Selfdual Variational Principles for Periodic Solutions of Hamiltonian and Other Dynamical S

陇东学院课程教案
2012-2013学年第二学期
课程名称：投资学
授课专业：财务管理专业
授课班级：2011级财管班
主讲教师：齐欣
所属院系部：经济管理学院
教研室：应用经济学教研室
教材名称：投资学
出版社、版次：中国人民大学出版社
第一版
2013年3月3日
陇东学院课程教案(首页）
陇东学院课程教案
使计算投资组合的期望收益率及期望收益率的方差。

参考资料（含参考书、文献、网址等）:
（1）是否有人会有兴趣投资股票B？
参考资料(含参考书、文献、网址等）：
如果无风险收益率是3％，计算收益—变动比率并排序。

2。

A先生投资5万元申购一只LOF基金-南方高增长，他采取了场外申购，即通过银行柜台等申购方式。

投资人A打算在天成基金和另一家以上证综指业绩为目标的基金中选择一家进行投资。

如果仅仅参考。

Macroeconomics R. GLENN HUBBARD COLUMBIA UNIVERSITY ANTHONY PATRICK O’BRIEN LEHIGH UNIVERSITY MATTHEW RAFFERTY QUINNIPIAC UNIVERSITY Boston Columbus Indianapolis New York San Francisco Upper Saddle RiverAmsterdam Cape Town Dubai London Madrid Milan Munich Paris Montreal Toronto Delhi Mexico City So Paulo Sydney Hong Kong Seoul Singapore Taipei TokyoAbout the AuthorsGlenn Hubbard Professor Researcher and Policymaker R. Glenn Hubbard is the dean and Russell L. Carson Professor of Finance and Economics in the Graduate School of Business at Columbia University and professor of economics in Columbia’s Faculty of Arts and Sciences. He is also a research associate of the National Bureau of Economic Research and a director of Automatic Data Processing Black Rock Closed- End Funds KKR Financial Corporation and MetLife. Professor Hubbard received his Ph.D. in economics from Harvard University in 1983. From 2001 to 2003 he served as chairman of the White House Council of Economic Advisers and chairman of the OECD Economy Policy Commit- tee and from 1991 to 1993 he was deputy assistant secretary of the U.S. Treasury Department. He currently serves as co-chair of the nonpar-tisan Committee on Capital Markets Regulation and the Corporate Boards Study Group. ProfessorHubbard is the author of more than 100 articles in leading journals including American EconomicReview Brookings Papers on Economic Activity Journal of Finance Journal of Financial EconomicsJournal of Money Credit and Banking Journal of Political Economy Journal of Public EconomicsQuarterly Journal of Economics RAND Journal of Economics and Review of Economics and Statistics.Tony O’Brien Award-Winning Professor and Researcher Anthony Patrick O’Brien is a professor of economics at Lehigh University. He received a Ph.D. from the University of California Berkeley in 1987. He has taught principles of economics money and banking and interme- diate macroeconomics for more than 20 years in both large sections and small honors classes. He received the Lehigh University Award for Distin- guished Teaching. He was formerly the director of the Diamond Center for Economic Education and was named a Dana Foundation Faculty Fel- low and Lehigh Class of 1961 Professor of Economics. He has been a visit- ing professor at the University of California Santa Barbara and Carnegie Mellon University. Professor O’Brien’s research has dealt with such issues as the evolution of the U.S. automobile industry sources of U.S. economiccompetitiveness the development of U.S. trade policy the causes of the Great Depression and thecauses of black–white income differences. His research has been published in leading journals in-cluding American Economic Review Quarterly Journal of Economics Journal of Money Credit andBanking Industrial Relations Journal of Economic History Explorations in Economic History andJournal of PolicyHistory.Matthew Rafferty Professor and Researcher Matthew Christopher Rafferty is a professor of economics and department chairperson at Quinnipiac University. He has also been a visiting professor at Union College. He received a Ph.D. from the University of California Davis in 1997 and has taught intermediate macroeconomics for 15 years in both large and small sections. Professor Rafferty’s research has f ocused on university and firm-financed research and development activities. In particular he is interested in understanding how corporate governance and equity compensation influence firm research and development. His research has been published in leading journals including the Journal of Financial and Quantitative Analysis Journal of Corporate Finance Research Policy and the Southern Economic Journal. He has worked as a consultantfor theConnecticut Petroleum Council on issues before the Connecticut state legislature. He has alsowritten op-ed pieces that have appeared in several newspapers including the New York Times. iii Brief Contents Part 1: Introduction Chapter 1 The Long and Short of Macroeconomics 1 Chapter 2 Measuring the Macroeconomy 23 Chapter 3 The Financial System 59 Part 2: Macroeconomics in the Long Run: Economic Growth Chapter 4 Determining Aggregate Production 105 Chapter 5 Long-Run Economic Growth 143 Chapter 6 Money and Inflation 188 Chapter 7 The Labor Market 231 Part 3: Macroeconomics in the Short Run: Theory and Policy Chapter 8 Business Cycles 271 Chapter 9 IS–MP: A Short-Run Macroeconomic Model 302 Chapter 10 Monetary Policy in the Short Run 363 Chapter 11 Fiscal Policy in the Short Run 407 Chapter 12 Aggregate Demand Aggregate Supply and Monetary Policy 448 Part 4: Extensions Chapter 13 Fiscal Policy and the Government Budget in the Long Run 486 Chapter 14 Consumption and Investment 521 Chapter 15 The Balance of Payments Exchange Rates and Macroeconomic Policy 559 Glossary G-1 Index I-1ivContentsChapter 1 The Long and Short of Macroeconomics 1WHEN YOU ENTER THE JOB MARKET CAN MATTER A LOT ........................................................ 11.1 What Macroeconomics Is About........................................................................... 2 Macroeconomics in the Short Run and in the Long Run .................................................... 2 Long-Run Growth in the United States ............................................................................. 3 Some Countries Have Not Experienced Significant Long-Run Growth ............................... 4 Aging Populations Pose a Challenge to Governments Around the World .......................... 5 Unemployment in the United States ................................................................................. 6 How Unemployment Rates Differ Across Developed Countries ......................................... 