1 Basics

1.1 Holding Based Approach(HBA)

\[h=S\beta+\mu\]

1.2 Return Based Analysis(ABA)

将基金历史收益与某些可观测的风格因素联系起来做回归分析，将各个因素的回归系数作为基金风格的测度.

1.2.1 Fama-French 3 factors model

按照“价值—成长”定位分为：价值型、平衡型、成长型。价值型基金是为了通过购买股票获得当期收益，即通过上市公司分红而获得收益；成长型基金是购买当期被低估的股票，为了获得资本增值，等待价格上涨带来的收益；平衡型基金则既要获得当期收益，同样要获得资本增值。
按照投资股票规模大小来区分：大盘型、中盘型、小盘型。简而言之，基金投资于大盘、中盘、小盘股，那么该基金的基金风格就是对应的大盘基金、中盘基金、小盘基金。

1.3 中性策略

中性策略就是构建投资组合，使得组合与市场之间相关系数为0，也就是投资组合不随市场的波动而波动。

1.3.1 中性策略根据实现手段可分为贝塔中性、市值中性和行业中性。

贝塔中性是指投资组合的贝塔值为0。
市值中性是指组合中多头部位中大、中、小盘股票的配比与空头部位指数的配比一致，做到市值中性不一定能实现贝塔中性，例如多头选一篮子创业板股票，空头用同市值的沪深300股指期货对冲，显然空头头寸无法覆盖多头头寸全部的风险敞口。
行业中性是指多头头寸与空头头寸行业板块配置一致，没有偏配，一般做到市值中性与行业中性的组合可以近似认为达到贝塔中性。A market-neutral strategy is a type of investment strategy undertaken by an investor or an investment manager that seeks to profit from both increasing and decreasing prices in one or more markets, while attempting to completely avoid some specific form of market risk. Market-neutral strategies are often attained by taking matching long and short positions in different stocks to increase the return from making good stock selections and decreasing the return from broad market movements.

1.3.2 How to Build a Sector-Neutral Stock Portfolio

Regardless of your investing style, you may not realize that if you focus on a particular type of stock, you could be creating an undiversified portfolio and taking unintended sector risk.
We believe most investors should try to build a "sector-neutral" portfolio when implementing their favorite stock-selection strategy.
sector neutrality won't typically result in much of a hit to your overall average returns, and you can still pick stocks using your favorite style.

1.3.3 A pure growth and value portfolio skews sector allocations most at IT, energy and consumer discretionary.

The benchmark may have a different weight decomposition that have a underweight on some sector or overweight on other sectors.

1.3.4 Steps:

First, the model ranks roughly 3,623 (by exposure signal) stocks within each sector;
selecting stocks from sectors:
- 在Pool里面的信号值[0, 1)代表该stock是否在benchmark里。由pool和benchmark我们能得到每只股票的行业分类，以及由他们之间交集得到的待选股票池。
- 1、把每个行业里面的股票按signal的信号强度(P(i,j),i:行业，j股票名)可以排序。
- 2、从每个行业里面按quantile从步骤1排序后的股票池里面选股票，得到两个结果，具体每个行业的股票（S(i,j)，i:行业，j股票名）和每个行业股票的数量N(i)。
- 3、利用benchmark的weight数据得到每个行业所占的权重W(i)。结果即为行业中性下每只股票的权重。
- 4、W(i)/N(i)等权重赋值到挑选出来的股票S(i,j)。
- For example, let’s say you have $10,000 to invest, equally allocated to large and small cap stocks. Owning 40 stocks equally weighted means that you would hold $250 in each position ($10,000 divided by 40). If a sector's weight is 20% of the benchmark, then 20% of your portfolio, or $2,000, would be invested in that sector. Because you’re investing $500 in each stock, you would hold 4 stocks in this sector ($2,000 divided by $500). Since you have equally allocated your capital to large and small cap stocks, you would own 2 large and 2 small cap stocks.

