Da Silva, Sergio (2015): Financial Market Efficiency Should be Gauged in Relative Rather than Absolute Terms. Published in: Journal of Stock & Forex Trading , Vol. 4, No. 1 (2015): p. 140.
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Abstract
Economists assess the efficiency of financial markets in absolute, all-or-nothing terms. However, this is at odds with a no-nonsense physics approach. Here, I describe how the relative efficiency of markets can be gauged taking advantage of algorithmic complexity theory. This is not physics-envy because the approach is superior in considering the proper randomness present in complex financial markets.
Item Type: | MPRA Paper |
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Original Title: | Financial Market Efficiency Should be Gauged in Relative Rather than Absolute Terms |
Language: | English |
Keywords: | Algorithmic complexity theory; Efficient market hypothesis; Financial market efficiency; Relative market efficiency; Mild type I randomness; Wild type II randomness |
Subjects: | G - Financial Economics > G0 - General > G00 - General G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading |
Item ID: | 64497 |
Depositing User: | Sergio Da Silva |
Date Deposited: | 23 May 2015 11:50 |
Last Modified: | 08 Oct 2019 16:45 |
References: | 1. Beechey M, Gruen D, Vickery J (2000) The efficient market hypothesis: A survey. Reserve Bank of Australia research discussion paper number 2000-2001. 2. Guttler C, Meurer R, Da Silva S (2008) Is the Brazilian stock market efficient? Economics Bulletin 7: 1-16. 3. Campbell JY, Lo AW, MacKinley AC (1997) The Econometrics of Financial Markets. Princeton: Princeton University Press. 4. Mantegna RN, Stanley HE (2000) An Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge: Cambridge University Press. 5. Giglio R, Matsushita R, Da Silva S (2008) The relative efficiency of stock markets. Economics Bulletin 7: 1-12. 6. Giglio R, Matsushita R, Figueiredo A, Gleria I, Da Silva S (2008) Algorithmic complexity theory and the relative efficiency of financial markets. Europhysics Letters 84: 48005-48010. 7. Giglio R, Da Silva S (2009) Ranking the stocks listed on Bovespa according to their relative efficiency. Applied Mathematical Sciences 3: 2133-2142. 8. Giglio R, Da Silva S, Gleria I, Ranciaro A, Matsushita R, Figueiredo A (2010) Efficiency of financial markets and algorithmic complexity. Journal of Physics: Conference Series 246: 012032. 9. Taufemback C, Giglio R, Da Silva S (2011) Algorithmic complexity theory detects decreases in the relative efficiency of stock markets in the aftermath of the 2008 financial crisis. Economics Bulletin 31: 1631-1647. 10. Taleb NN (2010) The black swan: The impact of the highly improbable, 2nd edition. New York: Random House. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/64497 |