Abstract: Disclosed in the present disclosure is a multi-scale analysis method for time series based on quantum walk, including (1). generating multi-scale and multi-feature sequences based on quantum walk; (2). screening feature sequences; (3). modeling and predicting time series based on regression analysis; (4). performing frequency domain and time domain-based result evaluation; and (5). performing experimental verification. The method of the present disclosure has the advantage that the multi-scale features of the quantum walk are applied to the analysis of time series, and by combining feature extraction methods under two rules, a model of an original time series is established based on extracted features by using linear, nonlinear and time-based regression methods. The analysis method for time series does not require pre-assumption such as stationarity assumption, and is a universal analysis method for time series.