博迪投资学第九版ppt
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兹维博迪-投资学-第九版-中文PPT课件
1-31
1-25
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系统性风险的上升
银行资产和负债的到期日和流动性之间并不匹配。
负债是短期的、流动的 资产是长期的、非流动的 需要不断再融资改善资产组合
高杠杆比率使得银行几乎没有保证金来确保其安全。
1-26
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系统性风险的上升
投资者过分依赖结构化产品，如信用违约掉期来实现信 用升级。
信用违约掉期合约通常是场外交易，缺少公开披露，没 有要求保证金。
为什么会低估信用风险?
没有人会预料到房地产市场的价格会一直下跌 跨地区来分散风险的愿望并未实现 代理问题和评级机构 信用违约掉期并未像预计那样降低风险
1-22
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信用违约掉期 (CDS)
信用违约掉期实质上是一种针对借款者违约的保险合同。 投资者购买次级贷款使用信用违约掉期来保证其安全性。
投资银行
• 同意买下新发行的股票 和债券
• 在一级市场上向公众销 售新证券
• 投资者在二级市场上买 卖一级市场发行的证券
商业银行
• 吸收存款、发放贷款
1-14
-
-
2008年的金融危机
金融危机的前情:
“大稳健”: 美国经历了一个低利率和经济稳定的时期，只有一 些温和的经济衰退，经济周期似乎已被驯服。
第一章
1
投资环境
McGraw-Hill/Irwin
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
-
-
实物资产与金融资产
实物资产 取决于该社会经济的生产能力，为经济创 造净利润。 如土地、建筑物、机器以及可用于生产产 品和提供服务的知识。
1-25
-
系统性风险的上升
银行资产和负债的到期日和流动性之间并不匹配。
负债是短期的、流动的 资产是长期的、非流动的 需要不断再融资改善资产组合
高杠杆比率使得银行几乎没有保证金来确保其安全。
1-26
-
系统性风险的上升
投资者过分依赖结构化产品，如信用违约掉期来实现信 用升级。
信用违约掉期合约通常是场外交易，缺少公开披露，没 有要求保证金。
为什么会低估信用风险?
没有人会预料到房地产市场的价格会一直下跌 跨地区来分散风险的愿望并未实现 代理问题和评级机构 信用违约掉期并未像预计那样降低风险
1-22
-
信用违约掉期 (CDS)
信用违约掉期实质上是一种针对借款者违约的保险合同。 投资者购买次级贷款使用信用违约掉期来保证其安全性。
投资银行
• 同意买下新发行的股票 和债券
• 在一级市场上向公众销 售新证券
• 投资者在二级市场上买 卖一级市场发行的证券
商业银行
• 吸收存款、发放贷款
1-14
-
-
2008年的金融危机
金融危机的前情:
“大稳健”: 美国经历了一个低利率和经济稳定的时期，只有一 些温和的经济衰退，经济周期似乎已被驯服。
第一章
1
投资环境
McGraw-Hill/Irwin
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
-
-
实物资产与金融资产
实物资产 取决于该社会经济的生产能力，为经济创 造净利润。 如土地、建筑物、机器以及可用于生产产 品和提供服务的知识。
Chap006 风险厌恶与风险资产配置兹维 博迪 《投资学 》第九版课件PPT
6-26
6.5 风险容忍度与资产配置
• 投资者必须从可行集中选择一种最优的资产组 合C：选择风险资产的比例y，使效用最大化。 ①完整资产组合的 E ( r ) r P f
②方差：
s ys
2 C 2
2 P
③效用函数：
1 2 U E (r ) As 2
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6-9
6.1.2 风险厌恶和效用价值
2、均值-方差(M-V) 准则 • 投资组合A优于投资组合B，如果： 与
ErA ErB
sA sB
• 至少有一个条件严格成立。 ① 期望收益率相同，风险低者更优。 ② 风险水平相同，期望收益高者更优。
图 6.8 用无差异曲线寻找最优组合
与资本配置线 相切的最高无差 异曲线，其切点 对应最优投资组 合的标准差和期 望收益。 y*的决策取决 于投资者的风险 厌恶水平。
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表 6.6 四条无差异曲线和资本配置线的 期望收益
给定s和U，求出E(r)，代入CAL
6-18
例： 相关数据
风险组合P的收益率为rP，期望收益为E( rP )，标准 差为sP；无风险资产的收益率为rf。
rf = 7% E(rp) = 15%
rC =yrP ＋ （1 － y）rf
srf = 0% sp = 22%
，取期望值
风险投资组合P的投资比例为y，无风险投资组合F 的投资比例为1-y，整个组合C的收益率rC为：
– 借出资金的资本配置线的斜率 = 8/22 = 0.36，
– 借入资金的资本配置线的斜率 = 6/22 = 0.27， ★资本配置线在P点重合。
Chap002 资产类别与金融工具兹维 博迪 《投资学 》第九版课件PPT
2-9
2.2 债券市场
1、中长期国债
① 期限： – 中期国债 – 期限最长是10年 – 长期国债 – 期限从10年到30年不等 ② 面值 – 1000美元； ③ 利息支付期—半年； ④ 行情– 以面值的百分比；1/32
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2-10
2.2 债券市场
