积极投资组合管理中的行业配置
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摘要
行业配置策略在动态投资组合管理中属于战术性资产配置的一部分,近年来得到广泛的关注和应用。全球资产管理行业趋势表明,相比区域、规模和风格配置,行业配置策略的重要性日益提升,并且在全球范围内也推出大量以行业配置为基础的资产管理产品。从上世纪60年代Benjamin F. King开创性地将行业因素引入多因子模型以来,学术研究领域对行业配置策略重要性的认同逐渐趋于一致,并且在行业配置方法上从传统的动量和反转策略逐步拓展到基于经济周期、货币环境和行业间相关关系的配置策略。近几年来,国内证券市场对行业配置的重视程度也显著提高,学术界和主要投资机构都推出了大量研究成果。
行业配置策略的理论基础是行业因子在证券截面收益中的解释程度。对国内市场的实证检验表明,在Fama-French框架下测算得到行业因子能够占到全部解释因子的60%,占到横截面收益总解释的30%,并且在市场震荡的平衡市中,行业因子的解释力度更为明显。这意味着,行业配置策略在实践中有广阔的应用空间,应当在理论上加以探索和完善。
行业配置策略构建的前提是形成有效率的行业分类。一般的行业分类标准分为管理型和投资型,目前A股市场所采用的各类行业标准都有其优劣势,其中中信行业分类标准相对折中地兼顾了产业面属性和市场面属性。另一方面,在对A股市场进行聚类分析后可以看到,在一般的行业划分标准之上,板块之间可以集聚分为资源类(煤炭、有色金属)、金融类(银行、房地产)、钢铁类、周期投资品类、非周期消费类、并购重组类和其他共七种,这种聚类分析的结果表明行业配置可以依据大类板块的划分展开。
自上世纪60年代以来,国内外研究在行业配置的各个领域都提出了相当多的结论,但分散在各个层面缺乏系统性的框架。而同期以来,资产配置与积极的组合管理理念逐步得到深入研究。因此,本文的核心是基于Grinold在1994年提出的积极组合管理理论,完善了行业配置策略的框架。从积极组合管理理论角度来看,能够战胜市场的超额收益与信息比率(IR)相关,这又来自于投资者预期超额收益的预测能力(信息系数),以及选择合适预测时间的能力(策略广度)。因此行业配置框架主要沿着这两方面展开,一方面是对行业预期收益率的预测,具体构建可以按照层次划分为基于经济周期和货币环境的宏观配置策略、基于领滞关系的中观配置策略和基于动量与反转的微观配置策略。另一方面则是构建基于此类信息和规律的动态再平衡框架。
本文在总结过往研究成果的基础上,着重对基于行业预期收益率预测的四种行业配置框架在A股市场应用性进行实证,并基于A股市场特征完善了配置框架的可操作细节。首先,在基于经济周期的行业配置策略中,本文对应用广泛的投资时钟进行了理论解释,经济周期之所以能够引起行业轮动的变化,大致来自于几个关键推动力：(1)技术冲击对关键行业的外生扩张；(2)产出在产业链不同环节自上游到下游的传导；(3)产出与投资的不匹配决定了行业收益的先后；(4)盈利能力变动的程度决定了收益对投资的敏感程度,盈利能力稳定的行业收益将仅依赖于产出。因此,在决定行业的周期性配置的因素中,有部分在行业间会有差异,例如折旧率、成本调整率、技术冲击,有部分因素则是经济周期波动下带来比率的变动,如产出-资本比率、投资-资本比率、资本边际收益率等。
其次,在基于货币环境的行业配置策略中,本文研究了数量型货币政策和价格型货币政策冲击下的行业配置规律,结果表明价格型的货币政策冲击对行业股价收益率的影响较短期,但解释程度小；数量型的货币政策冲击对行业股价收益率影响较长期,但解释程度相对较高；不论是价格型还是数量型的货币政策,初期对偏周期类行业的冲击都较为明显,但长期来看影响最大的还是金融行业。本文还构建了顺周期轮动策略和跨周期稳健策略,可以看到：(1)长期来看非周期行业要优于周期行业,顺周期配置对货币环境最敏感的行业能够显著提高收益水平；(2)顺周期行业轮动策略或者跨周期最优组合都能够战胜市场,并且策略行业轮动配置策略比Markowitz跨周期的最优组合策略更有效；(3)长期来看,即便是顺周期行业轮动策略也无法战胜消费和医药这两类长期稳定增长的行业。和基于经济周期的配置策略一样,基于货币环境的配置策略也为战略性配置规划提供了基础。
再次,本文研究了基于行业之间领滞关系的配置策略,这种关系对于揭示行业板块之间风格转换具有重要意义,对于A股市场的实证表明：(1)银行在系统内形成的冲击对房地产最为强烈,同时在短期内对周期品行业影响较大；(2)石油石化行业走势独立,但在短期内能够对所有行业形成较大冲击,中长期以后这种冲击明显消除；(3)周期性行业的冲击造成了其他行业在正向反映后迅速回落,有色金属造成的市场波动要明显大于钢铁行业；(4)医药行业可以作为消费行业的典型代表,电子元器件行业可以作为科技类或者成长股的典型代表；(5)所有行业在系统内的冲击通常在1个月左右时间表现明显,之后新增信息的影响就趋于减弱,周期性行业走势相对要独立。
