Identifying Financial Bubbles Using Finite-time Singularity GARCH Model: A Case Study of Tehran Stock Exchange

Abstract

The purpose of this study was to identify financial bubbles using finite-time singularity GARCH model in the case study of Tehran Stock Exchange for the period 2004 to 2013. Statistical sample of study included 102 manufacturing companies listed in Tehran Stock Exchange Tehran. To achieve to this goal, two hypotheses were proposed. To test the hypotheses, Dickey-Fuller test, GARCH model (1, 1) vector auto-regression, and BEKK method were used. The results of this study suggest that both hypotheses were confirmed, in other words, in the financial bubbles situation, autocorrelation of stock returns is significant. I addition, by adding a regression component to see the possible positive feedback effects of price on return or return on stock return, we can see the returns autocorrelation in GARCH (1, 1) model.

DOI: 10.5901/mjss.2016.v7n4S2p109