Forecasting of Turkish Sovereign Sukuk Prices Using Artificial Neural Network Model

Recently, artificial neural networks have been successfully applied in many areas such as forecasting financial time series, predicting failure, and classification of ratings. However, it has hardly sukuk prices, which is considered the most common Islamic capital market instrument. Since a new asset, there are not enough studies this area. Therefore, study aims to forecast Turkish sovereign prices using with network model reveal determinants prices. For purpose, multi-layer feed forward designed dollar-based international price data issued by Ministry Treasury Finance. The dollar index, volatility geopolitical risk Standard Poor’s Middle East North Africa Eurobond constituted input variables formed output. As result, were forecasted accurately at success rate 99.98%. accurate will play critical role reducing perception investors increasing their profitability. findings important terms proving that an effective for revealing MENA