Abstract
The investment market is rapidly changing and asset prices may vary greatly in a relatively short period of time due to their instability. We analyze the variation characteristics of gold and bitcoin prices. Obviously, the gold price movements are significantly more stable than bitcoin, so we consider using a long- term low-frequency trading strategy with wavelet transform for gold and a short-term high- frequency trading strategy for bitcoin. Based on these indicators, a multilayer perceptual (MLP) neural network was used to develop price prediction models for each of the two assets. These models achieve accurate forecasting of future prices based on historical data, and the models’ test error levels are both about 2%.
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