7 Inflation Rates Fluctuate Over Time and Across Countries................................................. 7 Econo mic Policy Can Help Stabilize the Economy .. (8)International Factors Have Become Increasingly Important in Explaining Macroeconomic Events................................................................................. 91.2 How Economists Think About Macroeconomics ............................................. 11 What Is the Best Way to Analyze Macroeconomic Issues .............................................. 11 Macroeconomic Models.................................................................................................. 12Solved Problem 1.2: Do Rising Imports Lead to a Permanent Reductionin U.S. Employment. (12)Assumptions Endogenous Variables and Exogenous Variables in EconomicModels ........................................................................................................ 13 Forming and Testing Hypotheses in Economic Models .................................................... 14Making the Connection: What Do People Know About Macroeconomicsand How Do They KnowIt .............................................................................................. 151.3 Key Issues and Questions of Macroeconomics ............................................... 16An Inside Look: Will Consumer Spending Nudge Employers to Hire................................ 18Chapter Summary and Problems ............................................................................. 20 Key Terms and Concepts Review Questions Problems and Applications Data Exercise Theseend-of-chapter resource materials repeat in all chapters.Chapter 2 Measuring the Macroeconomy 23HOW DO WE KNOW WHEN WE ARE IN ARECESSION ........................................................... 23Key Issue andQuestion .................................................................................................... 232.1 GDP: Measuring Total Production and Total Income ..................................... 25 How theGovernment Calculates GDP (25)Production and Income (26)The Circular Flow of Income (27)An Example of Measuring GDP (29)National Income Identities and the Components of GDP (29)vvi CONTENTS Making the Connection: Will Public Employee Pensions Wreck State and Local Government Budgets.................................................................... 31 The Relationship Between GDP and GNP........................................................................ 33 2.2 Real GDP Nominal GDP and the GDP Deflator.............................................. 33 Solved Problem 2.2a: Calculating Real GDP . (34)Price Indexes and the GDP Deflator (35)Solved Problem 2.2b: Calculating the Inflation Rate ..........................................................36 The Chain-Weighted Measure of Real GDP ....................................................................37 Making the Connection: Trying to Hit a Moving Target: Forecasting with “Real-Time Data” .................................................................................. 37 Comparing GDP Across Countries................................................................................... 38 Making the Connection: The Incredible Shrinking Chinese Economy ................................ 39 GDP and National Income .............................................................................................. 40 2.3 Inflation Rates and Interest Rates ....................................................................... 41 The Consumer Price Index .............................................................................................. 42 Making the Connection: Does Indexing Preserve the Purchasing Power of Social Security Payments ................................................................ 43 How Accurate Is theCPI ............................................................................................... 44 The Way the Federal Reserve Measures Inflation ............................................................ 44 InterestRates .................................................................................................................. 45 2.4 Measuring Employment and Unemployment .. (47)Answering the Key Question ............................................................................................ 49 An Inside Look: Weak Construction Market Persists.......................................................... 50 Chapter 3 The Financial System 59 THE WONDERFUL WORLD OFCREDIT ................................................................................... 59 Key Issue and Question .................................................................................................... 59 3.1 Overview of the Financial System ...................................................................... 60 Financial Markets and Financial Intermediaries ................................................................ 61 Making the Connection: Is General Motors Making Cars or Making Loans .................... 62 Making the Connection: Investing in the Worldwide Stock Market . (64)Banking and Securitization (67)The Mortgage Market and the Subprime Lending Disaster (67)Asymmetric Information and Principal–Agent Problems in Financial Markets...................68 3.2 The Role of the Central Bank in the Financial System (69)Central Banks as Lenders of Last Resort ..........................................................................69 Bank Runs Contagion and Asset Deflation ....................................................................70 Making the Connection: Panics Then and Now: The Collapse of the Bank of United States in 1930 and the Collapse of Lehman Brothers in2008 (71)3.3 Determining Interest Rates: The Market for Loanable Funds and the Market forMoney .......................................................................................... 76 Saving and Supply in the Loanable Funds Market ........................................................... 76 Investment and the Demand for Loanable Funds ............................................................ 77 Explaining Movements in Saving Investment and the Real Interest Rate (78)CONTENTS .。

