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    Book details
    Format: epub
    File Size: 12 MB
    Print Length: 378 pages
    Publisher: Packt Publishing; 1 edition (30 March 2019)
    Sold by: Amazon Asia-Pacific Holdings Private Limited
    Language: English
    ASIN: B07Q5W7GB1

    Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras

    Key Features

    Understand Python data structure fundamentals and work with time series data
    Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance
    Explore various Python programs and learn finance paradigms
    Book Description
    Python is one of the most popular languages used for quantitative finance. With this book, you’ll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management.

    The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you’ll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you’ll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You’ll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction.

    By the end of this book, you will be equipped with the skills you need to perform different financial analysis tasks using Python

    What you will learn

    Clean financial data with data preprocessing
    Visualize financial data using histograms, color plots, and graphs
    Perform time series analysis with pandas for forecasting
    Estimate covariance and the correlation between securities and stocks
    Optimize your portfolio to understand risks when there is a possibility of higher returns
    Calculate expected returns of a stock to measure the performance of a portfolio manager
    Create a prediction model using recurrent neural networks (RNN) with Keras and TensorFlow
    Who this book is for
    This book is ideal for aspiring data scientists, Python developers and anyone who wants to start performing quantitative finance using Python. You can also make this beginner-level guide your first choice if you’re looking to pursue a career as a financial analyst or a data analyst. Working knowledge of Python programming language is necessary.

    Table of Contents

    Python for Finance 101
    Getting started with Numpy, Pandas and Matplotlib
    Time Series Analysis and Forecasting
    Measuring Investment Risks
    Portfolio Allocation and Markowitz Portfolio Optimization
    The Capital Asset Pricing Model
    Regression Analysis in Finance
    Monte Carlo simulations for decision-making
    Option Pricing-Black Scholes Model
    Introduction to Deep Learning with TensorFlow and Keras
    Stock Market Analysis and Forecasting Case study
    What Is Next
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    Category:Books
    Language:English  English
    Total Size:12.44 MB
    Info Hash:E78F0E68039E070C717A7BF2866EB74E87218A3F
    Added By:DiamondB Verified Uploader
    Date Added:2019-09-05 21:21:37
    Torrent Status:Torrent Verified


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