000			01563nam a22002657a 4500
005			20250626153413.0
008			250626b |||||||| |||| 00| 0 eng d
020			_a9781032209265
040			_aCSL _cCSL
041			_2eng _aeng
084			_aB2811:(X:8D) R3 _qCSL
100			_a Swishchuk , Anatoliy _eauthor. _9814730
245			_aStochastic Modelling of Big Data in Finance
260			_aBoca Raton : _bCRC Press/Taylor & Francis, _c2023.
300			_axxiii, 280p. _b: ill. _c; 24 cm.
490			_aChapman & Hall/CRC Financial mathematics series
500			_aIncludes bibliography and index.
520			_aStochastic Modelling of Big Data in Finance provides a rigorous overview and exploration of stochastic modelling of big data in finance (BDF). The book describes various stochastic models, including multivariate models, to deal with big data in finance. This includes data in high-frequency and algorithmic trading, specifically in limit order books (LOB), and shows how those models can be applied to different datasets to describe the dynamics of LOB, and to figure out which model is the best with respect to a specific data set. The results of the book may be used to also solve acquisition, liquidation and market making problems, and other optimization problems in finance.
650			_a Finance. _9814731
650			_aStochastic modeling. _9814732
650			_aQuantitative. _9721606
650			_aHawkes processes. _9814733
650			_aBig data.
942			_2CC _cTEXL _hB2811:(X:8D) R3 _n0
999			_c1433017 _d1433017