Stochastic variational principle on riemannianmanifoldsGavriel SegreMay28,20021Most of the conceptual appeal of Stochastic Mechanics [4]disappears as soon as one realizes that it may be ultimatively seen as a corollary of Fukushima’s Theorem on symmetric Dirichlet forms (generalized by Albeverio,Ma and R¨o ckner for non-symmetric Dirichlet forms)applied in the ground-state representa-tion (sometimes called the Darboux representation )[5],[7],[8],[6].Given an Hilbert space H and a positive,symmetric,bilinear form on H E :D (E )×D (E )→R (a symmetric form from here and beyond)defined on a dense subset D (E )×D (E )of H ×H (that I will denote as (D (E ),E ))let us introduce the symmetric form on H :E 1:D (E )×D (E )→R(1)E 1(f,g ):=E (f,g )+(f,g )(2)Clearly (D (E ),E 1)is a pre-Hilbert space .We will say that the form (D (E ),E )is closed if (D (E ),E 1)is also an Hilbert space ,i.e.if it is complete in the norm · 1:= E 1(·,·).We will say that (D (E ),E )is closable if it has a closed extension.In this case we define the closure of E as the smallest closed extension (D (¯E),¯E )of (D (E ),E ).The closure condition guarantees the existence of a whole plethora of bijec-tive correspondences:1.there is a one-to-one correspondence between closed symmetric forms and positive self-adjoint operators on H according to which the oper-ator (D (H ),H )corresponds the closed symmetric form:(D (E ):=D (√),E (f,g ):=(√f ,√g )(3)2.there is a one-to-one correspondence between positive self-adjoint op-erators and strongly continuous contraction semigroups on H ac-cording to which the operator (D (H ),H )corresponds to the strongly-continuous contraction semigroup (T t :=e −tH )t ≥03.there is a one-to-one correspondence between strongly continuous con-traction semigroups and strongly continuous contraction resol-vents according to which the strongly continuous contraction semigroup (T t )t ≥0corresponds to the strongly-continuous contraction-resolvent (G α)α≥0:G αf := ∞e −αs T sf ds ∀f ∈H (4)The full power of this chain of one-to-one correspondences arises,anyway,when one consider Dirichlet forms :in fact,for Dirichlet forms,one can add a link to the chain of one-to-one correspondences associating to a Dirichlet form the Markovian stochastic process2having as transition-probability-function the integral kernel of the associated strongly-continuous contraction semigroup.Supponing that H =L 2(M,µ)for a proper Borel measure space (M ,B ,µ)will say that the closed symmetric form :(D (E ),E )is a Dirichlet form iff:E (f ,f )≤E (f,f )∀f ∈D (E )(5)where f :=min(1,max(f,0)).The Dirichlet-condition of a symmetric form corresponds to specular con-ditions on the other links of the chain of one-to-one correspondences above in-troduced:namely one has that:(D (E ),E )is Dirichlet ⇔(D (H ),H )is Dirichlet ⇔(T t )t ≥0is markovian(6)where a self-adjoint operator (D (A ),A )is said Dirichlet iff:(Af ,max(0,f −1))≥0∀f ∈D (A )(7)while a strongly-continuous contraction semigroup is said markovian iff:0≤f ≤1⇒0≤T t f ≤1∀f ∈H (8)Let us now assume that (M,B )is Hausdorffand that the measure µis σ−finite .We will say that a symmetric form E is properly associated with a Markov process (X t )t ≥0on M if E ·[f (X t )]is an E−quasi-continuous µ-version of (e −tH f )(·)where E -quasi-continuous means continuous modulo E -exceptional sets,i.e.modulo set S ⊂M :E −cap (S )=0(9)where the E -capacity of S is defined as:E −cap (S ):=inf {E 1(f,f ):f ∈D (E ),f ≥1,µ−a.e.on S }(10)if S is open,and:E −cap (S ):=inf {E −cap (U ):U open U ⊃S }(11)if S is arbitrary.We will say that a Dirichlet form (D (E ),E )is regular if C 0(M ) D (E )is dense both in (C 0(M ), · ∞)and in (D (E ), · 1),where C 0(M )denotes the set of compact-supported functions on M, · ∞denotes the usual uniform norm,while · 1:= E 1(·,·).The fundamental Fukushima Theorem grants that if a Dirichlet form is reg-ular than it is properly associated to a Markov process (X t ).3Let us now pass to analyze concretely the more important application of this general mathematical framework,starting from the definition of the brownian motion on a riemannian manifold(M,g):the starting point is the symmetric form:(D(E):=C∞0(M),E(f,g):=<d f,dg>)(12) where C∞0(M)denotes the set of compact-supported smooth functions on M, while<·,·>is the g-metric induced scalar product on the space Γ(T(0,n)M)of the sections of the(0,n)-tensor bundle(i.e.the space of the n-differential forms on M):<ω,ν>:=Mω∧ νω,ν∈Γ(T(0,n)M),n∈N(13)where is the Hodge duality operator on(M,g).The closure(D(¯E),¯E)is a Dirichlet form,usually called the heat Dirichlet form on(M,g)whose associated positive self-adjoint operator is precisely the Laplace-Beltrami operator defined on the2th Sobolev space on M:(−∆g:=d d†+d†d,H2(M))(14) The brownian motion on(M,g)is then defined precisely as the Markov process on(M,g)properly associated to the heat Dirichlet form on(M,g ).Let us now modify a bit the scenario introducing the Hilbert space:H:=L2(M,dµg)(15) and associating to a generic wave-functionψ∈H the symmetric form:(D(Eψ):=C∞0(M),Eψ(f,g):=M|ψ|2d f∧ dg)(16)on the Hilbert space:Hψ:=L2(M,|ψ|2dµg)(17) Since its closure(D(¯Eψ),¯Eψ)is a Dirichlet form,the Fukushima’s Theorem al-lows to associate to the wave-functionψthe markovian stochastic process xψover(M,g)properly associated to(D(¯Eψ),¯Eψ).For example,in the particular case in which(M,g)is the one-dimensional euclidean space(R,δ)while:ψ(y):=1π14e−y22(18)is the ground-state wave-function of the harmonic-oscillator’s hamiltonian,xψis the Ornstein-Uhlenbeck stochastic process over(R,δ).4Returning to the general case let us denote by ˆH ψthe positive self-adjoint operator over H ψassociated to the Dirichlet form (D (¯E ψ),¯E ψ).One has that ψis the ground-state eigenfunction of ˆHψ,correponding to the zero eigenvalue.It easily follows that ψis the solution of the variational problem:δS 1(ψ)=0(19)δ2S 1(ψ)>0(20)where S 1:H →R is the functional:S 1(ψ):=<ψ|ˆH ψ|ψ><ψ|ψ>(21)Denoted by M (M,g )the set of all the markovian stochastic processes over (M ,g )let us introduce the functional S 2:H →R defined as:S 2(x ψ):=S 1(ψ)(22)One has then that,obviously,x ψis the solution of the stochastic action principle:δS 2(x ψ)=0(23)δ2S 2(x ψ)>0(24)Let us now observe that such a stochastic variational principle is different and incompatible with Guerra’s way of formulating the stochastic action principle on manifolds [3],[1],[2]as we will know show:let us introduce the following one-parameter family of wave functions be-longing to the Hilbert space H :=L 2(M,dµg ):ψp (q ):=N (p )e (d g (p,q ))22p ∈M (25)where d g (p,q )is the geodesic distance among the points p and q of (M,g),while N(p)is a normalization factor such that:ψp 2H =1∀p ∈M (26)Let us now observe that in the particular case in which (M,g )is the one-dimensional euclidean space (R ,δ)and p :=0the wave-function of eq.25re-duces to the one-dimensional harmonic-oscillator’s ground-state’s wave-function of eq.18and conseguentially,the markovian process x ψreduces to the one-dimensional Ornstein-Uhlenbeck process.This doesn’t occurs,instead in the Guerra’s approach to the same situa-tion whose starting point is the ill-defined construction of a stochastic action functional that is:•expressed in terms of local coordinates but not invariant under change of local coordinates5•dependent among the totally arbitrary choice of an affine connection that is notfixed to be the Levi-Civita connection of(M,g)and whose variation is,in a totally inconsistent way,claimed to correspond to a sort of gauge transformation•depends critically upon an ad-hoc regularization procedure,resulting in the more possibly arbitary renormalized stochastic actionThe absolute mathematical inconsistence of such an approach is definitively proved by the own fact that,in the one-dimensional euclidean limit,the solu-tion of the stochastic variational equation it gives rise to is not the Ornstein-Uhlenbeck process.References[1]E.Aldrovandi D.Dohrn F.Guerra.The stochastic action of dynamical sys-tems on curved manifolds.The isokinetic developing map on trajectories.In Stochastic Processes,Physics and Geometry,Singapore,1989.World Scien-tific.[2]E.Aldrovandi D.Dohrn F.Guerra.The stochastic action of dynamicalsystems on curved manifolds.The geodesic interpolation.Journal of Math-ematical Physics,31:639,1990.[3]F.Guerra.Stochastic variational principles and Quantum Mechanics.Ann.Inst.Henri Poincar´e,49(315),October1988.[4]E.Nelson.Quantum Fluctuations.Princeton University Press,Princeton,1985.[5]S.Albeverio J.Brasche M.R¨o ckner.Dirichlet forms and generalizedSchr¨o dinger operators.In H.Holden A.Jensen,editor,Schr¨o dinger Op-erators.Springer-Verlag,Berlin,1988.[6]S.Albeverio Y.G.Kondratiev M.R¨o ckner.Infinite Dimensional Diffusions,Markov Fields,Quantum Fields and Stochastic Quantization.In A.I.Car-doso M.de Faria J.Pottchof R.Seneor L.Streit,editor,Stochastic Analysis and Applications in Physics,pages1–34.Kluwer Academic Publishers,Dor-drecht,1994.[7]Z.M.Ma M.R¨o ckner.Introduction to the Theory of(Non-Symmetric)Dirichlet Forms.Springer-Verlag,Berlin,1992.[8]M.Fukushima Y.Oshima M.Takeda.Dirichlet Forms and SymmetricMarkov Process.Walter de Gruyter,Berlin,1994.6。