2 Barra Portfolio Management

提供了一个可以构建组合，预测风险并进行对冲的分析框架
能够识别出资产收益背后的共同的，基本面的驱动因素
对收益和风险在系统性因素和个别因素两个方面进行切分
Barra 对每个资产计算出其对各因子的风险暴露度，能迅速捕捉
上市公司的基本面情况以及市场趋势的变化

Model	how its used
Brinson-Fachler Attribution	To evaluate top-down sector allocation strategies in equity or balanced portfolios
Asset Selection Attribution	To evaluate bottom-up stock picking strategies in equity or balanced portfolios
Barra Equity Factor Attribution	To identify granular sources of return in equity portfolios
Fixed Income Attribution	To identify sources of active return due to yield curve movements and credit/spread bets in fixed income portfolios

2.1 Barra China Equity Model

2.1.1 国家因子

2.1.2 风格因子

Size: 捕捉大盘股和小盘股之间的收益差异
Non-linear Size：描述了无法由规模因子解释的但与规模有关的收益差异，通常代表中盘股
Earnings Yield：描述了由盈利收益导致的收益差异
Book-to-Price：描述了股票估值高低不同而产生的收益差异,即价值因子
Growth：描述了对销售或盈利增长预期不同而产生的收益差异
Leverage：描述了高杠杆股票与低杠杆股票之间的收益差异
Momentum (动量)：描述了过去半年到一年里相对强势的股票与弱势股票之间的差异
Beta：捕捉那些无法用国家因子解释的市场风险
Residual Volatility：解释了剥离了市场风险后的波动率高低产生的收益率差异
Liquidity：解释了由股票相对的交易活跃度不同而产生的收益率差异

2.1.3 行业因子

Energy 能源
Chemicals 化工
Construction Materials 基建材料
Diversified Metals 贵金属
Materials 材料
Aerospace and Defense 航空
Building Products 建筑
Construction and Engineering 基建工程
Electrical Equipment 电子设备
Industrial Conglomerates 工业集团
Industrial Machinery 工业机械
Trading Companies and Distributors 外贸
Commercial and Professional Services 服务业
Airlines 航空运输
Marine 军工
Road Rail and Transportation Infrastructure 铁路
Automobiles and Components 汽车
Household Durables (non-Homebuilding) 家庭耐用消费品
Leisure Products Textiles Apparel and Luxury 休闲用品、纺织品、服装和奢侈品
Consumer Services 消费服务
Media 媒体
Retail 铁路
Food Staples Retail Household Personal Prod 零售业家用个人用品
Beverages 饮料
Food Products 食品
Health 医疗
Banks 银行
Diversified Financial Services 非银行金融
Real Estate 房地产
Software 软件
Hardware and Semiconductors 硬件和半导体
Utilities 公用事业( A utility is an important service such as water, electricity, or gas that is provided for everyone, and that everyone pays for.)

2.1.4 股票收益的几个基本面来源

资产收益率可以归因到几个不同的基本面因子上。如，投资期间中股票所有的风格，所在行业，或是所处国家： \[r_k = x_{k,1}*f_1 + x_{k,2}*f_2 + ... + x_{k,n}*f_n + u_{k,spacefic}\] $r_k$ asset k return, $x_{k,n}$ observed exposure of asset k to common factors, observed exposure or sensitivity of asset k to factor n. $f_n$ estimated return of factor n. $u_{k,spacefic}$ specific return of asset k.

2.2 风格分析

2.2.1 Factor exposure

风格因子背后通常是各种财务指标或是市场价格指标.
风格因子的暴露度是经过标准化的(Normalization).
- 标准化的目的是使不同的数据和时间之间可以在同一量纲上进行比较。 Barra会先对各项指标先做标准化，然后构建成风格因子的暴露度，最后再对暴露度进行标准化.
风格因子暴露度的单位是标准差.
行业因子是虚拟变量.

