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Numpy For Quantitative Finance

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Numpy For Quantitative Finance

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Author : Reactive Publishing
language : en
Publisher: Independently Published
Release Date : 2024-06-04

Numpy For Quantitative Finance written by Reactive Publishing and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-04 with Business & Economics categories.

Reactive Publishing Unlock the potential of NumPy in the realm of quantitative finance with "NumPy with Quantitative Finance," an essential guide for financial analysts, data scientists, and quantitative researchers. This expert-level book bridges the gap between Python programming and financial theory, providing a comprehensive resource for applying NumPy to solve complex financial problems. Dive into financial data manipulation, statistical analysis, and mathematical modeling using NumPy's robust array processing capabilities. This book offers practical, hands-on examples and detailed explanations to help you master key concepts such as portfolio optimization, risk management, derivatives pricing, and algorithmic trading. Written by industry experts, "NumPy with Quantitative Finance" covers: Efficient data handling and preprocessing for financial datasets Advanced statistical methods and time series analysis Implementation of Monte Carlo simulations for risk assessment Optimization techniques for portfolio management Pricing of complex derivatives using numerical methods Development of quantitative trading strategies With this book, you'll gain the knowledge and skills to leverage NumPy for powerful quantitative finance applications, enhancing your analytical capabilities and driving more informed financial decisions. Elevate your expertise and stay ahead in the competitive financial landscape.

Quantitative Finance With Python

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Author : Chris Kelliher
language : en
Publisher: CRC Press
Release Date : 2022-05-19

Quantitative Finance With Python written by Chris Kelliher and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-19 with Business & Economics categories.

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.

Python For Finance

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Author : Yuxing Yan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-04-25

Python For Finance written by Yuxing Yan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-25 with Computers categories.

A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.

An Introduction To Machine Learning In Quantitative Finance

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Author : Hao Ni
language : en
Publisher: World Scientific
Release Date : 2021-04-07

An Introduction To Machine Learning In Quantitative Finance written by Hao Ni and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-07 with Business & Economics categories.

In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!

Applied Quantitative Finance

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Author : Mauricio Garita
language : en
Publisher: Springer Nature
Release Date : 2021-09-03

Applied Quantitative Finance written by Mauricio Garita and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-03 with Business & Economics categories.

This book provides both conceptual knowledge of quantitative finance and a hands-on approach to using Python. It begins with a description of concepts prior to the application of Python with the purpose of understanding how to compute and interpret results. This book offers practical applications in the field of finance concerning Python, a language that is more and more relevant in the financial arena due to big data. This will lead to a better understanding of finance as it gives a descriptive process for students, academics and practitioners.

Advanced Quantitative Finance

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Author : William Johnson
language : en
Publisher: HiTeX Press
Release Date : 2024-10-18

Advanced Quantitative Finance written by William Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-18 with Business & Economics categories.

"Advanced Quantitative Finance: Trading, Risk, and Portfolio Optimization" unfolds as an essential guide for anyone eager to delve into the sophisticated world of modern finance. This comprehensive text blends theoretical underpinnings with practical insights, offering a robust exploration of the quantitative techniques driving today's markets. Each chapter systematically demystifies complex subjects—from risk management and derivatives pricing to algorithmic trading and asset pricing models—empowering readers to grasp the nuances of financial analysis with clarity and precision. Structured for both novices and seasoned professionals, the book navigates the latest advancements in machine learning, big data analytics, and behavioral finance, presenting them as indispensable tools for the contemporary financial landscape. With a focus on actionable knowledge and strategic applications, readers will gain the proficiency needed to enhance their decision-making, optimize investment portfolios, and effectively manage risk in an ever-evolving economic environment. This book is your invitation to not only understand quantitative finance but to excel in it, unlocking new levels of insight and innovation in your financial pursuits.

Python For Finance

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Author : Yves Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-12-11

Python For Finance written by Yves Hilpisch and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-11 with Business & Economics categories.

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

Python For Finance

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Author : Yves Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-12-11

Mastering Pandas For Finance

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Author : Michael Heydt
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-05-25

Mastering Pandas For Finance written by Michael Heydt and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-25 with Computers categories.

If you are interested in quantitative finance, 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 knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

Machine Learning For Risk Calculations

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Author : Ignacio Ruiz
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-28

Machine Learning For Risk Calculations written by Ignacio Ruiz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-28 with Business & Economics categories.

State-of-the-art algorithmic deep learning and tensoring techniques for financial institutions The computational demand of risk calculations in financial institutions has ballooned and shows no sign of stopping. It is no longer viable to simply add more computing power to deal with this increased demand. The solution? Algorithmic solutions based on deep learning and Chebyshev tensors represent a practical way to reduce costs while simultaneously increasing risk calculation capabilities. Machine Learning for Risk Calculations: A Practitioner’s View provides an in-depth review of a number of algorithmic solutions and demonstrates how they can be used to overcome the massive computational burden of risk calculations in financial institutions. This book will get you started by reviewing fundamental techniques, including deep learning and Chebyshev tensors. You’ll then discover algorithmic tools that, in combination with the fundamentals, deliver actual solutions to the real problems financial institutions encounter on a regular basis. Numerical tests and examples demonstrate how these solutions can be applied to practical problems, including XVA and Counterparty Credit Risk, IMM capital, PFE, VaR, FRTB, Dynamic Initial Margin, pricing function calibration, volatility surface parametrisation, portfolio optimisation and others. Finally, you’ll uncover the benefits these techniques provide, the practicalities of implementing them, and the software which can be used. Review the fundamentals of deep learning and Chebyshev tensors Discover pioneering algorithmic techniques that can create new opportunities in complex risk calculation Learn how to apply the solutions to a wide range of real-life risk calculations. Download sample code used in the book, so you can follow along and experiment with your own calculations Realize improved risk management whilst overcoming the burden of limited computational power Quants, IT professionals, and financial risk managers will benefit from this practitioner-oriented approach to state-of-the-art risk calculation.

Numpy For Quantitative Finance

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