درخت حوزه‌های تخصصی

Out of 64 possible catastrophic events in the whole world, about 34 of them have been experienced in Iran; more than 80% of the regions are exposed to natural disasters risks such as earthquakes exposure. Domestic insurance capacity does not cover this volume of risk and the need for external reinsurance capacity is always felt. Catastrophe bonds structure as a financial & insurance innovative solution (Alternative Risk Transfer Instruments) allows an issuing institution to transfer catastrophic exposures and risk to capital market's investors by creating capital relief and additional risk capacity for our insurance industry. We adjusted the formal cat bonds structure with the Islamic jurisprudence. According to the systematic review research method 8 steps, the Sukuk model was implemented based on the extracted concepts from 23 Farsi articles and 50 English articles. After that interviews by 18 experts who were selected by purposive & Snowball sampling, The Delphi method was used to obtain the opinion of experts and their opinion was modified and implemented in the final model. In the open coding stage, 415 concepts were extracted which were classified into 10 categories and finally presented in 4 Propositions/themes. The trustworthiness and authenticity did base on the four-stage model of Lincoln and Guba and also its complementary step. We finally suggested that the catastrophe bond instrument could be issued in the form of a cat takaful (CT) sukuk contract template, as a solution for transferring catastrophic risks to the Islamic financial market.

The modeling of strategies for buying and selling in Stock Market Investment has been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Markov Switching models for forecasting the time series observations based on stock prices. The semi-parametric estimators for these models are a class of popular methods that have been used extensively by researchers to increase the accuracy of estimation. The main part of these estimators is based on kernel functions. Despite the existence of many kernel functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel in these estimators. But there is a question if other types of kernel function can be used in these estimators. This paper tries to introduce the other kernel functions that can be a good replacement for this kernel function to increase the ability of Markov Switching models. We first test six popular kernel functions to find the best one based on simulation studies and then offer the new strategy of buying and selling stocks by the best kernel function selection on real data.