第四,本文研究了传统的基于动量和反转的行业配置策略,这种策略在整个行业配置框架中居于战术性调整地位。A股市场中各行业动量特征差别较大,反转特征并不明显,其中周期性行业动量通常较短,基本在2周左右,而非周期性行业动量都在8周左右。动态模拟显示在大部分的期间组合内动量和反转都是有效的,这种策略可以获得正收益；对于动量策略,在较小观察期和持有期内的策略效果明显,而反转策略则需要考察更长观察期和适度的持有期,能够取得比较好的策略效果。
上述四种配置策略为预测行业板块的预期收益率提供了基础,但这只是整个积极组合管理中行业配置框架的一部份。在此基础上,本文系统性地提出了基于Grinold(1994)提出的积极组合管理思想的动态行业配置框架。其核心理念是基于经济周期和货币环境形成战略性配置规划,确定较长时间内的配置方向；之后综合考虑市场预期反映、分析师业绩调整、行业之间的领滞关系、动量与反转关系等信息,构成动态的组合再平衡；在完成大类板块的配置后,进一步对细分行业进行对比研究,选择可能具有超额收益的行业。为了更加规范化地将信息转化为组合,本文还提出了一种数量化的算法,用以分配上述三个层面决策的权重,最终形成投资决策中可以操作的行业配置规划表。
作为延伸,本文进一步思考了行业配置策略的核心理念及未来发展。相比宏观策略和微观策略,行业配置策略的困境体现在时间维度差别较大、目标界定相对比较模糊、目标成分本身不稳定性明显以及信息获取状况更为复杂等方面。技术性的行业配置策略更多相似于市场分析,依靠与交易对手的智慧较量来获得利润,从先验规律上能够得到合理的操作框架,但未来充满不确定性,行业自身在经济实体和市场实体中的不稳定性决定了其理论框架的不完备性。而艺术性的行业配置策略相似于证券分析,尽管与单个证券的分析相比难度更大,但却是具备稳定框架、能够在不确定的未来中获得确定性方法的模式。
未来行业配置策略的发展可能也会相应地按着这两个方向去演变。市场分析的策略模式将演变为更为复杂的金融工程与数据挖掘,利用市场交易的有效性缺陷来获得套利利润,最后将逐步演变为依靠金融技术手段的程式交易。证券分析的策略模式将更加演变为类似于选股的方法,从行业的盈利周期、安全边际、成长空间等方面不断完善,并且能够解决行业结构的不稳定性。随着国内证券市场的不断完善和逐步成熟,行业配置策略也将日益体现出其技术性和艺术性的鲜明特征。
Industry allocation strategy is a part of tactical asset allocation in the management of dynamic investment portfolio, which has been widely focused and applied in recent years. The industrial trend in the global asset management indicates that the importance of industry allocation strategy is increasing day by day, compared with region, scale and style allocation. Besides this, huge amount of asset management products based on industry allocation have been promoted globally. Benjamin F. King started to introduce industry factor into multi-factor model creatively since the 60s of last century. The academic research field gradually developed same recognition of the importance of industry allocation strategy, and gradually shifted from the conventional momentum and inversion strategy to the configuration strategy based on economic cycle, monetary environment and inter-industrial correlation for the industry allocation methodology. The domestic security market attached remarkably increased importance to the industry allocation in recent years. The academic circle and major investment institutions have come up with huge amount of research findings.