2.3 权益证券
• 1、普通股：代表所有权 – 剩余索取权最后 – 有限责任 • 2、优先股： 永续性 – 固定收益； – 求偿权优先于普通股，次于债券； – 税务处理：股利部分免税； • 美国存托凭证ADR：在美国市场上ODIE, KANE, MARCUS
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2-21
标准普尔指数
• 标准普尔500指数：
– 涵盖500家公司的指数
– 市值加权指数
• 投资者可以购买指数投资组合:
– 购买与各种指数相对应的共同基金；
– 购买交易所交易基金 (ETFs)；
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2-8
2.2 债券市场
• 1、中期国债和长期国债 • 2、通胀保值债券 • 3、联邦机构债券 • 4、国际债券 • 5、市政债券 • 6、公司债券 • 7、抵押贷款和抵押担保证券
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第二章
资产类别与金融工具
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McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
Chap012 行为金融与技术分析兹维 博迪 《投资学 》第九版课件PPT
由框定依赖导致的认知与判断的偏差即为框定偏差它是指人们的判断与决策依赖于所面临的决策问题的形式即尽管问题的本质相同但因形式的不同也会导致人们做出不同的决策
第十二章
行为金融与技术分析
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McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
1. 基本趋势/主要趋势: 股价的长期趋势，持续时间从 几个月到几年不等。 2. 二级趋势或中间趋势: 价格对目标趋势线的短期偏 离，当价格回归到趋势值时，这些偏离就会消失。 3. 三级趋势或次要趋势: 几乎不重要的日波动。
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12-19
12-21
图12.5 移动平均线（惠普公司）
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12-22
趋势与修正: 宽度
宽度:常用的测量 方法是计算价格 出现上涨的股票 数量和出现下跌 的股票数量之差。
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12-23
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12-26
12.2.3 警告!
• 很可能会观察出实际上并不存在的波动形式。 • 图12.8A 是基于真实的数据资料。图B描述的 是利用任意数字算出的股票收益。 • 图12.9 描述的是图12.8对应的每周股价变化， 可以看出其明显的随机性。
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12-12
第十二章
行为金融与技术分析
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McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
1. 基本趋势/主要趋势: 股价的长期趋势，持续时间从 几个月到几年不等。 2. 二级趋势或中间趋势: 价格对目标趋势线的短期偏 离，当价格回归到趋势值时，这些偏离就会消失。 3. 三级趋势或次要趋势: 几乎不重要的日波动。
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12-19
12-21
图12.5 移动平均线（惠普公司）
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12-22
趋势与修正: 宽度
宽度:常用的测量 方法是计算价格 出现上涨的股票 数量和出现下跌 的股票数量之差。
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12-23
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12-26
12.2.3 警告!
• 很可能会观察出实际上并不存在的波动形式。 • 图12.8A 是基于真实的数据资料。图B描述的 是利用任意数字算出的股票收益。 • 图12.9 描述的是图12.8对应的每周股价变化， 可以看出其明显的随机性。
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12-12
博迪投资学第九版课件
p
24-11
Risk Adjusted Performance: Treynor
2) Treynor Measure
(rP rf )
P
rp = Average return on the portfolio
rf = Average risk free rate ßp = Weighted average beta for portfolio
24-2
Introduction
• Two common ways to measure average portfolio return: 1. Time-weighted returns 2. Dollar-weighted returns • Returns must be adjusted for risk.
