On January 27, 2016, AlphaGo, an artificial intelligence robot developed by Google's DeepMind company, defeated a professional Go player for the first time without handicap. After successively defeating South Korean champion playerLee Sedol, Chinese champion player Ke Jie, and a team of five world Go champions, AlphaGo became famous.
Whether AlphaGo can represent the development direction of intelligent computers is still controversial, but its appearance at least shows that computer technology has entered the era of new information technology. The big data, big calculations, and big decisions behind AlphaGo are subtly reducing the gap between it and human intelligence.
As the frontier of new technologies, the blockchain field includes many emerging computer technologies. In addition to the professional and huge underlying technology construction, the blockchain services that users can most intuitively experience are its various applications at the basic level. In the field of blockchain, various transaction forms and functions are also extensive applications of new computer technologies.
AlphaGo in the crypto industry: AI quantification
In traditional trading, people are accustomed to formulating trading strategies based on past trading experience or habits, which seems reasonable; but the market is constantly changing, and personal “databases” are inevitably not comprehensive enough. Coupled with the dominance of the market's “hidden power”, the original confident trading strategy cannot maintain a stable trading winning rate.
Generally speaking, when the market conditions are stable, subjective trading strategies can often play a good role, but when encountering market sentiment fluctuations or unilateral market conditions, traders’ strategies will be affected by many factors, which will eventually lead to Loss of revenue. People can feel who is buying and selling in the market, but it is difficult to follow the known trading rules, especially the influence of FOMO sentiment, and then make mistakes in trading strategies.
Compared with traditional transactions, AI quant is like AlphaGo in the crypto industry can give high winning rate and earing rate.
AI quantification, generally also called automated trading, refers to the use of advanced technical models to replace human subjective judgments, which greatly reduces the impact of investor sentiment fluctuations, and avoids making non-determinisms when the market is extremely enthusiastic or extremely pessimistic. In the field of digital currency, there are many ways of quantitative trading, such as cross-platform arbitrage, trend trading, hedging, grid trading, etc.
As a frequently used trading form of quantitative trading, grid trading is quite representative. To put it simply, it is a short-term trading method that uses a grid to capture price fluctuations. As long as the price touches the grid, it automatically buys or sells a certain amount of digital currency. These are based on the model. The trading method for decision-making based on operating results has the characteristics of discipline, system, arbitrage, and probability of winning. It is a sign of a mature trading market.
Supercomputer VS professional trader
The job of a trader is exciting. Professional traders often desire volatility because they cannot make money without volatility, or they cannot use their talents as a professional trader. They have extremely high trading literacy. At the same time, different traders also have different styles. Some are based on stable returns, and some prefer risky investments.
However, the lack of high-quality trading strategies, the inability to capture the trading market in a timely manner, and the inability to maintain stable trading income for a long period of time affect the trading psychology of traders all the time, which prevents them from always focusing on trading strategies, and the turbulent trading market is also It will not leave them too much breathing time, which is obviously not feasible in terms of long-term investment.
The emergence of quantitative trading has just solved this dilemma. Traders can use this mathematical model tool to easily formulate trading strategies, thereby realizing considerable trading benefits. This is mainly because it effectively avoids human prejudice when formulating and implementing trading strategies, and can still reap higher returns without being affected by people's subjective consciousness.
Quantitative trading also has potential risks, such as being vulnerable to network interruptions, lack of risk control measures, and incomplete historical data. Fortunately, the above shortcomings are not stubborn problems. A high-quality trading platform with a good network and technical support can effectively avoid these shortcomings.
How to play AI quantitative strategy on Gate.io
Gate.io's online quantitative trading center is intended to help users easily realize quantitative trading of digital assets, providing a large library of quantitative strategies for novices and professional users; at the same time, it can also help users use various quantitative models to strictly automate, stabilize and program It can overcome the cognitive bias caused by manual judgment.
At present, Gate.io's AI quantitative strategy system includes two strategic areas; grid trading and CTA signal tracking, as well as practical functions such as one-click copy trading and data backtesting.
Grid trading is divided into spot grid and contract grid, and the total investment has exceeded 900 million US dollars. AI Smart Grid is back-tested based on historical data of the past 7 days, and automatically calculates the grid parameters with the highest return rate: upper limit price, lower limit price, and number of grids. Users only need to select the proportion of the investment amount and click to create an AI strategy, and then you will create an own grid trading strategy.
CTA signal tracking includes strategies such as MACD, MACD-RSI, double moving average, double moving average-RSI, and custom indicators. Among them, the use of the combination of MACD and RSI indicators and the combination of dual moving averages and RSI indicators can effectively predict future market trends and more accurately grasp trading opportunities.
One-click copy trading, allow users to choose trusted traders’ quantitative strategy transactions based on comprehensive consideration of factors such as annualized rate of return, total return, and strategy running time. The system will automatically copy and execute the trader's strategy to help users obtain a target earing rate that is same as the professional investors. The initial creator of the copied strategy can also enjoy a 5% profit share. The more followers, the higher the profit.
Back-testing function, back-testing according to different quantitative strategies and time periods set by the user, the back-test results will display the complete transaction data under the strategy and time period, including total profit, maximum profit and loss, maximum retracement percentage, etc. The user can perform a back-test before executing the strategy, and use the back-test result as a reference to judge the feasibility of the strategy.
Try the AI quantitative strategy immediately
Gate.io's AI quantitative strategy essentially relies on intelligent data statistics and programmatic transactions through scientific mathematical models. The rich strategy library is suitable for novice users, ordinary users and professional users. It circumvents the natural shortcomings of personal decision-making mistakes. Users can freely choose to use strategies, refer to and follow a large number of professional trading strategies, and can easily obtain considerable quantitative benefits based on the correct use of intelligent quantitative strategies.
Author: Gate.io ResearcherJacky.S
*This article only represents the views of observers and does not constitute any investment advice.
*The content of this article is original and the copyright belongs to Gate.io. If you need to reprint, please indicate the author and source, otherwise legal responsibility will be pursued.
