From Google Home to Alexa, the role of artificial intelligence (AI) seems to have grown over the years. It is now believed that AI will play a bigger role when it comes to cryptocurrencies traded. “As more financial institutions start offering cryptocurrencies as a wealth management offering, the roles of AI-supported trading will become more popular. There are over 4,000 cryptocurrencies, and even older coins show large fluctuations in their prices. Likewise, Bitcoin’s 30-day volatility index is double its 2016 value (according to data published on buybitcoinworldwide), “Saurav Raaj, founder and director of Wize, an infrastructure of non-fungible tokens (NFT) for companies. .
According to industry observers, AI is used in smart trading systems for stock market forecasting and currency price prediction. According to a report from IEEE Access, generalized autoregressive conditional heteroskedasticity (GARCH), is a statistical time series model used to understand volatility. “AI is in the area of market sentiment analysis. Unlike traditional stocks, discussions between trading communities and social media reports can guide trading decisions. Artificial intelligence with natural language processing (NLP) can analyze market and community sentiments and provide valuable insights to traders, ”added Raaj.
Courtesy: IEEE Access, ResearchGate.
It is believed that the trading decision is usually based on behavioral biases that lead them to act on an emotion that could lead to errors when processing information. “AI-driven cryptocurrency trading is unlikely to eliminate emotional factors, it is likely to amplify it via machine learning. A deliberate solution in AI programs to avoid trading with large corrections and spikes can However, it is also likely to slow down the usual stop-loss or take-profit exercise, “said Liquing Yu, an analyst in the Economic Intelligence Unit (EIU) for India, Indonesia and Singapore.
Additionally, industry experts have noted that when properly implemented and trained, AI can help eliminate human bias. According to Vikram Pandya, director, Fintech, SP Jain, it definitely helps to make scientific decisions supported by data and not by impulses.
According to the June 2019 Business Insider Report, there are three areas where AI is used in the banking industry, namely, conversational banking, fraud detection, risk assessment, and credit underwriting. AI-based systems can help process trading data which can help traders make better investment decisions. “Artificial intelligence with machine learning (ML) can provide safeguards against such attacks and reduce damage in real time. In extreme cases, it can be used to trigger automatic switches and even interrupt trades,” added Raaj.
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