24-7
Time-Weighted Return
53 50 2 r1 10% 50 54 53 2 r2 5.66% 53
rG = [ (1.1) (1.0566) ]1/2 – 1 = 7.81% The dollar-weighted average is less than the time-weighted average in this example because more money is invested in year two, when the return was lower.
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24-14
M Measure
• Developed by Modigliani and Modigliani • Create an adjusted portfolio (P*)that has the same standard deviation as the market index. • Because the market index and P* have the same standard deviation, their returns are comparable:
Chap009 资本资产定价模型兹维 博迪 《投资学 》第九版课件PPT
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9-18
图9.3 证券市场线和一只α值为正的股票
股票的实际期望 收益与正常期望收 益之间的差，称为 股票的阿尔法，。 被低估的股票期 望收益值将高于证 券市场线给出的正 常收益值。
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9-24
9.4 计量经济学与期望收益—贝塔关系
9.3.2 实证检验不支持CAPM
• 实证拒绝了假设：α等于0。 • 统计偏差的引进。 • 米勒和斯科尔斯的论文证明了计量问题可 能会导致拒绝资本资产定价模型，即使该 模型是非常有效的。 • 但也可能是模型本身的问题。
E r r
M f
9-7
• 变换一下，我们可以得到：
ErGE rf GE ErM rf
– 风险溢价取决于两个因素：
• 一是市场组合风险报酬[E(r )－rf]； • 二是资产对市场组合的风险暴露程度β；
M
注意：预测的是收益
9-8
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E (rM ) rf M E ( r ) r M f
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9-15
9.1.5 证券市场线★
均衡市场中，所有证券 都必须在证券市场线上。 证券市场线：期望收益 -贝塔关系。斜率为市 场投资组合的风险溢价 ：【E(rM)-rf 】。
• βi为个股对市场组合方差的贡献。
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9-18
图9.3 证券市场线和一只α值为正的股票
股票的实际期望 收益与正常期望收 益之间的差，称为 股票的阿尔法，。 被低估的股票期 望收益值将高于证 券市场线给出的正 常收益值。
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9-24
9.4 计量经济学与期望收益—贝塔关系
9.3.2 实证检验不支持CAPM
• 实证拒绝了假设：α等于0。 • 统计偏差的引进。 • 米勒和斯科尔斯的论文证明了计量问题可 能会导致拒绝资本资产定价模型，即使该 模型是非常有效的。 • 但也可能是模型本身的问题。
E r r
M f
9-7
• 变换一下，我们可以得到：
ErGE rf GE ErM rf
– 风险溢价取决于两个因素：
• 一是市场组合风险报酬[E(r )－rf]； • 二是资产对市场组合的风险暴露程度β；
M
注意：预测的是收益
9-8
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E (rM ) rf M E ( r ) r M f
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9-15
9.1.5 证券市场线★
均衡市场中，所有证券 都必须在证券市场线上。 证券市场线：期望收益 -贝塔关系。斜率为市 场投资组合的风险溢价 ：【E(rM)-rf 】。
• βi为个股对市场组合方差的贡献。
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博迪投资学第九版课件
Security D and Security E
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7-9
Two-Security Portfolio: Risk
• Another way to express variance of the portfolio:
2 P wD wDCov(rD , rD ) wE wE Cov(rE , rE ) 2wD wE Cov(rD , rE )
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7-20
Figure 7.6 The Opportunity Set of the Debt and Equity Funds and Two Feasible CALs
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7-15
Figure 7.3 Portfolio Expected Return as a Function of Investment Proportions
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7-16
Figure 7.4 Portfolio Standard Deviation as a Function of Investment Proportions
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7-5
Figure 7.2 Portfolio Diversification
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7-6
Covariance and Correlation
• Portfolio risk depends on the correlation between the returns of the assets in the portfolio
《投资学》(博迪)ppt课件
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表25.6 综合评分与单项评分
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表 25.7 综合风险与政治风险预测
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表25.7 的解释
该表通过情景分析了解国家风险。 风险稳定度就是最好情况的风险值减去最
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熊市中国际分散化投资还会带来好处吗?
