ChatGPT Trading Strategy Made 19527% Profit ( FULL TUTORIAL )

TradeIQ
11 Mar 202308:11

TLDRThe video script outlines a high-risk trading strategy aimed at rapidly increasing a small capital from $100 to $10,000. It utilizes a combination of three TradingView tools: a machine learning-based indicator, an EMA ribbon, and an RSI. The strategy involves specific entry and exit conditions, such as price action relative to EMAs, RSI levels, and machine learning signals. The backtesting results show a significant increase in the account balance, but the strategy's higher risk per trade is noted, with a recommendation to test it on a paper account before actual use.

Takeaways

  • 🚀 The goal is to turn $100 into $10,000 using a high-risk trading strategy.
  • 🤖 The strategy utilizes an AI-based trading view indicator that's currently popular.
  • 📊 The strategy involves three free TradingView tools: Machine Learning KN, EMA Ribbon, and RSI.
  • 📈 The Machine Learning KN indicator analyzes historical data to predict future price movements.
  • 📉 The EMA Ribbon uses multiple exponential moving averages to identify market trends.
  • 🔍 The RSI is modified for increased sensitivity, with upper and lower bands set at 60 and 40 respectively.
  • 🛒 Entry conditions for a long trade include the price above the 200 EMA, a green ribbon, a pullback without closing below the long-term EMA, a blue label from the ML strategy, and an RSI signal.
  • 📉 For short trades, wait for the price and ribbon to fall below the 200 EMA, a red ribbon, a pullback without closing above the 200 EMA, and an overbought RSI.
  • 📝 Risk management is crucial; set a stop loss and adjust it once a quarter of the profit target is reached.
  • 🔄 Backtesting results show a starting balance of $100 increased to $19,527 after 100 trades.
  • ⚠️ The strategy carries higher risk with a 5% risk per trade, which may not be suitable for all traders.

Q & A

  • What was the initial goal of the trading strategy discussed in the video?

    -The initial goal of the trading strategy was to turn 100 dollars into ten thousand dollars in the shortest amount of time possible.

  • What are the three free TradingView tools included in the strategy?

    -The three free TradingView tools included in the strategy are the Machine Learning KN-based Strategy, the EMA Ribbon, and the Relative Strength Index (RSI).

  • How does the Machine Learning KN-based Strategy work?

    -The Machine Learning KN-based Strategy works by analyzing historical market data and predicting the direction of future price movements based on patterns in the data using a classification algorithm called KN, which classifies data points based on their nearest neighbors in a feature space.

  • What is the purpose of the EMA Ribbon in the strategy?

    -The EMA Ribbon is used to identify the direction and strength of a trend in the market by plotting several exponential moving averages (EMAs) with different time periods stacked on top of each other, creating a ribbon-like appearance on the chart.

  • How is the RSI used in this trading strategy?

    -In this strategy, the RSI is made more sensitive by adjusting the upper and lower bands to 60 and 40, respectively. It is used as a secondary confirmation to filter out false signals and to identify valid trade entries based on the strength of a security's price action.

  • What are the entry conditions for a long trade according to the strategy?

    -For a long trade, the entry conditions are: the price must close above the 200 EMA, the ribbon must be green and above the 200 EMA, the price must pull back into the ribbon without closing below the long-term EMA, the Machine Learning Strategy must print a blue label, and the RSI must not be oversold prior to the buy signal.

  • How should the stop loss and target be set in this strategy?

    -The stop loss should be set below the recent swing low, and the target should be two times the risk. Once a quarter of the profit is made, the stop loss should be adjusted to break-even.

  • What is the backtesting result of the strategy?

    -After 100 trades, the strategy increased the starting account balance of 100 dollars to 19,527 dollars.

  • What is the risk per trade set in this strategy?

    -The risk per trade in this strategy is set at five percent of the account balance, which is higher than the usual risk level but is appropriate for the goal of growing a small account quickly.

  • What is the importance of forward testing in a paper account before using the strategy?

    -Forward testing in a paper account is crucial to validate the strategy's effectiveness and to ensure that it works as expected without risking real capital. It helps in understanding the strategy's performance in real market conditions.

Outlines

00:00

🤖 AI Trading Strategy Development

The speaker discusses their quest for a specific trading strategy to rapidly increase their capital. They initially receive generic advice from Chat GPT but eventually ask for a strategy using an AI-based trading view indicator that's gaining popularity. After receiving a detailed strategy, the speaker makes tweaks and plans to test its effectiveness 100 times using Ethereum's three-minute price chart. The strategy involves three free TradingView tools: a machine learning-based strategy indicator, an EMA ribbon, and an RSI for confirmation. The speaker explains each tool's function and how they contribute to the trading strategy.

