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OSCILLATOR STRATEGIES APPLICATION IN STOCK MOVEMENT PREDICTION ON THE RUSSIAN FINANCIAL MARKET: EFFICIENCY ISSUES
Resumo
Background: Technical analysis is one of the most frequently used by traders instruments. However, many of its elements (in particular oscillators) may show varying efficiency depending on the particular markets characteristics. Therefore, taking into account the distinctive features of the Russian stock market, it is reasonable to examine which oscillators can be effectively applied on it. Objective: The purpose of the study is to analyze the effectiveness of technical analysis indicators for forecasting shares of the Russian stock market and to develop the most effective trading strategy combining various oscillators. Methods: In order to achieve this, the selection of stocks suitable for testing and technical analysis indicators representing various groups is carried out. The accuracy and the total number of signals act as criteria for the indicators effectiveness, while accuracy is given the main attention. The interval from mid-2020 to mid-2021 is used for testing. Results: Based on the results obtained, the indicators are divided into efficiency groups; recommendations for the application of each oscillator are given. The result of the study is the development of the most effective strategies for the usage of technical analysis indicators that have passed the test. The strengths and weaknesses of each formed strategy are highlighted. Conclusion: The novelty of the research lies in obtaining the results of comparing the different types of technical analysis indicators effectiveness in the modern conditions of the Russian stock market and in building optimal strategies for their application.
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Abuselidze, G., Slobodianyk, A., & Reznik, N. (2019). Ensuring trading strategies profitability with technical analysis tools and computer technology. SHS Web of Conferences, 71(7), 04005.
Galanov, V.A., Kalinkina, K.E., & Galanova, A.V. (2017). K voprosu o dostovernosti rynochnoj ceny akcii dlya celej ocenki [To the question on the reliability of the market price of the action for the assessment purposes]. Property Relations in the Russian Federation, 3(86), 47-57.
Han, Y., Liu, Y., Zhou, G., & Zhu, Y. (2021). Technical analysis in the stock market: A review. SSRN Electronic Journal. https://dx.doi.org/10.2139/ssrn.3850494
Hauser, S., & Kedar-Levy, H. (2018). Liquidity might come at cost: The role of heterogeneous preferences. Journal of Financial Markets, 39, 1-23.
Horak, J., & Sulek, J. (2021). A basic technical analysis of shares on the example of a specific company. SHS Web of Conferences, 91(2), 01041.
Investment Company "FINAM". (n.d.). Retrieved from https://www.finam.ru (accessed November 15, 2021).
Lavrenova, E.S., & Ilina, T.G. (2020). A note on the predictability of the Russians stock market. Vestnik Tomskogo gosudarstvennogo universiteta. Ekonomika, 49, 160-182.
Ma, A.K.C., Chan, M.W.M., Poon, J.C.Y., & Yan, Y. (2013). Technical trading strategies with market impact. Investment Management and Financial Innovations, 10(2), 93-102.
Masry, M. (2017). The impact of technical analysis on stock returns in an emerging capital markets (ECM’s) country: Theoretical and empirical study. International Journal of Economics and Finance, 9(3), 91-107.
Moscow Stock Exchange. (n.d.). Retrieved from https://www.moex.com (accessed November 15, 2021).
Novikov, P.A., & Valiev, R.R. (2018). Hidden Markov models and neural networks in formation of investment portfolio. Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 160(2), 357-363.
Saibel’, N.Yu., & Koval'chuk, A.V. (2018). Fondovyj rynok Rossii: Problemy i perspektivy razvitiya [The Russian stock market: Problems and development prospects]. Finance and Credit, 3(771), 613-626.
Singh, J., & Khushi, M. (2021). Feature learning for stock price prediction shows a significant role of analyst rating. Applied System Innovation, 4(1), 17.
Snigaroff, R.G., & Wroblewski, D. (2018). An earnings, liquidity, and market model. Applied Economics, 50(57), 6220-6248.
Souza, M., Ramos, D., Pena, M., Sobreiro, V., & Kimura, H. (2018). Examination of the profitability of technical analysis based on moving average strategies in BRICS. Financial Innovation, 4, 3. https://doi.org/10.1186/s40854-018-0087-z
Stankovic, J., Markovic, I., & Stojanovic, M. (2015). Investment strategy optimization using technical analysis and predictive modeling in emerging markets. Procedia Economics and Finance, 19, 51-62.
Sturm, R.R. (2013). Market efficiency and technical analysis: Can they coexist? Research in Applied Economics, 5(3), 1-16.
Sulistiawan, D., Arni, F., & Feliana, Y.K. (2020). Examining trading strategies using trend following indicators for Indonesian stock market. International Journal of Trade and Global Markets, 13(1), 52-60.
Tolkachev, I.S., & Kotov, A.S. (2021). Pervichnyj analiz prigodnosti akcij dlya vklyucheniya v aktivnuyu torgovuyu strategiyu [The initial analysis of the share suitability for the inclusion into an active trading strategy]. Scientific Research and Development. Economics of the Firm, 4(37), 80-89.
TradingView. (n.d.). Retrieved from https://ru.tradingview.com (accessed December 18, 2021).
Vorobyov, Yu.N. (2017). Fondovyj rynok Rossijskoj Federacii: Sostoyanie i perspektivy [Stock market of the Russian Federation: State and prospects]. Scientific Bulletin: Finance, Banking, Investment, 1(38), 111-126.
DOI: http://dx.doi.org/10.21902/Revrima.v4i37.6089
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Revista Relações Internacionais do Mundo Atual e-ISSN: 2316-2880
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