在资本市场动荡时 期，国家组合投资 收益之间的相关性 将增大。
罗尔模型揭示了全 球股价变动背后一 个广泛的因素。
预测：
分散化只能减轻各 国特殊事件的影响。
在1987年发生了什 么? 2008年呢?
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和外币。
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国际化投资的风险因素
风险变化的两 个来源:
1. 以当地货币计量的收益 率
2. 当地货币调整为本国货 币后的收益率
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例 25.1 汇率风险
假设英国无风险利率为10% 现在的汇率是 1英镑兑2美元 。
一个投资者有20,000 美元，即可以购买 10,000 英镑，一年后投资可得11,000英镑。
如果汇率下跌为1英镑兑1.80美元那么最终 只能得到19, 800美元, 损失了200美元。
对美国投资者而言，这项投资并不是无风 险的。
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27-11
Table 27.4 The Optimal Risky Portfolio with Constraint on the Active Portfolio (wA ≤1)
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• How accurate is your forecast?
• Regress forecast alphas on actual, realized alphas to adjust alpha for the accuracy of the analysts’ previous forecasts.
• The BL model is a generalization of the TB model that allows you to have views about relative performance that cannot be used in the TB model.
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27-13
Table 27.5 The Optimal Risky Portfolio with the Analysts’ New Forecasts
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Adjusting Forecasts for the Precision of Alpha
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27-17
Steps in the Black-Litterman Model
1. Estimate the covariance matrix from recent historical data.
2. Determine a baseline forecast.
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27-15
Figure 27.4 Organizational Chart for Portfolio Management
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The Black-Litterman Model
CHAPTER 27
The Theory of Active Portfolio Management
McGraw-Hill/Irwin
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Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
Treynor-Black Model
• Use the TB model for the management of security analysis with proper adjustment of alpha forecasts.
INVESTMENTS | BODIE, KANE, MARCUS
INVESTMENTS | BODIE, KANE, MARCUS
27-20
BL Conclusions
• The Black-Litterman (BL) model and the Black-Treynor (TB) model are complements.
• The models are identical with respect to the optimization process and will chose identical portfolios given identical inputs.
27-12
Figure 27.2 Reduced Efficiency when Benchmark is Lowered
Benchmark risk is the standard deviation of the tracking error, TE = RP-RM. Control it by restricting WA.
27-18
Figure 27.5 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level
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27-19
Figure 27.6 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level
• Table D shows:
– Performance increases are very modest. – M-square increases by only 19 basis points.
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27-6
Table 27.2 Stock Prices and Analysts’ Target Prices for June 1, 2006
• Black-Litterman model
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27-3
Table 27.1 Construction and Properties of the Optimal Risky Portfolio
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Let’s add these new forecasts to the spreadsheet model and re-calculate Table D.
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27-7
Figure 27.1 Rates of Return on the S&P 500 (GSPC) and the Six Stocks
information ratio in the universe of securities, 3.the precision of the security analysts.
INVESTMENTS | BODIE, KANE, MARCUS
27-2
Overview
• Treynor-Black model – The optimization uses analysts’ forecasts of superior performance. – The model is adjusted for tracking error and for analyst forecast error.
27-23
Value of Active Management
• Kane, Marcus, and Trippi show that active management fees depend on:
1.the coefficient of risk aversion, 2.the distribution of the squared
3. Integrate the manager’s private views.
4. Develop revised (posterior) expectations.
5. Apply portfolio optimization.
INVESTMENTS | BODIE, KANE, MARCUS
• The business cycle and other macroeconomic variables may be better forecasters of expected returns.
• Historical variance is a good predictor of expected future variance.
INVESTMENTS | BODIE, KANE, MARCUS
27-22
BL vs. TB
Black-Litterman Model
• Use the BL model for asset allocation.
• Views about relative performance are useful even when the degree of confidence is inaccurately estimated.
Treynor-Black Model
• TB model is not applied in the field because it results in “wild” portfolio weights.
• The extreme weights are a consequence of failing to adjust alpha values to reflect forecast precision.
INVESTMENTS | BODIE, KANE, MARCUS
27-8
Table 27.3 The Optimal Risky Portfolio
INVESTMENTS | BODIE, KANE, MARCUS
27-9
Results
• The Sharpe ratio increases to 2.32, a huge risk-adjusted return advantage.
