{"product_id":"python-for-finance-cookbook-second-edition-over-80-powerful-recipes-for-effective-financial-data-analysis-9781803243191","title":"Python for Finance Cookbook - Second Edition: Over 80 powerful recipes for effective financial data analysis","description":"\u003cp\u003e\u003cstrong\u003eUse modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePurchase of the print or Kindle book includes a free eBook in the PDF format\u003c\/strong\u003e\u003c\/p\u003eKey Features\u003cul\u003e\n\u003cli\u003eExplore unique recipes for financial data processing and analysis with Python\u003c\/li\u003e\n\u003cli\u003eApply classical and machine learning approaches to financial time series analysis\u003c\/li\u003e\n\u003cli\u003eCalculate various technical analysis indicators and backtest trading strategies\u003c\/li\u003e\n\u003c\/ul\u003eBook Description\u003cp\u003ePython is one of the most popular programming languages in the financial industry, with a huge collection of accompanying libraries. In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions.\u003c\/p\u003e\u003cp\u003eYou will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data. While doing so, you will also learn how to use Streamlit to create elegant, interactive web applications to present the results of technical analyses.\u003c\/p\u003e\u003cp\u003eUsing the recipes in this book, you will become proficient in financial data analysis, be it for personal or professional projects. You will also understand which potential issues to expect with such analyses and, more importantly, how to overcome them.\u003c\/p\u003eWhat you will learn\u003cul\u003e\n\u003cli\u003ePreprocess, analyze, and visualize financial data\u003c\/li\u003e\n\u003cli\u003eExplore time series modeling with statistical (exponential smoothing, ARIMA) and machine learning models\u003c\/li\u003e\n\u003cli\u003eUncover advanced time series forecasting algorithms such as Meta's Prophet\u003c\/li\u003e\n\u003cli\u003eUse Monte Carlo simulations for derivatives valuation and risk assessment\u003c\/li\u003e\n\u003cli\u003eExplore volatility modeling using univariate and multivariate GARCH models\u003c\/li\u003e\n\u003cli\u003eInvestigate various approaches to asset allocation\u003c\/li\u003e\n\u003cli\u003eLearn how to approach ML-projects using an example of default prediction\u003c\/li\u003e\n\u003cli\u003eExplore modern deep learning models such as Google's TabNet, Amazon's DeepAR and NeuralProphet\u003c\/li\u003e\n\u003c\/ul\u003eWho this book is for\u003cp\u003eThis book is intended for financial analysts, data analysts and scientists, and Python developers with a familiarity with financial concepts. You'll learn how to correctly use advanced approaches for analysis, avoid potential pitfalls and common mistakes, and reach correct conclusions for a broad range of finance problems.\u003c\/p\u003e\u003cp\u003eWorking knowledge of the Python programming language (particularly libraries such as pandas and NumPy) is necessary.\u003c\/p\u003eTable of Contents\u003col\u003e\n\u003cli\u003eAcquiring Financial Data\u003c\/li\u003e\n\u003cli\u003eData Preprocessing\u003c\/li\u003e\n\u003cli\u003eVisualizing Financial Time Series\u003c\/li\u003e\n\u003cli\u003eExploring Financial Time Series Data\u003c\/li\u003e\n\u003cli\u003eTechnical Analysis and Building Interactive Dashboards\u003c\/li\u003e\n\u003cli\u003eTime Series Analysis and Forecasting\u003c\/li\u003e\n\u003cli\u003eMachine Learning-Based Approaches to Time Series Forecasting\u003c\/li\u003e\n\u003cli\u003eMulti-Factor Models\u003c\/li\u003e\n\u003cli\u003eModelling Volatility with GARCH Class Models\u003c\/li\u003e\n\u003cli\u003eMonte Carlo Simulations in Finance\u003c\/li\u003e\n\u003cli\u003eAsset Allocation\u003c\/li\u003e\n\u003cli\u003eBacktesting Trading Strategies\u003c\/li\u003e\n\u003cli\u003eApplied Machine Learning: Identifying Credit Default\u003c\/li\u003e\n\u003cli\u003eAdvanced Concepts for Machine Learning Projects\u003c\/li\u003e\n\u003cli\u003eDeep Learning in Finance\u003c\/li\u003e\n\u003c\/ol\u003e\u003cbr\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50525993500946,"sku":"9781803243191","price":45.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_46cc860d-419c-42a7-9322-bc8f691454c3.jpg?v=1731253287","url":"https:\/\/surprise-castle.myshopify.com\/products\/python-for-finance-cookbook-second-edition-over-80-powerful-recipes-for-effective-financial-data-analysis-9781803243191","provider":"Surprise Castle","version":"1.0","type":"link"}