When using deep learning to predict crypto prices, essential data includes historical price and volume, order book depth, market sentiment (social media, news), blockchain on-chain metrics, macroeconomic indicators, and derivatives market data. High-quality, diverse datasets significantly improve model accuracy and robustness.
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Bitcoin’s trading volume often correlates with price volatility. Rising volume during price moves suggests strength, while low volume may indicate a lack of conviction or potential reversal.
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Panic selling triggers sharp, sudden price drops due to low liquidity and high emotional trading. It often leads to cascading liquidations in leveraged positions, amplifying volatility. This behavior can turn minor dips into full-blown crashes, especially in thin markets.
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