Comparative analysis of investor sentiment with weather conditions using interval type 2 fuzzy hybrid decision making and regression methods: Evidence from chinese stock markets
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CitationHsiao, Hsiao-F., Xia, C., Yüksel, S. ve Dinçer, H. (2020). Comparative analysis of investor sentiment with weather conditions using interval type 2 fuzzy hybrid decision making and regression methods: Evidence from chinese stock markets. Economic Computation and Economic Cybernetics Studies and Research, 54(3), 263-278. https://dx.doi.org/10.24818/18423264/22.214.171.124
This study investigates the local weather effects on investor sentiment as well as returns in the China's stock market. For this purpose, a comparative evaluation is performed by making both econometric analysis and fuzzy logic-based examination. In the first stage, in the second stage, interval type 2 (IT2) fuzzy DEVIATEL and TOPSIS methods are used respectively for evaluating the performance of stock markets in the selected provinces of China. On the other side, linear regression analysis is made to reach this objective. In this framework, stock returns of China A -shares for the period of 1 January 2011 - 31 December 2017 are taken into consideration. The results of these two different analyses are quite consistent. The findings indicate that investors feel more optimistic about stocks and are more inclined to invest when sunlight is stronger. In addition to this issue, it is also concluded that investors are more inclined to invest in local stocks because of home bias and this situation leads to increase in the local stock market returns. Therefore, in bad weather, it would be appropriate to receive incentives to facilitate investors to trade on the stock exchange. For example, it is important to take measures to reduce the problems of investors' motivation, such as inaccessibility of session rooms and slow delivery of orders.