内部控制英文文献目录1. 内部控制管制对盈余质量的影响：来自德国的证据( March 2008 )The effect of internal control regulation on earnings quality: Evidence from Germany2. 内部控制制度如何影响财务报告？( Altamuro ，June 24, 2009)How Does Internal Control Regulation Affect Financial Reporting3. 财务报告内部控制缺陷的决定因素( Doyle ，May 15, 2006)Determinants of weaknesses in internal control over financial reporting4. 应计质量与财务报告内部控制( Doyle，January 24, 2007)Accruals Quality and Internal Control over Financial Reporting5. SOX 内部控制缺陷对公司风险与权益资本成本的影响( Ashbaugh-Skaife ，June 10, 2008) The Effect of SOX Internal Control Deficiencies on Firm Risk and Cost of Equity6. 审计委员会质量、审计师独立性与内部控制缺陷( Zhang)Audit Committee Quality, Auditor Independence, and Internal Control Weaknesses7. 小企业受益于内部控制缺陷审计师认证吗Do Small Firms Benefit from Auditor Attestation of Internal Control Effectiveness8. 内部控制缺陷的决定因素( Jahmani)Determinants of Internal Control Weaknesses In Accelerated Filers9. 操控性应计项目能帮助区分内部控制缺陷和欺诈吗Do Discretionary Accruals Help Distinguish between Internal Control Weaknesses and Fraud10. 财务报告质量对债务契约的影响：来自内部控制缺陷报告的证据 ( Costello ，September 4, 2010) The impact of financial reporting quality on debt contracting: Evidence from internal control weakness reports11. 重大内部控制缺陷与盈余管理Material Internal Control Weaknesses and Earnings Management in the Post-SOX Environment12. 家族企业的内部控制( April 2013 )Internal Controls in Family-Owned Firms ()13. 内部控制质量对企业并购绩效的影响研究Study on the Impact of the Quality of Internal Control on the Performance of M&A14. 内部控制质量与信用违约互换利差( January 2014)Internal Control Quality and Credit Default Swap Spreads15. 家族企业内部控制：特征和后果Internal Control in Family Firms: Characteristics and Consequences16. 内部控制报告与会计信息质量：洞察”遵守或解释的“内部控制制度Internal control reporting and accounting quality ：Insight "comply-or-explain" internal control regime17. 内部控制报告与会计稳健性Internal Control Reporting and Accounting Conservatism18. 会计信息质量影响产品市场契约吗？来自政府合同授予的证据( March 2014 )Does Accounting Quality Influence Product Market Contracting? Evidence from Government Contract Awards19. 公司特征与财务报告质量：尼日利亚制造业上市公司的证据20. 内部控制情况与专家审计师选择The Association between Internal Control Situations and Specialist Auditor Choices21. 审计费用反应了控制风险的风险溢价吗( 2013-07 )Do Audit Fees Reflect Risk Premiums for Control Risk?22. 内部控制质量与审计定价Internal Control Quality and Audit Pricing under the Sarbanes-Oxley Act23. 内部控制缺陷与权益资本成本：来自萨班斯法案404 节披露的证据Internal Control Weakness and Cost of Equity: Evidence from SOX Section 404 Disclosures24. 内部控制缺陷与信息不确定性Internal Control Weaknesses and Information Uncertainty25. 重大内部控制缺陷与股票价格崩溃危险：来自404 条款披露的证据( May 2013 )Material Weaknessin Internal Control and Stock Price Crash Risk: Evidence from SOX Section 404 Disclosure 26. SOX 内部控制缺陷对公司风险与权益资本成本的影响The Effect of SOX Internal Control Deficiencies on Firm Risk and Cost of Equity27. 信用评级、债务成本与内部控制信息披露：SOX302 和SOX404 法的比较28. 萨班斯-奥克斯利法案对会计信息债务契约价值的影响The Effect of Sarbanes-Oxley on the Debt Contracting Value of Accounting Information29. 财务报告内部控制的不利意见与审计师解聘/辞职Adverse Internal Control over Financial Reporting Opinions and Auditor Dismissals/Resignations30. 新管理人员任命与随后的SOX 法案404 的意见Appointment of New Executives and Subsequent SOX 404 Opinion31. 萨班斯奥克斯利：有关萨班斯法案404 影响的证据Sarbanes-Oxley: The Evidence Regarding the Impact of Sox 40432. 内部控制有效性自愿披露的经济决定因素及后果：从首次公开发行的证据( March 2013 ) Economic Determinants and Consequences of Voluntary Disclosure of Internal Control Effectiveness: Evidence from Initial Public Offerings33. 非营利组织中内部控制问题的原因和后果The Causes and Consequences of Internal Control Problems in Nonprofit Organizations34. SOX 内部控制披露在公司控制权市场中的价值The Value of SOX Internal Control Disclosures in the Market for Corporate Control35. 内部控制缺陷与销售、一般的及行政费用的非对称性行为Internal Control Weakness and the Asymmetrical Behavior of Selling, General, and Administrative Costs36. 内部控制缺陷及补救措施披露对投资者感知的盈余质量的影响The Impact of Disclosures of Internal Control Weaknesses and Remediation on Investor-Perceived Earnings Quality37. 内部控制缺陷与美国上市的中国公司与美国公司的审计师SOX Internal Control Deficiencies and Auditors of U.S.-Listed Chinese versus U.S. Firms38. 内部控制信息披露与代理成本—来自瑞士的非金融类上市公司的证据( January 2013) Internal Control Disclosure and Agency Costs Evidence from Swiss listed non-financial Companies39. 