Gold and bitcoin trading strategies: a comprehensive model for optimal investment returns

Abstract

While Bitcoin has been a hot topic in the investment world due to its rising value, gold remains a popular investment option. To create a value prediction model for the best investment strategy, we utilized LSTM and found that it had a higher fitting effect than other two models, grey prediction and time series. The accuracy rate is 88.7%, the loss rate is 0.135%. We test different batch sizes to ensure the accuracy of prediction and established an appropriate algorithm to calculate the best investment strategy for each day. To test the accuracy of the model, we use four methods, including testing the accuracy of the risk factor in the model, observing the growth of total asset value, calculating the error rate of the investment process, and performing robustness analysis under low investment costs. We also perform sensitivity analysis to determine the impact of transaction costs on the strategy and results. The results show that the fluctuation in Bitcoin transaction costs is more significant and can affect the frequency of trading activities, ultimately affecting the final profit.