.09.008Search in Google Scholar

30. Zhang, Q., Sornette, D., BalcIlar, M., Gupta, R., Ozdemir, Z. A., & Yetkiner, H. (2016). LPPLS bubble indicators over two centuries of the S&P 500 index. Physica A: Statistical Mechanics and Its Applications, 458. https://doi.org/10.1016/j.physa.2016.03.10310.1016/j.physa.2016.03.103Search in Google Scholar