The theoretical basis for the industry allocation strategy is the illustration degree of industry factors in security benefit. The solid evidence and test to the domestic market indicates that the industry factors can account for 60% of the total illustration factors according to the calculation results with FF framework, and accounting for 30% of the overall illustration of cross sectional benefits, and the illustration strength of industry factors is more prominent in the balance of fluctuating market. This means that Industry allocation strategy has wide space to develop for application, and should be theoretically further explored and improved.
The prerequisite for establishing industry allocation strategy is the formation of efficient industrial classification. The general standard for the industrial classification includes management type and investment type. The current various standards for the industrial classification in A share market have both advantages and disadvantages, among which the standard by CITIC relatively took into account both the industrial attributes and market attributes. On the other hand, it can be seen from the cluster analysis on A share market that on top of the general standard for industrial classification, the sectors can be grouped into resource type (coal, non-ferrous metal), finance type (bank and real estate), iron & steel, cycle investment category, non-cycle investment category, merger and reorganization type etc. altogether seven types. The result of this type of cluster analysis shows that industry allocation can base on the division of large categories of sectors.
There have been tremendous amount of conclusions drawn from domestic and foreign studies on each area of industry allocation since the 60s of last century, however they are scattered at each level lacking systematic framework. While in the same time period, asset allocation and active portfolio management concept have been gradually studied in depth. Therefore, the core of the text is based on the theory of active portfolio management put forward by Grinold in 1994, which improved the framework of industry allocation strategy. Looking from the perspective of active portfolio management theory, the excess returns which can overcome the market is related to information ratio (IR). This is also attributed to the prediction capacity (information coefficient) of the investor for the expected excess returns, and the capacity of predicting the right time for the investment (strategy span). Therefore, the industry allocation framework mainly unfolds from these two aspects, on one hand, is the prediction of industrial expected rate of return, the concrete structure can be classified into the following different levels:the macro-configuration strategy based on economic cycle and monetary environment; the medium configuration strategy based on the lead-lag relationship and the micro-configuration strategy based on momentum and inversion. On the other hand, is the dynamic rebalance framework based on this type of information n and rules.
The text focuses on the provision of solid evidence for the applicability of the four types of industry allocation frameworks in A share market on the basis of summarizing former study results, and improved the operatable details of the framework based on the A share market characteristics. First of all, for the industry allocation strategy based on economic cycle, the text gives theoretical elaboration of investment clock which is widely applied. The key driving forces for the change of industry wheeled by economic cycle is the following:(1) the exogenous expansion of technical impact on key industries; (2) the transmission of output from upper stream to lower stream at different links of the industrial chain; (3) the mismatch of output and investment determines the sequence of industrial returns; (4) the profitability change determines the sensitivity of returns on investment, the industry returns with stable profitability will only rely on the output. Therefore, there are some differences among industries in determining the factors of industrial cycle configuration, for example:depreciation rate, cost adjustment rate, technical impact. Some factors cause the change of ratio with the fluctuation of economic cycle, for example:output-capital ratio, investment-capital ratio, marginal return on capital etc.
