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  • Ben Graham Was A Quant: Raising The IQ Of The Intelligent In
    該商品所屬分類:投資理財 -> 投資理財
    【市場價】
    3289-4768
    【優惠價】
    2056-2980
    【作者】 Steven 
    【所屬類別】 圖書  英文原版書  經管類Business  ProfessionalInvesting圖書  投資理財  英文原版書-投資理財 
    【出版社】Wiley 
    【ISBN】9780470642078
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    內容介紹



    開本:16開
    紙張:膠版紙
    包裝:精裝

    是否套裝:否
    國際標準書號ISBN:9780470642078
    叢書名:Wiley

    作者:Steven
    出版社:Wiley
    出版時間:2011年04月 


        
        
    "

    內容簡介
    Innovative insights on creating models that will help youbecome a disciplined intelligent investor
    The pioneer of value investing, Benjamin Graham, believed in aphilosophy that continues to be followed by some of today's mostsuccessful investors, such as Warren Buffett. Part of thisphilosophy includes adhering to your stock selection process come"hell or high water" which, in his view, was one of the mostimportant aspects of investing.
    So, if a quant designs and implements mathematical models forpredicting stock or market movements, what better way to remainobjective, then to invest using algorithms or the quantitativemethod? This is exactly what Ben Graham Was a Quant will show youhow to do. Opening with a brief history of quantitative investing,this book quickly moves on to focus on the fundamental andfinancial factors used in selecting "Graham" stocks, demonstratehow to test these factors, and discuss how to combine them into aquantitative model.
    Reveals how to create custom screens based on Ben Graham'smethods for security selection

    Innovative insights on creating models that will help you
    become a disciplined intelligent investor

    The pioneer of value investing, Benjamin Graham, believed in a
    philosophy that continues to be followed by some of today's most
    successful investors, such as Warren Buffett. Part of this
    philosophy includes adhering to your stock selection process come
    hell or high water" which, in his view, was one of the most
    important aspects of investing.

    So, if a quant designs and implements mathematical models for
    predicting stock or market movements, what better way to remain
    objective, then to invest using algorithms or the quantitative
    method? This is exactly what Ben Graham Was a Quant will show you
    how to do. Opening with a brief history of quantitative investing,
    this book quickly moves on to focus on the fundamental and
    financial factors used in selecting "Graham" stocks, demonstrate
    how to test these factors, and discuss how to combine them into a
    quantitative model.

    Reveals how to create custom screens based on Ben Graham's
    methods for security selection

    Addresses what it takes to find those factors most influential in
    forecasting stock returns

    Explores how to design models based on other styles and
    international strategies

    If you want to become a better investor, you need solid insights
    and the proper guidance. With Ben Graham Was a Quant, you'll
    receive this and much more, as you learn how to create quantitative
    models that follow in the footsteps of Graham's value
    philosophy.

    作者簡介

    Steven P. Greiner, Ph.D., has served as the senior
    quantitative strategist and portfolio manager for Allegiant Asset
    Management (now wholly owned by PNC Capital Advisors) and was a
    member of its Investment Committee. Prior to this, he was a senior
    quantitative strategist for large capitalization investments at
    Harris Investment Management. He has more than twenty years of
    quantitative and modeling experience. Currently, Dr. Greiner is the
    head of Risk Research for FactSet Research Systems. He received a
    BS in mathematics and chemistry from the University of Buffalo, an
    MS and PhD in physical chemistry from the University of Rochester,
    and attained postdoctoral experience from the Free University
    Berlin, Department of Physics.

    目錄
    Preface.
    Introduction: The Birth of the Quant.
    Characterizing the Quant.
    Active versus Passive Investing.
    Chapter 1: Desperately Seeking Alpha.
    The Beginnings of the Modern Alpha Era.
    Important History of Investment Management.
    Methods of Alpha Searching.
    Chapter 2: Risky Business.
    Experienced versus Exposed Risk.
    The Black Swan: A Minor ELE Event—Are Quants to Blame?
    Active versus Passive Risk.
    Other Risk Measures: VAR, CVAR, and ETL.
    Summary.

    Preface.


    Introduction: The Birth of the Quant.


    Characterizing the Quant.


    Active versus Passive Investing.


    Chapter 1: Desperately Seeking Alpha.


    The Beginnings of the Modern Alpha Era.


    Important History of Investment Management.


    Methods of Alpha Searching.


    Chapter 2: Risky Business.


    Experienced versus Exposed Risk.


    The Black Swan: A Minor ELE Event—Are Quants to Blame?


    Active versus Passive Risk.


    Other Risk Measures: VAR, CVAR, and ETL.


    Summary.


    Chapter 3: Beta Is Not Sharpe Enough.


    Back to Beta.


    Beta and Volatility.


    The Way to a Better “Beta”: Introducing the g-Factor.


    Tracking Error: The Deviant Differential Measurer.


    Summary.


    Chapter 4: Mr. Graham, I Give You Intelligence.


    Fama-French Equation.


    The Graham Formula.


    Factors for Use in Quant Models.


    Momentum: Increasing Investor Interest.


    Volatility as a Factor in Alpha Models.


    Chapter 5: Modeling Pitfalls and Perils.


    Data Availability, Look-Ahead, and Survivorship Biases.


    Building Models One Can Trust.


    Scenario, Out-Of-Sample, and Shock Testing.


    Data Snooping and Mining.


    Statistical Significance and Other Fascinations.


    Choosing an Investment Philosophy.


    Growth, Value, Quality.


    Investment Consultant as Dutch Uncle.


    Where are the Relative Growth Managers?


    Chapter 6: Testing the Graham “Crackers”...er,
    Factors.


    The First Tests: Sorting.


    Time-Series Plots.


    The Next Tests: Scenario Analysis.


    Chapter 7: Building Models from Factors.


    Surviving Factors.


    Weighting the Factors.


    The Art versus Science of Modeling.


    Time-Series of Returns.


    Other Conditional Information.


    The Final Model.


    Other Methods of Measuring Performance: Attribution Analysis Via
    Brinson and Risk Decomposition.


    Regression of the Graham Factors with Forward Returns.


    Chapter 8: Building Portfolios from Models.


    The Deming Way: Benchmarking Your Portfolio.


    Portfolio Construction Issues.


    Using an Online Broker: Fidelity, E*Trade, TD-Ameritrade,
    Schwab, Interactive Brokers, and TradeStation.


    Working with A Professional Investment Management System:
    Bloomberg, Clarify, and Factset.


    Chapter 9: Barguments: The Anti-Dementia Bacterium.


    The Colossal Non-Failure of Asset Allocation.


    The Stock Market as a Class of Systems.


    Stochastic Portfolio Theory: An Introduction.


    Portfolio Optimization: The Layman’s Perspective.


    Tax-Efficient Optimization.


    Summary.


    Chapter 10: Past and Future View.


    Why did Global Contagion and Meltdown Occur?


    Fallout of Crises.


    The Rise of the Multi-National State Owned Enterprises.


    The Emerged Markets.


    The Future Quant.


    Notes.


    Acknowledgments.


    About the Author.


    Index.



     
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