05:04

📈 Implementing and Testing the Strategy

The speaker elaborates on the strategy's entry conditions for both long and short trades, emphasizing the importance of the 200 EMA, the EMA ribbon's color, and the RSI's overbought or oversold status. They also discuss the risk management aspect, setting a stop loss and adjusting it once a quarter of the profit target is reached. The speaker shares the backtesting results, which show a significant increase in the account balance from $100 to $19,527 after 100 trades. They note that while the strategy is riskier, it can be suitable for those looking to grow a small account quickly and advise viewers to test the strategy on a paper account before actual trading.

Mindmap

Keywords

💡Trading Strategy

A trading strategy is a comprehensive approach to trading that includes specific rules for when to enter and exit trades, manage risk, and maximize profits. In the video, the strategy aims to turn $100 into $10,000 quickly by focusing on volatile assets and technical analysis. The strategy involves using a combination of indicators and specific entry and exit rules.

💡Highly Volatile Assets

Highly volatile assets are financial instruments, such as stocks or cryptocurrencies, that experience significant price fluctuations in a short period. These assets can offer high returns but also come with increased risk. In the context of the video, focusing on such assets is part of the strategy to achieve rapid capital growth.

💡Technical Analysis

Technical analysis is a method of evaluating securities by analyzing past market data, primarily price and volume. It aims to identify patterns and trends to predict future price movements. In the video, technical analysis is used to guide trading decisions based on historical market data.

💡Machine Learning Indicator

A machine learning indicator is a tool that applies machine learning algorithms to financial data to predict market behavior. These indicators analyze historical data to identify patterns that might indicate future price movements. In the video, the machine learning indicator is used to classify whether a stock price is likely to go up or down.

💡Exponential Moving Average (EMA) Ribbon

The EMA ribbon is a trading indicator that plots multiple exponential moving averages (EMAs) on a price chart to identify trends. EMAs give more weight to recent prices, making them more responsive to current market conditions. The ribbon's slope and color indicate the market trend, with an upward slope indicating an uptrend and a downward slope indicating a downtrend.

💡Relative Strength Index (RSI)

The RSI is a momentum oscillator that measures the speed and change of price movements. It is typically used to identify overbought or oversold conditions. An RSI above 70 suggests the asset may be overbought, while an RSI below 30 suggests it may be oversold. In the video, the RSI is adjusted to be more sensitive for better trade entries.

💡Entry Conditions

Entry conditions are the specific criteria that must be met before a trade can be executed. These conditions help traders determine the right time to enter a market position. In the video, entry conditions for a long trade include the price being above the 200 EMA, the ribbon being green, and a buy signal from the machine learning indicator.

💡Stop Loss

A stop loss is an order placed with a broker to sell a security when it reaches a certain price. It is designed to limit an investor's loss on a position in a security. In the video, setting a stop loss is part of the risk management strategy to protect the account from significant losses.

💡Risk Management

Risk management in trading involves the process of identifying, analyzing, and accepting or mitigating risks. It is crucial for protecting the trader's capital and ensuring sustainable growth. The video emphasizes the importance of setting a risk per trade, such as 5% of the account balance, to manage potential losses.

💡Backtesting

Backtesting is the process of evaluating a trading strategy by running it through historical data to see how it would have performed in the past. It helps traders understand the potential effectiveness of a strategy before implementing it in live trading. The video concludes with backtesting results to demonstrate the strategy's performance.

💡Paper Trading

Paper trading is the practice of simulating trades in a virtual environment without risking real money. It allows traders to test strategies and learn from their decisions without financial consequences. The video encourages viewers to perform paper trading before applying the strategy with real money.

Highlights

The strategy aims to turn $100 into $10,000 using AI-based trading view indicators.

The strategy includes three free TradingView tools: Machine Learning KN, EMA Ribbon, and RSI.

Machine Learning KN analyzes historical market data to predict future price movements.

EMA Ribbon identifies the direction and strength of market trends using multiple exponential moving averages.

RSI is used to measure the strength of a security's price action, with modifications made for increased sensitivity.

Entry conditions for a long trade include the price closing above the 200 EMA, a green ribbon, and a pullback into the ribbon.

A blue label from the Machine Learning strategy and an RSI below 40 are required for a long trade entry.

For a short trade, wait for the price and ribbon to fall below the 200 EMA, a red ribbon, and an overbought RSI.

The risk per trade is set at 5% to potentially grow a small account fast, though it involves higher risk.

Backtesting results show an increase from $100 to $19,527 after 100 trades.

The strategy's win rate is not the highest but offers a balance of risk and reward.

The video emphasizes the importance of forward testing on a paper account before actual trading.

The Machine Learning KN indicator is non-repaintable and requires waiting for candle closure for valid signals.

The EMA Ribbon helps filter out fake signals but may still require additional confirmation.

The RSI is used as a secondary confirmation for trade entries, with adjusted upper and lower bands.

Stop loss and profit targets are set based on risk management principles.

The strategy is suitable for those looking to grow a small account quickly but with an understanding of the risks involved.

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