Besides this, for the industry allocation strategy based on monetary environment, the text studied the rule of industry allocation under the impact of quantitative monetary policy and pricing monetary policy. The results showed that the impact of pricing monetary policy on the rate of returns from industrial share price lasts shorter period of time, but with low illustration degree; While the impact of quantitative monetary policy on the rate of returns from industrial share price lasts longer period of time, but with relatively higher illustration degree; Both of the two types of monetary policies have more prominent impact on cycle industry at the initial stage, but for the long run, the financial industry is most affected. The text also established cycle rotation strategy and cross cycle stable strategy. We can see that:(1) non cycle industries are superior to cycle industries for the long run, the cycle configuration can significantly raise the returns level for those industries most sensitive to monetary environment; (2) the cycle industry rotation strategy or cross cycle optimized portfolio can both overcome the market, and the industry rotation configuration strategy is more effective than the cross cycle optimized portfolio strategy put forward by Markowitz. (3) for the long run, even the cycle industry rotation strategy will not be able to defeat the consumption and medicine industries which have long time demonstrated steady growth. Like the configuration strategy based on economic cycle, the configuration strategy based on monetary environment also laid foundation for the strategic configuration plan.
Next,the text studies the configuration strategy based on the lead-lag relationship among sectors, which is very significant to reveal the style change among the industrial sectors, the solid evidence from A share market shows that:(1) the impact formed in the system by bank affects the real estate industry the most, meanwhile it has greater impact on cycle industry in short run; (2) The development trend of oil and petrochemical industry is independent, however, they can cause great impact on all the industries in short run. This impact will obviously disappear in the mid and long run; (3) the impact of cycle industry leads to the rapid drop of other industries after positive reflection. Non-ferrous metal industry causes larger market fluctuation than iron & steel industry. (4) Medical industry can typically represents consumption industry, electronics industry represents science & technology type or growth stocks;(5) the impact of all the industries in the system shows obvious signs will show in about one month, and then the impact of additional message gradually weakens, the development trends of cycle industries are relatively independent.
The fourth, the text studied the conventional industry allocation strategy based on momentum and inversion, which is in the tactical adjustment position in the whole industry allocation framework. There is great discrepancy among the characteristics of the momentum of each industry in A share market, with less obvious inversion features. The momentum of cycle industries is usually shorter, basically around two weeks, while the momentum of non-cycle industries is about 8 weeks The dynamic simulation indicates that the momentum and inversion in majority of portfolio are effective, and this type of strategy can get positive returns; For the momentum strategy, the effects are more obvious during short observation time period and during holding period, while the inversion strategy requires longer observation time period and moderate holding period to see the better effects of strategy.
The above-mentioned four types of configuration strategy provided foundation for predicting the expected rate of returns from industrial sectors, but this is only a part of the industry allocation framework in the whole active portfolio management. On top of that, the text systematically put forward the dynamic industry allocation framework based on the active portfolio management concept put forward by Grinold (1994). The core concept is the strategic configuration plan based on economic cycle and monetary environment, identifying the configuration direction for the long time to come; Then the comprehensive considerations were given to the expected market response, adjustment of analysts performance, lead-lag relationship among industries, momentum & inversion relationship etc., forming the rebalance of dynamic portfolio;After the configuration of large segments, further comparative studies were conducted on the categorized industries, to select potential industries with excess returns. In order to convert the information into portfolio following certain standards, the text proposed a type of quantitative calculation method, to weigh the policy making at three levels as mentioned above and to come up with operatable industry allocation plan chart for investment policy.
As the extension, the text further touched on the core concept of industry allocation strategy and future development trend. Compared with macro and micro strategy, the dilemma of the industry allocation strategy includes:greater discrepancy in time dimension, comparative vague targets identified, obvious instability of targets composition themselves and more complicated information obtaining process etc. The technical industry allocation strategy is more like market analysis, relying on the wisdom competition with trade partners to gain profits. Rational operation framework can be established based on tested rules, however, there are many uncertainties about future. The instability of the industry itself in economic entities and market entities determines the incompleteness of theoretical framework. While the artistic industry allocation strategy is similar to security analysis, although more difficult compared with single security analysis, yet it has stable framework, and can obtain definite methodology for the uncertain future.
