Financial Economics
Reza Taleblou; Parisa Mohajeri; Abbas Shakeri; teymoor mohammadi; zahra zabihi
Abstract
Achieving the correct insight into the structure of connectedness and the spillover of volatilities between different stock exchange industries plays an important role in risk management and forming an optimal stock portfolio. Also, the analysis of inter-sectoral connectedness helps policy makers in ...
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Achieving the correct insight into the structure of connectedness and the spillover of volatilities between different stock exchange industries plays an important role in risk management and forming an optimal stock portfolio. Also, the analysis of inter-sectoral connectedness helps policy makers in designing policies that stimulate economic growth and implementing preventive measures to curb the propagation of systemic risk. In this regard, this article tries to use the data of 3370 trading days during the period of 1388/07/01 to 1402/06/31, encompassing 20 stock market industries (which constitute more than 80% of the Iranian stock market) and applying the connectedness approach based on the vector autoregression model with time-varying parameters (TVP-VAR), to estimate the systemic risk and volatility connectedness of the stock market network. In addition, we implement the minimum connectedness approach in the optimal stock portfolio and compared its performance with two other conventional approaches. The findings reveal that, first; the systemic risk in Iranian stock market is significant and has reached unprecedented figures of 80% in the last three years. Second, the four major export industries (petrochemicals, metals, mining and refining) experience the strongest pairwise connectedness, and among them, base metals appear as one of the most important transmitters of volatilities to the entire stock network. Thirdly, the stock portfolio based on the minimum connectedness method, compared to the minimum variance and minimum correlation methods, shows a better performance based on the criteria of cumulative return and hedge ratio efficiency.
Parisa Mohajeri; Zahra Zabihi; Sahar Sadeghi; Ziba Eghtesadi
Abstract
Since the introduction of supply-use input-output model by the United Nations in its 1968 SNA, there has been a controversy on choosing the most appropriate technology assumption for estimating symmetric product by product input-output table. These arguments have focused on two technology assumptions; ...
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Since the introduction of supply-use input-output model by the United Nations in its 1968 SNA, there has been a controversy on choosing the most appropriate technology assumption for estimating symmetric product by product input-output table. These arguments have focused on two technology assumptions; the product technology assumption (PTA) and the activity technology assumption (ATA). The PTA states that each product has a unique input structure that is independent of producing industry. In contrast, the ATA is defined as each activity has its own specific way of production, irrespective of its product mix. Each assumption has its own advantages and disadvantages. Because of ATA’s inconsistency with some fundamental economic theories, “Product Technology” assumption is more widely applied for calculating symmetric product-by-product input-output table. In this paper, we show that only PTA fulfills the four desirable properties (material balance, financial balance, scale invariance and price invariance) which are introduced by Jansen and ten Raa (1990) but ATA fulfils only one of them. This result can be used by compliers and users in choosing the appropriate economic assumptions for deriving symmetric input-output tables.
