AlphaGo, an AI Go game software system, beat World Go champion Lee Sedol in 2016. Then, AlphaGo Master defeated Ke Jie, the world No. 1 ranking Go player in 2017. At this point, in Go, the most racking-brains game in the field of board and card games, the result of Human-Machine Battle has been settled, machine swept all the top human masters, the power of artificial intelligence (AI) is invincible and no doubt about it.
The next logical question could be : "What would happen if the stock market had a Human-Machine Battle?"
About this question, people's views are not as certain as board and card games. Most people advocate that machines and artificial intelligence technology can not defeat human beings in the fields of economy and finance. The reason is simple:
There are boundaries, clear rules, unified standards, clear order of taking turns, equal opportunities for all sides in board and card games. For machines with strong computing power, certain results can be solved sooner or later. And when it comes to computing power, of course, humans can't compete with sleepless computers.
Economics, finance and securities are quite different. There are no boundaries, neither orders and equality. And rules are fuzzy, standards are uneven in these fields. In the stock market, big institutional investors have much more insider information than retail investors dreaming for. Even the same piece of information published under the fairest conditions can be interpreted in opposite ways.
The stock market is a chaotic market, where the fluctuations are not entirely caused by economic activities, but certain partly by human emotions.
Computers can calculate astronomical figures that people can not image, but it is impossible to calculate the hearts of people, human nature and human feelings.
This, of course, makes sense. However, with the rapid development of Artificial Intelligence technology, there are always some "technical maniacs" against this tone. They've challenged this "mission impossible" over and over again, even built two ETFs powered entirely by AI, which have indeed outperformed most human fund managers, but far weaker than Warren Buffett, the best human stock trading master. Here's a comparison of their growth rates:
Since December 14, 2020, the growth rate of Berkshire Hathaway Inc. stock BRK-A (red line), owned and managed by Warren Buffett, has been outpacing AIEQ (gray line), the first ETF powered by Artificial intelligence machines in the world. AIEQ only surpassed Buffett shortly on November 18, 2021. Only one day later, it was reversed by Buffett, and then fell into a slump, and falling far behind.
So it is right to believe that in the "Human-Machine Battle" in the stock markets, the machine cannot win...
Wait a minute!
Look at the same chart, July 5, 2022, an orange line is catching up and overtaking the red line!
The orange line represents the growth rate of Candlelight, another AI trading system. Starting from December 14, 2020, this AI algorithmic trading system developed by us has been continuously tested (test conditions: real time, real field, real price and virtual capital). Since then, the growth rate of "Candlelight" AI algorithmically trading system has been slowly climbing.
In April 2021, Candlelight outperformed ARKK (green line), The ARK Innovation ETF managed by Cathie Wood. Ms. Wood was admired by many fans after her breakout years in 2020 and early 2021. This was the first milestone for Candlelight.
In January 2022, Candlelight surpassed its rival, AIEQ. AIEQ is equipped with IBM's "Watson" supercomputer hardware platform and Google's AI software platform. No matter whether its hardware or software, it is representing the highest level of Artificial Intelligence technology in the world.
In May 2021, Candlelight shortly surpassed AIEQ. After January 2022, Candlelight quickly ran away from AIEQ and has remained in the lead ever since. Surpassing AIEQ marks the second important milestone of Candlelight.
QRFT (yellow line) is another AI-driven ETF. Unlike AIEQ, which uses IBM's "Watson" supercomputer general-purpose platform, QRFT claims to use AI systems specifically designed and developed for investment task. Its performance in real operation is as same as AIEQ roughly. The Candlelight system established a lead over QRFT after June 2022.
In March 2022, Candlelight surpassed the growth rate of the S&P 500 Index (blue line) for the first time. July, Candlelight surpassed the S&P 500 Index again, officially passing the third milestone and maintaining the advantage, which means that the profitability of the pure machine trading system outperforms the market.
This seeming low-end target is actually beyond the reach of many human fund managers, and even Warren Buffett's growth rate was briefly suppressed by the Index in November 2021.
