LEADER 00000cam a2200553 i 4500 
003    OCoLC 
005    20240129213017.0 
006    m     o  d         
007    cr unu|||||||| 
008    190801s2019    enka    ob    000 0 eng d 
020    1789345278 
020    9781789345278|q(electronic bk.) 
029 1  AU@|b000070841413 
035    (OCoLC)1110727639 
037    CL0501000062|bSafari Books Online 
040    UMI|beng|erda|epn|cUMI|dN$T|dOCLCF|dDST|dOCLCQ|dOCLCO|dOL$
       |dOCLCQ|dOCLCO|dOCLCL 
049    INap 
082 04 005.133 
082 04 005.133|223 
099    eBook O'Reilly for Public Libraries 
100 1  Weiming, James Ma,|eauthor. 
245 10 Mastering Python for finance :|bimplement advanced state-
       of-the-art financial statistical applications using Python
       /|cJames Ma Weiming.|h[O'Reilly electronic resource] 
250    Second edition. 
264  1 Birmingham, UK :|bPackt Publishing,|c2019. 
300    1 online resource (1 volume) :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
500    Previous edition published: 2015. 
504    Includes bibliographical references. 
520    Take your financial skills to the next level by mastering 
       cutting-edge mathematical and statistical financial 
       applications Key Features Explore advanced financial 
       models used by the industry and ways of solving them using
       Python Build state-of-the-art infrastructure for modeling,
       visualization, trading, and more Empower your financial 
       applications by applying machine learning and deep 
       learning Book Description The second edition of Mastering 
       Python for Finance will guide you through carrying out 
       complex financial calculations practiced in the industry 
       of finance by using next-generation methodologies. You 
       will master the Python ecosystem by leveraging publicly 
       available tools to successfully perform research studies 
       and modeling, and learn to manage risks with the help of 
       advanced examples. You will start by setting up your 
       Jupyter notebook to implement the tasks throughout the 
       book. You will learn to make efficient and powerful data-
       driven financial decisions using popular libraries such as
       TensorFlow, Keras, Numpy, SciPy, and scikit-learn. You 
       will also learn how to build financial applications by 
       mastering concepts such as stocks, options, interest rates
       and their derivatives, and risk analytics using 
       computational methods. With these foundations, you will 
       learn to apply statistical analysis to time series data, 
       and understand how time series data is useful for 
       implementing an event-driven backtesting system and for 
       working with high-frequency data in building an 
       algorithmic trading platform. Finally, you will explore 
       machine learning and deep learning techniques that are 
       applied in finance. By the end of this book, you will be 
       able to apply Python to different paradigms in the 
       financial industry and perform efficient data analysis. 
       What you will learn Solve linear and nonlinear models 
       representing various financial problems Perform principal 
       component analysis on the DOW index and its components 
       Analyze, predict, and forecast stationary and non-
       stationary time series processes Create an event-driven 
       backtesting tool and measure your strategies Build a high-
       frequency algorithmic trading platform with Python 
       Replicate the CBOT VIX index with SPX options for studying
       VIX-based strategies Perform regression-based and 
       classification-based machine learning tasks for prediction
       Use TensorFlow and Keras in deep learning neural network 
       architecture Who this book is for If you are a financial 
       or data analyst or a software developer in the financial 
       ... 
588 0  Online resource; title from title page (Safari, viewed 
       July 30, 2019). 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Python (Computer program language) 
650  0 Application software|xDevelopment. 
650  0 Computers|xFinance. 
650  0 Finance|xMathematical models. 
650  6 Python (Langage de programmation) 
650  6 Logiciels d'application|xDéveloppement. 
650  6 Ordinateurs|xFinances. 
650  6 Finances|xModèles mathématiques. 
650  7 Application software|xDevelopment|2fast 
650  7 Computers|xFinance|2fast 
650  7 Finance|xMathematical models|2fast 
650  7 Python (Computer program language)|2fast 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9781789346466/?ar
       |zAvailable on O'Reilly for Public Libraries 
938    EBSCOhost|bEBSC|n2116431 
994    92|bJFN