Dynamic Efficiency in Tehran Stock Exchange by Kalman Filter

Subject Areas : Financial Knowledge of Securities Analysis

Zahra Farshadfar ¹ , Marcel Prokopczuk ²

1 - Department of Economics, College of Humanities, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
2 - Institute for Financial Markets, Leibniz University Hannover, Hannover, Germany.

Received: 2018-08-14 Accepted : 2018-12-01 Published : 2019-06-22

Keywords: Dynamic Efficiency, Evolving Efficiency, Kalman Filter, State Space Model,

Abstract :

Estimating informative efficiency in financial market is crucial for investors. They can gain unusual profit when the market is inefficient. As informative efficiency is evolving and undergoing changes in emerging markets such as Iran, classic methods for efficiency estimation in these kind of financial markets are not suitable. Therefore, in such markets a hybrid method needs to be applied in such a way that the existing status of efficiency (static approach) and the efficiency during time (dynamic approach- in the absence of static efficiency) can be studied. The present study aims to determine the efficiency of Tehran Stock Exchange market by both static and dynamic approach. In order to obtain this goal, a combination of TVPGARCH and Kalman filter methods were applied on weekly total price index data during 2008 to 2017. Results indicate that the performance in Tehran Stock Exchange market in the static form does not have week efficiency. On the other hand, there is no evidence of efficiency dynamicity in Tehran Stock Exchange market performance during the studied period.

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