Trading (and Cryptocurrency Trading) with the Help of Artificial Intelligence
There are two ways to think about AI’s role in cryptocurrency trading. The first role is seeing AI as a tool that investors can use to trade smarter, to trade faster, and to trade based on more data. The second role is related to the first, but not necessarily in a good way – AI could potentially shrink the size of the asset management/hedge fund business, by taking the jobs of thousands of data crunchers and analysts who would technically no longer be needed. By some estimates, AI is set to replace 90,000 asset management jobs and 45,000 sales and trading jobs by 2025.
Let’s start with role #1 – AI being a revolutionary tool to help investors trade. There is already evidence showing that hedge funds that have integrated AI into their trading platforms have seen a boost in performance. To give one example, the hedge fund Renaissance Technologies has integrated AI into their platform and has seen dramatic results. Their Medallion Fund is a prime example, as it has delivered positive returns between 20% – 98% from 2002 to 2016. During the 2007-2008 financial crisis, the Medallion Fund delivered annual returns of 85.8% and 98.2%, respectively, which is nothing short of remarkable performance given the S&P 500 was down over 40% during the same period.
This is great news for hedge funds, but what about retail investors? Until recently, retail investors have not had easy access to Artificial Intelligence or algorithms to analyze data or furnish trading ideas. The landscape is changing quickly, however. Tickeron is one of the first – if not the first – company to offer AI to the retail investor. They have developed algorithms that can scan the market to identify patterns and trends, and the AI will deliver backtested statistics, target prices, and trading ideas right into investors’ inboxes.
But that’s not all. Investors can also customize the AI tools to search for specific asset classes like stocks or cryptocurrencies, and can also tweak the settings to look for certain types of technical trading patterns and “confidence levels” for the AI. Indeed, the AI has some trades it is more confident about than others, based on how good the data is.
The second role for AI is as a super analyst within hedge funds and asset management firms. Back in the old days (not really that long ago, actually), traders physically went onto the trading floors to buy and sell stocks, bonds, and commodities, and maybe from time to time rebalance their portfolios. That was that.
Today, high frequency trading and a constant flow of information make hedge funds and asset managers much nimbler in their trading strategies, which much more dynamic investment strategies. Fueling these new trading strategies is AI, with computers and machine learning applications that can consume mountains of data and help managers execute precise trades. AI helps these shops trade in conventional securities and has helped add liquidity to the equity markets, and many think it will soon bring all of the same benefits to the cryptocurrency world as well.
With these developments in the hedge fund space, we once again arrive at the question – what about the retail investor? Will he or she also have access to AI for cryptocurrency trading? The answer is similar to the one I gave earlier: Tickeron is developing the technology to give retail investors access to AI for trading in cryptocurrency markets. Will you be a part of it?
Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
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