Financial market risk early warning method in internet environment

Abstract

The invention discloses a financial market risk early warning method in an internet environment, which comprises the following steps: 1, preprocessing data; 2, selecting emotion seed words by using aTF algorithm, expanding an emotion dictionary by using Word2vec, defining a degree adverb weight, and calculating a text emotion intensity index; and 3, using an MF-DCCA model to calculate a cross multi-fractal spectrum; 4, constructing a characteristic index which influences the stock abnormal income; and 5 constructing a stock abnormal income prediction analysis model. According to the method,a more accurate risk early warning model can be constructed, so that more accurate risk prediction is realized, a basis is provided for financial market supervision, and a reference is provided for investor investment decision making.

Description

technical field [0001] The invention relates to the field of text data mining and risk early warning, in particular to a financial market risk early warning method under the Internet environment. Background technique [0002] The financial market plays an important role in the national economy and is an important part of the development of China's market economy. Early warning of financial market risks can not only ensure the healthy and stable development of the social economy at the macro level, but also enable the Chinese economy to form a virtuous circle, and can implement more effective supervision and analysis of the financial market; It is necessary for investors to invest in risk, provide reference for investment decision-making, obtain investment benefits, conduct scientific analysis of financial markets, and early warning modeling. [0003] Domestic and foreign scholars' research on financial market risk early warning has gradually shifted from the traditional pre...

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Problems solved by technology

In addition, there are studies that use online comment text data as risk warning factors, including the number of comments and the emotional value index of comments. However, the traditional methods do not fully cover the field and network emotional words in the process of calculating emotional strength. The definition of degree adverb weight is highly subjective and lacks objective evaluation, resulting in inaccurate calculation of emotional strength

In addition, there is no unified understanding of the research methods of risk early warning in the financial market. The internal and external factors of the market are not added to the model at the same time, and the interaction between various factors is ignored. In summary, the current risk early warning model is not accurate enough.

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