The development of future industry allocation strategy may follow these two directions accordingly. The strategy model for market analysis will evolve into more complicated financial engineering and data exploitation, to gain profits by using the defects of efficacy in market transaction, and in the end gradually evolve into program trading which rely on financial technical instruments. The strategy model of security analysis will further evolve into an approach similar to security selection, will be continuously improved in different aspects, such as the profit cycle of industry, safety margin, growth space etc., and the instability of industrial structure can be addressed. With the continuous improvement and gradual mature of domestic security market, the industry allocation strategy will also demonstrate its distinctive technical and artistic features.
行业配置策略的理论基础是行业因子在证券截面收益中的解释程度。对国内市场的实证检验表明,在Fama-French框架下测算得到行业因子能够占到全部解释因子的60%,占到横截面收益总解释的30%,并且在市场震荡的平衡市中,行业因子的解释力度更为明显。这意味着,行业配置策略在实践中有广阔的应用空间,应当在理论上加以探索和完善。
行业配置策略构建的前提是形成有效率的行业分类。一般的行业分类标准分为管理型和投资型,目前A股市场所采用的各类行业标准都有其优劣势,其中中信行业分类标准相对折中地兼顾了产业面属性和市场面属性。另一方面,在对A股市场进行聚类分析后可以看到,在一般的行业划分标准之上,板块之间可以集聚分为资源类(煤炭、有色金属)、金融类(银行、房地产)、钢铁类、周期投资品类、非周期消费类、并购重组类和其他共七种,这种聚类分析的结果表明行业配置可以依据大类板块的划分展开。
自上世纪60年代以来,国内外研究在行业配置的各个领域都提出了相当多的结论,但分散在各个层面缺乏系统性的框架。而同期以来,资产配置与积极的组合管理理念逐步得到深入研究。因此,本文的核心是基于Grinold在1994年提出的积极组合管理理论,完善了行业配置策略的框架。从积极组合管理理论角度来看,能够战胜市场的超额收益与信息比率(IR)相关,这又来自于投资者预期超额收益的预测能力(信息系数),以及选择合适预测时间的能力(策略广度)。因此行业配置框架主要沿着这两方面展开,一方面是对行业预期收益率的预测,具体构建可以按照层次划分为基于经济周期和货币环境的宏观配置策略、基于领滞关系的中观配置策略和基于动量与反转的微观配置策略。另一方面则是构建基于此类信息和规律的动态再平衡框架。
本文在总结过往研究成果的基础上,着重对基于行业预期收益率预测的四种行业配置框架在A股市场应用性进行实证,并基于A股市场特征完善了配置框架的可操作细节。首先,在基于经济周期的行业配置策略中,本文对应用广泛的投资时钟进行了理论解释,经济周期之所以能够引起行业轮动的变化,大致来自于几个关键推动力：(1)技术冲击对关键行业的外生扩张；(2)产出在产业链不同环节自上游到下游的传导；(3)产出与投资的不匹配决定了行业收益的先后；(4)盈利能力变动的程度决定了收益对投资的敏感程度,盈利能力稳定的行业收益将仅依赖于产出。因此,在决定行业的周期性配置的因素中,有部分在行业间会有差异,例如折旧率、成本调整率、技术冲击,有部分因素则是经济周期波动下带来比率的变动,如产出-资本比率、投资-资本比率、资本边际收益率等。
其次,在基于货币环境的行业配置策略中,本文研究了数量型货币政策和价格型货币政策冲击下的行业配置规律,结果表明价格型的货币政策冲击对行业股价收益率的影响较短期,但解释程度小；数量型的货币政策冲击对行业股价收益率影响较长期,但解释程度相对较高；不论是价格型还是数量型的货币政策,初期对偏周期类行业的冲击都较为明显,但长期来看影响最大的还是金融行业。本文还构建了顺周期轮动策略和跨周期稳健策略,可以看到：(1)长期来看非周期行业要优于周期行业,顺周期配置对货币环境最敏感的行业能够显著提高收益水平；(2)顺周期行业轮动策略或者跨周期最优组合都能够战胜市场,并且策略行业轮动配置策略比Markowitz跨周期的最优组合策略更有效；(3)长期来看,即便是顺周期行业轮动策略也无法战胜消费和医药这两类长期稳定增长的行业。和基于经济周期的配置策略一样,基于货币环境的配置策略也为战略性配置规划提供了基础。
