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170–172) defined moving averages as transformations of a price series that allow us to identify trends from data smoothing.Īccording to Gerritsen ( 2016), the success of technical analysis trading rules would conflict with the weak form of the Efficient Market Hypothesis (EMH) (Fama 1970), which holds that current asset prices reflect all relevant past data. These indicators seek to estimate patterns of future behavior and predict buy and sell opportunities solely from the previously verified pricing of assets. Indicators include the Relative Strength Index (RSI), the Moving Average Convergence Divergence (MACD), and the Average Directional Index (ADX), among others. The tools used by TA can provide an index of resistance and support as well. The graphs reflect indicators, such as moving averages and oscillators, that allow analysts to detect trends, identify points of inflection in the price movement, and track capital inflows and outflows. 1–2), graphs are the primary instruments of TA. TA uses a systematic, graphical approach to identify patterns of historical trading prices and market movements, and then formulate predictions that may generate abnormally strong returns. The work presented in this paper updated the findings of previous research, and found that technical analysis can help fundamental analysis identify the most dynamic companies in the stock market. We demonstrated that this trading system, using technical analysis techniques, could surpass the profitability of a buy and hold strategy for a portion of the traded assets, calculated by country. To this end, we developed an automated trading system based on the moving averages of past prices. The goal of our research was to investigate the profitability of trading strategies based on TA in the stock markets of BRICS countries. Their study demonstrated that the duration of these standards is sufficient for the investor to make above-average profits, even if the investments incur transaction costs.
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( 2015), TA is a way of detecting trends in asset prices based on the premise that the price series moves according to investors’ perceived standards. The objective is to enhance the return of an investment portfolio by understanding the interaction of price indicators for the portfolio’s holdings over an identified time period. The basic principle of technical analysis (TA) is that patterns related to past prices of instruments traded in the asset markets can be used to predict the direction of future prices. We also found that technical analysis can help fundamental analysis identify the most dynamic companies in the stock market. The returns from the sample portfolio were very strong in Russia and India. There were groups of assets from each country that performed well above the portfolio average, surpassing the returns obtained using a buy and hold strategy.
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Our results showed that the returns obtained by the automated system, on average, exceeded the value invested. Our assessment updated the findings of previous research by including more recent data and adding South Africa, the latest member included in BRICS. We developed an automated trading system that simulated transactions in this portfolio using technical analysis techniques. To implement this research, we created a comprehensive portfolio containing the assets traded in the markets of each BRICS member. In addition, we searched for evidence that technical analysis and fundamental analysis can complement each other in these markets. In this paper, we investigated the profitability of technical analysis as applied to the stock markets of the BRICS member nations.