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Modeling dynamic volatility under uncertain environment with fuzziness and randomness
The problem related to predicting dynamic volatility in financial market plays a crucial role in many contexts.
Stochastic volatility modeling of high-frequency CSI 300 index and dynamic jump prediction driven by machine learning
This paper models stochastic process of price time series of CSI 300 index in Chinese financial market, analyzes volatility characteristics of intraday high-frequency price data.
Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters
In this paper we implement a combination of data-science and fuzzy theory to improve the classical Barndorff-Nielsen and Shephard model, and implement this to analyze the S&P 500 index.
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