再次,本文研究了基于行业之间领滞关系的配置策略,这种关系对于揭示行业板块之间风格转换具有重要意义,对于A股市场的实证表明：(1)银行在系统内形成的冲击对房地产最为强烈,同时在短期内对周期品行业影响较大；(2)石油石化行业走势独立,但在短期内能够对所有行业形成较大冲击,中长期以后这种冲击明显消除；(3)周期性行业的冲击造成了其他行业在正向反映后迅速回落,有色金属造成的市场波动要明显大于钢铁行业；(4)医药行业可以作为消费行业的典型代表,电子元器件行业可以作为科技类或者成长股的典型代表；(5)所有行业在系统内的冲击通常在1个月左右时间表现明显,之后新增信息的影响就趋于减弱,周期性行业走势相对要独立。
第四,本文研究了传统的基于动量和反转的行业配置策略,这种策略在整个行业配置框架中居于战术性调整地位。A股市场中各行业动量特征差别较大,反转特征并不明显,其中周期性行业动量通常较短,基本在2周左右,而非周期性行业动量都在8周左右。动态模拟显示在大部分的期间组合内动量和反转都是有效的,这种策略可以获得正收益；对于动量策略,在较小观察期和持有期内的策略效果明显,而反转策略则需要考察更长观察期和适度的持有期,能够取得比较好的策略效果。
上述四种配置策略为预测行业板块的预期收益率提供了基础,但这只是整个积极组合管理中行业配置框架的一部份。在此基础上,本文系统性地提出了基于Grinold(1994)提出的积极组合管理思想的动态行业配置框架。其核心理念是基于经济周期和货币环境形成战略性配置规划,确定较长时间内的配置方向；之后综合考虑市场预期反映、分析师业绩调整、行业之间的领滞关系、动量与反转关系等信息,构成动态的组合再平衡；在完成大类板块的配置后,进一步对细分行业进行对比研究,选择可能具有超额收益的行业。为了更加规范化地将信息转化为组合,本文还提出了一种数量化的算法,用以分配上述三个层面决策的权重,最终形成投资决策中可以操作的行业配置规划表。
作为延伸,本文进一步思考了行业配置策略的核心理念及未来发展。相比宏观策略和微观策略,行业配置策略的困境体现在时间维度差别较大、目标界定相对比较模糊、目标成分本身不稳定性明显以及信息获取状况更为复杂等方面。技术性的行业配置策略更多相似于市场分析,依靠与交易对手的智慧较量来获得利润,从先验规律上能够得到合理的操作框架,但未来充满不确定性,行业自身在经济实体和市场实体中的不稳定性决定了其理论框架的不完备性。而艺术性的行业配置策略相似于证券分析,尽管与单个证券的分析相比难度更大,但却是具备稳定框架、能够在不确定的未来中获得确定性方法的模式。
未来行业配置策略的发展可能也会相应地按着这两个方向去演变。市场分析的策略模式将演变为更为复杂的金融工程与数据挖掘,利用市场交易的有效性缺陷来获得套利利润,最后将逐步演变为依靠金融技术手段的程式交易。证券分析的策略模式将更加演变为类似于选股的方法,从行业的盈利周期、安全边际、成长空间等方面不断完善,并且能够解决行业结构的不稳定性。随着国内证券市场的不断完善和逐步成熟,行业配置策略也将日益体现出其技术性和艺术性的鲜明特征。
Industry allocation strategy is a part of tactical asset allocation in the management of dynamic investment portfolio, which has been widely focused and applied in recent years. The industrial trend in the global asset management indicates that the importance of industry allocation strategy is increasing day by day, compared with region, scale and style allocation. Besides this, huge amount of asset management products based on industry allocation have been promoted globally. Benjamin F. King started to introduce industry factor into multi-factor model creatively since the 60s of last century. The academic research field gradually developed same recognition of the importance of industry allocation strategy, and gradually shifted from the conventional momentum and inversion strategy to the configuration strategy based on economic cycle, monetary environment and inter-industrial correlation for the industry allocation methodology. The domestic security market attached remarkably increased importance to the industry allocation in recent years. The academic circle and major investment institutions have come up with huge amount of research findings.
