With the development of economy, gold and bitcoin have gradually become two important investment assets. However, due to the high volatility of them, the investment process is often accompanied by huge risks, and it is common to gain losses. This paper proposes a gold and Bitcoin investment strategy model based on a combination of grey prediction and linear programming. We predict future markets through grey prediction to calculate the relative strength index in economics, according to which and market openness we select linear programming or equation solving in order to maximize future returns and obtain the best portfolio strategy. In the process of solving linear programming, the standard deviation rate is also introduced for risk control. What’s more, we judge the merits and demerits of the model by proving prediction accuracy, comparing future market volatility, and observing risk aversion. Average absolute percentage error is introduced to measure prediction accuracy. Experiments have shown that the overall forecast accuracy is high, the predicted volatility trend is roughly the same as the actual volatility trend, the risk aversion is effective, and our model is reliable and forward-looking.

Xinlei Lin, Zhaotong Wu, Yuhan Tang. Trading Strategy of Gold and Bitcoin Based on Optimization Algorithm. Academic Journal of Business & Management (2022) Vol. 4, Issue 7: 72-76. https://doi.org/10.25236/AJBM.2022.040712.

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