Determining the most efficient technical indicator of investing in financial markets based on trends, volume, momentum and volatility

In this paper, we investigate the most efficient technical indicator of the top five selected indicators of investing in financial markets. The indicators are based on a trend on the entire market, volume in each time period, momentum, and volatility of the financial instruments, e.g. Bollinger Bands, SMA, EMA, VWAP, MACD, RSI respectively. Our primary focus is on financial markets of the United States; however, our research findings can be applied to any index throughout the world. This dissertation strongly supports the idea of utilisation of technical analysis to have an edge while trading on financial markets. This paper uses IXIC (NASDAQ Composite Index) and SPY (SPDR S&P 500 ETF Trust) data concerning the period from 2000 to 2020. To empirically test the predictability of these indicators, however, we used the time spans of 2007–2008 and 2019–2020. Due to the economic recession and the COVID-19 pandemic in the respective periods, the time is suitable for testing our indicators because of comparatively higher volatility on the markets. Advanced econometrics (time series) models are used to fit the data and to make price predictions. ARFIMA along with GARCH are the best fitted models for both time series.