The theoretical basis for the industry allocation strategy is the illustration degree of industry factors in security benefit. The solid evidence and test to the domestic market indicates that the industry factors can account for 60% of the total illustration factors according to the calculation results with FF framework, and accounting for 30% of the overall illustration of cross sectional benefits, and the illustration strength of industry factors is more prominent in the balance of fluctuating market. This means that Industry allocation strategy has wide space to develop for application, and should be theoretically further explored and improved.
The prerequisite for establishing industry allocation strategy is the formation of efficient industrial classification. The general standard for the industrial classification includes management type and investment type. The current various standards for the industrial classification in A share market have both advantages and disadvantages, among which the standard by CITIC relatively took into account both the industrial attributes and market attributes. On the other hand, it can be seen from the cluster analysis on A share market that on top of the general standard for industrial classification, the sectors can be grouped into resource type (coal, non-ferrous metal), finance type (bank and real estate), iron & steel, cycle investment category, non-cycle investment category, merger and reorganization type etc. altogether seven types. The result of this type of cluster analysis shows that industry allocation can base on the division of large categories of sectors.
There have been tremendous amount of conclusions drawn from domestic and foreign studies on each area of industry allocation since the 60s of last century, however they are scattered at each level lacking systematic framework. While in the same time period, asset allocation and active portfolio management concept have been gradually studied in depth. Therefore, the core of the text is based on the theory of active portfolio management put forward by Grinold in 1994, which improved the framework of industry allocation strategy. Looking from the perspective of active portfolio management theory, the excess returns which can overcome the market is related to information ratio (IR). This is also attributed to the prediction capacity (information coefficient) of the investor for the expected excess returns, and the capacity of predicting the right time for the investment (strategy span). Therefore, the industry allocation framework mainly unfolds from these two aspects, on one hand, is the prediction of industrial expected rate of return, the concrete structure can be classified into the following different levels:the macro-configuration strategy based on economic cycle and monetary environment; the medium configuration strategy based on the lead-lag relationship and the micro-configuration strategy based on momentum and inversion. On the other hand, is the dynamic rebalance framework based on this type of information n and rules.
The text focuses on the provision of solid evidence for the applicability of the four types of industry allocation frameworks in A share market on the basis of summarizing former study results, and improved the operatable details of the framework based on the A share market characteristics. First of all, for the industry allocation strategy based on economic cycle, the text gives theoretical elaboration of investment clock which is widely applied. The key driving forces for the change of industry wheeled by economic cycle is the following:(1) the exogenous expansion of technical impact on key industries; (2) the transmission of output from upper stream to lower stream at different links of the industrial chain; (3) the mismatch of output and investment determines the sequence of industrial returns; (4) the profitability change determines the sensitivity of returns on investment, the industry returns with stable profitability will only rely on the output. Therefore, there are some differences among industries in determining the factors of industrial cycle configuration, for example:depreciation rate, cost adjustment rate, technical impact. Some factors cause the change of ratio with the fluctuation of economic cycle, for example:output-capital ratio, investment-capital ratio, marginal return on capital etc.
Besides this, for the industry allocation strategy based on monetary environment, the text studied the rule of industry allocation under the impact of quantitative monetary policy and pricing monetary policy. The results showed that the impact of pricing monetary policy on the rate of returns from industrial share price lasts shorter period of time, but with low illustration degree; While the impact of quantitative monetary policy on the rate of returns from industrial share price lasts longer period of time, but with relatively higher illustration degree; Both of the two types of monetary policies have more prominent impact on cycle industry at the initial stage, but for the long run, the financial industry is most affected. The text also established cycle rotation strategy and cross cycle stable strategy. We can see that:(1) non cycle industries are superior to cycle industries for the long run, the cycle configuration can significantly raise the returns level for those industries most sensitive to monetary environment; (2) the cycle industry rotation strategy or cross cycle optimized portfolio can both overcome the market, and the industry rotation configuration strategy is more effective than the cross cycle optimized portfolio strategy put forward by Markowitz. (3) for the long run, even the cycle industry rotation strategy will not be able to defeat the consumption and medicine industries which have long time demonstrated steady growth. Like the configuration strategy based on economic cycle, the configuration strategy based on monetary environment also laid foundation for the strategic configuration plan.
