Mystical Traveler (Volume 2 of 2) (EasyRead Super Large 24pt Edition) PDF Download
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Author:
Publisher: ReadHowYouWant.com
ISBN: 1458724468
Category :
Languages : en
Pages : 290
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Book Description
Author:
Publisher: ReadHowYouWant.com
ISBN: 1458724468
Category :
Languages : en
Pages : 290
Get Book
Book Description
Author:
Publisher: ReadHowYouWant.com
ISBN: 1442955899
Category :
Languages : en
Pages : 526
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Book Description
Author:
Publisher: ReadHowYouWant.com
ISBN: 1458724328
Category :
Languages : en
Pages : 414
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Author:
Publisher: ReadHowYouWant.com
ISBN: 144297687X
Category :
Languages : en
Pages : 386
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Book Description
Author:
Publisher: ReadHowYouWant.com
ISBN: 1442967641
Category :
Languages : en
Pages : 402
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Book Description
Author: Roger Zelazny
Publisher: Harper Collins
ISBN: 9780060567231
Category : Fiction
Languages : en
Pages : 308
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Book Description
Earth is long since dead. On a colony planet, a band of men has gained control of technology, made themselves immortal, and now rules their world as the gods of the Hindu pantheon. Only one dares oppose them: he who was once Siddhartha and is now Mahasamatman. Binder of Demons. Lord of Light.
Author: Yves Hilpisch
Publisher: "O'Reilly Media, Inc."
ISBN: 1491945389
Category : Computers
Languages : en
Pages : 989
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Book Description
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
Author: Eryk Lewinson
Publisher: Packt Publishing Ltd
ISBN: 1789617324
Category : Computers
Languages : en
Pages : 426
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Book Description
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.
Author: Sylvia Browne
Publisher: Harper Collins
ISBN: 0061995479
Category : Body, Mind & Spirit
Languages : en
Pages : 322
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Book Description
“I have known Sylvia for twenty years, and I have the greatest respect for her. People seek her out for her much celebrated intuitive skills, however, I have sought her out for her friendship and kindness. I applaud her for the peace and solace that she has brought to so many.” — Montel Williams “An amazing woman, an amazing life, and a book I couldn’t put down. Sylvia is a true inspiration.” — Jeanne Cooper, star of The Young and the Restless Reaching deep beneath the surface of her life—then and now—renowned psychic and #1 New York Times bestselling author Sylvia Browne (The Other Side and Back) candidly discusses details of her professional and personal experiences that she’s never publically revealed before.
Author: Yves Hilpisch
Publisher: "O'Reilly Media, Inc."
ISBN: 1492055387
Category : Business & Economics
Languages : en
Pages : 478
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Book Description
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
