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003			BD-DhUL
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007			cr uuu---uuuuu
008			231107s2021 sz a ob 000 0 eng
010			_a 2023403007
020			_a9783039439751
020			_a3039439758
020			_a9783039439768
020			_a3039439766
020			_a9783039439751 (hbk)
040			_aDLC _cDLC _dBD-DhUL _dBD-DhUL
042			_apcc
082			_a658.150285 _bFIN
245	0	0	_aFinancial Statistics and Data Analytics / _ceditors Shuangzhe Liu, Milind Sathye.
264		1	_aBasel, Switzerland : _bMDPI - Multidisciplinary Digital Publishing Institute, _c2020.
300			_a1 online-resource (232 p.) _bix, 220 p. :
300			_aix, 220 p. : _bill. (some col.) ; _c25 cm.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline-resource _bcr _2rdacarrier
365			_aUSD _b63.9
490		0	_aJournal of risk and financial management
504			_aIncludes bibliographical references
520			_aModern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.
546			_aEnglish.
650		4	_aFinancial management _x Data processing
700	1		_aSathye, Milind _eeditor.
700	1		_aShuangzhe Liu _eeditor.
856	4	0	_uhttps://directory.doabooks.org/handle/20.500.12854/68428 _mX:DOAB _xVerlag _zkostenfrei
906			_a0 _bibc _corigres _d3 _encip _f20 _gy-gencatlg
942			_2ddc _cBK
955			_bff21 2023-11-07 z-processor
999			_c259576 _d259576