Day traders, who trade over time horizons
of one day or less, account for around 30% of the total transaction volume at
present. Most day tradersí trading strategies are based on their own experiences
or news headlines. They may also rely on technical indicators, such as the
Relative Strength Index (RSI), to predict short-term trading opportunities and
stock index turning points for making selling and buying decisions with respect
to stock index futures. This study determined exact RSI indicators, which
enhanced the accuracy of short-term stock index prediction. We then tested the
proposed modelís performance during an unprecedented crisis such as COVID-19.
We used artificial intelligence techniques, such as the SMO algorithm, to
evaluate the performance of the proposed model and apply empirical methods on
short-term stock index futures datasets to explore the impact of different RSI
indicators on the turning points of the stock index futures. The results show
that RSI 20 based on regular and COVID-19 periods can enable day traders to
achieve higher profits compared to the RSI 30 index.
Keywords: Day traders, Relative
strength index, Short-term investment, Artificial intelligence, COVID-19.