USING BROWN’S MODEL FOR STOCK PRICES FORECASTING

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USING BROWN’S MODEL FOR STOCK PRICES FORECASTING

Journal Title: Проблеми системного підходу в економіці - Year 2018, Vol 1, Issue 63

Abstract

In the conditions of our country’s economic turbulence, owners, when creating a company, have certain risks associated with the likelihood of its value decrease. The purpose of study in this article is method development for Brown’s model using for stock prices forecasting. In January 2018, the growth of trading volumes at PJSC “PFTS Stock Exchange” was recorded. Compared to the same period of 2017, the value of exchange contracts increased by 12.9% and amounted to 6388.94 million UAH. In total, 698 contracts were concluded by the stock exchanges (+ 13.5%). In January 2018, the value of the PFTS Index increased by 6.40% to 335.24 points. Today Markowitz, Sharpe, and Quasi-Sharpe models are used for stock portfolio optimization. The Markowitz model should be used with the stable state of the stock market. The main disadvantage of the model is that the expected stocks’ yield is assumed to be equal to the average return on the basis of past periods data. When considering a large number of stocks, Sharpe model is used. The main drawback of the model is the need to forecast the yield on the stock market and the risk-free rate of return. The risk of risk-free returns fluctuations is not taken into account. In addition, with a significant change in between risk-free yield and stock market yield ratio, the model gives a bias. Since the capitalization of the company is closely linked to the market shares price, share price forecasting is a relevant task. This is especially important in short-term forecasting, under rapidly changing external conditions. Brown and Holt’s adaptive models are used for forecasting. Forecast for Brown’s linear models for MSFT share rate for 2 months was built. Projected stock price forecasts are calculated in a similar way for other American and Ukrainian companies. The error between real and predictable data is equal to 2.3%, therefore, it can be stated that the model fully satisfies the goal. This article analyses the existing methods of securities portfolio forming. Brown’s model is analysed for short-term forecasting of stock prices, under rapidly changing external conditions. An example of Brown’s model using is provided for Microsoft share price forecast. Brown’s model was used to predict Ukrainian enterprises, in particular, Kyivenergo and Avdeyevka Coke Plant. It should be noted that the calculation error for American companies is 2.3%. For Kyivenergo company – 1.43%. The analysed error between real and predicted data makes it possible to assert that Brown’s model gives precise results.

Authors and Affiliations

O. V. Tsesliv, D. S. Zinchenko

Keywords

capitalization of the enterprise share market value of shares modelling optimization of portfolio of securities Brown’s model

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EP ID EP562055
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