Multivariate Stable Distributions and Their Applications

The article "Multivariate Stable Distributions and Their Applications for Modeling Cryptocurrency-Returns" would likely focus on the use of mathematical models based on multivariate stable distributions to analyze and predict returns in the cryptocurrency market.

A stable distribution is a type of probability distribution that is characterized by having a constant variance and is invariant under linear transformations. These distributions have been widely used in various fields, including finance, to model asset returns.

In this article, the authors may discuss how multivariate stable distributions can be applied to cryptocurrency returns data, taking into account the unique features and challenges of this market, such as its volatility, liquidity, and regulatory environment.

They may also compare the performance of different multivariate stable distributions for modeling cryptocurrency returns and evaluate the robustness of their models through simulations and real-world data analysis.

Finally, the authors may provide insights and recommendations for practitioners and researchers on how to effectively use multivariate stable distributions for modeling and predicting cryptocurrency returns.

11-02-2023