Unraveling the impact of Iranian currency exchange on central bank digital currency: navigating through history-oriented bias

Abstract

This study examines the dynamics of the Iranian foreign exchange market and its impact on the exchange rate used by traders, and not the official rate in Iran. The study aims to extend Fama's theory of market efficiency and proposes a new model to define the opposite point called "Historical bias". The study applied the ARIMA and Markov switching models and dynamic conditional correlation to measure the speed of information circulation and to investigate the origin of the Iranian foreign exchange market's impact on the trader rate of the Dollar market. The study analyzed the convergence of the Iranian foreign exchange market based on different rates, the exchange rate used by traders, and the official rate and its effect on developing CBDC in Iran. The results of this study show that based on Fama's theory of market efficiency the foreign exchange market in Iran could have a 15% history-oriented bias, which is significant and would be an important problem for the launching of CBDC in Iran.

Keywords

• central bank digital currency (cbdc)
• market efficiency
• dynamic conditional correlation (dcc)
• iran currency exchange
• history-oriented bias