Academic journal article Business: Theory and Practice

EMA versus SMA Usage to Forecast Stock Markets: The Case of S&P 500 and OMX Baltic Benchmark/Eksponentinio Ir Paprasto Slankiojo Vidurkio Naudojimo Lyginimas Prognozuojant Akciju Rinkas: S&P 500 Ir OMX Baltic Benchmark Atvejis

Academic journal article Business: Theory and Practice

EMA versus SMA Usage to Forecast Stock Markets: The Case of S&P 500 and OMX Baltic Benchmark/Eksponentinio Ir Paprasto Slankiojo Vidurkio Naudojimo Lyginimas Prognozuojant Akciju Rinkas: S&P 500 Ir OMX Baltic Benchmark Atvejis

Article excerpt

1. Introduction

At the period of economic instability financial market players suffer large losses. Everyone expects the financial markets, especially stock markets, to rise. Financial crisis of 2009 showed the investors' belief that the stock value will raise and never fall led to the bear market cycle.

Nowadays econometric science permits to apply its rules for the stock market forecast process, so investors can predict stock prices, the direction of the index trend, etc. but not all methods are efficient. One of the methods widely used by investors is technical analysis which uses the historical prices of a financial instrument to indicate the future behaviour of prices. Technical analysis consists of a number of specific methods and is opposite to fundamental analysis principles. The moving average method is generally used over several last decades. The specific moving averages like simple moving average, exponential moving average, etc. can provide different results predicting the stock market prices. It is necessary to find out which method is more accurate and more efficient. Previous researches show that indexes of Baltic States stock exchange were never tested although traders in Estonia, Latvia and Lithuania use different software based on technical analysis methods to predict the future stock prices. So it is necessary to make suggestions for those traders who prefer to trade not only in US markets but in Baltic markets too. The main research paper target is to compare Technical Analysis rules--Simple Moving Average and Exponential Moving Average application possibilities to forecast different stock markets: S&P 500 and OMX Baltic Benchmark Index. The main method to compare forecast rules is systematic error evaluation system which helps to estimate bias and to decide whether method is appropriate to forecast the stock market. The results can influence present investment forecast techniques and help to find out which method usage is more appropriate for each stock market.

2. Literature review on technical analysis issue

The moving average method is one of the most widely used methods of technical analysis (TA). Technical analysis can be described as the various stock market forces interactions and their impact on share prices survey. Technical factors related to stock market conditions are focused on price changes, market volume, the demand and the supply of the stocks (Norvaisiene 2005). Growing stock market and rising activity of the investors attract more increasing attention (Dudzeviciute 2004). Technical analysis involves making investment decisions which are based on past price movements and this method is very popular with the investment community (Taylor, Allen 1992). Edwards and Magee (1992) imply that moving averages can be classified as simple moving average (SMA), weighted moving average (WMA) or exponential Moving Average (EMA) and linear moving average (LMA). They concluded, that SMA can work properly as well but more complicated MA is more useful using computer to make the forecast. Exponential smoothing method (EMA) is relatively easy to use and requires a small number of historical data. When the smoothing constant is chosen then only two items of data are required to calculate forecasts. Marshall et al. (2007) and academia concluded that the return in stock markets can be predicted but the traders cannot profit from this forecast of return. Hartmann et al. (2008) imply that investors are able to forecast stock market and the return in real time. Technical Analysis supporters use gathered historical data and on these bases make charts (Weller et al. 2009). Girdzijauskas et al. (2009) have found out that the exponential growth models are more suitable for the modelling processes in the near future. Plummer (1989) states, that technical analysis rules have been used in financial markets for over a century. Early studies (Alexander 1964; Fama, Blume 1966) tested some TA strategies using equity index data. …

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