2021/06/24 by Bruno Ebner, Ebner, Bruno, Lena Eid +3
Economics, Econometrics and Finance · #62E10 #62G10 #Complex Systems and Time Series Analysis #FOS: Mathematics #Financial Risk and Volatility Modeling #Statistics Theory (math.ST) #Stochastic processes and financial applications
paper · pdf · doi:10.48550/arxiv.2106.13073
openalex publication_date 2021/06/24 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
We introduce a new characterization of the Cauchy distribution and propose a class of goodness-of-fit tests to the Cauchy family. The limit distribution is derived in a Hilbert space framework under the null hypothesis and under fixed alternatives. The new tests are consistent against a large class of alternatives. A comparative Monte Carlo simulation study shows that the test is competitive to the state of the art procedures, and we apply the tests to log-returns of cryptocurrencies.