Static & Dynamic Models & Stock Market Efficiency Evaluation of T.S.E. Listed Companies’

The purpose of this paper is to evaluate weak-form market efficiency using static (fixed-coefficient models) & dynamic (time-varying models) models. Studying efficient market hypothesis (EMH) in emerging markets is an important subject among many researchers, due to many reasons mostly market efficiency in these markets is on doubts, it looks that methodological & statistical deficiencies provoked these problems. In previous studies mostly total market efficiency was considered as a whole market, regardless of lots of differences existed in individual companies. However, market efficiency tests should be examined among individual companies in order to compare each stock characteristic.

In this paper, we evaluate weak-form market efficiency; applying static & dynamic ARMA-GARCH models through a sample of 58 T.S.E. listed companies’ daily returns from 2006 to 2018.

Testing the significance of auto-regressive coefficients in static models shows that 15 cases have been confirmed & 43 cases have been rejected. To test more scrutinously, dynamic models have been fitted for those 43 rejected cases. The results show that 12 companies were both efficient & zero-convergent & the informational efficiencies of 31 companies were rejected (among which 9 ones were zero-convergent, too). Thus, we couldn't confirm any of the two hypotheses, included weak-form market efficiency & the movement toward weak-form market efficiency.

The difference in the dynamic & static models’ results shows the impact of the type of method selected on the results of weak-form market efficiencies’ test. Also, the time-line charts of 21 companies could explain some improvement in the degree of market efficiency & positive change since 2006. Finally, using dynamic models in the robustness test demonstrate that the more a company is liquid, the more is the probability of the weak-form market efficiency to be confirmed.