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Using the Bollinger Bands trading strategy (BBTS), investors are advised to buy (and then sell) Bitcoin and Ethereum spot prices in response to BBTS's oversold (overbought) signals. As a result of analyzing whether investors would profit from round-turn trading of these two spot prices, this study may reveal the following remarkable outcomes and investment strategies. This study first demonstrated that using our novel design with a heatmap matrix would result in multiple higher returns, all of which were greater than the highest return using the conventional design. We contend that such an impressive finding could be the result of big data analytics and the adaptability of BBTS in our new design. Second, because cryptocurrency spot prices are relatively volatile, such indices may experience a significant rebound from oversold to overbought BBTS signals, resulting in the potential for much higher returns. Third, if history repeats itself, our findings might enhance the profitability of trading these two spots. As such, this study extracts the diverse trading performance of multiple BB trading rules, uses big data analytics to observe and evaluate many outcomes via heatmap visualization, and applies such knowledge to investment practice, which may contribute to the literature. Consequently, this study may cast light on the significance of decision-making through the utilization of big data analytics and heatmap visualization. [ABSTRACT FROM AUTHOR]

In the past, it was believed that investors may generate abnormal returns (AR) for trading stocks by employing technical trading rules. However, since the COVID-19 pandemic broke out, stock markets around the world seem to suffer a serious impact. Therefore, whether investors can beat the markets by applying technical trading rules during the period of COVID-19 pandemic becomes an important issue for market participants. The purpose of this study is to examine the profitability of trading stocks with the use of technical trading rules under the COVID-19 pandemic. By trading the constituent stocks of DJ 30 and NASDAQ 100, we find that almost all of the trading rules employed in this study fail to beat the market during the COVID-19 pandemic period, which is different from the results in 2019. The revealed findings of this study may shed light on that investors should adopt technical trading with care when stock markets are seriously affected by black swan events like COVID-19. [ABSTRACT FROM AUTHOR]

We explore whether investors would receive excess profits by round-turn trading (hereafter referred to as trading) Bitcoin futures based on Bollinger Bands trading strategy (BBTS). Since investors are suggested to first buy (then sell) Bitcoin futures as oversold (overbought) signals emitted by the BBTS (i.e. penetrating lower (upper) Bollinger Bands regarded as a buying (selling) signal), we aim to explore whether investors would have better returns by trading such futures according to the BBTS. Results show that the average holding period return (AHPR) is over 20% for trading Bitcoin futures following the BBTS. Furthermore, after we adjust the 60-day moving average (MA) instead of the 20-day MA for the BBTS, the AHPR is above 50%. It is noted that if the margin could be deemed as an investment amount, its rate of return would be much higher than the 50% for trading Bitcoin futures. [ABSTRACT FROM AUTHOR]

Since the yields of trading stocks are affected by numerous elements, this study aims to explore whether the profitability of trading stock with the use of technical trading rules, such as Stochastic Oscillator Indicators (SOI) and Relative Strength Index (RSI), would matter in the fourth quarter of the year. By employing the data of Dow Jones 30 (DJI 30) and NASDAQ 100 (NDX100) from 2011 to 2020 and from 1991 to 2020, this study reports that investors applying SOI and RSI would have higher cumulative abnormal returns (CARs) in Quarter 4 as compared with those in Quarters 1–3, respectively. The revealed findings indicate that the quarterly effect should be taken into account by investors when trading DJI 30 and NDX100, the representative indices for US stock markets. More importantly, this study may contribute to the existing literature due to the rare discussion of this interesting issue in the past research. [ABSTRACT FROM AUTHOR]

We explore the profitability of day trading Bitcoin futures following diverse consecutive 3 bullish (bearish) one-minute candlesticks and then adopt stop-loss or take-profit only as exits. We reveal that different from our cognition, adopting take-profit strategies would have a notable average positive profit per trade (APPT), which is robust by employing the upward trend out-of-sample data different from the downward trend in-sample data. We infer that such impressive findings might result from temporary rising (falling) prices likely manipulated for appealing to investors pursuing long (short) positions. As a result, investors may realize profit instead of suffering loss frequently by adopting take-profit exits since mean reversion might often occur after such manipulation. Moreover, we argue that stop-loss might be redundant for day trading such futures because stop-loss seems enclosed in the mechanism of day trading. [ABSTRACT FROM AUTHOR]