Optimal Prediction of Bitcoin Prices Based on Deep Belief Network and Lion Algorithm with Adaptive Price Size: Optimal Prediction of Bitcoin Prices

In this digital world, Bitcoin is an acknowledged cryptocurrency that makes it appealing for traders and speculators. However, it is a challenging task to foresee the exchange rate of the Bitcoin, due to its high volatility. Further, in the cryptocurrency market, it is vital to predict the Bitcoin price, which leads to high budgetary advantages and fences against market risks. This paper introduces a new bitcoin prediction model that includes three major phases: data collection, Feature Extraction, and Prediction. The initial phase is data collection, where Bitcoin raw data are collected, from which the features are extracted in the Features Extraction phase. The feature extraction is a unique mechanism for detecting the bitcoin prices on day-by-day and minute-by-minute. The indexed data collected are computed regarding certain standard indicators like average true range, exponential moving average, relative strength index, and rate of change. These technical indicators based features are subjected to the prediction phase. As the major contribution, the prediction process is made precisely by deploying an improved deep belief network model, whose weights and activation function are fine-tuned using a new modified Lion Algorithm referred to as Lion Algorithm with Adaptive Price Size. Finally, the performance of the proposed work is compared and proved its superiority over other conventional models.