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Information Journal Paper

Title

INTRODUCING AN EARLY WARNING SYSTEM FOR HIGH VOLATILITY IN TEHRAN STOCK EXCHANGE: MARKOV SWITCHING GARCH APPROACH

Pages

  27-40

Abstract

 The goal of this paper is to introduce a new model to predict the high VOLATILITY of TEHRAN STOCK EXCHANGE. For do it, a MARKOV SWITCHING GARCH models was modeled. With Estimating this model, the transition probability matrix of two states of high and low VOLATILITY, was calculated. Using this matrix, we can forecast the probability of market fluctuations in the each period ahead and we can obtain a suitable model for forecasting high VOLATILITY. According to the model selection criteria consist of AIC and BIC, the Markov regime switching GARCH model with GED distribution is the best model for forecasting VOLATILITY in TEHRAN STOCK EXCHANGE. Based on this model, in this paper, an EARLY WARNING SYSTEM has been introduced in TEHRAN STOCK EXCHANGE. This model can be used for policy makers to prevent the occurrence of high VOLATILITY and to increase the security of investors in TEHRAN STOCK EXCHANGE.

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    APA: Copy

    NADEMI, YOUNES, ABOUNOORI, ESMAEIL, & ELMI, ZAHRA. (2016). INTRODUCING AN EARLY WARNING SYSTEM FOR HIGH VOLATILITY IN TEHRAN STOCK EXCHANGE: MARKOV SWITCHING GARCH APPROACH. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), 8(28), 27-40. SID. https://sid.ir/paper/200221/en

    Vancouver: Copy

    NADEMI YOUNES, ABOUNOORI ESMAEIL, ELMI ZAHRA. INTRODUCING AN EARLY WARNING SYSTEM FOR HIGH VOLATILITY IN TEHRAN STOCK EXCHANGE: MARKOV SWITCHING GARCH APPROACH. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)[Internet]. 2016;8(28):27-40. Available from: https://sid.ir/paper/200221/en

    IEEE: Copy

    YOUNES NADEMI, ESMAEIL ABOUNOORI, and ZAHRA ELMI, “INTRODUCING AN EARLY WARNING SYSTEM FOR HIGH VOLATILITY IN TEHRAN STOCK EXCHANGE: MARKOV SWITCHING GARCH APPROACH,” FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), vol. 8, no. 28, pp. 27–40, 2016, [Online]. Available: https://sid.ir/paper/200221/en

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