Much research in recent years has focused on stock price prediction. In previous research learning data of a prediction target company is used. However, there is not learning data for the prediction target company often in the real world. In this research existing data of other companies is used as learning data based on Bayesian statistics. In previous research deep learning by fully connected neural networks is applied to predict stock price. In this research deep learning by fully connected neural networks based on Bayesian statistics is applied to predict stock price. This research is one of the extended research of the previous research from the viewpoint of Bayesian statistics. A new prediction method is proposed. Results of some stock price prediction experiments and investment simulations are shown. The effectiveness of the proposed method is shown by the results of the investment simulations.