Devinder K. Gandhi

Testing For Nonlinearity & Modeling Volatility In Emerging Capital Markets: The Case Of Tunisia

Capital market efficiency of emerging markets has been investigated widely in recent years. But to-date the empirical results remain inconclusive because most empirical studies use empirical tests, which are designed to detect linear structure in financial time series. However, recent developments in econometrics of financial markets show evidence of nonlinear relationships in asset returns in developed markets. Given the features of emerging capital markets, nonlinearity is most likely to be even more present in these developing markets compared to developed ones. In the present paper we reject the weak-form efficient market hypothesis of the Tunisian Stock Market (TSE). Using the BDS test, we find evidence of nonlinearity in variance, and develop a FIEGARCH (1, 1) model accordingly.

On the validity of conventional statistical tests given evidence of non-synchronous trading and non-linear dynamics in returns generating process

Based on the recent developments in market microstructure and applications of nonlinear dynamics and chaos theory to financial time series, the subsequent article questions the validity of traditional methods used to test the efficient market hypothesis. In particular, it emphasizes the invalidity of unit roots tests since they are not predictability tests.