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cognivateAI Quantitative Trading Training Outline
Guidance: Differentiated characteristics of Air Coins and Infrastructure Coins.
First, Professional Knowledge Course Arrangement
1. The rules of price fluctuations.
2. The logic of price fluctuations.
3. The patterns of price fluctuations.
4. The four basic logical principles and practical application skills of investment decision-making in the cryptocurrency world. (Psychological expectation logic, capital-driven logic, demand logic, and inflation logic)
5. Interpretation of macroeconomic data. (The operating rules and truths of GDP. The help of CPI and PPI in investment decision-making. Prospective expectations of the MI and M2 scissors difference.)
6. The importance and application skills of industry supply and demand analysis in selecting targets.
7. Through the above learning, enable users to apply the knowledge learned to independently predict trends, select targets, correctly interpret various macro data, understand policy implications, and seize investment opportunities.
Second, Traditional Technical Indicators Lecture
1. K-line, let you understand different K-line application techniques.
2. Trend indicators, why is your trend signal always lagging?
3. Price indicators, why can’t your price signal always capture tops and bottoms?
4. Energy indicators, why can’t your energy signal reflect its own flow?
5. Time indicators, why does your time signal always fail to keep up with the cyclical rhythm of market fluctuations?
Third, Operation Course Arrangement for Quantitative Systems
1. What is a true AI quantitative trading system?
2. Is a quantitative trading system the same as placing orders on a computer?
3. Principles and operations of cognivateAI quantitative design.
4. Learning and application of cognivateAI quantitative packaging strategies.
5. Principles, thoughts, and methods of building cognivateAI quantitative models.
6. Design principles of the three basic models of cognivateAI quantitative.
7. Explanation of cognivateAI quantitative functions.
8. Model building and technical validation.
Fourth, Expected Outcomes.
Enable users to achieve and fully realize the following goals.
1. Independently control cognivateAI quantitative.
2. Machine analysis, machine decision-making, machine trading fully achieve unity of knowledge and action.
3. Subjectively misjudge the market, and the robot can correct mistakes.
4. Subjectively judge the market correctly, and the robot can heavily invest.
5. In volatile markets, the robot can achieve small losses and small profits, controlling drawdowns.
6. High selling and low buying, rolling operations, big profits when right, stop losses when wrong, never hold positions.
Fifth, Class Arrangement
Class Time: Online live broadcast, every evening: 8:30-10:30.
Learning Cost: Free. $RAVE
Guidance: Differentiated characteristics of Air Coins and Infrastructure Coins.
First, Professional Knowledge Course Arrangement
1. The rules of price fluctuations.
2. The logic of price fluctuations.
3. The patterns of price fluctuations.
4. The four basic logical principles and practical application skills of investment decision-making in the cryptocurrency world. (Psychological expectation logic, capital-driven logic, demand logic, and inflation logic)
5. Interpretation of macroeconomic data. (The operating rules and truths of GDP. The help of CPI and PPI in investment decision-making. Prospective expectations of the MI and M2 scissors difference.)
6. The importance and application skills of industry supply and demand analysis in selecting targets.
7. Through the above learning, enable users to apply the knowledge learned to independently predict trends, select targets, correctly interpret various macro data, understand policy implications, and seize investment opportunities.
Second, Traditional Technical Indicators Lecture
1. K-line, let you understand different K-line application techniques.
2. Trend indicators, why is your trend signal always lagging?
3. Price indicators, why can’t your price signal always capture tops and bottoms?
4. Energy indicators, why can’t your energy signal reflect its own flow?
5. Time indicators, why does your time signal always fail to keep up with the cyclical rhythm of market fluctuations?
Third, Operation Course Arrangement for Quantitative Systems
1. What is a true AI quantitative trading system?
2. Is a quantitative trading system the same as placing orders on a computer?
3. Principles and operations of cognivateAI quantitative design.
4. Learning and application of cognivateAI quantitative packaging strategies.
5. Principles, thoughts, and methods of building cognivateAI quantitative models.
6. Design principles of the three basic models of cognivateAI quantitative.
7. Explanation of cognivateAI quantitative functions.
8. Model building and technical validation.
Fourth, Expected Outcomes.
Enable users to achieve and fully realize the following goals.
1. Independently control cognivateAI quantitative.
2. Machine analysis, machine decision-making, machine trading fully achieve unity of knowledge and action.
3. Subjectively misjudge the market, and the robot can correct mistakes.
4. Subjectively judge the market correctly, and the robot can heavily invest.
5. In volatile markets, the robot can achieve small losses and small profits, controlling drawdowns.
6. High selling and low buying, rolling operations, big profits when right, stop losses when wrong, never hold positions.
Fifth, Class Arrangement
Class Time: Online live broadcast, every evening: 8:30-10:30.
Learning Cost: Free. $RAVE
Disclaimer: Includes third-party opinions. No financial advice. May include sponsored content. See T&Cs.