Ben Graham Was a Quant: Raising the IQ of the Intelligent Investor (Wiley Finance)

Ben Graham Was a Quant: Raising the IQ of the Intelligent Investor (Wiley Finance)
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作者:
出版社: Wiley
2011-04
版次: 1
ISBN: 9780470642078
定价: 355.60
装帧: 精装
开本: 16开
纸张: 胶版纸
页数: 338页
正文语种: 英语
丛书: Wiley Finance
  • Thepioneerofvalueinvesting,BenjaminGraham,believedinaphilosophythatcontinuestobefollowedbysomeoftoday'smostsuccessfulinvestors,suchasWarrenBuffett.Partofthisphilosophyincludesadheringtoyourstockselectionprocesscome"hellorhighwater,"which,inhisview,wasoneofthemostimportantaspectsofinvesting.So,ifaquantdesignsandimplementsmathematicalmodelsforpredictingstockormarketmovements,whatbetterwaytoremainobjectivethantoinvestusingalgorithmsinaquantitativemethod?ThisisexactlywhatBenGrahamWasaQuantwillshowyouhowtodo.Openingwithabriefhistoryofquantitativeinvesting,thisbookquicklymovesontofocusonthefundamentalandfinancialfactorsusedinselecting"Graham"stocks,demonstratehowtotestthesefactorswithcurrentsoftware,anddiscusshowtocombinethemintoaquantitativemodel.Alongtheway,BenGrahamWasaQuantalsotakesthetimetodefinethesearchforAlphaandexplainwhatitis,highlightsomeoftheinadequaciesofmodernportfoliotheory,andintroducespecificriskmeasuresyoushouldbecomefamiliarwith.Oneofthebestaspectsofquantitativeinvestingisthatitultimatelyleadstodisciplined,andintelligent,investing.BenGrahamWasaQuantwillhelpyouachievethisgoalbycodifyingGraham'svaluephilosophyandcombiningitwithquantitativemethods—allwhileusingaminimumofmathematics.Withthisbookasyourguide,you'lldiscoverabetterwaytoinvest,asyoulearnhowtocreatequantitativemodelsthatfollowinthefootstepsofGraham'sprovenvalueapproach. StevenP.Greiner,Ph.D.,hasservedastheseniorquantitativestrategistandportfoliomanagerforAllegiantAssetManagement(nowwhollyownedbyPNCCapitalAdvisors)andwasamemberofitsInvestmentCommittee.Priortothis,hewasaseniorquantitativestrategistforlargecapitalizationinvestmentsatHarrisInvestmentManagement.Hehasmorethantwentyyearsofquantitativeandmodelingexperience.Currently,Dr.GreineristheheadofRiskResearchforFactSetResearchSystems.HereceivedaBSinmathematicsandchemistryfromtheUniversityofBuffalo,anMSandPhDinphysicalchemistryfromtheUniversityofRochester,andattainedpostdoctoralexperiencefromtheFreeUniversityBerlin,DepartmentofPhysics. 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 ViaBrinson 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.
  • 内容简介:
    Thepioneerofvalueinvesting,BenjaminGraham,believedinaphilosophythatcontinuestobefollowedbysomeoftoday'smostsuccessfulinvestors,suchasWarrenBuffett.Partofthisphilosophyincludesadheringtoyourstockselectionprocesscome"hellorhighwater,"which,inhisview,wasoneofthemostimportantaspectsofinvesting.So,ifaquantdesignsandimplementsmathematicalmodelsforpredictingstockormarketmovements,whatbetterwaytoremainobjectivethantoinvestusingalgorithmsinaquantitativemethod?ThisisexactlywhatBenGrahamWasaQuantwillshowyouhowtodo.Openingwithabriefhistoryofquantitativeinvesting,thisbookquicklymovesontofocusonthefundamentalandfinancialfactorsusedinselecting"Graham"stocks,demonstratehowtotestthesefactorswithcurrentsoftware,anddiscusshowtocombinethemintoaquantitativemodel.Alongtheway,BenGrahamWasaQuantalsotakesthetimetodefinethesearchforAlphaandexplainwhatitis,highlightsomeoftheinadequaciesofmodernportfoliotheory,andintroducespecificriskmeasuresyoushouldbecomefamiliarwith.Oneofthebestaspectsofquantitativeinvestingisthatitultimatelyleadstodisciplined,andintelligent,investing.BenGrahamWasaQuantwillhelpyouachievethisgoalbycodifyingGraham'svaluephilosophyandcombiningitwithquantitativemethods—allwhileusingaminimumofmathematics.Withthisbookasyourguide,you'lldiscoverabetterwaytoinvest,asyoulearnhowtocreatequantitativemodelsthatfollowinthefootstepsofGraham'sprovenvalueapproach.
  • 作者简介:
    StevenP.Greiner,Ph.D.,hasservedastheseniorquantitativestrategistandportfoliomanagerforAllegiantAssetManagement(nowwhollyownedbyPNCCapitalAdvisors)andwasamemberofitsInvestmentCommittee.Priortothis,hewasaseniorquantitativestrategistforlargecapitalizationinvestmentsatHarrisInvestmentManagement.Hehasmorethantwentyyearsofquantitativeandmodelingexperience.Currently,Dr.GreineristheheadofRiskResearchforFactSetResearchSystems.HereceivedaBSinmathematicsandchemistryfromtheUniversityofBuffalo,anMSandPhDinphysicalchemistryfromtheUniversityofRochester,andattainedpostdoctoralexperiencefromtheFreeUniversityBerlin,DepartmentofPhysics.
  • 目录:
    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 ViaBrinson 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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