Quantum Modelling and Data Analysis

In financial market, financial data are treated as classical random variables. There are naive assumptions for such random variables: independent and identically distributed. However, these assumptions are not always true for sample data. This thesis applies quantum mechanics in data analysing. The aim is to treat data as quantum observables and they are not necessarily to be observed independently. Then, quantum observables are analysed with machine learning tools. With quantum mechanics, stochastic process can be modelled with dependent jumps .