基于马尔科夫和ARIMA模型的销量预测

Sales Forecast Based on Markov and ARIMA Models

摘要: 许多商家对于因货物存量不足而导致的补单问题存在极大的困扰，且补单问题主要存在两个问题：对现金流的占用和库存问题。因此，有效解决合理的补单策略是商家们急需解决的问题。本文基于某商家的历年销量数据，在数据预处理的基础上，从模型假设、模型建立与求解等几个方面对该商家的销售量数据进行ARIMA模型的建立，并根据ARIMA模型对未来几天的销售量进行拟合和预测分析，然后用马尔可夫模型进行结果检验，为该商家的补单及存货提供理论依据。

Abstract: Many merchants are deeply troubled by the problem of filling orders caused by insufficient stock of goods, and the problem of filling orders mainly has two problems: the occupation of cash flow and the problem of inventory. Therefore, effective and reasonable replenishment strategy is an urgent problem for merchants. Based on the sales data of business over the years, and on the basis of data preprocessing, this paper studies the sales volume of a business from several aspects, such as model hypothesis, model establishment and solution. According to the establishment of ARIMA model, and according to ARIMA model, the sales volume in the next few days is fitted and predicted, and then the results are tested by Markov model, which provides a theoretical basis for the replenishment and inventory of the merchant.