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Research on Quantitative Trading Model
Ying Ge (Soochow University), Yue Cao (Soochow University), Zi Yang (Soochow University), Yuyao Wang (Soochow University), Xin Quan Ge (Huai'an University)
Résumé : With the rapid development of data science, quantitative trading models have become prevalent in financial markets. Based on Apriori algorithm, we analyze the rise characteristics of gold and bitcoin. Based on the principle of financial investment, BiLSTM with attention mechanism and VaR, the transaction decision model was established. We also establish a exponential model to identify how much money should be invested each time. Simultaneously, we apply a modified greedy algorithm to decide our investing decisions and it turns out to be quiet successful. Generally, the trading model established in this paper has good sensitivity to adapt to market changes and has strong risk resistance.