Sector₁	Sector₂	…	Sector_n
0/1	0/1	…	0/1

2.2.2 A股成长性最高的和最低的10只股票

对模型样本空间各股按Growth因子暴露度进行排序.
财务指标:

\[Growth = Sales Growth(0.47) + Analystpredicted Earnings Growth (0.240) + Earnings Growth Rate Long Term(0.180) + Earnings Growth Rate Short Term(0.110)\]

2.2.3 A股最贵的和最便宜的10只股票

对模型样本空间各股按Book-to-Price因子暴露度进行排序.
财务指标

\[ Value = Book-to-price(1.00)\] Value因子暴露度越高，说明股票越便宜.

2.2.4 A股最强势的和最弱势的10只股票

对模型样本空间各股按Momentum因子暴露度进行排序.
技术指标

\[Momentum = Relative strength(1.00)\]

2.2.5 A股规模最大和最小的10只股票

对模型样本空间各股按Size因子暴露度进行排序.
财务指标

\[Size = Log of Market Capitalization(1.00)\]

2.2.6 华夏成长小组合相对于沪深300指数的风格分析 – 表格

用市值加权求得组合层面的暴露度

Asset Name	Weight (%)	Growth Exp	Size Exp	Momentum Exp	Book-to-Price Exp
广联达	8.25%	0.98	-0.22	1.54	-1.75
许继电气	6.15%	0.65	-0.16	1.31	-1.48
伊利股份	19.75%	0.61	1.15	2.74	-1.51
天士力	6.75%	0.54	0.89	1.81	-1.87
云南白药	7.70%	0.36	1.15	1.97	-1.77
大北农	7.11%	0.3	0.29	0.69	-1.51
兴业银行	12.43%	0.18	1.15	0.28	0.95
长城汽车	11.69%	-0.15	1.15	2.77	-1.47
烟台万润	7.79%	-0.38	-1.79	0.8	-0.84
海通证券	12.36%	-0.9	1.15	0.63	-0.13
组合层面	100.00%	0.19	0.65	1.57	-1.04

与沪深300的风格进行比较

用市值加权求得组合层面每个因子的暴露度，得到Portfolio Exposure,与Benchmark Exposure比较。

Factor	Portfolio Exposure	Benchmark Exposure	Active Exposure
Beta	0.57	0.37	0.20
Book-to-Price	-1.04	0.14	-1.18
Earnings Yield	-0.71	0.34	-1.05
Growth	0.19	0.08	0.11
Leverage	-0.79	0.18	-0.97
Liquidity	0.60	0.54	0.06
Momentum	1.57	-0.06	1.63
Non-linear Size	-0.27	-0.28	0.01
Residual Volatility	0.84	-0.04	0.88
Size	0.65	0.72	-0.07

2.3 业绩归因

用市值加权求得组合层面每个因子不同日期暴露度，再计算暴露度的Daily/Weekly/Monthly Return.

风格因子收益率 – 与上市公司基本面相关的因子
- Size: 捕捉大盘股和小盘股之间的收益差异
- Non-linear Size：描述了无法由规模因子解释的但与规模有关的收益差异，通常代表中盘股
- Earnings Yield：描述了由盈利收益导致的收益差异
- Book-to-Price：描述了股票估值高低不同而产生的收益差异,即价值因子
- Growth：描述了对销售或盈利增长预期不同而产生的收益差异
- Leverage：描述了高杠杆股票与低杠杆股票之间的收益差异
风格因子收益率 – 与市场表现相关的因子
- Momentum (动量)：描述了过去半年到一年里相对强势的股票与弱势股票之间的差异
- Beta：捕捉那些无法用国家因子解释的市场风险
- Residual Volatility：解释了剥离了市场风险后的波动率高低产生的收益率差异
- Liquidity：解释了由股票相对的交易活跃度不同而产生的收益率差异

2.3.1 华夏成长小组合业绩表现 – 累积收益率

起始日	2012/09/28
结束日	2013/10/31
小组合收益率	31.36%
基准收益率	-6.17%
=主动收益	=25.18%
主动风险	11.29%

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