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Quality money management = process e...
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Quality money management = process engineering and best practices for systematic trading and investment /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Quality money management/ Andrew Kumiega, Benjamin Van Vliet.
其他題名:
process engineering and best practices for systematic trading and investment /
作者:
Kumiega, Andrew.
其他作者:
Van Vliet, Benjamin.
出版者:
Amsterdam ;Elsevier/Academic Press, : c2008.,
面頁冊數:
viii, 295 p. :ill. ; : 27 cm.;
叢書名:
The financial market technology series
標題:
Financial engineering. -
電子資源:
An electronic book accessible through the World Wide Web; click for information
電子資源:
http://www.loc.gov/catdir/enhancements/fy0808/2007052636-d.html
ISBN:
9780123725493
Quality money management = process engineering and best practices for systematic trading and investment /
Kumiega, Andrew.
Quality money management
process engineering and best practices for systematic trading and investment /[electronic resource] :Andrew Kumiega, Benjamin Van Vliet. - Amsterdam ;Elsevier/Academic Press,c2008. - viii, 295 p. :ill. ;27 cm. - The financial market technology series.
Includes bibliographical references (p. 279-285) and index.
Contents -- Preface -- CHAPTER 1Introduction -- CHAPTER 2Key Concepts and Definitions of Terms -- CHAPTER 3Overview of the Trading/Investment System Development Methodology -- CHAPTER 4Managing Design and Development -- CHAPTER 5Types of Trading Systems -- CHAPTER 6Stage 0: The Money Document -- STAGE 1: Design and Document Trading/Investment Strategy -- CHAPTER 7STAGE 1: Overview -- CHAPTER 8Describe Trading/Investment Idea -- CHAPTER 9Research Quantitative Methods -- CHAPTER 10Prototype in Modeling Software -- CHAPTER 11Check Performance -- CHAPTER 12Gate 1 -- STAGE 2: Backtest -- CHAPTER 13STAGE 2: Overview -- CHAPTER 14Gather Historical Data -- CHAPTER 15Develop Cleaning Algorithms -- CHAPTER 16Perform In Sample / Out of Sample Tests -- CHAPTER 17Check Performance and Shadow Trade -- CHAPTER 18Gate 2 -- STAGE 3: Implement -- CHAPTER 19STAGE 3: Overview -- CHAPTER 20Plan and Document Technology Specifications -- CHAPTER 21Design System Architecture -- CHAPTER 22Build and Document the System -- CHAPTER 23Check Performance and Probationary Trade -- CHAPTER 24Gate 3 -- STAGE 4: Manage Portfolio and Risk -- CHAPTER 25 STAGE 4:Overview -- CHAPTER 26Plan Performance and Risk Processes -- CHAPTER 27Define Performance Controls -- CAHPTER 28Perform SPC Analysis -- CHAPTER 29Determine Causes of Variation -- CHAPTER 30Kaizen: Continuous Improvement.
The financial markets industry is at the same crossroads as the automotive industry in the late 1970s. Margins are collapsing and customization is rapidly increasing. The automotive industry turned to quality and its no coincidence that in the money management industry many of the spectacular failures have been due largely to problems in quality control. The financial industry in on the verge of a quality revolution. New and old firms alike are creating new investment vehicles and new strategies that are radically changing the nature of the industry. To compete, mutual funds, hedge fund industries, banks and proprietary trading firms are being forced to quicklyy research, test and implement trade selection and execution systems. And, just as in the early stages of factory automation, quality suffers and leads to defects. Many financial firms fall short of quality, lacking processes and methodologies for proper development and evaluation of trading and investment systems. Authors Kumiega and Van Vliet present a new step-by-step methodology for such development. Their methodology (called KV) has been presented in numerous journal articles and at academic and industry conferences and is rapidly being accepted as the preferred business process for the institutional trading and hedge fund industries for development, presentation, and evaluation of trading and investment systems. The KV model for trading system development combines new product development, project management and software development methodologies into one robust system. After four stages, the methodology requires repeating the entire waterfall for continuous improvement. The discussion quality and its applications to the front office is presented using lessons learned by the authors after using the methodology in the real world. As a result, it is flexible and modifiable to fit various projects in finance in different types of firms. Their methodology works equally well for short-term trading systems, longer-term portfolio management or mutual fund style investment strategies as well as more sophisticated ones employing derivative instruments in hedge funds. Additionally, readers will be able to quickly modify the standard KV methodology to meet their unique needs and to quickly build other quantitatively drive applications for finance. At the beginning and the end of the book the authors pose a key question: Are you willing to change and embrace quality for the 21st century or are willing to accept extinction? The real gem in this book is that the concepts give the reader a road map to avoid extinction. * Presents a robust process engineering framework for developing and evaluating trading and investment systems * Best practices along the step-by-step process will mitigate project risk, model risk, and ensure data quality. * Includes a quality model for backtesting and managing market risk of working systems.
Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2008.
Mode of access: World Wide Web.
ISBN: 9780123725493
Source: 134202:134330Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:
591542
Financial engineering.
Index Terms--Genre/Form:
554714
Electronic books.
LC Class. No.: HG4515.95 / .K86 2008eb
Dewey Class. No.: 332.6
Quality money management = process engineering and best practices for systematic trading and investment /
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process engineering and best practices for systematic trading and investment /
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Contents -- Preface -- CHAPTER 1Introduction -- CHAPTER 2Key Concepts and Definitions of Terms -- CHAPTER 3Overview of the Trading/Investment System Development Methodology -- CHAPTER 4Managing Design and Development -- CHAPTER 5Types of Trading Systems -- CHAPTER 6Stage 0: The Money Document -- STAGE 1: Design and Document Trading/Investment Strategy -- CHAPTER 7STAGE 1: Overview -- CHAPTER 8Describe Trading/Investment Idea -- CHAPTER 9Research Quantitative Methods -- CHAPTER 10Prototype in Modeling Software -- CHAPTER 11Check Performance -- CHAPTER 12Gate 1 -- STAGE 2: Backtest -- CHAPTER 13STAGE 2: Overview -- CHAPTER 14Gather Historical Data -- CHAPTER 15Develop Cleaning Algorithms -- CHAPTER 16Perform In Sample / Out of Sample Tests -- CHAPTER 17Check Performance and Shadow Trade -- CHAPTER 18Gate 2 -- STAGE 3: Implement -- CHAPTER 19STAGE 3: Overview -- CHAPTER 20Plan and Document Technology Specifications -- CHAPTER 21Design System Architecture -- CHAPTER 22Build and Document the System -- CHAPTER 23Check Performance and Probationary Trade -- CHAPTER 24Gate 3 -- STAGE 4: Manage Portfolio and Risk -- CHAPTER 25 STAGE 4:Overview -- CHAPTER 26Plan Performance and Risk Processes -- CHAPTER 27Define Performance Controls -- CAHPTER 28Perform SPC Analysis -- CHAPTER 29Determine Causes of Variation -- CHAPTER 30Kaizen: Continuous Improvement.
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The financial markets industry is at the same crossroads as the automotive industry in the late 1970s. Margins are collapsing and customization is rapidly increasing. The automotive industry turned to quality and its no coincidence that in the money management industry many of the spectacular failures have been due largely to problems in quality control. The financial industry in on the verge of a quality revolution. New and old firms alike are creating new investment vehicles and new strategies that are radically changing the nature of the industry. To compete, mutual funds, hedge fund industries, banks and proprietary trading firms are being forced to quicklyy research, test and implement trade selection and execution systems. And, just as in the early stages of factory automation, quality suffers and leads to defects. Many financial firms fall short of quality, lacking processes and methodologies for proper development and evaluation of trading and investment systems. Authors Kumiega and Van Vliet present a new step-by-step methodology for such development. Their methodology (called KV) has been presented in numerous journal articles and at academic and industry conferences and is rapidly being accepted as the preferred business process for the institutional trading and hedge fund industries for development, presentation, and evaluation of trading and investment systems. The KV model for trading system development combines new product development, project management and software development methodologies into one robust system. After four stages, the methodology requires repeating the entire waterfall for continuous improvement. The discussion quality and its applications to the front office is presented using lessons learned by the authors after using the methodology in the real world. As a result, it is flexible and modifiable to fit various projects in finance in different types of firms. Their methodology works equally well for short-term trading systems, longer-term portfolio management or mutual fund style investment strategies as well as more sophisticated ones employing derivative instruments in hedge funds. Additionally, readers will be able to quickly modify the standard KV methodology to meet their unique needs and to quickly build other quantitatively drive applications for finance. At the beginning and the end of the book the authors pose a key question: Are you willing to change and embrace quality for the 21st century or are willing to accept extinction? The real gem in this book is that the concepts give the reader a road map to avoid extinction. * Presents a robust process engineering framework for developing and evaluating trading and investment systems * Best practices along the step-by-step process will mitigate project risk, model risk, and ensure data quality. * Includes a quality model for backtesting and managing market risk of working systems.
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