LEADER 03506nam 2200493 450 001 9910555131603321 005 20200311052708.0 010 $a1-119-40473-8 010 $a1-119-40472-X 010 $a1-119-40474-6 035 $a(CKB)4950000000162529 035 $a(MiAaPQ)EBC5977946 035 $a(CaSebORM)9781119404750 035 $a(EXLCZ)994950000000162529 100 $a20191209d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine learning and big data with kdb+/q /$fJan Novotny [and three others] 205 $a1st edition 210 1$aChichester, West Sussex, England :$cWiley,$d[2020] 210 4$dİ2020 215 $a1 online resource (640 pages) 225 1 $aWiley finance 311 $a1-119-40475-4 330 $aUpgrade your programming language to more effectively handle high-frequency data Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Ideally designed to handle the speed and volume of high-frequency financial data at sell- and buy-side institutions, these tools have become the de facto standard; this book provides the foundational knowledge practitioners need to work effectively with this rapidly-evolving approach to analytical trading. The discussion follows the natural progression of working strategy development to allow hands-on learning in a familiar sphere, illustrating the contrast of efficiency and capability between the q language and other programming approaches. Rather than an all-encompassing ?bible?-type reference, this book is designed with a focus on real-world practicality ­to help you quickly get up to speed and become productive with the language. Understand why kdb+/q is the ideal solution for high-frequency data Delve into ?meat? of q programming to solve practical economic problems Perform everyday operations including basic regressions, cointegration, volatility estimation, modelling and more Learn advanced techniques from market impact and microstructure analyses to machine learning techniques including neural networks The kdb+ database and its underlying programming language q offer unprecedented speed and capability. As trading algorithms and financial models grow ever more complex against the markets they seek to predict, they encompass an ever-larger swath of data ­? more variables, more metrics, more responsiveness and altogether more ?moving parts.? Traditional programming languages are increasingly failing to accommodate the growing speed and volume of data, and lack the necessary flexibility that cutting-edge financial modelling demands. Machine Learning and Big Data with KDB+/Q opens up the technology and flattens the learning curve to help you quickly adopt a more effective set of tools. 410 0$aWiley finance series. 606 $aInvestments$xData processing 608 $aElectronic books. 615 0$aInvestments$xData processing. 676 $a332.60285416 700 $aNovotny$b Jan$f1982-$01217387 702 $aBilokon$b Paul 702 $aGaliotos$b Aris 702 $aDeleze$b Frederic 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910555131603321 996 $aMachine learning and big data with kdb+$92815461 997 $aUNINA