خلاصة:
The present study models the risk of investment in the petrochemical industry considering the impacts of exchange rate (US dollar to Iran''''s Rial) movements using the time series data from November 2008 to March 2019 and ARFIMA-FIGARCH framework. The empirical results prove the existence of the Fractal Market Hypothesis, FMH, and the Long Memory property in both the risk and return of the petrochemical stock index. These findings can be culminated in reaching a reliable and significant model to evaluate the investment risk in the petrochemical industry. In line with this, to analyze the idea whether considering the exchange rate movements matter for assessing the risk management in the petrochemical industry, the effects of exchange rate movements as a crucial source of systematic risk in Iran has been taken into consideration in the process of modelling the risk of investment in that industry. Our results demonstrate that the exchange rate movements have had a direct and significant effect on the investment risk of that industry so that if, on average, one percent change occurs in the exchange rate, the investment risk in this industry changes by 57% in the same direction.
ملخص الجهاز:
ARTICLE INFO ABSTRACT Abstract>The present study models the risk of investment in the petrochemical industryconsidering the impacts of exchange rate (US dollar to Iran's Rial) movements using the time series data from November 2008 to March 2019 and ARFIMA- FIGARCH framework.
The empirical results prove the existence of the Fractal Market Hypothesis, FMH, and the Long Memory property in both the risk and return of the petrochemical stock index.
On this basis, analyzing the FMH and EMH hypothe- ses; consequently, considering long-memory features through a non-linear framework, can en- hance the accuracy and efficiency of the model base on which the investment risk in petrochem- ical industry should be extracted.
4. 3 ARFIMA-FIGARCH Model As stated earlier, in order to model the investment risk in the petrochemical industry, and analyze the effects of exchange rate on it, the ARFIMA-FIGARCH model is used, which, in addition to its significant reliability in modelling the risk of high-volatile data, its capability to consider the essential characteristics of financial markets, long memory feature, is noteworthy.
Furthermore, in analyzing the effects of exchange rate as one of the most important factors of systematic risk and based on the results of estimated coefficients, it should be stated that, these impacts are consistent with empirical evidence in this field (which is con- sistent with the results of some other studies such as Zolfaghari and Sahabi [54]; Šimáková [47]; Ghosh [19]; Bernhofen and Xu [7]).