On July 5, 2022, after 19 months of continuous forward testing, the latest version of "Candlelight" finally passed the fourth milestone and surpassed Buffett's growth rate for the first time. To be honest, when we developed this software, we did not expect to be able to compete with the top human master, Mr. Buffett. Our goal is to beat another machine operating fund AIEQ only, that is enough to prove that our machine algorithm is better than the peer, the design goal is 100% achieved. Satisfied. Especially from March to May 2022, under the superimposed impact of war, inflation, interest rate hike and other major impacts, the growth rate of "Candlelight" once suffered a heavy decline, which was left a dozen streets away by master Buffett, and even faced the dilemma of being surpassed again by the rival AIEQ. As we have been very frustrated, Candlelight AI Algorithmic Trading System drives machine to make a series of adjustments, fights back continuously, finally get rid of the darkness and weakness. July 5, 2022, unexpectedly, narrowly exceeded Warren Buffet’s performance, which was unreachable before, completed a "mission impossible".
On October 13, 2022, Candlelight stepped on its fifth milestone: the completion of a full 100 forward testing transactions. As we all know, repeatability is a hard-core indicator to verify a model. The success of one or two sets of experiments does not mean anything. The results of ten or eight sets of experiments could be also highly contingence. Only when certain phenomena can be repeated, we can be sure that they are not coincidental. After 22 months, since December 14, 2020 to October 13, 2022. The operation of 100 opening and closing positions completely carried out by machines has basically tested the Repeatability and Robustness of the Candlelight system, in the complex market environment.
On December 14, 2022, Candlelight passed its sixth milestone: two years of continuous forward testing. While the Quantity of tests is a very important hardcore metric, there is another metric that is equally important: Time Span. In addition to the constraints of boundaries, rules, criteria, order, and so on mentioned above, there is another big difference between stock trading and board/card games: stock trading will be influenced greatly by the dimension of time.
The time span factor is not considered in the programming of AI for board and card games. As long as the results of a batch of tests confirm that the algorithm works, it is feasible, even if these sets of tests are completed intensively in a short period of time, because the test objects do not have periodic fluctuations. The test subjects of board and card games are the rules of the games themselves, which are eternal and do not change over time.
Stock trading is another story. It is a part of human economic activity, and it rises and falls with the fluctuations of financial markets. Such financial market fluctuations not only come from the economic activities themselves, nor reflect the supply and demand relationship of commodities alone. More often, they are also closely related to the political environment and natural changes, not to mention unpredictable shocks such as wars, epidemics and disasters. In any country, under any economic system, economic and market cyclical fluctuations are unavoidable. From three or five years to ten or eight years, human economic activity has always been a cycle of booms and busts. Even within a year, with the climate of cold and warm change, various markets have varying degrees of peak-season and off-season shock.
Therefor, algorithmic trading systems developed for stock markets must also be able to withstand the test of economic fluctuations to be practical. If only a short period of intensive testing is successful, it just means that the system works in one economy situation and may not reproduce the same results in another. We believe that a truly effective AI algorithmic trading system should cover at least one cycle of booms and busts, and the more economic fluctuations it can span, the more battle-ready the system will be.
In these 113 groups of consecutive forward testing (conditions: real time, real field, real price, virtual money) :
The Candlelight Algorithmic Trading System takes profit 79 times, break-even retreats 15 times, stops loss 19 times. The Wins/Losses Ratio is 4.2:1, the average Return per trade is 1.2%, and the average holding time is 13.4 days.
48 times Long and 65 times Short.
For Long positions, takes profit 30 times, break-even retreats 10 times, 8 times stops loss. The Wins/Losses Ratio is 3.8 to 1, the average Return per trade is 0.6%, and the average holding time is 14.9 days.
For Short positions, takes profit 49 times, break-even retreats 5 times, 11 times stops loss. The Wins/Losses Ratio is 4.5 to 1, the average Return per trade is 1.7%, and the average holding time is 12.2 days.
