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    Estimating Return Rate of Blockchain Financial Product by ANFIS-PSO Method
    (Springer International Publishing Ag, 2022) Birim, Sule Ozturk; Sonmez, Filiz Eratas; Liman, Yagmur Saglam
    Today, blockchain technology is developing rapidly and the volume of blockchain financial product trading is increasing rapidly as well. The aim of this study is to predict the return rates of cryptocurrencies with the help of artificial learning applications, considering the complex and unstable structure of the financial system. The rate of return is one of the important criteria used for investment decisions. Therefore, an efficient method for return rate prediction will help investors in preparing their portfolios. Ethereum, one of the top three most traded cryptocurrencies in the world, was chosen for empirical analysis. The adaptive neuro-fuzzy inference system approach (ANFIS) has emerged as a method that has been frequently used in recent years. ANFIS uses optimization algorithms to obtain the best prediction performance based on neural network modeling. The ANFIS approach has a multilayered structure consisting of many nodes inside and connections between the layers. ANFIS retains the properties of a fuzzy system while applying the principles of a neural network. Computations in the layers are conducted to learn and reproduce the information of the system. In this study, the particle swarm optimization (PSO) algorithm is used to train the ANFIS network. PSO aims to find the best-performing model in predicting the prices of three major cryptocurrencies that are Bitcoin, Ethereum, and Tether. The prediction accuracy of the proposed models was checked on the test set with performance indicators of root mean squared error (RMSE) and mean absolute percentage error (MAPE). The ANFIS-PSO approach gives strong results in cryptocurrency rate of return estimation.
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    Öğe
    The Relationship Between Financial Development And Economic Growth: Evidence From European Transition Economies
    (Eskisehir Osmangazi Univ, Fac Education, 2017) Saglam, Yagmur; Sonmez, Filiz Eratas
    The main purpose of this paper is to investigate the relationship between financial development and economic growth, based on European transition economies. For this purpose we used Barro (1991) type growth model which claimed that finance is a key to economic growth. The model includes real gross domestic product (GDP) and composite index of financial development (FD). At the empirical model, scope of the panel data analysis, primarily the heterogeneity of variables were investigated and then the cross-section dependency was examined. Also, stability of the series was tested with the second-generation unit root tests. After the existence of the co-integration relationship between the series, long term regression parameters were examined. According to the empirical results, in the long term, it is expected that there is a one way relationship from financial development to growth.