Next,the text studies the configuration strategy based on the lead-lag relationship among sectors, which is very significant to reveal the style change among the industrial sectors, the solid evidence from A share market shows that:(1) the impact formed in the system by bank affects the real estate industry the most, meanwhile it has greater impact on cycle industry in short run; (2) The development trend of oil and petrochemical industry is independent, however, they can cause great impact on all the industries in short run. This impact will obviously disappear in the mid and long run; (3) the impact of cycle industry leads to the rapid drop of other industries after positive reflection. Non-ferrous metal industry causes larger market fluctuation than iron & steel industry. (4) Medical industry can typically represents consumption industry, electronics industry represents science & technology type or growth stocks;(5) the impact of all the industries in the system shows obvious signs will show in about one month, and then the impact of additional message gradually weakens, the development trends of cycle industries are relatively independent.
The fourth, the text studied the conventional industry allocation strategy based on momentum and inversion, which is in the tactical adjustment position in the whole industry allocation framework. There is great discrepancy among the characteristics of the momentum of each industry in A share market, with less obvious inversion features. The momentum of cycle industries is usually shorter, basically around two weeks, while the momentum of non-cycle industries is about 8 weeks The dynamic simulation indicates that the momentum and inversion in majority of portfolio are effective, and this type of strategy can get positive returns; For the momentum strategy, the effects are more obvious during short observation time period and during holding period, while the inversion strategy requires longer observation time period and moderate holding period to see the better effects of strategy.
The above-mentioned four types of configuration strategy provided foundation for predicting the expected rate of returns from industrial sectors, but this is only a part of the industry allocation framework in the whole active portfolio management. On top of that, the text systematically put forward the dynamic industry allocation framework based on the active portfolio management concept put forward by Grinold (1994). The core concept is the strategic configuration plan based on economic cycle and monetary environment, identifying the configuration direction for the long time to come; Then the comprehensive considerations were given to the expected market response, adjustment of analysts performance, lead-lag relationship among industries, momentum & inversion relationship etc., forming the rebalance of dynamic portfolio;After the configuration of large segments, further comparative studies were conducted on the categorized industries, to select potential industries with excess returns. In order to convert the information into portfolio following certain standards, the text proposed a type of quantitative calculation method, to weigh the policy making at three levels as mentioned above and to come up with operatable industry allocation plan chart for investment policy.
As the extension, the text further touched on the core concept of industry allocation strategy and future development trend. Compared with macro and micro strategy, the dilemma of the industry allocation strategy includes:greater discrepancy in time dimension, comparative vague targets identified, obvious instability of targets composition themselves and more complicated information obtaining process etc. The technical industry allocation strategy is more like market analysis, relying on the wisdom competition with trade partners to gain profits. Rational operation framework can be established based on tested rules, however, there are many uncertainties about future. The instability of the industry itself in economic entities and market entities determines the incompleteness of theoretical framework. While the artistic industry allocation strategy is similar to security analysis, although more difficult compared with single security analysis, yet it has stable framework, and can obtain definite methodology for the uncertain future.
The development of future industry allocation strategy may follow these two directions accordingly. The strategy model for market analysis will evolve into more complicated financial engineering and data exploitation, to gain profits by using the defects of efficacy in market transaction, and in the end gradually evolve into program trading which rely on financial technical instruments. The strategy model of security analysis will further evolve into an approach similar to security selection, will be continuously improved in different aspects, such as the profit cycle of industry, safety margin, growth space etc., and the instability of industrial structure can be addressed. With the continuous improvement and gradual mature of domestic security market, the industry allocation strategy will also demonstrate its distinctive technical and artistic features.
引文
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