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Financial Computing and Data Analytics

We focus on methodological and empirical research on methodological and empirical research on statistical computing, data science, and mathematical modelling mainly with applications in finance and risk management. Our financial markets research is based on both modern data science approaches as well on more traditional statistical methods with rich data sets.

Research focus and goals

Model and analyze the financial market with data science techniques. The main objectives are: i) analyze investors behavior, ii) model and analyze limit order book markets, iii) model volatility in stock markets, and iv) develop option pricing methods. This is relevant not only for academics but also practitioners who are working for financial risk management and market supervision.


We use unique, large and extensive data sets, which include investor-level data over 20 years on daily bases, covering more than 1 million Finnish investors. This data sets allows us to examine the actual behavior of human-beings in financial decision making. Moreover, we use massive ultra-high-frequency limit order book data from both Nordic and US stock markets.

This data, together with machine learning techniques, allows us to identify how markets are driven by information incorporated in the limit order books, a question which is crucial for traders, risk management, market making, and financial supervision.