Let's take a look back at some of the most dramatic events that happened during the past 24 months and 113 groups of live testing:
December 2020: one full year of the COVID-19 outbreak;
January 2021: Capitol Hill Riots, USA political turmoil;
August 2021: Afghanistan changed, and the United States accepted defeat and withdrew hastily;
December 2021: two full years of the COVID-19 outbreak;
January 2022: USA reports inflation rate hit 7% last month;
February 2022: Russia-Ukraine war broke out;
March 2022: The Fed raised interest rates by 25 points for the first time in nearly three years; America's inflation rate jumped to 8.5% last month; Shanghai lockdown; The Russia-Ukraine peace talk, which turned out to be a scam;
May 2022: The Fed raised interest rates by 50 points due to severe inflation;
June 2022: USA inflation rate hit 8.6%, the highest since 1981; The Fed raised interest rates by a whopping 75 points;
July 2022: US inflation hit 9.1%, the highest since 1981; The Fed raised another blockbuster 75 points interest rates; The USA economy grew at a negative rate for the second quarter in a row; Political turmoil in UK, prime minister resigned;
August 2022: China reported unemployment at 5.4% last month and youth unemployment at 19.9%;
September 2022: Queen of UK Elizabeth II died; Russia partially mobilized and the war escalated; The explosion of the Nord Stream gas pipeline between Russia and Germany, worsening the European energy crisis and high inflation; US inflation still high, the Fed raised thirdly blockbuster 75 points interest rates;
October 2022: USA-Saudi Arabia relations broke down as OPEC+ announced crude oil production cuts; The Crimean bridge was bombed; UK's new prime minister resigns after just 45 days, the shortest serving in the history of UK;
November 2022: US inflation remained high and the Federal Reserve raised interest rates by 75 heavy points for the fourth time this year;
December 2012: G7 and the European Union set a cap on the price of Russian oil, the international energy supply waves again; Fed raises rates aggressively by 50 points to fight inflation...
Candlelight Algorithmic Trading System is surfing in such a stormy sea completely by its independent judgment. The machine carries out whole process of long and short two-way operations, zero human intervention. So far, this system has met or even exceeded our design expectations.
Candlelight does not achieve this performance overnight. Since 2018, this AI trading system developed by us has conducted forward simulation tests in the US stock market according to the real-time market environment, and posted every operation and action on social networks, left verifiable records and milestones. It has been more than four years until 2022. The algorithm has gone through three major iterations, optimization, polishing and numerous small upgrades. Continuous tests show that: it is not a "mission impossible" to completely make machine learning, automatically generate buying and selling signals, operate without manual intervention in the whole process, and make long-term profits. We have already gone through this.
The creator of "Candlelight" once took part in the Automated Trading Championship 2008, the highest level FOREX programming competition on the Earth, and finally ranked 56th among 2420 participants in the world, a TOP 3% class rank.
Since February 2020, we have continuously published the real-time forward test records of "Candlelight" in the US stock market on major social networking sites. The original data and operation records of these experiments can be reviewed. In each post, we reveal the next day's plan, the target price, for readers and viewers to verify.
Our next stage of optimization is to improve the stability of the growth rate, avoid big ups and downs.
Candlelight keeps challenging the best players. Thanks for continuous attention and witness.
Disclaimer:
This video or article, including all of its features, content, and services, is provided for informational and entertainment purposes only. All features, content, and services have been researched and expressed to the best of its knowledge and belief. Nevertheless, no guarantee can be provided for the correctness, completeness, or accuracy of this information.
Please be aware: I am neither a financial adviser nor a CPA. All Stock Trading Signals, Plans, Predictions and Actions here are 100% generated by "Candlelight" Artificial Intelligence Machine Learning Algorithm. It is under testing in real time and market prices, by virtual funds. Some of the models used by Machine Learning Trading System are predictive in nature. The use of predictive models has inherent risks. When Models and Data prove to be incorrect or incomplete, any decisions made in reliance thereon expose the System to potential risks. For example, by relying on Models and Data, the System may be induced to buy certain targets at prices that are too high, to sell at prices that are too low, or too early, or too late, then miss some favorable opportunities.
The performance represented is historical. Past performance may not be a reliable indicator of future results. None of the authors, contributors, administrators, or anyone else connected with this System, in any way whatsoever, can be responsible for your use of the information contained in or linked from here. Any action you take upon the information from here is strictly at your own risk.
This video or article is based on personal opinion and experience, and it should not be considered professional financial investment advice. The ideas and strategies should never be used without first assessing your own personal and financial situation. All contents are our TEST records only, not for real trading. Market is dangerous, trading is risky, DO NOT copy anything we do.
