### An Empirical Test of the Theory of Efficient Markets of Stock Prices

#### Abstract

A structure of the statistical tests motivated by Cromwell, Labys&Terraza^{[23]}has been used to build linear and nonlinear **predictability** models.Most importantly, the variance ratio test and that of AR-GARCH model is used to test the dual hypotheses of the random walk and **efficiency**in stock markets. Whilein all or nothing condition of market efficiency, the variance ratio tests show weak signs of predictability and in contrast to the AR-GARCH model that shows strong signs of predictability. Testing efficiency over time shows that **price-fluctuations** between periods of predictability and unpredictability and theseare not correlated through indices. This study then contributes to the empirical evidence that the efficient market hypothesis should not be an all or nothing condition but be stated as a time varying condition where prices fluctuate between periods of efficiency and inefficiency. It is found that market microstructure can cause problems for certain measuring frequencies and a sufficiently risk averse investor may be happy to pay a premium to avoid any unforecastable asset price **volatilities** as inLeroy^{[11]}andLucas^{[12]}. Three random walk models also do not prevent questioning the validity of predictability of stock prices.

#### Keywords

#### Full Text:

PDF#### References

Fama, E. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417. doi:10.2307/2325486

Cootner, Paul H. The Random Character Of Stock Market Prices. 1st ed. Cambridge, Massachusetts: The M.I.T Press, 1964. Print.

Cowles, Alfred. "Can Stock Market Forecasters Forecast?". Econometrica 1.3 (1933): 309. Web.

Working, Holbrook. "A Random-Difference Series For Use In The Analysis Of Time Series". Journal of the American Statistical Association 29.185 (1934): 11. Web.

Kendall, M. G., and A. Bradford Hill. "The Analysis Of Economic Time-Series-Part I: Prices". Journal of the Royal Statistical Society. Series A (General) 116.1 (1953): 11. Web

Samuelson, Paul A., (1965:Spring) Proof That Properly Anticipated Prices Fluctuate Randomly , Industrial Management Review, 6:2,p.41

Fama, E. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38(1), 34-105.

Grossman, S. (1976). On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information. The Journal of Finance, 31(2), 573-585. doi:10.2307/2326627

Grossman, S., & Stiglitz, J. (1982). On the Impossibility of Informationally Efficient Markets: Reply. The American Economic Review, 72(4), 875-875.

Black, F. (1986). Noise. The Journal of Finance, 41(3), 529-543. doi:10.2307/2328481

LeRoy, S. (1973). Risk Aversion and the Martingale Property of Stock Prices. International Economic Review, 14(2), 436-446. doi:10.2307/2525932

Lucas, R. (1978). Asset Prices in an Exchange Economy. Econometrica, 46(6), 1429-1445. doi:10.2307/1913837

Lo, Andrew W. "The Adaptive Markets Hypothesis". The Journal of Portfolio Management 30.5 (2004): 15-29. Web

Lo, Andrew W. Market Efficiency: Stock Market Behavior In Theory And Practice, Volume 1 & 2. 1st ed. Great Britain: Edward Elgar Publishin Limited, 1997. Print.

Urquhart, Andrew, and Frank McGroarty. "Are Stock Markets Really Efficient? Evidence Of The Adaptive Market Hypothesis". International Review of Financial Analysis 47 (2016): 39-49. Web.

Lim, K.P. and Brooks, R., 2011. The evolution of stock market efficiency over time: a survey of the empirical literature. Journal of Economic Surveys, 25(1), pp.69-108.

Todea, A., Ulici, M. and Silaghi, S., 2009. Adaptive markets hypothesis: Evidence from Asia-Pacific financial markets. The Review of Finance and Banking, 1(1).

Hull, M. and McGroarty, F., 2014. Do emerging markets become more efficient as they develop? Long memory persistence in equity indices. Emerging Markets Review, 18, pp.45-61.

Urquhart, A. and McGroarty, F., 2016. Are stock markets really efficient? Evidence of the adaptive market hypothesis. International Review of Financial Analysis, 47, pp.39-49.

Urquhart, A. and Hudson, R., 2013. Efficient or adaptive markets? Evidence from major stock markets using very long run historic data. International Review of Financial Analysis, 28, pp.130-142.

Ghazani, M.M. and Araghi, M.K., 2014. Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange. Research in International Business and Finance, 32, pp.50-59

Alvarez-Ramirez, J., Rodriguez, E. and Espinosa-Paredes, G., 2012. Is the US stock market becoming weakly efficient over time? Evidence from 80-year-long data. Physica A: Statistical Mechanics and its Applications, 391(22), pp.5643-5647

Campbell, John Y, Andrew W Lo, and Archie Craig MacKinlay. The Econometrics Of Financial Markets. 1st ed. Princeton, N.J.: Princeton University Press, 1997. Print.

Voit, Johannes. The Statistical Mechanics Of Financial Markets. 1st ed. Berlin: Springer, 2001. Print.

Øksendal, B. K. Stochastic Differential Equations. 1st ed. Springer, 2003. Print.

Goodman, J. 2004, Stochastic Calculus Notes, Available from: http://www.math.nyu.edu/faculty/goodman/teaching/StochCalc2004/notes/l1.pdf

Ljung, G.M. and Box, G.E., 1978. On a measure of lack of fit in time series models. Biometrika, 65(2), pp.297-303.

Cromwell, Jeff B et al.Multivariate Tests For Time Series Models. 1st ed. Thousand Oaks, Calif.: Sage Publications, 1994. Print.

Lo, A., &MacKinlay, A. (1988). Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test. The Review of Financial Studies, 1(1), 41-66. Retrieved from http://www.jstor.org/stable/2962126

Dougherty, Christopher R. S. Introduction To Econometrics. 4th ed. Oxford University Press, 2011. Print.

Ghalanos, Alexios. "Introduction To The Rugarch Package". r-project. N.p., 2015. Web. 11 May 2017.Availablefrom: https://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf

Bollerslev, T., 1986. Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), pp.307-327.

Officer, R.R., 1973. The variability of the market factor of the New York Stock Exchange. the Journal of Business, 46(3), pp.434-453.

Garman, M.B. and Klass, M.J., 1980. On the estimation of security price volatilities from historical data. Journal of business, pp.67-78.

Parkinson, M., 1980. The extreme value method for estimating the variance of the rate of return. Journal of business, pp.61-65.

Merton, R.C., 1980. On estimating the expected return on the market: An exploratory investigation. Journal of financial economics, 8(4), pp.323-361.

Cromwell, J.B., Hannan, M.J., Labys, W.C. and Terraza, M., 1994. Multivariate tests for time series models. Quantitative Applications in the Social Sciences Series, No. 100.

DOI: http://dx.doi.org/10.18686/fm.v3i2.1077

### Refbacks

- There are currently no refbacks.

Copyright (c) 2018 Keshab Bhattarai

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.