Yan Chenge1, Wu Zebin1, Gan Haoyu1, Zhu Ziwen2
1School of Science and Engineering, the Chinese University of Hong Kong, Shenzhen, 518172, China
2School of Management and Economics, the Chinese University of Hong Kong, Shenzhen, 518172, China
In recent years, the gold-bitcoin market and corresponding trading strategies have received more scholarly attentions. Predicting gold and bitcoin prices from historical data is a specific stream in this academic area. Many scholars have used financial methods or statistical methods to construct trading models. However, one of the limitations is that few previous studies combined both financial and statistical methods. Therefore, the present study aims to build a mathematical model that predicts price dynamics of gold and bitcoin and utilizes some connections between finance and statistics. To achieve this goal, some financial indicators were computed and Holt-Winters’ Model was applied. The research result shows that a trading strategy can be developed with the help of our proposed model and trading shrink ratio, which functions as the risk controller. The sensitivity test indicates that the proposed model has little sensitivity towards commission fees, which means that the model can be widely used in similar situations. In general, this study outlines an analytical approach to evaluate profits in gold-bitcoin market. Traders can generate considerable profits from the proposed trading strategy.
bitcoin-gold trading; mathematical models; Holt-Winters; dynamic strategies
Yan Chenge, Wu Zebin, Gan Haoyu, Zhu Ziwen. Mathematical modeling and dynamic trading strategies for gold and bitcoin. Academic Journal of Mathematical Sciences (2022) Vol. 3, Issue 1: 47-54. https://doi.org/10.25236/AJMS.2022.030107.
 Ahn, D. H, Conrad, J, & Dittmar, R. F. (2003). Risk adjustment and trading strategies[J]. The Review of Financial Studies, 16(2): 459-485.
 Farmer, J. D., & Joshi, S. (2002). The price dynamics of common trading strategies. Journal of Economic Behavior & Organization, 49(2), 149-171.
 Bouri, E, Shahzad, S. J. H, Roubaud, D, Kristoufek, L, & Lucey, B. (2020). Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis[J]. The Quarterly Review of Economics and Finance, 77: 156-164.
 Cuoco, D., He, H., & Isaenko, S. (2008). Optimal dynamic trading strategies with risk limits. Operations Research, 56(2), 358-368
 Meucci, A. (2005). Risk and asset allocation (Vol. 1). New York: Springer.
 O'Hara, H. T., Lazdowski, C., Moldovean, C., & Samuelson, S. T. (2000). Financial indicators of stock price performance. American Business Review, 18(1), 90.
 Holt, C. E. (1957). Forecasting seasonals and trends by exponentially weighted averages (O.N.R. Memorandum No. 52). Carnegie Institute of Technology, Pittsburgh USA.
 Winters, P. R. (1960). Forecasting sales by exponentially weighted moving averages. Management Science, 6(3), 324–342.
 Brennan, M. J, Schwartz, E. S, & Lagnado, R. (1997). Strategic asset allocation[J]. Journal of Economic dynamics and Control, 21(8-9): 1377-1403.