萨班斯奥克斯利法案与公司投资：来自自然实验的新证据The Sarbanes-Oxley Act and Corporate Investment: New Evidence from a Natural Experiment40. 国内投资者保护、所有权结构与交叉上市公司遵守SOX 要求披露内部控制缺陷Home Country Investor Protection, Ownership Structure and Cross-Listed Firms 'Compliance with SOX-Mandated Internal Control Deficiency Disclosure41. 审计师对披露重大缺陷相关风险的看法Auditors ' Percenpsti o f the Risks Associated with Disclosing Material Weaknesses42. 交叉上市公司提供与美国公司相同质量的披露？来自萨班斯-奥克斯利法案302 条款下的内部控制缺陷信息披露的证据Do cross-listed firms provide the same quality disclosure as U.S. firms? Evidence from the internal control deficiency disclosure under Section 302 of the Sarbanes-Oxley Act43. 内部控制缺陷与并购绩效Internal Control Weaknesses and Acquisition Performance44. 萨班斯-奥克斯利法案302 条款下的内部控制缺陷对审计费用的影响The Effect of Internal Control Weakness under Section 404 of the Sarbanes-Oxley Act on Audit Fees45. 审计师对财务报告内部控制的评价对审计费用、债务成本及净遵从收益The Effect of Auditors ' Assessment of Internal Control of over Financial Reporting on Audit Fees, Cost of Debt and Net Compliance Benefit46. 上市公司披露的信息含量与萨班斯-奥克斯利法案Information Content of Public Firm Disclosures and the Sarbanes-Oxley Act47. 财务错报与股票市场的契约：从增发的证据Financial Misstatements and Contracting in the Equity Market: Evidence from Seasoned Equity Offerings48. 公司治理质量与SOX 302 条款下内部控制报告Corporate Governance Quality and Internal Control Reporting Under Sox Section 30249. 审计委员会质量、审计师独立性与内部控制缺陷Audit Committee Quality, Auditor Independence, and Internal Control Weaknesses50. SOX404 条款的影响：成本，盈余质量与股票价格The Effect of SOX Section 404: Costs, Earnings Quality, and Stock Prices51. 内部控制缺陷与银行贷款契约：来自SOX404 条款披露的证据Internal Control Weakness and Bank Loan Contracting: Evidence from SOX Section 404 Disclosures52. 审计师对财务报告内部控制的决策：分析、综合和研究方向Auditors I'nternal Control Over Financial Reporting Decisions: Analysis, Synthesis, and Research Directions 53. 应计质量与财务报告内部控制( Doyle ，The Accounting Review, forthcoming )Accruals Quality and Internal Control over Financial Reporting54. 业绩基础CEO 和CFO 薪酬对内部控制质量的影响The impact of performance-based CEO and CFO compensation on internal control quality55. 内部控制重大缺陷与CFO 薪酬Internal Control Material Weaknesses and CFO Compensation56. 财务报告内部控制缺陷的决定因素Determinants of weaknesses in internal control over financial reporting57. 内部控制与管理指南Internal Control and Management Guidance58. 2002 萨班斯-奥克斯利法案302 条款下内部控制缺陷的市场反应以及这些缺陷的特征Market Reactions to the Disclosure of Internal Control Weaknesses and to the Characteristics of thoseWeaknesses under Section 302 of the Sarbanes Oxley Act of 200259. 自愿报告内部风险管理和控制系统的经济激励Economic Incentives for Voluntary Reporting on Internal Risk Management and Control Systems60. 后萨班斯法案时代审计意见的信息含量The information content of audit opinions in the post-sox era61. 上市公司披露的信息含量与萨班斯-奥克斯利法案( April, 2010 )Information Content of Public Firm Disclosures and the Sarbanes-Oxley Act62. 信息摩擦如何影响公司资产流动性的选择？萨班斯法案404 条款的影响How do Informational Frictions Affect the Firm s Choice of A'sset Liquidity? The Effect of SOX Section 404 63. 已审计的信息披露给资本市场参与者带来利益是什么( December 19, 2013)What are the benefits of audited disclosures to equity market participants64. 诉讼风险与审计定价：公众股权的作用( January 7, 2013)Litigation Risk and Audit Pricing: The Role of Public Equity65. 萨班斯-奥克斯利法案对IPO 和高收益债券发行人的影响The Impact of Sarbanes-Oxley on IPOs and High Yield Debt Issuers66. 来自金融危机的公司治理的经验教训The Corporate Governance Lessons from the Financial Crisis67. 谁对企业欺诈吹口哨Who Blows the Whistle on Corporate Fraud68. 内部控制缺陷与现金持有价值Internal Control Weakness and Value of Cash Holdings69. 民族文化和制度环境对内部控制信息披露的影响The impact of national culture and institutional Environment on internal control disclosures70. 财务报告质量与权益资本成本之间联系的讨论：一些个人的意见( June 6, 2013)Some Personal Observations on the Debate on the Link between Financial Reporting Quality and the Cost of Equity Capital71. 使用盈利预测同时估计企业层面的权益资本成本和长期增长Using Earnings Forecasts to Simultaneously Estimate Firm-Specific Cost of Equity and Long-Term Growth72. 高管薪酬差距与权益资本成本Executive Pay Disparity and the Cost of Equity Capital73. 财务报告质量与公司债券市场(博士论文，Mingzhi Liu, 2011 )Financial Reporting Quality and Corporate Bond MarketsReferencesAboody, D., J. 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美国的三大微积分教材用作大学的主要微积分教材，受到广大学生的青睐和推崇。