– The portfolio is too risky and most of the risk is nonsystematic risk.
• A solution: Restrict extreme positions. – This results in a lack of diversification.
27-11
Table 27.4 The Optimal Risky Portfolio with Constraint on the Active Portfolio (wA ≤1)
INVESTMENTS | BODIE, KANE, MARCUS
• How accurate is your forecast?
• Regress forecast alphas on actual, realized alphas to adjust alpha for the accuracy of the analysts’ previous forecasts.
• The BL model is a generalization of the TB model that allows you to have views about relative performance that cannot be used in the TB model.
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27-13
Table 27.5 The Optimal Risky Portfolio with the Analysts’ New Forecasts
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27-14
Adjusting Forecasts for the Precision of Alpha
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27-17
Steps in the Black-Litterman Model
1. Estimate the covariance matrix from recent historical data.
2. Determine a baseline forecast.
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27-15
Figure 27.4 Organizational Chart for Portfolio Management
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27-16
The Black-Litterman Model
CHAPTER 27
The Theory of Active Portfolio Management
McGraw-Hill/Irwin
INVESTMENTS | BODIE, KANE, MARCUS
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
Treynor-Black Model
• Use the TB model for the management of security analysis with proper adjustment of alpha forecasts.
INVESTMENTS | BODIE, KANE, MARCUS
INVESTMENTS | BODIE, KANE, MARCUS
27-20
BL Conclusions
• The Black-Litterman (BL) model and the Black-Treynor (TB) model are complements.
• The models are identical with respect to the optimization process and will chose identical portfolios given identical inputs.
27-12
Figure 27.2 Reduced Efficiency when Benchmark is Lowered
Benchmark risk is the standard deviation of the tracking error, TE = RP-RM. Control it by restricting WA.
27-18
Figure 27.5 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level
INVESTMENTS | BODIE, KANE, MARCUS
27-19
Figure 27.6 Sensitivity of Black-Litterman Portfolio Performance to Confidence Level
• Table D shows:
– Performance increases are very modest. – M-square increases by only 19 basis points.
INVESTMENTS | BODIE, KANE, MARCUS
27-6
Table 27.2 Stock Prices and Analysts’ Target Prices for June 1, 2006
• Black-Litterman model
INVESTMENTS | BODIE, KANE, MARCUS
27-3
Table 27.1 Construction and Properties of the Optimal Risky Portfolio
INVESTMENTS | BODIE, KANE, MARCUS
Let’s add these new forecasts to the spreadsheet model and re-calculate Table D.
INVESTMENTS | BODIE, KANE, MARCUS
27-7
Figure 27.1 Rates of Return on the S&P 500 (GSPC) and the Six Stocks
information ratio in the universe of securities, 3.the precision of the security analysts.
INVESTMENTS | BODIE, KANE, MARCUS
27-2
Overview
• Treynor-Black model – The optimization uses analysts’ forecasts of superior performance. – The model is adjusted for tracking error and for analyst forecast error.
27-23
Value of Active Management
• Kane, Marcus, and Trippi show that active management fees depend on:
1.the coefficient of risk aversion, 2.the distribution of the squared
3. Integrate the manager’s private views.
4. Develop revised (posterior) expectations.
5. Apply portfolio optimization.
INVESTMENTS | BODIE, KANE, MARCUS
• The business cycle and other macroeconomic variables may be better forecasters of expected returns.
• Historical variance is a good predictor of expected future variance.
INVESTMENTS | BODIE, KANE, MARCUS
27-22
BL vs. TB
Black-Litterman Model
• Use the BL model for asset allocation.
• Views about relative performance are useful even when the degree of confidence is inaccurately estimated.
Treynor-Black Model
• TB model is not applied in the field because it results in “wild” portfolio weights.
• The extreme weights are a consequence of failing to adjust alpha values to reflect forecast precision.
INVESTMENTS | BODIE, KANE, MARCUS
27-8
Table 27.3 The Optimal Risky Portfolio
INVESTMENTS | BODIE, KANE, MARCUS
27-9
Results
• The Sharpe ratio increases to 2.32, a huge risk-adjusted return advantage.
– The portfolio is too risky and most of the risk is nonsystematic risk.
• A solution: Restrict extreme positions. – This results in a lack of diversification.