Python For Financial Modeling
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Financial Modelling In Python
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Author : Shayne Fletcher
language : en
Publisher: John Wiley & Sons
Release Date : 2010-10-28
Financial Modelling In Python written by Shayne Fletcher 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 2010-10-28 with Business & Economics categories.
"Fletcher and Gardner have created a comprehensive resource that will be of interest not only to those working in the field of finance, but also to those using numerical methods in other fields such as engineering, physics, and actuarial mathematics. By showing how to combine the high-level elegance, accessibility, and flexibility of Python, with the low-level computational efficiency of C++, in the context of interesting financial modeling problems, they have provided an implementation template which will be useful to others seeking to jointly optimize the use of computational and human resources. They document all the necessary technical details required in order to make external numerical libraries available from within Python, and they contribute a useful library of their own, which will significantly reduce the start-up costs involved in building financial models. This book is a must read for all those with a need to apply numerical methods in the valuation of financial claims." –David Louton, Professor of Finance, Bryant University This book is directed at both industry practitioners and students interested in designing a pricing and risk management framework for financial derivatives using the Python programming language. It is a practical book complete with working, tested code that guides the reader through the process of building a flexible, extensible pricing framework in Python. The pricing frameworks' loosely coupled fundamental components have been designed to facilitate the quick development of new models. Concrete applications to real-world pricing problems are also provided. Topics are introduced gradually, each building on the last. They include basic mathematical algorithms, common algorithms from numerical analysis, trade, market and event data model representations, lattice and simulation based pricing, and model development. The mathematics presented is kept simple and to the point. The book also provides a host of information on practical technical topics such as C++/Python hybrid development (embedding and extending) and techniques for integrating Python based programs with Microsoft Excel.
Python For Financial Modeling
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Author : Thompson Carter
language : en
Publisher: Independently Published
Release Date : 2025-01-09
Python For Financial Modeling written by Thompson Carter and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
Python for Financial Modeling: Build Powerful Financial Models Using Python's Data Science Libraries Take your financial analysis to the next level with Python for Financial Modeling. This practical guide shows you how to leverage Python's powerful data science libraries to create advanced financial models, automate tasks, and gain deeper insights into financial data. Designed for finance professionals, analysts, and data enthusiasts, this book provides a hands-on approach to solving real-world financial challenges. From analyzing stock prices to building risk management models, you'll learn to use Python as a powerful tool for making data-driven decisions and optimizing financial performance. What You'll Learn: Core Python programming concepts essential for financial modeling. Working with libraries like pandas, NumPy, and matplotlib for data analysis and visualization. Building financial models for valuation, portfolio optimization, and risk assessment. Automating financial tasks such as data scraping, cleaning, and reporting. Creating predictive models using machine learning techniques for financial forecasting. Real-world case studies, including stock market analysis and Monte Carlo simulations. Whether you're managing investments, analyzing market trends, or creating reports, this book equips you with the skills to confidently apply Python in finance and transform raw data into actionable insights. Unlock the future of financial modeling with Python for Financial Modeling. Empower your career and make smarter financial decisions today!
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.
Financial Modeling Mastery
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Author : William Johnson
language : en
Publisher: HiTeX Press
Release Date : 2024-10-11
Financial Modeling Mastery 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 2024-10-11 with Business & Economics categories.
"Financial Modeling Mastery: Building Robust Models for Market Success" is a comprehensive guide crafted to empower readers with the essential skills and knowledge needed to navigate the intricate world of financial modeling. Geared towards both novices and seasoned professionals, this book delves into the foundational principles of quantitative finance, portfolio management, and financial market dynamics, while seamlessly integrating advanced topics such as machine learning, algorithmic trading, and risk management. Through clear explanations and real-world applications, readers will gain the ability to construct sophisticated models that inform strategic decision-making and optimize investment strategies. Each chapter is meticulously designed to build upon the last, ensuring a coherent understanding of how various mathematical tools, valuation techniques, and data analysis methods translate into actionable financial insights. The practical focus is augmented by a deep dive into the ethical considerations and best practices necessary for creating transparent and reliable models. By the conclusion of this volume, readers will not only possess a robust toolkit for financial analysis but also the confidence to leverage these models to identify opportunities and mitigate risks in today's complex financial landscape.
