Python for Finance: Analyze Big Financial Data
| Author | : | |
| Rating | : | 4.28 (588 Votes) |
| Asin | : | 1491945281 |
| Format Type | : | paperback |
| Number of Pages | : | 606 Pages |
| Publish Date | : | 2014-05-12 |
| Language | : | English |
DESCRIPTION:
William P Ross said Suitable Financial Resource But Needs Work On Python Parts. This book addresses a niche audience who is experienced in financial analysis but has little programming experience. In the first few chapters we are introduced to Python and why it has become popular in the financial field. Some sample code is shown for how you would setup an options simulation using Monte Carlo methods.The middle chapters cover different Python libraries which are useful in finance such as Numpy and Pandas. The later chapters cover financial simulations again. I did not really understand this ordering of the chapters. It felt like the book dived too fast into simulations, then took a bunch of steps back to cover Py. Code examples have become dated J.T. Code examples are quickly becoming outdated. You will spend a decent amount of time just trying to figure out why the code isn't working then searching for current code to replace the dated stuff.. "Clear explanations and great examples" according to Scott A. Guillaudeu. It's worth the price for Chapter 8: Performance Python alone. The whole book is easy to read and gives nice clear explanations for some very complicated topics.
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 practicesFinancial 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 regressionSpecial topics: performance Python for financial algorithms, such a
The Python Quants offer, among others, the Python Quant Platform (quant-platform) and DX Analytics (dx-analytics). Yves also lectures on mathematical finance and organizes meetups and conferences about Python for Quantitative Finance in New York and London.. About the AuthorYves Hilpisch is the founder and managing partner of The Python Quants, an analytics software provider and financial engineering group
Yves Hilpisch is the founder and managing partner of The Python Quants, an analytics software provider and financial engineering group. Yves also lectures on mathematical finance and organizes meetups and conferences about Python for Quantitative Finance in New York and London.. The Python Quants offer, among others, the Python Quant Platform (quant-platform) and