它们分别是：《Calculus: Single Variable》（单变量微积分）、《Calculus: Multivariable》（多元微积分）和《Calculus: Early Transcendentals》（早期超越微积分）。

《Calculus: Single Variable》是由美国出版商John Wiley & Sons出版的微积分教材，
其作者是知名数学家James Stewart。

这本书涵盖了微积分中的几何、微分和积分，以及
无穷小量、洛必达法则、泰勒展开式等内容，以深入浅出的方式讲解了微积分的基本概念。

《Calculus: Multivariable》是由美国出版商John Wiley & Sons出版的多元微积分教材，其作者是知名数学家Ron Larson。

书中涵盖了多元微积分的概念，包括多元函数、定积分、无穷积分、曲线积分、曲面积分等等，以及其他相关概念。

《Calculus: Early Transcendentals》是由美国出版商John Wiley & Sons出版的早期超
越微积分教材，其作者是知名数学家William L. Briggs。

本书涵盖了微积分的早期超越概念，包括微分法则、泰勒级数展开、Taylor多项式、流形和空间曲线、曲面积分等等，以
及微积分相关的其他概念。

美国的三大微积分教材既让学生掌握了微积分的最新发展，又满足了学生的学习需求，具有重要的教学价值。

它们的出版和使用，不仅提高了学生的学习效果，也为美国教育发
展作出了贡献。

CHAPTER 10: ARBITRAGE PRICING THEORY ANDMULTIFACTOR MODELS OF RISK AND RETURN PROBLEM SETS1. The revised estimate of the expected rate of return on the stock would be the oldestimate plus the sum of the products of the unexpected change in each factor times the respective sensitivity coefficient:Revised estimate = 12% + [(1 × 2%) + (0.5 × 3%)] = 15.5%Note that the IP estimate is computed as: 1 × (5% - 3%), and the IR estimate iscomputed as: 0.5 × (8% - 5%).2. The APT factors must correlate with major sources of uncertainty, i.e., sources ofuncertainty that are of concern to many investors. Researchers should investigatefactors that correlate with uncertainty in consumption and investment opportunities.GDP, the inflation rate, and interest rates are among the factors that can be expected to determine risk premiums. In particular, industrial production (IP) is a goodindicator of changes in the business cycle. Thus, IP is a candidate for a factor that is highly correlated with uncertainties that have to do with investment andconsumption opportunities in the economy.3. Any pattern of returns can be explained if we are free to choose an indefinitelylarge number of explanatory factors. If a theory of asset pricing is to have value, itmust explain returns using a reasonably limited number of explanatory variables(i.e., systematic factors such as unemployment levels, GDP, and oil prices).4. Equation 10.11 applies here:E(r p) = r f + βP1 [E(r1 ) −r f ] + βP2 [E(r2 ) – r f]We need to find the risk premium (RP) for each of the two factors:RP1 = [E(r1 ) −r f] and RP2 = [E(r2 ) −r f]In order to do so, we solve the following system of two equations with two unknowns: .31 = .06 + (1.5 ×RP1 ) + (2.0 ×RP2 ).27 = .06 + (2.2 ×RP1 ) + [(–0.2) ×RP2 ]The solution to this set of equations isRP1 = 10% and RP2 = 5%Thus, the expected return-beta relationship isE(r P) = 6% + (βP1× 10%) + (βP2× 5%)5. The expected return for portfolio F equals the risk-free rate since its beta equals 0.For portfolio A, the ratio of risk premium to beta is (12 − 6)/1.2 = 5For portfolio E, the ratio is lower at (8 – 6)/0.6 = 3.33This implies that an arbitrage opportunity exists. For instance, you can create aportfolio G with beta equal to 0.6 (the same as E’s) by combining portfolio A and portfolio F in equal weights. The expected return and beta for portfolio G are then: E(r G) = (0.5 × 12%) + (0.5 × 6%) = 9%βG = (0.5 × 1.2) + (0.5 × 0%) = 0.6Comparing portfolio G to portfolio E, G has the same beta and higher return.Therefore, an arbitrage opportunity exists by buying portfolio G and selling anequal amount of portfolio E. The profit for this arbitrage will ber G – r E =[9% + (0.6 ×F)] − [8% + (0.6 ×F)] = 1%That is, 1% of the funds (long or short) in each portfolio.6. Substituting the portfolio returns and betas in the expected return-beta relationship,we obtain two equations with two unknowns, the risk-free rate (r f) and the factor risk premium (RP):12% = r f + (1.2 ×RP)9% = r f + (0.8 ×RP)Solving these equations, we obtainr f = 3% and RP = 7.5%7. a. Shorting an equally weighted portfolio of the ten negative-alpha stocks andinvesting the proceeds in an equally-weighted portfolio of the 10 positive-alpha stocks eliminates the market exposure and creates a zero-investmentportfolio. Denoting the systematic market factor as R M, the expected dollarreturn is (noting that the expectation of nonsystematic risk, e, is zero):$1,000,000 × [0.02 + (1.0 ×R M)] − $1,000,000 × [(–0.02) + (1.0 ×R M)]= $1,000,000 × 0.04 = $40,000The sensitivity of the payoff of this portfolio to the market factor is zerobecause the exposures of the positive alpha and negative alpha stocks cancelout. (Notice that the terms involving R M sum to zero.) Thus, the systematiccomponent of total risk is also zero. The variance of the analyst’s profit is notzero, however, since this portfolio is not well diversified.For n = 20 stocks (i.e., long 10 stocks and short 10 stocks) the investor willhave a $100,000 position (either long or short) in each stock. Net marketexposure is zero, but firm-specific risk has not been fully diversified. Thevariance of dollar returns from the positions in the 20 stocks is20 × [(100,000 × 0.30)2] = 18,000,000,000The standard deviation of dollar returns is $134,164.b. If n = 50 stocks (25 stocks long and 25 stocks short), the investor will have a$40,000 position in each stock, and the variance of dollar returns is50 × [(40,000 × 0.30)2] = 7,200,000,000The standard deviation of dollar returns is $84,853.Similarly, if n = 100 stocks (50 stocks long and 50 stocks short), the investorwill have a $20,000 position in each stock, and the variance of dollar returns is100 × [(20,000 × 0.30)2] = 3,600,000,000The standard deviation of dollar returns is $60,000.Notice that, when the number of stocks increases by a factor of 5 (i.e., from 20 to 100), standard deviation decreases by a factor of 5= 2.23607 (from$134,164 to $60,000).8. a. )(σσβσ2222e M +=88125)208.0(σ2222=+×=A50010)200.1(σ2222=+×=B97620)202.1(σ2222=+×=Cb. If