关键词: 大数据, 网络结构, 碳价预测

Abstract: This paper analyzes the effect of structured data and unstructured information on carbon price forecasting in order to learn if big data can help us predict carbon price. We choose international carbon spot price, carbon futures price and exchange rate as structured data, Baidu search index and media index as unstructured information. Considering that it is not reasonable when there are a lot of explanatory variables by taking every variables equally, we proposes network autoregressive distributed lag(ADL) model, taking variables as a network when we estimate parameters and choose variables. The empirical results show that network ADL model is better than other models, which can get high accuracy, and it is more suitable for predicting based on big data.

Key words: Big Data, Network, Carbon Price Forecasting