AI: a cost-effective strategy for the equity market’s continued growth
Profit is typically the main objective of trading. Statistical data-based technical analysis and decision-making are integral parts of its process. Humans can analyze data and look for market trends, but technology like artificial intelligence is also more capable of doing this work.
For instance, institutional investors have been using trading robots with an emphasis on monitoring price fluctuations for years: A JPMorgan study from 2020 found that over 60% of deals surpassing $10 million were carried out using algorithms. The algorithmic trading market’s overall volume is anticipated to reach $19 billion by 2024, up $4 billion from the current level.
The dynamics are far more crucial to pay attention to than the numbers, which appear to be big.
Why are trading robots and algorithms being used by market participants more frequently? Can AI perform additional tasks for various market participants, such as retail investors, some of whom have only recently started trading?
The markets overcame significant obstacles on a global scale and grew for a number of reasons over the past few years:
- The COVID-19 epidemic has caused an increase in distance work: The Bureau of Labor Statistics estimates that there were 10.8 million unemployed persons in the fourth quarter of 2020, which is 4.9 million higher than there were at the end of 2019. Many of them began looking for alternative means of support.
- A significant influx of new traders using different online trading platforms has been caused by increased telecom and internet connectivity globally.
- Trading, especially through mobile apps, was made available to everyone due to high market liquidity and low transaction costs.
The entire stock volume from US individual investors, however, decreased from 24% to 19% by Q3 2021, according to Bloomberg. The requirement for more time-sensitive research and market situation monitoring tools, along with increasing market volatility, are likely contributing factors to this.
The entry barrier must be reduced if new traders are to be attracted. The features and usefulness of a trading platform, along with the trader’s understanding of the market and the amount of time needed for research, can all affect how successful a rookie trader is.
As a result, a broker gains a competitive advantage by cutting down on the amount of trading time or required competence.
Standalone trading robots assist in copying and maintaining user-defined strategies to save time for critical traders.
If it takes into consideration the most recent market happenings, the creation of personalized current instructional content can also be advantageous. Brokers may make it simpler by utilizing generative language model solutions, which use AI to create original material based on trader interests.
Participants in the retail business have also taken notice of the rapid growth of AI. Both seasoned and novice traders in the financial markets have probably seen instances where AI outperforms humans at particular jobs.
However, having the right tools is crucial, especially for retail trading, since they not only increase the likelihood of profit but also lower the chance of failure. Thanks to revolutionary AI technology, they can easily analyze enormous amounts of data, track performance in real-time, and eventually make better trading decisions.
And as we have seen, AI enables the release of even bigger datasets from structured resources. It also potentially releases resources from unstructured collections like social media. For instance, technical analysis tools powered by artificial intelligence (AI) are being utilized to generate stock ratings, including buy/sell/hold indicators based on previous performance suited to sector and industry benchmarks. Others share their perspective on price objectives, projections, and peer evaluations.
Although AI won’t be the “silver bullet” in every situation, its use has already improved data collecting and usage, which will continue to help forecast and detect more pertinent market trends become more accurate. The progressive growth of trading platforms powered by automation and artificial intelligence will fuel a rise in market participation in the long run.