there are an infinite number of assets with identical characteristics, then awell-diversified portfolio of each type will have only systematic risk since thenonsystematic risk will approach zero with large n. Each variance is simply β2 × market variance:222Well-diversified σ256Well-diversified σ400Well-diversified σ576A B C;;;The mean will equal that of the individual (identical) stocks.c. There is no arbitrage opportunity because the well-diversified portfolios allplot on the security market line (SML). Because they are fairly priced, there isno arbitrage.9. a. A long position in a portfolio (P) composed of portfolios A and B will offer anexpected return-beta trade-off lying on a straight line between points A and B.Therefore, we can choose weights such that βP = βC but with expected returnhigher than that of portfolio C. Hence, combining P with a short position in Cwill create an arbitrage portfolio with zero investment, zero beta, and positiverate of return.b. The argument in part (a) leads to the proposition that the coefficient of β2must be zero in order to preclude arbitrage opportunities.10. a. E(r) = 6% + (1.2 × 6%) + (0.5 × 8%) + (0.3 × 3%) = 18.1%b.Surprises in the macroeconomic factors will result in surprises in the return ofthe stock:Unexpected return from macro factors =[1.2 × (4% – 5%)] + [0.5 × (6% – 3%)] + [0.3 × (0% – 2%)] = –0.3%E(r) =18.1% − 0.3% = 17.8%11. The APT required (i.e., equilibrium) rate of return on the stock based on r f and thefactor betas isRequired E(r) = 6% + (1 × 6%) + (0.5 × 2%) + (0.75 × 4%) = 16% According to the equation for the return on the stock, the actually expected return on the stock is 15% (because the expected surprises on all factors are zero bydefinition). Because the actually expected return based on risk is less than theequilibrium return, we conclude that the stock is overpriced.12. The first two factors seem promising with respect to the likely impact on the firm’scost of capital. Both are macro factors that would elicit hedging demands acrossbroad sectors of investors. The third factor, while important to Pork Products, is a poor choice for a multifactor SML because the price of hogs is of minor importance to most investors and is therefore highly unlikely to be a priced risk factor. Betterchoices would focus on variables that investors in aggregate might find moreimportant to their welfare. Examples include: inflation uncertainty, short-terminterest-rate risk, energy price risk, or exchange rate risk. The important point here is that, in specifying a multifactor SML, we not confuse risk factors that are important toa particular investor with factors that are important to investors in general; only the latter are likely to command a risk premium in the capital markets.13. The formula is ()0.04 1.250.08 1.50.02.1717%E r =+×+×==14. If 4%f r = and based on the sensitivities to real GDP (0.75) and inflation (1.25),McCracken would calculate the expected return for the Orb Large Cap Fund to be:()0.040.750.08 1.250.02.040.0858.5% above the risk free rate E r =+×+×=+=Therefore, Kwon’s fundamental analysis estimate is congruent with McCracken’sAPT estimate. If we assume that both Kwon and McCracken’s estimates on the return of Orb’s Large Cap Fund are accurate, then no arbitrage profit is possible.15. In order to eliminate inflation, the following three equations must be solvedsimultaneously, where the GDP sensitivity will equal 1 in the first equation,inflation sensitivity will equal 0 in the second equation and the sum of the weights must equal 1 in the third equation.1.1.250.75 1.012.1.5 1.25 2.003.1wx wy wz wz wy wz wx wy wz ++=++=++=Here, x represents Orb’s High Growth Fund, y represents Large Cap Fund and z represents Utility Fund. Using algebraic manipulation will yield wx = wy = 1.6 and wz = -2.2.16. Since retirees living off a steady income would be hurt by inflation, this portfoliowould not be appropriate for them. Retirees would want a portfolio with a return positively correlated with inflation to preserve value, and less correlated with the variable growth of GDP. Thus, Stiles is wrong. McCracken is correct in that supply side macroeconomic policies are generally designed to increase output at aminimum of inflationary pressure. Increased output would mean higher GDP, which in turn would increase returns of a fund positively correlated with GDP.17. The maximum residual variance is tied to the number of securities (n ) in theportfolio because, as we increase the number of securities, we are more likely to encounter securities with larger residual variances. The starting point is todetermine the practical limit on the portfolio residual standard deviation, σ(e P ), that still qualifies as a well-diversified portfolio. A reasonable approach is to compareσ2(e P) to the market variance, or equivalently, to compare σ(e P) to the market standard deviation. Suppose we do not allow σ(e P) to exceed pσM, where p is a small decimal fraction, for example, 0.05; then, the smaller the value we choose for p, the more stringent our criterion for defining how diversified a well-diversified portfolio must be.Now construct a portfolio of n securities with weights w1, w2,…,w n, so that Σw i =1. The portfolio residual variance is σ2(e P) = Σw12σ2(e i)To meet our practical definition of sufficiently diversified, we require this residual variance to be less than (pσM)2. A sure and simple way to proceed is to assume the worst, that is, assume that the residual variance of each security is the highest possible value allowed under the assumptions of the problem: σ2(e i) = nσ2MIn that case σ2(e P) = Σw i2 nσM2Now apply the constraint: