Is There a Weekend Effect? Russian Stock Market Research Based on Fuzzy Systems

HSE Economic Journal Pub Date : 2023-01-01 DOI:10.17323/1813-8691-2023-27-3-412-434

V. Sviyazov

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引用次数: 0

Abstract

The problem of volatility forecasting with and without consideration of weekly seasonality effect (the weekend effect) is examined in this research. The question of the seasonality existence is understood in the following sense: do models, which incorporate seasonality, feature better forecasts? The fuzzy GARCH model, which accounts for a weekly seasonality effect is presented in the paper. This model is based on the ordinary GARCH model but allows for the use different dependences in different clusters (both of volatility and seasonality), as well as for the so-called soft switching between the clusters. The suggested method is applied to two indices, which can be deemed as indicators of the Russian stock market condition. The indices are the MOEX Russia Index and the RTS Index. The proposed model is challenged against a fuzzy model without seasonality and a classic GARCH model. The conducted calculations suggest that there is no significant improvement of a forecast if a seasonality is embedded into the fuzzy GARCH model. Fuzzy models show comparable results with regards to the conventional autoregressive conditional heteroskedasticity model. Thus, fuzzy models can be used along with traditional models, however day of the week consideration doesn’t yield a greater quality of volatility forecasts, at least on the samples used. The fuzzy GARCH model may be useful for financial risks estimation and for evaluation of the Value at Risk metric in particular.

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周末效应存在吗?基于模糊系统的俄罗斯股票市场研究

本文研究了考虑周季节性效应(周末效应)和不考虑周季节性效应的波动率预测问题。季节性存在的问题可以从以下意义上理解:包含季节性的模型是否具有更好的预测?本文提出了考虑周季节性影响的模糊GARCH模型。该模型基于普通GARCH模型，但允许在不同的集群中使用不同的依赖关系(波动性和季节性)，以及所谓的集群之间的软切换。将所提出的方法应用于两个指数，这两个指数可以看作是俄罗斯股市状况的指标。这些指数是MOEX俄罗斯指数和RTS指数。该模型与不带季节性的模糊模型和经典GARCH模型进行了比较。所进行的计算表明，如果在模糊GARCH模型中嵌入季节性因素，预测结果不会有显著改善。模糊模型与传统的自回归条件异方差模型具有可比性。因此，模糊模型可以与传统模型一起使用，但是考虑一周中的哪一天并不能产生更高质量的波动率预测，至少在使用的样本上是这样。模糊GARCH模型可用于财务风险估计，特别是对风险值度量的评价。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

HSE Economic Journal Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)

CiteScore

1.10

自引率

0.00%

发文量

期刊介绍： The HSE Economic Journal publishes refereed papers both in Russian and English. It has perceived better understanding of the market economy, the Russian one in particular, since being established in 1997. It disseminated new and diverse ideas on economic theory and practice, economic modeling, applied mathematical and statistical methods. Its Editorial Board and Council consist of prominent Russian and foreign researchers whose activity has fostered integration of the world scientific community. The target audience comprises researches, university professors and graduate students. Submitted papers should match JEL classification and can cover country specific or international economic issues, in various areas, such as micro- and macroeconomics, econometrics, economic policy, labor markets, social policy. Apart from supporting high quality economic research and academic discussion the Editorial Board sees its mission in searching for the new authors with original ideas. The journal follows international reviewing practices – at present submitted papers are subject to single blind review of two reviewers. The journal stands for meeting the highest standards of publication ethics.