Python For Excel Pros
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Author : REACTIVE. PUBLISHING
language : en
Publisher: Independently Published
Release Date : 2025-03-20
Python For Excel Pros 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 2025-03-20 with Computers categories.
Reactive Publishing Supercharge your Excel workflows with the power of Python-the ultimate tool for finance professionals, analysts, and data-driven decision-makers. Python for Excel Pros is your complete guide to automating financial modeling, streamlining data analysis, and unlocking next-level efficiency in Excel. This book bridges the gap between traditional Excel methods and the future of financial automation, equipping you with the tools to enhance productivity, eliminate repetitive tasks, and build dynamic financial models. Whether you're a financial analyst, accountant, or data scientist, this book delivers a high-performance framework to take your Excel expertise to the next level. What You'll Learn: Python + Excel Integration - Use libraries like pandas, openpyxl, and xlwings to automate workflows. Advanced Financial Modeling - Build dynamic, scalable models beyond Excel's built-in functions. Data Automation & Analysis - Process large datasets with Python's superior efficiency. Real-Time Data Processing - Connect to APIs, import market data, and automate updates. Excel Macros & VBA vs. Python - Transition from legacy automation to modern Python scripting. Machine Learning in Excel - Apply AI-driven insights for predictive financial analysis. Whether you're enhancing corporate finance reports, optimizing investment models, or automating complex calculations, this book delivers the Python-powered strategies you need to stay ahead in finance and analytics. The future of Excel is Python-master it today.
Financial Theory With Python
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Author : Yves Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-23
Financial Theory With Python 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 2021-09-23 with Business & Economics categories.
Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance. Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other. Draw upon mathematics to learn the foundations of financial theory and Python programming Learn about financial theory, financial data modeling, and the use of Python for computational finance Leverage simple economic models to better understand basic notions of finance and Python programming concepts Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy
Financial Modeling Fifth Edition
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Author : Simon Benninga
language : en
Publisher: MIT Press
Release Date : 2022-02-01
Financial Modeling Fifth Edition written by Simon Benninga and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Business & Economics categories.
A substantially updated new edition of the essential text on financial modeling, with revised material, new data, and implementations shown in Excel, R, and Python. Financial Modeling has become the gold-standard text in its field, an essential guide for students, researchers, and practitioners that provides the computational tools needed for modeling finance fundamentals. This fifth edition has been substantially updated but maintains the straightforward, hands-on approach, with an optimal mix of explanation and implementation, that made the previous editions so popular. Using detailed Excel spreadsheets, it explains basic and advanced models in the areas of corporate finance, portfolio management, options, and bonds. This new edition offers revised material on valuation, second-order and third-order Greeks for options, value at risk (VaR), Monte Carlo methods, and implementation in R. The examples and implementation use up-to-date and relevant data. Parts I to V cover corporate finance topics, bond and yield curve models, portfolio theory, options and derivatives, and Monte Carlo methods and their implementation in finance. Parts VI and VII treat technical topics, with part VI covering Excel and R issues and part VII (now on the book’s auxiliary website) covering Excel’s programming language, Visual Basic for Applications (VBA), and Python implementations. Knowledge of technical chapters on VBA and R is not necessary for understanding the material in the first five parts. The book is suitable for use in advanced finance classes that emphasize the need to combine modeling skills with a deeper knowledge of the underlying financial models.
Stochastic Finance With Python
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Author : Avishek Nag
language : en
Publisher: Springer Nature
Release Date : 2024-12-13
Stochastic Finance With Python written by Avishek Nag and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Computers categories.