Σw i2 nσM2 ≤ (pσM)2This requires that: nΣw i2 ≤ p2Or, equivalently, that: Σw i2 ≤ p2/nA relatively easy way to generate a set of well-diversified portfolios is to use portfolio weights that follow a geometric progression, since the computations then become relatively straightforward. Choose w1 and a common factor q for the geometric progression such that q < 1. Therefore, the weight on each stock is a fraction q of the weight on the previous stock in the series. Then the sum of n terms is:Σw i= w1(1– q n)/(1– q) = 1or: w1 = (1– q)/(1– q n)The sum of the n squared weights is similarly obtained from w12 and a common geometric progression factor of q2. ThereforeΣw i2 = w12(1– q2n)/(1– q 2)Substituting for w1 from above, we obtainΣw i2 = [(1– q)2/(1– q n)2] × [(1– q2n)/(1– q 2)]For sufficient diversification, we choose q so that Σw i2 ≤ p2/nFor example, continue to assume that p = 0.05 and n = 1,000. If we chooseq = 0.9973, then we will satisfy the required condition. At this value for q w1 = 0.0029 and w n = 0.0029 × 0.99731,000In this case, w1 is about 15 times w n. Despite this significant departure from equal weighting, this portfolio is nevertheless well diversified. Any value of q between0.9973 and 1.0 results in a well-diversified portfolio. As q gets closer to 1, theportfolio approaches equal weighting.18. a. Assume a single-factor economy, with a factor risk premium E M and a (large)set of well-diversified portfolios with beta βP. Suppose we create a portfolio Zby allocating the portion w to portfolio P and (1 – w) to the market portfolioM. The rate of return on portfolio Z is:R Z = (w × R P) + [(1 – w) × R M]Portfolio Z is riskless if we choose w so that βZ = 0. This requires that:βZ = (w × βP) + [(1 – w) × 1] = 0 ⇒w = 1/(1 – βP) and (1 – w) = –βP/(1 – βP)Substitute this value for w in the expression for R Z:R Z = {[1/(1 – βP)] × R P} – {[βP/(1 – βP)] × R M}Since βZ = 0, then, in order to avoid arbitrage, R Z must be zero.This implies that: R P = βP × R MTaking expectations we have:E P = βP × E MThis is the SML for well-diversified portfolios.b. The same argument can be used to show that, in a three-factor model withfactor risk premiums E M, E1 and E2, in order to avoid arbitrage, we must have:E P = (βPM × E M) + (βP1 × E1) + (βP2 × E2)This is the SML for a three-factor economy.19. a. The Fama-French (FF) three-factor model holds that one of the factors drivingreturns is firm size. An index with returns highly correlated with firm size (i.e.,firm capitalization) that captures this factor is SMB (small minus big), thereturn for a portfolio of small stocks in excess of the return for a portfolio oflarge stocks. The returns for a small firm will be positively correlated withSMB. Moreover, the smaller the firm, the greater its residual from the othertwo factors, the market portfolio and the HML portfolio, which is the returnfor a portfolio of high book-to-market stocks in excess of the return for aportfolio of low book-to-market stocks. Hence, the ratio of the variance of thisresidual to the variance of the return on SMB will be larger and, together withthe higher correlation, results in a high beta on the SMB factor.b.This question appears to point to a flaw in the FF model. The model predictsthat firm size affects average returns so that, if two firms merge into a largerfirm, then the FF model predicts lower average returns for the merged firm.However, there seems to be no reason for the merged firm to underperformthe returns of the component companies, assuming that the component firmswere unrelated and that they will now be operated independently. We mighttherefore expect that the performance of the merged firm would be the sameas the performance of a portfolio of the originally independent firms, but theFF model predicts that the increased firm size will result in lower averagereturns. Therefore, the question revolves around the behavior of returns for aportfolio of small firms, compared to the return for larger firms that resultfrom merging those small firms into larger ones. Had past mergers of smallfirms into larger firms resulted, on average, in no change in the resultantlarger firms’ stock return characteristics (compared to the portfolio of stocksof the merged firms), the size factor in the FF model would have failed.Perhaps the reason the size factor seems to help explain stock returns is that,when small firms become large, the characteristics of their fortunes (andhence their stock returns) change in a significant way. Put differently, stocksof large firms that result from a merger of smaller firms appear empirically tobehave differently from portfolios of the smaller component firms.Specifically, the FF model predicts that the large firm will have a smaller riskpremium. Notice that this development is not necessarily a bad thing for thestockholders of the smaller firms that merge. The lower risk premium may bedue, in part, to the increase in value of the larger firm relative to the mergedfirms.CFA PROBLEMS1. a. This statement is incorrect. The CAPM requires a mean-variance efficientmarket portfolio, but APT does not.b.This statement is incorrect. The CAPM assumes normally distributed securityreturns, but APT does not.c. This statement is correct.2. b. Since portfolio X has β = 1.0, then X is the market portfolio and E(R M) =16%.Using E(R M ) = 16% and r f = 8%, the expected return for portfolio Y is notconsistent.3. d.4. c.5. d.6. c. Investors will take on as large a position as possible only if the mispricingopportunity is an arbitrage. Otherwise, considerations of risk anddiversification will limit the position they attempt to take in the mispricedsecurity.7. d.8. d.。