Journal of Economic Modeling Research

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Given the importance and role of capital markets in the economy, its characteristics have been regarded by researchers in this field. Hence, the main purpose of the present study is testing the existence of multiple price bubbles in Tehran stock market. For this purpose, the monthly data on the total price index and price-dividend ratio for periods 2000 – 2013 has been used. In this study generalized supremum Augmented Dickey – Fuller test, which has been recently introduced, is used due to critical review of conventional methods of testing the bubbles and also the possibility of a multiple bubble in time series. In addition to the testing of multiple Bubbles, with using this method there is the possibility of determining their period of creation and decay. The results showed that in the period under review, in the period 2003:3 - 2003:5 and 2004:12 - 2005:7 hypotheses price bubble in the stock market is confirmed.

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The bubble of Asset Price is the deviation of the asset price from its fundamental value. Since the many of the financial crisis arise from bursting bubble of financial assets, the explore of bubble behaviors in these markets and the early detection for the prevention of adverse economic consequences is important. Considering the criticisms of conventional tests for detecting price bubbles and also the importance of the subject, in this study, we have considered the new methods proposed by Phillips, et al. (2011, 2012) based on Right-Tailed Augmented Dickey-Fuller (RTADF) tests. In this regard, in order to testing explosive behavior and multiple bubbles and determining bubble periods in Iranian informal exchange market, we have applied the tests of SADF and GSADF according to monthly data for the nominal exchange rate from 2002:04 to 2016:03. Since the explosive behavior in nominal exchange rate might be driven by the its fundamentals, to comment on the existence of rational bubbles in the exchange market, we have evaluated the ratio of the nominal exchange rate to the relative prices of tradable and non-tradable goods. Based on the obtained results, the Iranian foreign exchange market has been experienced explosive behavior and multiple bubbles in the period of under study. Moreover, the relative prices of traded goods explain some explosiveness in the Iranian exchange market. Our findings suggest that the explosive behavior in nominal exchange rate from 2008:10-2008:12, 2012:01-2012:03 and 2013:09-2013:11 was because of rational bubbles in exchange rate and in other periods was driven by the relative price of tradable goods. Therefore, it is suggested to control the sharp exchange rate movements, in addition to bubbles, fluctuations in prices of traded goods market require more attention. Also, due to the possibility of bubbles repetition, the GSADF test is the better test to detect bubbles.

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Noise traders make decisions based on market sentiment and buy and sell assets based on unrelated information. These traders generally have poor timing, follow trends, and overreact to good or bad news. The experience of financial markets shows that noise traders cause excess volatility and deviation of the stock value from its intrinsic value. This study seeks to evaluate the role of noise traders on the occurrence of bubbles in the Tehran Stock Exchange in the period 2011 to 2017 .Therefore, the research hypothesis is: "The effect of noise trading on the occurrence of bubbles in the Tehran Stock Exchange is positive and significant." In this study, PCA method is used to extract a composite sentiment index, The GSADF method also is employed to determine the bubble periods of the Tehran Stock Exchange price index. Finally, the logit method is applied to measure the effect of noise trading on the bubble in the stock market price index. The results show that the effect of noise trading on the occurrence of bubbles is positive and significant. Also, the estimation of the final marginal effect indicates that the increase of one unit of optimistic sentiment and optimistic sentiment with a lag in the stock market increases the probability of bubbles by 24 and 28%, respectively.