AI-based Trading Strategy for Fast Profits using Volatile Assets
Discover an AI-based trading strategy to turn $100 into $10,000 quickly using volatile assets and technical analysis.
00:00:00 Discover an AI-based trading strategy to turn $100 into $10,000 in the shortest time possible using volatile assets and technical analysis.
📈 Using highly volatile assets and technical analysis.
🤖 Creating a trading strategy using an AI-based indicator.
⚙️ Testing the strategy using the price of Ethereum on a three-minute timeframe.
00:01:12 Learn a profitable trading strategy using the KNN algorithm for predicting stock price movements based on historical data.
📈 K Nearest Neighbors (KNN) is a classification algorithm used to predict stock price movements based on historical data.
📊 Technical indicators, such as moving averages, relative strength index, and momentum indicators, are used to create feature vectors for KNN classification.
🔵🔴 The KNN algorithm generates buy and sell signals based on the strength of the signals, with blue and pink labels indicating buy and sell respectively.
📉 The EMA ribbon, another trading indicator, is used in conjunction with KNN to filter out false signals and improve trading strategy.
00:02:25 Learn how to use the EMA ribbon indicator to identify market trends and potential buy/sell signals. Combine it with the RSI for confirmation.
📊 The video explains the concept of EMA ribbon, which is created by plotting multiple EMAs with different time periods on a price chart to identify the trend direction and strength.
🔍 The EMA ribbon indicator can be used to generate potential buy or sell signals based on the trend direction and price location relative to the moving averages.
💪 To confirm the signals, the video suggests using the relative strength index (RSI) as a secondary confirmation tool, which measures the strength of a security's price action on a chart ranging from 0 to 100.
00:03:38 This tutorial explains a trading strategy that made 19527% profit. It includes setting specific entry conditions for long trades and managing risk.
⚙️ Adjusting the RSI to be more sensitive for valid trade entries.
📈 Entry conditions for a long trade: price above 200 EMA, ribbon above 200 EMA, pullback into ribbon without closing below long-term EMA, and blue label from machine learning strategy.
💰 Managing trades: setting stop loss, target profit, and adjusting stop loss to secure the trade.
00:05:04 Learn a profitable trading strategy using technical indicators and machine learning. Buy when price is in an up trend and RSI is oversold, and sell when price falls below the 200 EMA.
📈 The strategy involves buying a security at a discounted price during an uptrend.
⬇️ For short trades, wait for the price and ribbon to fall below the 200 EMA and the ribbon to turn red.
00:06:18 Learn a profitable trading strategy using technical indicators and machine learning. Backtesting results show a 19527% profit increase.
📈 The trading strategy involves using the 200 EMA and RSI to identify entry points.
💰 Setting stop loss and target levels, and adjusting the stop loss once a quarter of the profit is made.
📊 The backtesting results showed a significant increase in the account balance.
00:07:32 Learn a high-risk trading strategy with a higher potential reward. Test it on a paper account before trying it with real money. Watch more crypto strategies in this playlist.
📈 This trading strategy has a higher risk and involves a higher reward.
💯 Risking 5% of your account per trade is recommended for growing a small account quickly.
📝 Don't forget to test the strategy on a paper account before implementing it.
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