Python Finance by Yuxing Yan (46 results)
- Softcover
Seller: BooksRun, Philadelphia, U.S.A.BooksRun
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Paperback. Condition: Fair. 2nd ed. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
Python for Finance: Apply powerful finance models and quantitative analysis with Python, 2nd Edition
- Softcover
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- Softcover
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- Softcover
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- Softcover
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Python for Finance: Apply powerful finance models and quantitative analysis with Python, 2nd Edition
- Softcover
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- Softcover
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- Softcover
Seller: BargainBookStores, Grand Rapids, U.S.A.BargainBookStores
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Paperback or Softback. Condition: New. Python for Finance. Book.
- Softcover
Seller: California Books, Miami, U.S.A.California Books
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- Softcover
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- Softcover
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paperback. Condition: New. 2nd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
- Softcover
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Paperback or Softback. Condition: New. Python for Finance. Book.
- Softcover
Seller: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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Python for Finance: Apply powerful finance models and quantitative analysis with Python, 2nd Edition
- Softcover
Seller: California Books, Miami, U.S.A.California Books
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- Softcover
Seller: Books Puddle, New York, U.S.A.Books Puddle
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Condition: New. pp. 408.
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Softcover
Seller: Rarewaves.com USA, London, United KingdomRarewaves.com USA
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US$ 81.00
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Digital. Condition: New. Learn and implement various Quantitative Finance concepts using the popular Python librariesAbout This Book. Understand the fundamentals of Python data structures and work with time-series data. Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplo…tlib. A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to financeWho This Book Is ForThis book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.What You Will Learn. Become acquainted with Python in the first two chapters. Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models. Learn how to price a call, put, and several exotic options. Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options. Understand the concept of volatility and how to test the hypothesis that volatility changes over the years. Understand the ARCH and GARCH processes and how to write related Python programsIn DetailThis book uses Python as its computational tool. Since Python is free, any school or organization can download and use it.This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures.This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.Style and approachThis book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.
- Softcover
Seller: online-buch-de, Dozwil, Switzerlandonline-buch-de
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US$ 41.56
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Paperback Apr 25, 2014. Condition: gebraucht; wie neu.
- Softcover
Seller: GreatBookPrices, Columbia, U.S.A.GreatBookPrices
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US$ 80.37
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Condition: As New. Unread book in perfect condition.
Python for Finance: Apply powerful finance models and quantitative analysis with Python, 2nd Edition
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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US$ 68.35
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Condition: New. In.
Python for Finance: Apply powerful finance models and quantitative analysis with Python, 2nd Edition
- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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US$ 64.67
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Paperback. Condition: New.
- Softcover
Seller: Books Puddle, New York, U.S.A.Books Puddle
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US$ 82.07
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Condition: New. pp. 586 2nd Edition.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 68.08
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Condition: New.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 72.14
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- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 77.19
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
Contact seller5-star sellerCondition: Used - Very good
US$ 36.33
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Condition: Gut. Zustand: Gut | Seiten: 586 | Sprache: Englisch | Produktart: Bücher | Learn and implement various Quantitative Finance concepts using the popular Python libraries Key Features:Understand the fundamentals of Python data structures and work with time-series data Implement key concepts in quantitative finance using…popular Python libraries such as NumPy, SciPy, and matplotlib A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance Book Description: This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option. What You Will Learn:Become acquainted with Python in the first two chapters Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models Learn how to price a call, put, and several exotic options Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options Understand the concept of volatility and how to test the hypothesis that volatility changes over the years Understand the ARCH and GARCH processes and how to write related Python programs Who this book is for: This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
Contact seller5-star sellerCondition: New
US$ 77.46
US$ 86.67 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Digital. Condition: New. Learn and implement various Quantitative Finance concepts using the popular Python librariesAbout This Book. Understand the fundamentals of Python data structures and work with time-series data. Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplo…tlib. A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to financeWho This Book Is ForThis book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.What You Will Learn. Become acquainted with Python in the first two chapters. Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models. Learn how to price a call, put, and several exotic options. Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options. Understand the concept of volatility and how to test the hypothesis that volatility changes over the years. Understand the ARCH and GARCH processes and how to write related Python programsIn DetailThis book uses Python as its computational tool. Since Python is free, any school or organization can download and use it.This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures.This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.Style and approachThis book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.
