Quantitative Methods Finance Using by Fry John (18 results)
- Softcover
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condition: new. Paperback. The book will form a solid foundation to support the transition of students into the world of work or further research.Professor Jane M Binner, Chair of Finance, Department of Finance, University of Birmingham, UKIn over 20 years of teaching quantitative methods, I have rarely come across a…book such as this which meets/exceeds all the expectations of its intended audience so wellTuan Yu, Lecturer, Kent Business School, Canterbury, UKThis is a fantastic book for anyone wanting to understand, learn and apply quantitative methods in finance using R Professor Raphael Markellos, Professor of Finance, Norwich Business School, UKQuantitative Methods in Finance Using R draws on the extensive teaching and research expertise of John Fry and Matt Burke, covering a wide range of quantitative methods in Finance that utilise the freely downloadable R software. With software playing an increasingly important role in finance, this book is a must-have introduction for finance students who want to explore how they can undertake their own quantitative analyses in dissertation and project work.Assuming no prior knowledge, and taking a holistic approach, this brand new title guides you from first principles and help to build your confidence in tackling large data sets in R. Complete with examples and exercises with worked solutions, Fry and Burke demonstrate how to use the R freeware for regression and linear modelling, with attention given to presentation and the importance of good writing and presentation skills in project work and data analysis more generally.Through this book, you will develop your understanding of:Descriptive statisticsInferential statisticsRegressionAnalysis of varianceProbability regression modelsMixed modelsFinancial and non-financial time seriesJohn Fry is a senior lecturer in Applied Mathematics at the University of Hull. Fry has a PhD in Mathematical Finance from the University of Sheffield. His main research interests span mathematical finance, econophysics, statistics and operations research. Matt Burke is a senior lecturer in Finance at Sheffield Hallam University. He holds a PhD in Finance from the University of East Anglia. Burkes main research interests lie in asset pricing and climate finance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
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- Softcover
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- Softcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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- Softcover
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- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 262 pages. 9.02x5.98x0.59 inches. In Stock.
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- Softcover
Seller: moluna, Greven, Germanymoluna
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Kartoniert / Broschiert. Condition: New. InhaltsverzeichnisChapter 1. IntroductionChapter 2. Summary statistics and elementary data presentation Chapter 3. Basic hypothesis testsChapter 4. An introduction to regressionChapter 5. The extra sum of squares princip.
- Softcover
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condition: new. Paperback. The book will form a solid foundation to support the transition of students into the world of work or further research.Professor Jane M Binner, Chair of Finance, Department of Finance, University of Birmingham, UKIn over 20 years of teaching quantitative methods, I have rarely come across a…book such as this which meets/exceeds all the expectations of its intended audience so wellTuan Yu, Lecturer, Kent Business School, Canterbury, UKThis is a fantastic book for anyone wanting to understand, learn and apply quantitative methods in finance using R Professor Raphael Markellos, Professor of Finance, Norwich Business School, UKQuantitative Methods in Finance Using R draws on the extensive teaching and research expertise of John Fry and Matt Burke, covering a wide range of quantitative methods in Finance that utilise the freely downloadable R software. With software playing an increasingly important role in finance, this book is a must-have introduction for finance students who want to explore how they can undertake their own quantitative analyses in dissertation and project work.Assuming no prior knowledge, and taking a holistic approach, this brand new title guides you from first principles and help to build your confidence in tackling large data sets in R. Complete with examples and exercises with worked solutions, Fry and Burke demonstrate how to use the R freeware for regression and linear modelling, with attention given to presentation and the importance of good writing and presentation skills in project work and data analysis more generally.Through this book, you will develop your understanding of:Descriptive statisticsInferential statisticsRegressionAnalysis of varianceProbability regression modelsMixed modelsFinancial and non-financial time seriesJohn Fry is a senior lecturer in Applied Mathematics at the University of Hull. Fry has a PhD in Mathematical Finance from the University of Sheffield. His main research interests span mathematical finance, econophysics, statistics and operations research. Matt Burke is a senior lecturer in Finance at Sheffield Hallam University. He holds a PhD in Finance from the University of East Anglia. Burkes main research interests lie in asset pricing and climate finance. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Softcover
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Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 262 pages. 9.02x5.98x0.59 inches. In Stock. This item is printed on demand.
- Softcover
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- Softcover
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Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Softcover
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Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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