Journey through the world of stochastic finance from learning theory, underlying models, and derivations of financial models (stocks, options, portfolios) to the almost production-ready Python components under cover of stochastic finance. This book will show you the techniques to estimate potential financial outcomes using stochastic processes implemented with Python. The book starts by reviewing financial concepts, such as analyzing different asset types like stocks, options, and portfolios. It then delves into the crux of stochastic finance, providing a glimpse into the probabilistic nature of financial markets. You’ll look closely at probability theory, random variables, Monte Carlo simulation, and stochastic processes to cover the prerequisites from the applied perspective. Then explore random walks and Brownian motion, essential in understanding financial market dynamics. You’ll get a glimpse of two vital modelling tools used throughout the book - stochastic calculus and stochastic differential equations (SDE). Advanced topics like modeling jump processes and estimating their parameters by Fourier-transform-based density recovery methods can be intriguing to those interested in full-numerical solutions of probability models. Moving forward, the book covers options, including the famous Black-Scholes model, dissecting it from both risk-neutral probability and PDE perspectives. A chapter at the end also covers the discovery of portfolio theory, beginning with mean-variance analysis and advancing to portfolio simulation and the efficient frontier. What You Will Learn Understand applied probability and statistics with finance Design forecasting models of the stock price with the stochastic process, Monte-Carlo simulation. Option price estimation with both risk-neutral probabilistic and PDE-driven approach. Use Object-oriented Python to design financial models with reusability. Who This Book Is For Data scientists, quantitative researchers and practitioners, software engineers and AI architects interested in quantitative finance
Data Analysis For Corporate Finance Building Financial Models Using Sql Python And Ms Powerbi
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Author : Mariano F. Scandizzo Cfa Cqf
language : en
Publisher: Fulton Books
Release Date : 2021-09-21
Data Analysis For Corporate Finance Building Financial Models Using Sql Python And Ms Powerbi written by Mariano F. Scandizzo Cfa Cqf and has been published by Fulton Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Business & Economics categories.
Have you ever tried to learn to code or to use advanced visualization tools? If so, I am sure you know how daunting it is to learn by yourself. Generally, tools and books follow an encyclopedism approach, i.e., books attempt to teach every feature about a coding language or tool. This implies hundreds, if not thousands of pages simply to tackle a single topic, whether SQL, Python, MS Excel, MS PowerBI, you name it. The journey from zero to hero to become proficient using numerical and visualization tools to take your career to the next level becomes an ordeal that requires years and thousands of pages just to begin putting the pieces of the puzzle together. However, the reality is that you do not need to learn absolutely every available feature to use those tools and deliver a superior project. Rather than teaching you about the forest, I will discuss specific trees. Why? Because once you become familiar and confident nurturing a few trees, growing a forest becomes a simple process of planting new trees. This book provides the fundamental blocks so that you can learn about financial data science and take these tools and start using them tomorrow. The scope of the selected tools will empower you to see a considerable improvement in your financial modeling skills. The book is designed to provide corporate finance professionals the ability to start immediately using advance tools for concrete real-world tasks. Therefore, this book is all about functionalism. It is about providing you with tools that will put you to work and dramatically change the way you analyze data. Once you see the benefits, it will become natural to keep expanding your domain knowledge, leveraging today's endless available educational resources.
Python In Excel For Finance
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Author : Hayden Van Der Post
language : en
Publisher: Independently Published
Release Date : 2025-10-06
Python In Excel For Finance written by Hayden Van Der Post and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-06 with Business & Economics categories.
Reactive Publishing The world of finance has changed, and so has Excel. With Python now seamlessly integrated into Microsoft Excel, financial modeling, forecasting, and data optimization have entered a new era. In Python in Excel for Finance, Hayden Van Der Post, renowned author, financial strategist, and data automation expert, reveals how to combine the familiarity of Excel with the power of Python to unlock professional-grade insights, automation, and predictive modeling. This groundbreaking guide bridges the gap between traditional finance and next-generation analytics. Designed for FP&A professionals, quantitative analysts, and financial engineers, it delivers a step-by-step roadmap for building smarter models, accelerating workflows, and enhancing decision-making precision. Inside you'll discover how to: Integrate Python directly inside Excel for seamless financial modeling Automate repetitive FP&A workflows and reporting pipelines Build Monte Carlo simulations and dynamic forecasting models Apply advanced statistical and optimization techniques for real-world finance Connect Excel to live APIs, databases, and data feeds for real-time insights Create interactive dashboards powered by Python logic and visualization libraries Transition from legacy VBA systems to modern, scalable automation Whether you're managing cash flows, analyzing portfolios, or designing quantitative strategies, this book equips you with the tools to think algorithmically, and execute flawlessly. No coding background required. No external integrations. Just Excel supercharged with Python, ready to redefine what's possible in finance.