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is fast making inroads into financial modelling and derivatives analytics, and recent developments allow Python to be as fast as pure C++ or C;
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of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial;
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in designing a pricing and risk management framework for financial derivatives using the Python programming language. It is a practical book complete;
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This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the;
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This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the;
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The comprehensive, broadly-applicable, real-world guide to financial modelling Financial Modelling in Practice, Second Edition covers the;
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Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key Features Use powerful Python;
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Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment;
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This book is aimed at those who wish to advance their knowledge and expertise in financial modelling by addressing common problems that;
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This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields;
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This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields;
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Building and maintaining effective financial models See-Through Modelling provides a solid theoretical and practical basis for becoming an;
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The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it;
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This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains;
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Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application;
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In today's financial market, portfolio and risk management are facing an array of challenges. This is due to increasing levels of knowledge;
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This second edition of Practical Financial Modelling is vital tool for all finance and management professionals whose work involves the;
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Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to;
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This is a succinct guide to the application and modelling of dependence models or copulas in the financial markets. First applied to credit;
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The 2008 financial crisis was a watershed moment which clearly influenced the public's perception of the role of 'finance' in society;
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Transform your approach to oprisk modelling with a proven, non-statistical methodology Operational Risk Modeling in Financial Services;
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, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some;
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This book is for all financial professionals whose work, to a greater or lesser degree, involves complex spreadsheets and financial models;
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Master complex workflows and conquer the world with Python and Maya About This Book * Improve your modelling skills and reduce your;
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in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and;
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Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic;
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Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework;
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