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Python For Finance

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 IO operations with PyTables datetime 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
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The financial industry has adopted Python at a tremendous rate recently with some of the largest investment banks & hedge funds using it to build core trading & risk management systems This hands-on guide helps both developers & quantitative analysts get started with Python & 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 & 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 Num Py array handling time series analysis with pandas visualization with matplotlib high performance IO operations with Py Tables datetime information handling & selected best practices Financial topics mathematical techniques with Num Py Sci Py & Sym Py such as regression & optimization; stochastics for Monte Carlo simulation value-at-Risk & Credit-value-at-Risk calculations; statistics for normality tests mean-variance portfolio optimization principal component analysis (PCA) & Bayesian regression Special topics performance Python for financial algorithms such as vectorization & parallelization integrating Python with Excel & building financial applications based on Web technologies

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Interactive - Interaction can take place between a person and a device
IO - Input/Output - the commpuncation between two devices or between a device and its operator.
Large - something that takes up more space than normal.
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Page Updated: 2022-04-14 12:22:47

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